From 00b9fc42ea0a4794cae3ada26b0f29679acf5024 Mon Sep 17 00:00:00 2001 From: Darice L Guittet Date: Thu, 6 Jul 2023 10:07:15 -0600 Subject: [PATCH] Pysam 4.2.0 (#151) * start * revert adjustment factors changes * update Examples * update files * update build_win.bat --- Examples/BatteryStateful.ipynb | 22 +- Examples/BatteryWithCustomDispatch.py | 2 +- Examples/FetchResourceFileExample.py | 2 +- Examples/GenericSystemSingleOwnerExample.py | 2 +- Examples/LoadToolsExample.py | 2 +- .../WaveFileReader_example.ipynb | 5 +- Examples/NonAnnualSimulation.ipynb | 5 +- Examples/PySAMWorkshop.ipynb | 25 +- .../ResidentialPVBatteryWithCustomDispatch.py | 2 +- Examples/SAMsimPVWattsCommercialExample.py | 2 +- ...ing the NREL bifacial PV HSAT system.ipynb | 18902 +--------------- .../pySAM_Pvsamv1_default_values.xlsx | Bin 0 -> 24608 bytes Examples/UtilityRateForecastExample.py | 2 + Examples/UtilityRatesExample.py | 2 +- .../Windpower Example/windpower-example.py | 2 +- RELEASE.md | 11 +- build_unix.sh | 4 +- build_win.bat | 2 +- docs/lists/configs.rst | 9 - docs/lists/models.rst | 4 +- docs/modules/EtesElectricResistance.rst | 20 +- docs/modules/MhkWave.rst | 12 +- docs/modules/Pvsamv1.rst | 20 +- docs/modules/Pvwattsv1.rst | 6 - docs/modules/Pvwattsv5.rst | 6 - docs/modules/Pvwattsv7.rst | 6 - docs/modules/Pvwattsv8.rst | 6 - docs/modules/Saleleaseback.rst | 6 + docs/modules/Swh.rst | 6 - docs/modules/TroughPhysical.rst | 6 - docs/modules/TroughPhysicalProcessHeat.rst | 6 - docs/modules/Windpower.rst | 12 +- docs/version_changes/4.2.0.rst | 17 + docs/versions.rst | 1 + files/version.py | 2 +- files/version_differ.py | 7 +- modules/Biomass.c | 19 + modules/Equpartflip.c | 270 +- modules/EtesElectricResistance.c | 169 +- modules/EtesPtes.c | 196 +- modules/GenericSystem.c | 19 + modules/Geothermal.c | 19 + modules/Hcpv.c | 19 + modules/HostDeveloper.c | 270 +- modules/Levpartflip.c | 270 +- modules/LinearFresnelDsgIph.c | 19 + modules/MhkWave.c | 27 +- modules/Pvsamv1.c | 391 +- modules/Pvwattsv1.c | 362 +- modules/Pvwattsv5.c | 362 +- modules/Pvwattsv7.c | 362 +- modules/Pvwattsv8.c | 362 +- modules/Saleleaseback.c | 403 +- modules/Sco2CspSystem.c | 13 +- modules/Sco2CspUdPcTables.c | 9 - modules/Singleowner.c | 150 +- modules/Swh.c | 362 +- modules/TcsMSLF.c | 19 + modules/TcsgenericSolar.c | 19 + modules/TcslinearFresnel.c | 19 + modules/TcsmoltenSalt.c | 180 +- modules/TcstroughEmpirical.c | 19 + modules/TcstroughPhysical.c | 19 + modules/TroughPhysical.c | 302 +- modules/TroughPhysicalCspSolver.c | 19 + modules/TroughPhysicalProcessHeat.c | 304 +- modules/Windpower.c | 27 +- src/AdjustmentFactors.c | 27 +- stubs/stubs/Equpartflip.pyi | 18 +- stubs/stubs/EtesElectricResistance.pyi | 10 +- stubs/stubs/EtesPtes.pyi | 13 +- stubs/stubs/HostDeveloper.pyi | 18 +- stubs/stubs/Levpartflip.pyi | 18 +- stubs/stubs/MhkWave.pyi | 32 +- stubs/stubs/Pvsamv1.pyi | 60 +- stubs/stubs/Pvwattsv1.pyi | 27 +- stubs/stubs/Pvwattsv5.pyi | 23 +- stubs/stubs/Pvwattsv7.pyi | 27 +- stubs/stubs/Pvwattsv8.pyi | 27 +- stubs/stubs/Saleleaseback.pyi | 31 +- stubs/stubs/Sco2CspSystem.pyi | 1 - stubs/stubs/Sco2CspUdPcTables.pyi | 1 - stubs/stubs/Singleowner.pyi | 10 +- stubs/stubs/Swh.pyi | 27 +- stubs/stubs/TcsmoltenSalt.pyi | 11 +- stubs/stubs/TroughPhysical.pyi | 23 +- stubs/stubs/TroughPhysicalProcessHeat.pyi | 23 +- stubs/stubs/Windpower.pyi | 28 +- tests/test_pysam_all.py | 24 +- 89 files changed, 3250 insertions(+), 21375 deletions(-) create mode 100644 Examples/SelectingModuleandInverterExample/pySAM_Pvsamv1_default_values.xlsx create mode 100644 docs/version_changes/4.2.0.rst diff --git a/Examples/BatteryStateful.ipynb b/Examples/BatteryStateful.ipynb index 150b9569..c3e16182 100644 --- a/Examples/BatteryStateful.ipynb +++ b/Examples/BatteryStateful.ipynb @@ -9,7 +9,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "4.1.0\n" + "4.2.0\n" ] } ], @@ -88,22 +88,22 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -130,22 +130,22 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -180,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -205,7 +205,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.0" + "version": "3.8.13" }, "vscode": { "interpreter": { diff --git a/Examples/BatteryWithCustomDispatch.py b/Examples/BatteryWithCustomDispatch.py index bb2fd7a5..aec346bc 100644 --- a/Examples/BatteryWithCustomDispatch.py +++ b/Examples/BatteryWithCustomDispatch.py @@ -4,7 +4,7 @@ Additional financial models, inputs, and outputs can be found at https://nrel-pysam.readthedocs.io/en/master/modules/Battery.html -Most recently tested against PySAM 4.1.0 +Most recently tested against PySAM 4.2.0 @author: brtietz """ diff --git a/Examples/FetchResourceFileExample.py b/Examples/FetchResourceFileExample.py index 959352b8..f8591685 100644 --- a/Examples/FetchResourceFileExample.py +++ b/Examples/FetchResourceFileExample.py @@ -10,7 +10,7 @@ To use the `FetchResourceFile` function, register an email address to receive a free API key at at https://developer.nrel.gov/signup/. -Most recently tested against PySAM 4.0.0 +Most recently tested against PySAM 4.2.0 @authors: skoeb, cpaulgilman ''' diff --git a/Examples/GenericSystemSingleOwnerExample.py b/Examples/GenericSystemSingleOwnerExample.py index 9787079f..d2a7ed8b 100755 --- a/Examples/GenericSystemSingleOwnerExample.py +++ b/Examples/GenericSystemSingleOwnerExample.py @@ -3,7 +3,7 @@ """ Created on Wed Mar 4 13:47:58 2020 -Most recently tested against PySAM 4.1.0 +Most recently tested against PySAM 4.2.0 @author: frohro """ diff --git a/Examples/LoadToolsExample.py b/Examples/LoadToolsExample.py index d31f13d0..c8adfd66 100644 --- a/Examples/LoadToolsExample.py +++ b/Examples/LoadToolsExample.py @@ -6,7 +6,7 @@ """ A usage example for LoadTools.get_monthly peaks with hourly annual data -Requires PySAM 4.1.0 or greater +Requires PySAM 4.2.0 or greater """ if __name__ == "__main__": df = pd.read_csv(str(Path(__file__).parent / "sample_load.csv"), dtype=float) diff --git a/Examples/Marine energy examples/WaveFileReader_example.ipynb b/Examples/Marine energy examples/WaveFileReader_example.ipynb index 4e617ce0..38ef0234 100644 --- a/Examples/Marine energy examples/WaveFileReader_example.ipynb +++ b/Examples/Marine energy examples/WaveFileReader_example.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -19,7 +20,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "4.1.0\n" + "4.2.0\n" ] } ], @@ -161,7 +162,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.0" + "version": "3.8.13" }, "vscode": { "interpreter": { diff --git a/Examples/NonAnnualSimulation.ipynb b/Examples/NonAnnualSimulation.ipynb index 2417c00a..cb61a02d 100644 --- a/Examples/NonAnnualSimulation.ipynb +++ b/Examples/NonAnnualSimulation.ipynb @@ -6,7 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "# Most recently tested against PySAM 4.1.0\n", + "# Most recently tested against PySAM 4.2.0\n", "\n", "import pandas as pd\n", "import json\n", @@ -16,6 +16,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -288,6 +289,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -331,6 +333,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ diff --git a/Examples/PySAMWorkshop.ipynb b/Examples/PySAMWorkshop.ipynb index 68c6cf7f..9e4a55cc 100644 --- a/Examples/PySAMWorkshop.ipynb +++ b/Examples/PySAMWorkshop.ipynb @@ -13,10 +13,11 @@ "\n", "https://sam.nrel.gov/software-development-kit-sdk/pysam.html\n", "\n", - "Edit: Most recently tested with Version 4.1.0" + "Edit: Most recently tested with Version 4.2.0" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -36,6 +37,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -68,6 +70,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -110,6 +113,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -236,6 +240,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -294,6 +299,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -360,7 +366,7 @@ " (0.0, 0.0, 0.0, 0.0, 0.0, -0.0, 6.389046797900428, 37.94398351785478, 67.06449907636099, 92.89776429848214)\n", "\n", "annual energy value\n", - " (0.0, 19406.19405690556, 19800.52382533316, 20202.44148167006, 20612.079886380227, 21029.57424662404, 21455.061069906493, 21888.678750448922, 22330.56790184979, 22780.871493923893, 23239.73432549519, 23707.302537008927, 24183.72454046737, 24669.151054164817, 25162.80184412058, 25665.452721768244, 26177.509583152998, 26699.12880537708, 27230.46804522286, 27771.6872915576, 28322.60044366972)\n" + " (0.0, 19406.19405690556, 19800.52382533316, 20202.441481670056, 20612.079886380227, 21029.57424662404, 21455.061069906493, 21888.678750448922, 22330.56790184979, 22780.871493923893, 23239.73432549519, 23707.302537008924, 24183.724540467367, 24669.151054164817, 25162.80184412058, 25665.45272176825, 26177.509583152998, 26699.128805377077, 27230.468045222864, 27771.6872915576, 28322.60044366972)\n" ] } ], @@ -375,6 +381,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -417,6 +424,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -496,10 +504,15 @@ "output_type": "stream", "text": [ "batt_kw\tbatt_kwh\tavg_npv\n", - "10\t40\t-131785.9623201237\n", - "20\t80\t-128677.60802359802\n", - "30\t120\t-126139.5470983437\n", - "40\t160\t-124008.21375974927\n" + "10\t40\t-131785.96232012415\n", + "20\t80\t-128677.60802319663\n", + "30\t120\t-126139.54922129444\n", + "40\t160\t-124008.20675169432\n", + "50\t200\t-122370.41001778266\n", + "60\t240\t-121195.93805275756\n", + "70\t280\t-120204.21032777404\n", + "80\t320\t-119364.54637950887\n", + "90\t360\t-118652.09661186521\n" ] } ], diff --git a/Examples/ResidentialPVBatteryWithCustomDispatch.py b/Examples/ResidentialPVBatteryWithCustomDispatch.py index f2a4a219..26312863 100644 --- a/Examples/ResidentialPVBatteryWithCustomDispatch.py +++ b/Examples/ResidentialPVBatteryWithCustomDispatch.py @@ -8,7 +8,7 @@ * PV: https://nrel-pysam.readthedocs.io/en/master/modules/Pvsamv1.html * Battery: https://nrel-pysam.readthedocs.io/en/master/modules/Battery.html -Most recently tested against PySAM 4.1.0 +Most recently tested against PySAM 4.2.0 @author: brtietz """ diff --git a/Examples/SAMsimPVWattsCommercialExample.py b/Examples/SAMsimPVWattsCommercialExample.py index a1bdd9d7..9e9ffd8f 100755 --- a/Examples/SAMsimPVWattsCommercialExample.py +++ b/Examples/SAMsimPVWattsCommercialExample.py @@ -13,7 +13,7 @@ Run the simulations. Print the results. -Most recently tested against PySAM 4.1.0 +Most recently tested against PySAM 4.2.0 @author: frohro """ diff --git a/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb b/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb index e0d438cd..1da831d3 100644 --- a/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb +++ b/Examples/SelectingModuleandInverterExample/Modeling the NREL bifacial PV HSAT system.ipynb @@ -39,7 +39,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 1, "id": "94ca714a", "metadata": {}, "outputs": [], @@ -49,7 +49,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 2, "id": "9ae8b95a", "metadata": {}, "outputs": [], @@ -67,17 +67,17 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 3, "id": "42cd3c81", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'4.1.0'" + "'4.2.0'" ] }, - "execution_count": 17, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -87,6 +87,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f8d7d426", "metadata": {}, @@ -95,6 +96,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "86fe29f7", "metadata": {}, @@ -106,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 4, "id": "2d969682", "metadata": {}, "outputs": [], @@ -115,6 +117,34 @@ ] }, { + "cell_type": "code", + "execution_count": 5, + "id": "6ee286fa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'constant': 0, 'dc_constant': 0}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import marshal\n", + "\n", + "# with open(\"/Users/dguittet/miniconda3/envs/pysam_build_3.8/lib/python3.8/site-packages/NREL_PySAM-4.2.0-py3.8-macosx-10.9-x86_64.egg/PySAM/defaults/pvsamv1_flatplatepvcommercial.df\", 'rb') as f:\n", + "with open(\"/Users/dguittet/SAM-Dev/pysam/build/lib.macosx-10.9-x86_64-cpython-38/PySAM/defaults/pvsamv1_flatplatepvcommercial.df\", 'rb') as f:\n", + " defaults = marshal.load(f)\n", + "\n", + "defaults['AdjustmentFactors']" + ] + }, + { + "attachments": {}, "cell_type": "markdown", "id": "17774306", "metadata": {}, @@ -124,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 6, "id": "706dcbfa", "metadata": {}, "outputs": [], @@ -133,6 +163,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "6204a319", "metadata": {}, @@ -142,7 +173,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 7, "id": "1bd67ff4", "metadata": {}, "outputs": [ @@ -8319,7 +8350,7 @@ " 'Outputs': {}}" ] }, - "execution_count": 20, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -8331,6 +8362,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "512208c7", "metadata": {}, @@ -8340,7 +8372,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 8, "id": "78353bde", "metadata": {}, "outputs": [], @@ -8365,6 +8397,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "3c69857f", "metadata": {}, @@ -8373,6 +8406,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ab7b1508", "metadata": {}, @@ -8382,7 +8416,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 9, "id": "b4f77fb6", "metadata": {}, "outputs": [], @@ -8414,7 +8448,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 10, "id": "99d60505", "metadata": {}, "outputs": [], @@ -8442,6 +8476,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "5ffda242", "metadata": {}, @@ -8451,7 +8486,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 11, "id": "3d4782b4", "metadata": {}, "outputs": [], @@ -8460,6 +8495,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c346e08a", "metadata": {}, @@ -8468,6 +8504,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2df8958d", "metadata": {}, @@ -8479,7 +8516,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 12, "id": "e42b5dfe", "metadata": {}, "outputs": [], @@ -8488,6 +8525,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "aa203284", "metadata": {}, @@ -8496,6 +8534,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "b27aafe4", "metadata": {}, @@ -8512,6 +8551,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "737e8ffa", "metadata": {}, @@ -8520,6 +8560,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f62c3317", "metadata": {}, @@ -8529,20 +8570,222 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 13, "id": "427886b3", "metadata": {}, "outputs": [ { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'pvlib'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[26], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mpvlib\u001b[39;00m\n\u001b[1;32m 2\u001b[0m CECMODS \u001b[39m=\u001b[39m pvlib\u001b[39m.\u001b[39mpvsystem\u001b[39m.\u001b[39mretrieve_sam(name\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mCECMod\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m 4\u001b[0m \u001b[39m# the CEC modules are a pandas DataFrame oriented as columns, transpose to arrange\u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[39m# as indices\u001b[39;00m\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pvlib'" - 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TechnologyBifacialSTCPTCA_cLengthWidthN_sI_sc_refV_oc_ref...a_refI_L_refI_o_refR_sR_sh_refAdjustgamma_rBIPVVersionDate
A10Green_Technology_A10J_S72_175Mono-c-Si0175.0914151.21.31.5760.825725.1743.99...1.9816965.1757030.00.316688287.10220316.057121-0.5072NSAM 2018.11.11 r21/3/2019
A10Green_Technology_A10J_S72_180Mono-c-Si0179.928155.71.31.5760.825725.3144.06...1.9884145.3161480.00.299919259.04794316.418983-0.5072NSAM 2018.11.11 r21/3/2019
A10Green_Technology_A10J_S72_185Mono-c-Si0184.7016160.21.31.5760.825725.4344.14...1.9848175.4356760.00.311962298.42443815.688233-0.5072NSAM 2018.11.11 r21/3/2019
A10Green_Technology_A10J_M60_220Multi-c-Si0219.876189.11.6241.6320.995607.9536.06...1.6730947.9590620.00.140393123.16840421.875164-0.5196NSAM 2018.11.11 r21/3/2019
A10Green_Technology_A10J_M60_225Multi-c-Si0224.9856193.51.6241.6320.995608.0436.24...1.6717828.0472060.00.14737164.41947920.698376-0.5196NSAM 2018.11.11 r21/3/2019
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5 rows × 25 columns

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" + ], + "text/plain": [ + " Technology Bifacial STC PTC A_c \\\n", + "A10Green_Technology_A10J_S72_175 Mono-c-Si 0 175.0914 151.2 1.3 \n", + "A10Green_Technology_A10J_S72_180 Mono-c-Si 0 179.928 155.7 1.3 \n", + "A10Green_Technology_A10J_S72_185 Mono-c-Si 0 184.7016 160.2 1.3 \n", + "A10Green_Technology_A10J_M60_220 Multi-c-Si 0 219.876 189.1 1.624 \n", + "A10Green_Technology_A10J_M60_225 Multi-c-Si 0 224.9856 193.5 1.624 \n", + "\n", + " Length Width N_s I_sc_ref V_oc_ref ... \\\n", + "A10Green_Technology_A10J_S72_175 1.576 0.825 72 5.17 43.99 ... \n", + "A10Green_Technology_A10J_S72_180 1.576 0.825 72 5.31 44.06 ... \n", + "A10Green_Technology_A10J_S72_185 1.576 0.825 72 5.43 44.14 ... \n", + "A10Green_Technology_A10J_M60_220 1.632 0.995 60 7.95 36.06 ... \n", + "A10Green_Technology_A10J_M60_225 1.632 0.995 60 8.04 36.24 ... \n", + "\n", + " a_ref I_L_ref I_o_ref R_s \\\n", + "A10Green_Technology_A10J_S72_175 1.981696 5.175703 0.0 0.316688 \n", + "A10Green_Technology_A10J_S72_180 1.988414 5.316148 0.0 0.299919 \n", + "A10Green_Technology_A10J_S72_185 1.984817 5.435676 0.0 0.311962 \n", + "A10Green_Technology_A10J_M60_220 1.673094 7.959062 0.0 0.140393 \n", + "A10Green_Technology_A10J_M60_225 1.671782 8.047206 0.0 0.14737 \n", + "\n", + " R_sh_ref Adjust gamma_r BIPV \\\n", + "A10Green_Technology_A10J_S72_175 287.102203 16.057121 -0.5072 N \n", + "A10Green_Technology_A10J_S72_180 259.047943 16.418983 -0.5072 N \n", + "A10Green_Technology_A10J_S72_185 298.424438 15.688233 -0.5072 N \n", + "A10Green_Technology_A10J_M60_220 123.168404 21.875164 -0.5196 N \n", + "A10Green_Technology_A10J_M60_225 164.419479 20.698376 -0.5196 N \n", + "\n", + " Version Date \n", + "A10Green_Technology_A10J_S72_175 SAM 2018.11.11 r2 1/3/2019 \n", + "A10Green_Technology_A10J_S72_180 SAM 2018.11.11 r2 1/3/2019 \n", + "A10Green_Technology_A10J_S72_185 SAM 2018.11.11 r2 1/3/2019 \n", + "A10Green_Technology_A10J_M60_220 SAM 2018.11.11 r2 1/3/2019 \n", + "A10Green_Technology_A10J_M60_225 SAM 2018.11.11 r2 1/3/2019 \n", + "\n", + "[5 rows x 25 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -8555,6 +8798,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "181242da", "metadata": {}, @@ -8564,7 +8808,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "8a0f40e3", "metadata": {}, "outputs": [ @@ -8655,7 +8899,7 @@ " \n", " \n", " a_ref\n", - " 1.88573\n", + " 1.885731\n", " \n", " \n", " I_L_ref\n", @@ -8663,7 +8907,7 @@ " \n", " \n", " I_o_ref\n", - " 7.72903e-11\n", + " 0.0\n", " \n", " \n", " R_s\n", @@ -8671,11 +8915,11 @@ " \n", " \n", " R_sh_ref\n", - " 830.976\n", + " 830.975952\n", " \n", " \n", " Adjust\n", - " 10.4\n", + " 10.40003\n", " \n", " \n", " gamma_r\n", @@ -8714,19 +8958,19 @@ "alpha_sc 0.004675\n", "beta_oc -0.139925\n", "T_NOCT 47.4\n", - "a_ref 1.88573\n", + "a_ref 1.885731\n", "I_L_ref 9.80468\n", - "I_o_ref 7.72903e-11\n", + "I_o_ref 0.0\n", "R_s 0.396799\n", - "R_sh_ref 830.976\n", - "Adjust 10.4\n", + "R_sh_ref 830.975952\n", + "Adjust 10.40003\n", "gamma_r -0.4028\n", "BIPV N\n", "Version SAM 2018.11.11 r2\n", "Date 1/3/2019" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -8738,6 +8982,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "fa3b5189", "metadata": {}, @@ -8746,6 +8991,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c1d545b0", "metadata": {}, @@ -8754,6 +9000,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f16bef3b", "metadata": {}, @@ -8763,7 +9010,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "0b7dca82", "metadata": {}, "outputs": [], @@ -8772,6 +9019,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "6e4307db", "metadata": {}, @@ -8787,7 +9035,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "ea1508c7", "metadata": {}, "outputs": [], @@ -8803,6 +9051,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2e860cb8", "metadata": {}, @@ -8814,7 +9063,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "5c9a6b68", "metadata": {}, "outputs": [], @@ -8824,7 +9073,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "65800ef5", "metadata": {}, "outputs": [], @@ -8840,7 +9089,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "a73a41d3", "metadata": {}, "outputs": [ @@ -8859,6 +9108,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "0611a179", "metadata": {}, @@ -8867,6 +9117,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f66f60da", "metadata": {}, @@ -8881,7 +9132,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "212271c2", "metadata": {}, "outputs": [], @@ -8894,6 +9145,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "b67e2f48", "metadata": {}, @@ -8905,7 +9157,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "3d6d1159", "metadata": {}, "outputs": [], @@ -8936,6 +9188,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "9acd301b", "metadata": {}, @@ -8945,7 +9198,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "6291f981", "metadata": {}, "outputs": [], @@ -8957,7 +9210,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "c0a5c496", "metadata": {}, "outputs": [], @@ -8992,6 +9245,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "bc72dd3f", "metadata": {}, @@ -9000,6 +9254,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "2d3aad1a", "metadata": {}, @@ -9011,7 +9266,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "3fffb682", "metadata": {}, "outputs": [], @@ -9022,6 +9277,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "039cc953", "metadata": {}, @@ -9031,7 +9287,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "c96dab31", "metadata": {}, "outputs": [ @@ -9151,7 +9407,7 @@ "Fronius International GmbH: Fronius Symo 10.0-3... 3/1/2019 N " ] }, - "execution_count": 24, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -9164,7 +9420,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "bf2ee70e", "metadata": {}, "outputs": [], @@ -9184,6 +9440,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f0285876", "metadata": {}, @@ -9193,7 +9450,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "id": "61ddd7e0", "metadata": {}, "outputs": [], @@ -9202,6 +9459,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "5f6f7891", "metadata": {}, @@ -9211,7 +9469,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "06a89af6", "metadata": {}, "outputs": [], @@ -9236,6 +9494,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "987cf355", "metadata": {}, @@ -9244,6 +9503,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "112d081e", "metadata": {}, @@ -9288,7 +9548,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "728a923a", "metadata": {}, "outputs": [], @@ -9307,6 +9567,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "9b3aecf8", "metadata": {}, @@ -9315,6 +9576,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c6c4ce0e", "metadata": {}, @@ -9324,7 +9586,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "a168d4a0", "metadata": {}, "outputs": [], @@ -9334,7 +9596,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "7c3a2fd2", "metadata": {}, "outputs": [], @@ -9343,6 +9605,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "68d89a8c", "metadata": {}, @@ -9356,7 +9619,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "id": "d4a387d5", "metadata": {}, "outputs": [], @@ -9380,6 +9643,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "9dc6584b", "metadata": {}, @@ -9393,7 +9657,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "id": "12639039", "metadata": {}, "outputs": [], @@ -9408,7 +9672,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "e50dbb64", "metadata": {}, "outputs": [], @@ -9420,6 +9684,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "4e2a005e", "metadata": {}, @@ -9429,7 +9694,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "id": "8b44af3d", "metadata": {}, "outputs": [ @@ -9528,17 +9793,17 @@ " \n", " \n", " 2020-01-01 07:00:00\n", - " 0.992530\n", - " 10.865571\n", - " 0.011139\n", + " 0.992529\n", + " 10.864574\n", + " 0.011138\n", " 29.900648\n", " 9.146110\n", " 0.2\n", " \n", " \n", " 2020-01-01 08:00:00\n", - " 5.500894\n", - " 62.895500\n", + " 5.500871\n", + " 62.895738\n", " 0.072938\n", " 39.650845\n", " 45.072811\n", @@ -9546,17 +9811,17 @@ " \n", " \n", " 2020-01-01 09:00:00\n", - " 26.062696\n", - " 424.179539\n", - " 0.487810\n", + " 26.062750\n", + " 424.206498\n", + " 0.487840\n", " 488.902252\n", " 92.055008\n", " 0.2\n", " \n", " \n", " 2020-01-01 10:00:00\n", - " 23.033394\n", - " 140.623805\n", + " 23.033611\n", + " 140.623599\n", " 0.171038\n", " 40.219421\n", " 139.379303\n", @@ -9564,54 +9829,54 @@ " \n", " \n", " 2020-01-01 11:00:00\n", - " 15.878670\n", - " 136.524303\n", - " 0.160222\n", + " 15.879076\n", + " 136.519918\n", + " 0.160217\n", " 1.458432\n", " 146.268784\n", " 0.2\n", " \n", " \n", " 2020-01-01 12:00:00\n", - " 15.672055\n", - " 138.869833\n", - " 0.162670\n", + " 15.671924\n", + " 138.874834\n", + " 0.162674\n", " 7.297924\n", " 143.908936\n", " 0.2\n", " \n", " \n", " 2020-01-01 13:00:00\n", - " 34.055688\n", - " 421.822650\n", - " 0.487029\n", + " 34.056311\n", + " 421.819334\n", + " 0.487023\n", " 514.294067\n", " 142.040833\n", " 0.2\n", " \n", " \n", " 2020-01-01 14:00:00\n", - " 30.092291\n", - " 547.726138\n", - " 0.627318\n", + " 30.095065\n", + " 547.718436\n", + " 0.627308\n", " 695.355957\n", " 87.838135\n", " 0.2\n", " \n", " \n", " 2020-01-01 15:00:00\n", - " 5.370426\n", - " 453.992020\n", - " 0.503567\n", + " 5.369947\n", + " 454.193254\n", + " 0.503796\n", " 704.084229\n", " 39.767941\n", " 0.2\n", " \n", " \n", " 2020-01-01 16:00:00\n", - " 1.112469\n", - " 23.395526\n", - " 0.023299\n", + " 1.112347\n", + " 23.427947\n", + " 0.023330\n", " 64.097702\n", " 13.479426\n", " 0.2\n", @@ -9692,16 +9957,16 @@ "2020-01-01 04:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "2020-01-01 05:00:00 0.000000 0.000000 0.000000 0.000000 0.007147 \n", "2020-01-01 06:00:00 0.000000 0.000000 0.000000 0.224083 0.000000 \n", - "2020-01-01 07:00:00 0.992530 10.865571 0.011139 29.900648 9.146110 \n", - "2020-01-01 08:00:00 5.500894 62.895500 0.072938 39.650845 45.072811 \n", - "2020-01-01 09:00:00 26.062696 424.179539 0.487810 488.902252 92.055008 \n", - "2020-01-01 10:00:00 23.033394 140.623805 0.171038 40.219421 139.379303 \n", - "2020-01-01 11:00:00 15.878670 136.524303 0.160222 1.458432 146.268784 \n", - "2020-01-01 12:00:00 15.672055 138.869833 0.162670 7.297924 143.908936 \n", - "2020-01-01 13:00:00 34.055688 421.822650 0.487029 514.294067 142.040833 \n", - "2020-01-01 14:00:00 30.092291 547.726138 0.627318 695.355957 87.838135 \n", - "2020-01-01 15:00:00 5.370426 453.992020 0.503567 704.084229 39.767941 \n", - "2020-01-01 16:00:00 1.112469 23.395526 0.023299 64.097702 13.479426 \n", + "2020-01-01 07:00:00 0.992529 10.864574 0.011138 29.900648 9.146110 \n", + "2020-01-01 08:00:00 5.500871 62.895738 0.072938 39.650845 45.072811 \n", + "2020-01-01 09:00:00 26.062750 424.206498 0.487840 488.902252 92.055008 \n", + "2020-01-01 10:00:00 23.033611 140.623599 0.171038 40.219421 139.379303 \n", + "2020-01-01 11:00:00 15.879076 136.519918 0.160217 1.458432 146.268784 \n", + "2020-01-01 12:00:00 15.671924 138.874834 0.162674 7.297924 143.908936 \n", + "2020-01-01 13:00:00 34.056311 421.819334 0.487023 514.294067 142.040833 \n", + "2020-01-01 14:00:00 30.095065 547.718436 0.627308 695.355957 87.838135 \n", + "2020-01-01 15:00:00 5.369947 454.193254 0.503796 704.084229 39.767941 \n", + "2020-01-01 16:00:00 1.112347 23.427947 0.023330 64.097702 13.479426 \n", "2020-01-01 17:00:00 0.000000 0.000000 0.000000 0.118982 0.056990 \n", "2020-01-01 18:00:00 0.000000 0.000000 0.000000 0.074463 0.000000 \n", "2020-01-01 19:00:00 0.000000 0.000000 0.000000 0.040330 0.011045 \n", @@ -9737,7 +10002,7 @@ "2020-01-01 23:00:00 0.2 " ] }, - "execution_count": 34, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -9752,7 +10017,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "id": "deb3ee05", "metadata": {}, "outputs": [], @@ -9763,20 +10028,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "id": "4c0cdea0", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", 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HcmV?d00001 diff --git a/Examples/UtilityRateForecastExample.py b/Examples/UtilityRateForecastExample.py index 620f1cca..f513d52f 100644 --- a/Examples/UtilityRateForecastExample.py +++ b/Examples/UtilityRateForecastExample.py @@ -14,6 +14,8 @@ The forecast code looks at the step-by-step (default hourly) costs of the rate, based on forecasts of generation and load This can either be run with all of the steps at once (single call to execute()) to generate an array of prices or by calling execute repeateadly, potentially in the loop with a model-predictive controller for energy storage + +Most recently tested against PySAM 4.2.0 """ # Get a key from https://api.openei.org:443 diff --git a/Examples/UtilityRatesExample.py b/Examples/UtilityRatesExample.py index 1cec296a..72b9d9b4 100644 --- a/Examples/UtilityRatesExample.py +++ b/Examples/UtilityRatesExample.py @@ -6,7 +6,7 @@ Additional financial models, inputs, and outputs can be found at: * PV: https://nrel-pysam.readthedocs.io/en/master/modules/Utilityrate5.html -Most recently tested against PySAM 4.1.0 +Most recently tested against PySAM 4.2.0 Requires: nrel-pysam, requests @author: brtietz diff --git a/Examples/Windpower Example/windpower-example.py b/Examples/Windpower Example/windpower-example.py index ee195251..51a6a77e 100644 --- a/Examples/Windpower Example/windpower-example.py +++ b/Examples/Windpower Example/windpower-example.py @@ -3,7 +3,7 @@ This example script shows basic steps for working with the Windpower module. See the readme for details. -Created with PySAM 4.1.0 in Python 3.8.7. Last tested with PySAM 4.1.0 with +Created with PySAM 4.2.0 in Python 3.8.7. Last tested with PySAM 4.2.0 with code generated by SAM 2022.11.21 r1 SSC 279. ''' diff --git a/RELEASE.md b/RELEASE.md index d8331d37..cc823dd5 100644 --- a/RELEASE.md +++ b/RELEASE.md @@ -1,13 +1,20 @@ # Release Notes +## Version 4.2.0, June 30, 2023 - SAM 2022.11.21, SSC Version 280 +* [SAM Release updates for Version 2022.11.21 Revision 3](https://nrel.github.io/SAM/doc/releasenotes.html) +* Fix support for arm64 and aarch64 (#143, #144) +* Fix URDB v8 function (#145) +* Windpower module example (#148) +* Battery functions for reopt sizing (#149) + ## Version 4.1.0, Feb 24, 2023 - SAM 2022.11.21, SSC Version 279 -* [SAM Release updates for Version 2022.11.21 Revision 1](https://nrel.github.io/SAM/doc/releasenotes.html) +* [SAM Release updates for Version 2022.11.21 Revision 2](https://nrel.github.io/SAM/doc/releasenotes.html) * Updated Documentation for INOUT variables (#141) * Added tolerance for Battery sizing tool (#140) * Add Python 3.11 support ## Version 4.0.0, Dec 10, 2022 - SAM 2022.11.21, SSC Version 278 -* [SAM Release updates for Version 2022.11.21 Revision 0](https://nrel.github.io/SAM/doc/releasenotes.html) +* [SAM Release updates for Version 2022.11.21 Revision 1](https://nrel.github.io/SAM/doc/releasenotes.html) * Added LoadTools, URDBv8 support and utility rate fixes (#126, 128) * License update (#127) * PySSC modifications for arrays (#125) diff --git a/build_unix.sh b/build_unix.sh index 53d60b43..e2245c61 100755 --- a/build_unix.sh +++ b/build_unix.sh @@ -7,8 +7,8 @@ # Building libssc and libSAM_api # requires SAM-Dev/CMakeList.txt that contains lk, wex, ssc and sam as subdirectories -rm -rf ~/SAM-Dev/cmake-build-release -mkdir -p ~/SAM-Dev/cmake-build-release +# rm -rf ~/SAM-Dev/cmake-build-release +# mkdir -p ~/SAM-Dev/cmake-build-release cd ~/SAM-Dev/cmake-build-release || exit cmake .. -DCMAKE_BUILD_TYPE=Release -DSAMAPI_EXPORT=1 -DSAM_SKIP_AUTOGEN=0 cmake --build . --target SAM_api -j 6 diff --git a/build_win.bat b/build_win.bat index 9b592b64..9c696e7f 100644 --- a/build_win.bat +++ b/build_win.bat @@ -15,7 +15,7 @@ cd %PYSAMDIR% echo y | rmdir build /s echo y | del dist\* -FOR %%i IN (pysam_build_3.6 pysam_build_3.7, pysam_build_3.8 pysam_build_3.9 pysam_build_3.10) DO ( +FOR %%i IN (pysam_build_3.6 pysam_build_3.7, pysam_build_3.8 pysam_build_3.9 pysam_build_3.10 pysam_build_3.11) DO ( call deactivate call activate %%i echo y | pip install -r tests/requirements.txt diff --git a/docs/lists/configs.rst b/docs/lists/configs.rst index 414ed309..edcd912a 100644 --- a/docs/lists/configs.rst +++ b/docs/lists/configs.rst @@ -1114,15 +1114,6 @@ Power Tower Molten Salt -- Merchant Plant :doc:`../modules/TcsmoltenSalt`, :doc:`../modules/Grid`, :doc:`../modules/Utilityrate5`, :doc:`../modules/Merchantplant` -Power Tower Molten Salt -- No Financial Model ------------------------------------------------------------------------ - - CSP molten salt power tower system using heat transfer and thermodynamic component models. Run the performance model with no financial model. - - Configuration name for defaults: *"MSPTNone"* - - :doc:`../modules/TcsmoltenSalt` - Power Tower Molten Salt -- Partnership Flip with Debt ----------------------------------------------------------------------- diff --git a/docs/lists/models.rst b/docs/lists/models.rst index 2426f173..0c4c6ada 100644 --- a/docs/lists/models.rst +++ b/docs/lists/models.rst @@ -257,10 +257,10 @@ SAM Wave Resource File Reader :doc:`../modules/Wfcheck` (HD) - Weather file checker. + Weather file checker for solar resource data. :doc:`../modules/Wfcsvconv` (HD) - Converter for TMY2, TMY3, INTL, EPW, SMW weather files to standard CSV format + Converter for TMY2, TMY3, INTL, EPW, SMW weather files with solar resource data to SAM CSV format :doc:`../modules/Wfreader` (HD) Standard Weather File Format Reader (TMY2, TMY3, EPW, SMW, WFCSV) diff --git a/docs/modules/EtesElectricResistance.rst b/docs/modules/EtesElectricResistance.rst index d8c85d88..cf010758 100644 --- a/docs/modules/EtesElectricResistance.rst +++ b/docs/modules/EtesElectricResistance.rst @@ -53,14 +53,30 @@ The variables listed below are interdependent with other variables. If you chang - const_per_upfront_rate5 + - dispatch_factor1 + + - dispatch_factor2 + + - dispatch_factor3 + + - dispatch_factor4 + + - dispatch_factor5 + + - dispatch_factor6 + + - dispatch_factor7 + + - dispatch_factor8 + + - dispatch_factor9 + - dispatch_factors_ts - dispatch_sched_weekday - dispatch_sched_weekend - - dispatch_tod_factors - - ppa_multiplier_model Functions diff --git a/docs/modules/MhkWave.rst b/docs/modules/MhkWave.rst index 1f079304..4d1a84aa 100644 --- a/docs/modules/MhkWave.rst +++ b/docs/modules/MhkWave.rst @@ -33,18 +33,18 @@ MHKWave Group .. autoclass:: PySAM.MhkWave.MhkWave.MHKWave :members: -AdjustmentFactors Group ------------------------- - -.. autoclass:: PySAM.MhkWave.MhkWave.AdjustmentFactors - :members: - Lifetime Group --------------- .. autoclass:: PySAM.MhkWave.MhkWave.Lifetime :members: +AdjustmentFactors Group +------------------------ + +.. autoclass:: PySAM.MhkWave.MhkWave.AdjustmentFactors + :members: + Outputs Group -------------- diff --git a/docs/modules/Pvsamv1.rst b/docs/modules/Pvsamv1.rst index ed906688..91210f91 100644 --- a/docs/modules/Pvsamv1.rst +++ b/docs/modules/Pvsamv1.rst @@ -53,14 +53,10 @@ The variables listed below are interdependent with other variables. If you chang - inv_cec_cg_psco - - inv_cec_cg_vdcmax - - inv_cec_cg_vdco - inv_ds_paco - - inv_ds_vdcmax - - inv_num_mppt - inv_pd_eff @@ -69,8 +65,6 @@ The variables listed below are interdependent with other variables. If you chang - inv_pd_pdco - - inv_pd_vdcmax - - inv_snl_c0 - inv_snl_c1 @@ -87,8 +81,6 @@ The variables listed below are interdependent with other variables. If you chang - inv_snl_pso - - inv_snl_vdcmax - - inv_snl_vdco - inverter_count @@ -361,12 +353,6 @@ Load Group .. autoclass:: PySAM.Pvsamv1.Pvsamv1.Load :members: -AdjustmentFactors Group ------------------------- - -.. autoclass:: PySAM.Pvsamv1.Pvsamv1.AdjustmentFactors - :members: - BatteryCell Group ------------------ @@ -415,6 +401,12 @@ GridLimits Group .. autoclass:: PySAM.Pvsamv1.Pvsamv1.GridLimits :members: +AdjustmentFactors Group +------------------------ + +.. autoclass:: PySAM.Pvsamv1.Pvsamv1.AdjustmentFactors + :members: + Outputs Group -------------- diff --git a/docs/modules/Pvwattsv1.rst b/docs/modules/Pvwattsv1.rst index 35640212..beaebb9d 100644 --- a/docs/modules/Pvwattsv1.rst +++ b/docs/modules/Pvwattsv1.rst @@ -33,12 +33,6 @@ PVWatts Group .. autoclass:: PySAM.Pvwattsv1.Pvwattsv1.PVWatts :members: -Shading Group --------------- - -.. autoclass:: PySAM.Pvwattsv1.Pvwattsv1.Shading - :members: - AdjustmentFactors Group ------------------------ diff --git a/docs/modules/Pvwattsv5.rst b/docs/modules/Pvwattsv5.rst index a57919ff..f1819f35 100644 --- a/docs/modules/Pvwattsv5.rst +++ b/docs/modules/Pvwattsv5.rst @@ -39,12 +39,6 @@ SystemDesign Group .. autoclass:: PySAM.Pvwattsv5.Pvwattsv5.SystemDesign :members: -Shading Group --------------- - -.. autoclass:: PySAM.Pvwattsv5.Pvwattsv5.Shading - :members: - AdjustmentFactors Group ------------------------ diff --git a/docs/modules/Pvwattsv7.rst b/docs/modules/Pvwattsv7.rst index 932859b2..af66d5bb 100644 --- a/docs/modules/Pvwattsv7.rst +++ b/docs/modules/Pvwattsv7.rst @@ -39,12 +39,6 @@ SystemDesign Group .. autoclass:: PySAM.Pvwattsv7.Pvwattsv7.SystemDesign :members: -Shading Group --------------- - -.. autoclass:: PySAM.Pvwattsv7.Pvwattsv7.Shading - :members: - AdjustmentFactors Group ------------------------ diff --git a/docs/modules/Pvwattsv8.rst b/docs/modules/Pvwattsv8.rst index d8eab473..35113845 100644 --- a/docs/modules/Pvwattsv8.rst +++ b/docs/modules/Pvwattsv8.rst @@ -39,12 +39,6 @@ SystemDesign Group .. autoclass:: PySAM.Pvwattsv8.Pvwattsv8.SystemDesign :members: -Shading Group --------------- - -.. autoclass:: PySAM.Pvwattsv8.Pvwattsv8.Shading - :members: - AdjustmentFactors Group ------------------------ diff --git a/docs/modules/Saleleaseback.rst b/docs/modules/Saleleaseback.rst index a7b73ec2..879e9471 100644 --- a/docs/modules/Saleleaseback.rst +++ b/docs/modules/Saleleaseback.rst @@ -83,6 +83,12 @@ SaleLeaseback Group .. autoclass:: PySAM.Saleleaseback.Saleleaseback.SaleLeaseback :members: +TimeOfDelivery Group +--------------------- + +.. autoclass:: PySAM.Saleleaseback.Saleleaseback.TimeOfDelivery + :members: + UtilityBill Group ------------------ diff --git a/docs/modules/Swh.rst b/docs/modules/Swh.rst index 93931f9e..e4b8582b 100644 --- a/docs/modules/Swh.rst +++ b/docs/modules/Swh.rst @@ -41,12 +41,6 @@ SWH Group .. autoclass:: PySAM.Swh.Swh.SWH :members: -Shading Group --------------- - -.. autoclass:: PySAM.Swh.Swh.Shading - :members: - AdjustmentFactors Group ------------------------ diff --git a/docs/modules/TroughPhysical.rst b/docs/modules/TroughPhysical.rst index d5180198..606a5ed2 100644 --- a/docs/modules/TroughPhysical.rst +++ b/docs/modules/TroughPhysical.rst @@ -68,12 +68,6 @@ ElectricityRates Group .. autoclass:: PySAM.TroughPhysical.TroughPhysical.ElectricityRates :members: -TimeOfDeliveryFactors Group ----------------------------- - -.. autoclass:: PySAM.TroughPhysical.TroughPhysical.TimeOfDeliveryFactors - :members: - Revenue Group -------------- diff --git a/docs/modules/TroughPhysicalProcessHeat.rst b/docs/modules/TroughPhysicalProcessHeat.rst index 94d8ce10..886d7131 100644 --- a/docs/modules/TroughPhysicalProcessHeat.rst +++ b/docs/modules/TroughPhysicalProcessHeat.rst @@ -62,12 +62,6 @@ SystemControl Group .. autoclass:: PySAM.TroughPhysicalProcessHeat.TroughPhysicalProcessHeat.SystemControl :members: -TimeOfDeliveryFactors Group ----------------------------- - -.. autoclass:: PySAM.TroughPhysicalProcessHeat.TroughPhysicalProcessHeat.TimeOfDeliveryFactors - :members: - System Group ------------- diff --git a/docs/modules/Windpower.rst b/docs/modules/Windpower.rst index 5659742a..2bfa4a87 100644 --- a/docs/modules/Windpower.rst +++ b/docs/modules/Windpower.rst @@ -65,18 +65,18 @@ Losses Group .. autoclass:: PySAM.Windpower.Windpower.Losses :members: -AdjustmentFactors Group ------------------------- - -.. autoclass:: PySAM.Windpower.Windpower.AdjustmentFactors - :members: - Uncertainty Group ------------------ .. autoclass:: PySAM.Windpower.Windpower.Uncertainty :members: +AdjustmentFactors Group +------------------------ + +.. autoclass:: PySAM.Windpower.Windpower.AdjustmentFactors + :members: + Outputs Group -------------- diff --git a/docs/version_changes/4.2.0.rst b/docs/version_changes/4.2.0.rst new file mode 100644 index 00000000..04f21333 --- /dev/null +++ b/docs/version_changes/4.2.0.rst @@ -0,0 +1,17 @@ +.. 4.2.0: + +Version 4.2.0 +=============================================== + +This page compares the PySAM Modules' input variables and the defaults for these input variables +between the current release and the last release. + +This helps track which variables and defaults have changed between releases to make it easier to notify users during version upgrade. + +Below are lists for each PySAM Module: + 1. New Default configurations + 2. Removed Default configurations + 3. Modified Variables: New variables, Removed variables and Type-changed variables + 4. Modified Default Values + +No changes diff --git a/docs/versions.rst b/docs/versions.rst index 14696651..cef2fc45 100644 --- a/docs/versions.rst +++ b/docs/versions.rst @@ -10,6 +10,7 @@ For a list of .. toctree:: :maxdepth: 2 + version_changes/4.2.0.rst version_changes/4.1.0.rst version_changes/4.0.0.rst version_changes/3.0.2.rst diff --git a/files/version.py b/files/version.py index fa721b49..ea5d65fc 100644 --- a/files/version.py +++ b/files/version.py @@ -1 +1 @@ -__version__ = '4.1.0' +__version__ = '4.2.0' diff --git a/files/version_differ.py b/files/version_differ.py index 03bf093e..3438adab 100644 --- a/files/version_differ.py +++ b/files/version_differ.py @@ -55,7 +55,7 @@ # To save the extracted file in directory of choice with same name as downloaded file. file_list_old = [] for tarinfo in tf: - if "defaults" in tarinfo.name and os.path.splitext(tarinfo.name)[1] == '.json': + if "api_autogen" in tarinfo.name and "defaults" in tarinfo.name and os.path.splitext(tarinfo.name)[1] == '.json': file_list_old.append(tarinfo.name) sam_path = os.environ.get('SAMNTDIR') @@ -243,7 +243,7 @@ def get_var_dict(): cmod_int = set(new_cmod_variables.keys()).intersection(set(old_cmod_variables.keys())) -for name in cmod_int: +for name in sorted(cmod_int): pysam_name = "".join([s.capitalize() for s in name.split('_')]) mod_variables = dict() @@ -333,3 +333,6 @@ def get_var_dict(): f.write(f" - {k}\n\n {list(v.keys())}\n\n") f.write("\n") f.write('\n') + + if len(doc_dict) == 0: + f.write(f'No changes\n') diff --git a/modules/Biomass.c b/modules/Biomass.c index 00630722..cc7967eb 100644 --- a/modules/Biomass.c +++ b/modules/Biomass.c @@ -2753,6 +2753,25 @@ BiomassModule_exec(PyObject *m) Biomass_Type.tp_dict = PyDict_New(); if (!Biomass_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Biomass_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Biomass_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Biopower type object to Biomass_Type if (PyType_Ready(&Biopower_Type) < 0) { goto fail; } PyDict_SetItemString(Biomass_Type.tp_dict, diff --git a/modules/Equpartflip.c b/modules/Equpartflip.c index c19dbd77..9897c3ac 100644 --- a/modules/Equpartflip.c +++ b/modules/Equpartflip.c @@ -77,54 +77,6 @@ static PyMethodDef Revenue_methods[] = { {NULL, NULL} /* sentinel */ }; -static PyObject * -Revenue_get_dispatch_factors_ts(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Equpartflip_Revenue_dispatch_factors_ts_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Equpartflip_Revenue_dispatch_factors_ts_aset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Equpartflip_Revenue_dispatch_sched_weekday_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Equpartflip_Revenue_dispatch_sched_weekday_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Equpartflip_Revenue_dispatch_sched_weekend_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Equpartflip_Revenue_dispatch_sched_weekend_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Equpartflip_Revenue_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Equpartflip_Revenue_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * Revenue_get_ppa_escalation(VarGroupObject *self, void *closure) { @@ -137,18 +89,6 @@ Revenue_set_ppa_escalation(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_Equpartflip_Revenue_ppa_escalation_nset, self->data_ptr); } -static PyObject * -Revenue_get_ppa_multiplier_model(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Equpartflip_Revenue_ppa_multiplier_model_nget, self->data_ptr); -} - -static int -Revenue_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Equpartflip_Revenue_ppa_multiplier_model_nset, self->data_ptr); -} - static PyObject * Revenue_get_ppa_price_input(VarGroupObject *self, void *closure) { @@ -222,24 +162,9 @@ Revenue_set_ppa_soln_tolerance(VarGroupObject *self, PyObject *value, void *clos } static PyGetSetDef Revenue_getset[] = { -{"dispatch_factors_ts", (getter)Revenue_get_dispatch_factors_ts,(setter)Revenue_set_dispatch_factors_ts, - PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), - NULL}, -{"dispatch_sched_weekday", (getter)Revenue_get_dispatch_sched_weekday,(setter)Revenue_set_dispatch_sched_weekday, - PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_sched_weekend", (getter)Revenue_get_dispatch_sched_weekend,(setter)Revenue_set_dispatch_sched_weekend, - PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_tod_factors", (getter)Revenue_get_dispatch_tod_factors,(setter)Revenue_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, {"ppa_escalation", (getter)Revenue_get_ppa_escalation,(setter)Revenue_set_ppa_escalation, PyDoc_STR("*float*: PPA escalation rate [%/year]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, -{"ppa_multiplier_model", (getter)Revenue_get_ppa_multiplier_model,(setter)Revenue_set_ppa_multiplier_model, - PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"ppa_price_input", (getter)Revenue_get_ppa_price_input,(setter)Revenue_set_ppa_price_input, PyDoc_STR("*sequence*: PPA price in first year input [$/kWh]\n\n**Required:**\nTrue"), NULL}, @@ -4702,6 +4627,162 @@ static PyMethodDef TimeOfDelivery_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +TimeOfDelivery_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factor9_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factors_ts(VarGroupObject *self, void *closure) +{ + return PySAM_array_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_factors_ts_aget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_array_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_factors_ts_aset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_sched_weekday_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_sched_weekday_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Equpartflip_TimeOfDelivery_dispatch_sched_weekend_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Equpartflip_TimeOfDelivery_dispatch_sched_weekend_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_ppa_multiplier_model(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Equpartflip_TimeOfDelivery_ppa_multiplier_model_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Equpartflip_TimeOfDelivery_ppa_multiplier_model_nset, self->data_ptr); +} + static PyObject * TimeOfDelivery_get_system_use_lifetime_output(VarGroupObject *self, void *closure) { @@ -4715,6 +4796,45 @@ TimeOfDelivery_set_system_use_lifetime_output(VarGroupObject *self, PyObject *va } static PyGetSetDef TimeOfDelivery_getset[] = { +{"dispatch_factor1", (getter)TimeOfDelivery_get_dispatch_factor1,(setter)TimeOfDelivery_set_dispatch_factor1, + PyDoc_STR("*float*: TOD factor for period 1\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDelivery_get_dispatch_factor2,(setter)TimeOfDelivery_set_dispatch_factor2, + PyDoc_STR("*float*: TOD factor for period 2\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDelivery_get_dispatch_factor3,(setter)TimeOfDelivery_set_dispatch_factor3, + PyDoc_STR("*float*: TOD factor for period 3\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDelivery_get_dispatch_factor4,(setter)TimeOfDelivery_set_dispatch_factor4, + PyDoc_STR("*float*: TOD factor for period 4\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDelivery_get_dispatch_factor5,(setter)TimeOfDelivery_set_dispatch_factor5, + PyDoc_STR("*float*: TOD factor for period 5\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDelivery_get_dispatch_factor6,(setter)TimeOfDelivery_set_dispatch_factor6, + PyDoc_STR("*float*: TOD factor for period 6\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDelivery_get_dispatch_factor7,(setter)TimeOfDelivery_set_dispatch_factor7, + PyDoc_STR("*float*: TOD factor for period 7\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDelivery_get_dispatch_factor8,(setter)TimeOfDelivery_set_dispatch_factor8, + PyDoc_STR("*float*: TOD factor for period 8\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDelivery_get_dispatch_factor9,(setter)TimeOfDelivery_set_dispatch_factor9, + PyDoc_STR("*float*: TOD factor for period 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factors_ts", (getter)TimeOfDelivery_get_dispatch_factors_ts,(setter)TimeOfDelivery_set_dispatch_factors_ts, + PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), + NULL}, +{"dispatch_sched_weekday", (getter)TimeOfDelivery_get_dispatch_sched_weekday,(setter)TimeOfDelivery_set_dispatch_sched_weekday, + PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_sched_weekend", (getter)TimeOfDelivery_get_dispatch_sched_weekend,(setter)TimeOfDelivery_set_dispatch_sched_weekend, + PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"ppa_multiplier_model", (getter)TimeOfDelivery_get_ppa_multiplier_model,(setter)TimeOfDelivery_set_ppa_multiplier_model, + PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), + NULL}, {"system_use_lifetime_output", (getter)TimeOfDelivery_get_system_use_lifetime_output,(setter)TimeOfDelivery_set_system_use_lifetime_output, PyDoc_STR("*float*: Lifetime hourly system outputs [0/1]\n\n**Options:**\n0=hourly first year,1=hourly lifetime\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nTrue"), NULL}, diff --git a/modules/EtesElectricResistance.c b/modules/EtesElectricResistance.c index 8495caa8..24fb63b4 100644 --- a/modules/EtesElectricResistance.c +++ b/modules/EtesElectricResistance.c @@ -2255,6 +2255,114 @@ static PyMethodDef TimeOfDeliveryFactors_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_factor9_nset, self->data_ptr); +} + static PyObject * TimeOfDeliveryFactors_get_dispatch_factors_ts(VarGroupObject *self, void *closure) { @@ -2291,18 +2399,6 @@ TimeOfDeliveryFactors_set_dispatch_sched_weekend(VarGroupObject *self, PyObject return PySAM_matrix_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_sched_weekend_mset, self->data_ptr); } -static PyObject * -TimeOfDeliveryFactors_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -TimeOfDeliveryFactors_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_EtesElectricResistance_TimeOfDeliveryFactors_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * TimeOfDeliveryFactors_get_ppa_multiplier_model(VarGroupObject *self, void *closure) { @@ -2316,6 +2412,33 @@ TimeOfDeliveryFactors_set_ppa_multiplier_model(VarGroupObject *self, PyObject *v } static PyGetSetDef TimeOfDeliveryFactors_getset[] = { +{"dispatch_factor1", (getter)TimeOfDeliveryFactors_get_dispatch_factor1,(setter)TimeOfDeliveryFactors_set_dispatch_factor1, + PyDoc_STR("*float*: Dispatch payment factor 1\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDeliveryFactors_get_dispatch_factor2,(setter)TimeOfDeliveryFactors_set_dispatch_factor2, + PyDoc_STR("*float*: Dispatch payment factor 2\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDeliveryFactors_get_dispatch_factor3,(setter)TimeOfDeliveryFactors_set_dispatch_factor3, + PyDoc_STR("*float*: Dispatch payment factor 3\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDeliveryFactors_get_dispatch_factor4,(setter)TimeOfDeliveryFactors_set_dispatch_factor4, + PyDoc_STR("*float*: Dispatch payment factor 4\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDeliveryFactors_get_dispatch_factor5,(setter)TimeOfDeliveryFactors_set_dispatch_factor5, + PyDoc_STR("*float*: Dispatch payment factor 5\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDeliveryFactors_get_dispatch_factor6,(setter)TimeOfDeliveryFactors_set_dispatch_factor6, + PyDoc_STR("*float*: Dispatch payment factor 6\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDeliveryFactors_get_dispatch_factor7,(setter)TimeOfDeliveryFactors_set_dispatch_factor7, + PyDoc_STR("*float*: Dispatch payment factor 7\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDeliveryFactors_get_dispatch_factor8,(setter)TimeOfDeliveryFactors_set_dispatch_factor8, + PyDoc_STR("*float*: Dispatch payment factor 8\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDeliveryFactors_get_dispatch_factor9,(setter)TimeOfDeliveryFactors_set_dispatch_factor9, + PyDoc_STR("*float*: Dispatch payment factor 9\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, {"dispatch_factors_ts", (getter)TimeOfDeliveryFactors_get_dispatch_factors_ts,(setter)TimeOfDeliveryFactors_set_dispatch_factors_ts, PyDoc_STR("*sequence*: Dispatch payment factor timeseries array\n\n**Required:**\nRequired if ppa_multiplier_model=1&etes_financial_model<5&is_dispatch=1&sim_type=1"), NULL}, @@ -2325,9 +2448,6 @@ static PyGetSetDef TimeOfDeliveryFactors_getset[] = { {"dispatch_sched_weekend", (getter)TimeOfDeliveryFactors_get_dispatch_sched_weekend,(setter)TimeOfDeliveryFactors_set_dispatch_sched_weekend, PyDoc_STR("*sequence[sequence]*: PPA pricing weekend schedule, 12x24\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), NULL}, -{"dispatch_tod_factors", (getter)TimeOfDeliveryFactors_get_dispatch_tod_factors,(setter)TimeOfDeliveryFactors_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Info:**\nWe added this array input after SAM 2022.12.21 to replace the functionality of former single value inputs dispatch_factor1 through dispatch_factor9\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), - NULL}, {"ppa_multiplier_model", (getter)TimeOfDeliveryFactors_get_ppa_multiplier_model,(setter)TimeOfDeliveryFactors_set_ppa_multiplier_model, PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, @@ -5060,6 +5180,25 @@ EtesElectricResistanceModule_exec(PyObject *m) EtesElectricResistance_Type.tp_dict = PyDict_New(); if (!EtesElectricResistance_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to EtesElectricResistance_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(EtesElectricResistance_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to EtesElectricResistance_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(EtesElectricResistance_Type.tp_dict, diff --git a/modules/EtesPtes.c b/modules/EtesPtes.c index 1fe27311..66cb6c86 100644 --- a/modules/EtesPtes.c +++ b/modules/EtesPtes.c @@ -2225,6 +2225,114 @@ static PyMethodDef TimeOfDeliveryFactors_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_factor9_nset, self->data_ptr); +} + static PyObject * TimeOfDeliveryFactors_get_dispatch_factors_ts(VarGroupObject *self, void *closure) { @@ -2261,18 +2369,6 @@ TimeOfDeliveryFactors_set_dispatch_sched_weekend(VarGroupObject *self, PyObject return PySAM_matrix_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_sched_weekend_mset, self->data_ptr); } -static PyObject * -TimeOfDeliveryFactors_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -TimeOfDeliveryFactors_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_EtesPtes_TimeOfDeliveryFactors_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * TimeOfDeliveryFactors_get_ppa_multiplier_model(VarGroupObject *self, void *closure) { @@ -2286,6 +2382,33 @@ TimeOfDeliveryFactors_set_ppa_multiplier_model(VarGroupObject *self, PyObject *v } static PyGetSetDef TimeOfDeliveryFactors_getset[] = { +{"dispatch_factor1", (getter)TimeOfDeliveryFactors_get_dispatch_factor1,(setter)TimeOfDeliveryFactors_set_dispatch_factor1, + PyDoc_STR("*float*: Dispatch payment factor 1\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDeliveryFactors_get_dispatch_factor2,(setter)TimeOfDeliveryFactors_set_dispatch_factor2, + PyDoc_STR("*float*: Dispatch payment factor 2\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDeliveryFactors_get_dispatch_factor3,(setter)TimeOfDeliveryFactors_set_dispatch_factor3, + PyDoc_STR("*float*: Dispatch payment factor 3\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDeliveryFactors_get_dispatch_factor4,(setter)TimeOfDeliveryFactors_set_dispatch_factor4, + PyDoc_STR("*float*: Dispatch payment factor 4\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDeliveryFactors_get_dispatch_factor5,(setter)TimeOfDeliveryFactors_set_dispatch_factor5, + PyDoc_STR("*float*: Dispatch payment factor 5\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDeliveryFactors_get_dispatch_factor6,(setter)TimeOfDeliveryFactors_set_dispatch_factor6, + PyDoc_STR("*float*: Dispatch payment factor 6\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDeliveryFactors_get_dispatch_factor7,(setter)TimeOfDeliveryFactors_set_dispatch_factor7, + PyDoc_STR("*float*: Dispatch payment factor 7\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDeliveryFactors_get_dispatch_factor8,(setter)TimeOfDeliveryFactors_set_dispatch_factor8, + PyDoc_STR("*float*: Dispatch payment factor 8\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDeliveryFactors_get_dispatch_factor9,(setter)TimeOfDeliveryFactors_set_dispatch_factor9, + PyDoc_STR("*float*: Dispatch payment factor 9\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, {"dispatch_factors_ts", (getter)TimeOfDeliveryFactors_get_dispatch_factors_ts,(setter)TimeOfDeliveryFactors_set_dispatch_factors_ts, PyDoc_STR("*sequence*: Dispatch payment factor timeseries array\n\n**Required:**\nRequired if ppa_multiplier_model=1&etes_financial_model<5&is_dispatch=1&sim_type=1"), NULL}, @@ -2295,9 +2418,6 @@ static PyGetSetDef TimeOfDeliveryFactors_getset[] = { {"dispatch_sched_weekend", (getter)TimeOfDeliveryFactors_get_dispatch_sched_weekend,(setter)TimeOfDeliveryFactors_set_dispatch_sched_weekend, PyDoc_STR("*sequence[sequence]*: PPA pricing weekend schedule, 12x24\n\n**Required:**\nRequired if ppa_multiplier_model=0&etes_financial_model<5&is_dispatch=1&sim_type=1"), NULL}, -{"dispatch_tod_factors", (getter)TimeOfDeliveryFactors_get_dispatch_tod_factors,(setter)TimeOfDeliveryFactors_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Info:**\nWe added this array input after SAM 2022.12.21 to replace the functionality of former single value inputs dispatch_factor1 through dispatch_factor9\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), - NULL}, {"ppa_multiplier_model", (getter)TimeOfDeliveryFactors_get_ppa_multiplier_model,(setter)TimeOfDeliveryFactors_set_ppa_multiplier_model, PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, @@ -3961,24 +4081,6 @@ Outputs_get_op_mode_3(VarGroupObject *self, void *closure) return PySAM_array_getter(SAM_EtesPtes_Outputs_op_mode_3_aget, self->data_ptr); } -static PyObject * -Outputs_get_operating_modes_a(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_EtesPtes_Outputs_operating_modes_a_aget, self->data_ptr); -} - -static PyObject * -Outputs_get_operating_modes_b(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_EtesPtes_Outputs_operating_modes_b_aget, self->data_ptr); -} - -static PyObject * -Outputs_get_operating_modes_c(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_EtesPtes_Outputs_operating_modes_c_aget, self->data_ptr); -} - static PyObject * Outputs_get_ppa_soln_mode(VarGroupObject *self, void *closure) { @@ -4532,15 +4634,6 @@ static PyGetSetDef Outputs_getset[] = { {"op_mode_3", (getter)Outputs_get_op_mode_3,(setter)0, PyDoc_STR("*sequence*: 3rd operating mode, if applicable"), NULL}, -{"operating_modes_a", (getter)Outputs_get_operating_modes_a,(setter)0, - PyDoc_STR("*sequence*: First 3 operating modes tried"), - NULL}, -{"operating_modes_b", (getter)Outputs_get_operating_modes_b,(setter)0, - PyDoc_STR("*sequence*: Next 3 operating modes tried"), - NULL}, -{"operating_modes_c", (getter)Outputs_get_operating_modes_c,(setter)0, - PyDoc_STR("*sequence*: Final 3 operating modes tried"), - NULL}, {"ppa_soln_mode", (getter)Outputs_get_ppa_soln_mode,(setter)0, PyDoc_STR("*float*: PPA solution mode [0/1]"), NULL}, @@ -5066,6 +5159,25 @@ EtesPtesModule_exec(PyObject *m) EtesPtes_Type.tp_dict = PyDict_New(); if (!EtesPtes_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to EtesPtes_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(EtesPtes_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to EtesPtes_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(EtesPtes_Type.tp_dict, diff --git a/modules/GenericSystem.c b/modules/GenericSystem.c index 4d456863..6ad4164f 100644 --- a/modules/GenericSystem.c +++ b/modules/GenericSystem.c @@ -920,6 +920,25 @@ GenericSystemModule_exec(PyObject *m) GenericSystem_Type.tp_dict = PyDict_New(); if (!GenericSystem_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to GenericSystem_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(GenericSystem_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Plant type object to GenericSystem_Type if (PyType_Ready(&Plant_Type) < 0) { goto fail; } PyDict_SetItemString(GenericSystem_Type.tp_dict, diff --git a/modules/Geothermal.c b/modules/Geothermal.c index 081e9808..0e3dd271 100644 --- a/modules/Geothermal.c +++ b/modules/Geothermal.c @@ -2282,6 +2282,25 @@ GeothermalModule_exec(PyObject *m) Geothermal_Type.tp_dict = PyDict_New(); if (!Geothermal_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Geothermal_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Geothermal_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the GeoHourly type object to Geothermal_Type if (PyType_Ready(&GeoHourly_Type) < 0) { goto fail; } PyDict_SetItemString(Geothermal_Type.tp_dict, diff --git a/modules/Hcpv.c b/modules/Hcpv.c index 20993c9b..8068a6c4 100644 --- a/modules/Hcpv.c +++ b/modules/Hcpv.c @@ -2114,6 +2114,25 @@ HcpvModule_exec(PyObject *m) Hcpv_Type.tp_dict = PyDict_New(); if (!Hcpv_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Hcpv_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Hcpv_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResourceData type object to Hcpv_Type if (PyType_Ready(&SolarResourceData_Type) < 0) { goto fail; } PyDict_SetItemString(Hcpv_Type.tp_dict, diff --git a/modules/HostDeveloper.c b/modules/HostDeveloper.c index 249ada05..f3140375 100644 --- a/modules/HostDeveloper.c +++ b/modules/HostDeveloper.c @@ -77,54 +77,6 @@ static PyMethodDef Revenue_methods[] = { {NULL, NULL} /* sentinel */ }; -static PyObject * -Revenue_get_dispatch_factors_ts(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_HostDeveloper_Revenue_dispatch_factors_ts_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_HostDeveloper_Revenue_dispatch_factors_ts_aset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_HostDeveloper_Revenue_dispatch_sched_weekday_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_HostDeveloper_Revenue_dispatch_sched_weekday_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_HostDeveloper_Revenue_dispatch_sched_weekend_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_HostDeveloper_Revenue_dispatch_sched_weekend_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_HostDeveloper_Revenue_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_HostDeveloper_Revenue_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * Revenue_get_flip_target_percent(VarGroupObject *self, void *closure) { @@ -161,18 +113,6 @@ Revenue_set_ppa_escalation(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_HostDeveloper_Revenue_ppa_escalation_nset, self->data_ptr); } -static PyObject * -Revenue_get_ppa_multiplier_model(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_HostDeveloper_Revenue_ppa_multiplier_model_nget, self->data_ptr); -} - -static int -Revenue_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_HostDeveloper_Revenue_ppa_multiplier_model_nset, self->data_ptr); -} - static PyObject * Revenue_get_ppa_price_input(VarGroupObject *self, void *closure) { @@ -246,18 +186,6 @@ Revenue_set_ppa_soln_tolerance(VarGroupObject *self, PyObject *value, void *clos } static PyGetSetDef Revenue_getset[] = { -{"dispatch_factors_ts", (getter)Revenue_get_dispatch_factors_ts,(setter)Revenue_set_dispatch_factors_ts, - PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), - NULL}, -{"dispatch_sched_weekday", (getter)Revenue_get_dispatch_sched_weekday,(setter)Revenue_set_dispatch_sched_weekday, - PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_sched_weekend", (getter)Revenue_get_dispatch_sched_weekend,(setter)Revenue_set_dispatch_sched_weekend, - PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_tod_factors", (getter)Revenue_get_dispatch_tod_factors,(setter)Revenue_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, {"flip_target_percent", (getter)Revenue_get_flip_target_percent,(setter)Revenue_set_flip_target_percent, PyDoc_STR("*float*: After-tax IRR target [%]\n\n**Constraints:**\nMIN=0,MAX=100\n\n**Required:**\nFalse. Automatically set to 11 if not assigned explicitly or loaded from defaults."), NULL}, @@ -267,9 +195,6 @@ static PyGetSetDef Revenue_getset[] = { {"ppa_escalation", (getter)Revenue_get_ppa_escalation,(setter)Revenue_set_ppa_escalation, PyDoc_STR("*float*: PPA escalation rate [%/year]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, -{"ppa_multiplier_model", (getter)Revenue_get_ppa_multiplier_model,(setter)Revenue_set_ppa_multiplier_model, - PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"ppa_price_input", (getter)Revenue_get_ppa_price_input,(setter)Revenue_set_ppa_price_input, PyDoc_STR("*sequence*: PPA price in first year input [$/kWh]\n\n**Required:**\nTrue"), NULL}, @@ -5578,6 +5503,162 @@ static PyMethodDef TimeOfDelivery_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +TimeOfDelivery_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factor9_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factors_ts(VarGroupObject *self, void *closure) +{ + return PySAM_array_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_factors_ts_aget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_array_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_factors_ts_aset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_sched_weekday_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_sched_weekday_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_HostDeveloper_TimeOfDelivery_dispatch_sched_weekend_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_HostDeveloper_TimeOfDelivery_dispatch_sched_weekend_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_ppa_multiplier_model(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_HostDeveloper_TimeOfDelivery_ppa_multiplier_model_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_HostDeveloper_TimeOfDelivery_ppa_multiplier_model_nset, self->data_ptr); +} + static PyObject * TimeOfDelivery_get_system_use_lifetime_output(VarGroupObject *self, void *closure) { @@ -5591,6 +5672,45 @@ TimeOfDelivery_set_system_use_lifetime_output(VarGroupObject *self, PyObject *va } static PyGetSetDef TimeOfDelivery_getset[] = { +{"dispatch_factor1", (getter)TimeOfDelivery_get_dispatch_factor1,(setter)TimeOfDelivery_set_dispatch_factor1, + PyDoc_STR("*float*: TOD factor for period 1\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDelivery_get_dispatch_factor2,(setter)TimeOfDelivery_set_dispatch_factor2, + PyDoc_STR("*float*: TOD factor for period 2\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDelivery_get_dispatch_factor3,(setter)TimeOfDelivery_set_dispatch_factor3, + PyDoc_STR("*float*: TOD factor for period 3\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDelivery_get_dispatch_factor4,(setter)TimeOfDelivery_set_dispatch_factor4, + PyDoc_STR("*float*: TOD factor for period 4\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDelivery_get_dispatch_factor5,(setter)TimeOfDelivery_set_dispatch_factor5, + PyDoc_STR("*float*: TOD factor for period 5\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDelivery_get_dispatch_factor6,(setter)TimeOfDelivery_set_dispatch_factor6, + PyDoc_STR("*float*: TOD factor for period 6\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDelivery_get_dispatch_factor7,(setter)TimeOfDelivery_set_dispatch_factor7, + PyDoc_STR("*float*: TOD factor for period 7\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDelivery_get_dispatch_factor8,(setter)TimeOfDelivery_set_dispatch_factor8, + PyDoc_STR("*float*: TOD factor for period 8\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDelivery_get_dispatch_factor9,(setter)TimeOfDelivery_set_dispatch_factor9, + PyDoc_STR("*float*: TOD factor for period 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factors_ts", (getter)TimeOfDelivery_get_dispatch_factors_ts,(setter)TimeOfDelivery_set_dispatch_factors_ts, + PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), + NULL}, +{"dispatch_sched_weekday", (getter)TimeOfDelivery_get_dispatch_sched_weekday,(setter)TimeOfDelivery_set_dispatch_sched_weekday, + PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_sched_weekend", (getter)TimeOfDelivery_get_dispatch_sched_weekend,(setter)TimeOfDelivery_set_dispatch_sched_weekend, + PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"ppa_multiplier_model", (getter)TimeOfDelivery_get_ppa_multiplier_model,(setter)TimeOfDelivery_set_ppa_multiplier_model, + PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), + NULL}, {"system_use_lifetime_output", (getter)TimeOfDelivery_get_system_use_lifetime_output,(setter)TimeOfDelivery_set_system_use_lifetime_output, PyDoc_STR("*float*: Lifetime hourly system outputs [0/1]\n\n**Options:**\n0=hourly first year,1=hourly lifetime\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nTrue"), NULL}, diff --git a/modules/Levpartflip.c b/modules/Levpartflip.c index 06b67a8a..b00a60ee 100644 --- a/modules/Levpartflip.c +++ b/modules/Levpartflip.c @@ -77,54 +77,6 @@ static PyMethodDef Revenue_methods[] = { {NULL, NULL} /* sentinel */ }; -static PyObject * -Revenue_get_dispatch_factors_ts(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Levpartflip_Revenue_dispatch_factors_ts_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Levpartflip_Revenue_dispatch_factors_ts_aset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Levpartflip_Revenue_dispatch_sched_weekday_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Levpartflip_Revenue_dispatch_sched_weekday_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Levpartflip_Revenue_dispatch_sched_weekend_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Levpartflip_Revenue_dispatch_sched_weekend_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Levpartflip_Revenue_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Levpartflip_Revenue_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * Revenue_get_flip_target_percent(VarGroupObject *self, void *closure) { @@ -161,18 +113,6 @@ Revenue_set_ppa_escalation(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_Levpartflip_Revenue_ppa_escalation_nset, self->data_ptr); } -static PyObject * -Revenue_get_ppa_multiplier_model(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Levpartflip_Revenue_ppa_multiplier_model_nget, self->data_ptr); -} - -static int -Revenue_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Levpartflip_Revenue_ppa_multiplier_model_nset, self->data_ptr); -} - static PyObject * Revenue_get_ppa_price_input(VarGroupObject *self, void *closure) { @@ -246,18 +186,6 @@ Revenue_set_ppa_soln_tolerance(VarGroupObject *self, PyObject *value, void *clos } static PyGetSetDef Revenue_getset[] = { -{"dispatch_factors_ts", (getter)Revenue_get_dispatch_factors_ts,(setter)Revenue_set_dispatch_factors_ts, - PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), - NULL}, -{"dispatch_sched_weekday", (getter)Revenue_get_dispatch_sched_weekday,(setter)Revenue_set_dispatch_sched_weekday, - PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_sched_weekend", (getter)Revenue_get_dispatch_sched_weekend,(setter)Revenue_set_dispatch_sched_weekend, - PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_tod_factors", (getter)Revenue_get_dispatch_tod_factors,(setter)Revenue_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, {"flip_target_percent", (getter)Revenue_get_flip_target_percent,(setter)Revenue_set_flip_target_percent, PyDoc_STR("*float*: After-tax IRR target [%]\n\n**Constraints:**\nMIN=0,MAX=100\n\n**Required:**\nFalse. Automatically set to 11 if not assigned explicitly or loaded from defaults."), NULL}, @@ -267,9 +195,6 @@ static PyGetSetDef Revenue_getset[] = { {"ppa_escalation", (getter)Revenue_get_ppa_escalation,(setter)Revenue_set_ppa_escalation, PyDoc_STR("*float*: PPA escalation rate [%/year]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, -{"ppa_multiplier_model", (getter)Revenue_get_ppa_multiplier_model,(setter)Revenue_set_ppa_multiplier_model, - PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"ppa_price_input", (getter)Revenue_get_ppa_price_input,(setter)Revenue_set_ppa_price_input, PyDoc_STR("*sequence*: PPA price in first year input [$/kWh]\n\n**Required:**\nTrue"), NULL}, @@ -5139,6 +5064,162 @@ static PyMethodDef TimeOfDelivery_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +TimeOfDelivery_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factor9_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factors_ts(VarGroupObject *self, void *closure) +{ + return PySAM_array_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_factors_ts_aget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_array_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_factors_ts_aset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_sched_weekday_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_sched_weekday_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Levpartflip_TimeOfDelivery_dispatch_sched_weekend_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Levpartflip_TimeOfDelivery_dispatch_sched_weekend_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_ppa_multiplier_model(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Levpartflip_TimeOfDelivery_ppa_multiplier_model_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Levpartflip_TimeOfDelivery_ppa_multiplier_model_nset, self->data_ptr); +} + static PyObject * TimeOfDelivery_get_system_use_lifetime_output(VarGroupObject *self, void *closure) { @@ -5152,6 +5233,45 @@ TimeOfDelivery_set_system_use_lifetime_output(VarGroupObject *self, PyObject *va } static PyGetSetDef TimeOfDelivery_getset[] = { +{"dispatch_factor1", (getter)TimeOfDelivery_get_dispatch_factor1,(setter)TimeOfDelivery_set_dispatch_factor1, + PyDoc_STR("*float*: TOD factor for period 1\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDelivery_get_dispatch_factor2,(setter)TimeOfDelivery_set_dispatch_factor2, + PyDoc_STR("*float*: TOD factor for period 2\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDelivery_get_dispatch_factor3,(setter)TimeOfDelivery_set_dispatch_factor3, + PyDoc_STR("*float*: TOD factor for period 3\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDelivery_get_dispatch_factor4,(setter)TimeOfDelivery_set_dispatch_factor4, + PyDoc_STR("*float*: TOD factor for period 4\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDelivery_get_dispatch_factor5,(setter)TimeOfDelivery_set_dispatch_factor5, + PyDoc_STR("*float*: TOD factor for period 5\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDelivery_get_dispatch_factor6,(setter)TimeOfDelivery_set_dispatch_factor6, + PyDoc_STR("*float*: TOD factor for period 6\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDelivery_get_dispatch_factor7,(setter)TimeOfDelivery_set_dispatch_factor7, + PyDoc_STR("*float*: TOD factor for period 7\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDelivery_get_dispatch_factor8,(setter)TimeOfDelivery_set_dispatch_factor8, + PyDoc_STR("*float*: TOD factor for period 8\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDelivery_get_dispatch_factor9,(setter)TimeOfDelivery_set_dispatch_factor9, + PyDoc_STR("*float*: TOD factor for period 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factors_ts", (getter)TimeOfDelivery_get_dispatch_factors_ts,(setter)TimeOfDelivery_set_dispatch_factors_ts, + PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), + NULL}, +{"dispatch_sched_weekday", (getter)TimeOfDelivery_get_dispatch_sched_weekday,(setter)TimeOfDelivery_set_dispatch_sched_weekday, + PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_sched_weekend", (getter)TimeOfDelivery_get_dispatch_sched_weekend,(setter)TimeOfDelivery_set_dispatch_sched_weekend, + PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"ppa_multiplier_model", (getter)TimeOfDelivery_get_ppa_multiplier_model,(setter)TimeOfDelivery_set_ppa_multiplier_model, + PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), + NULL}, {"system_use_lifetime_output", (getter)TimeOfDelivery_get_system_use_lifetime_output,(setter)TimeOfDelivery_set_system_use_lifetime_output, PyDoc_STR("*float*: Lifetime hourly system outputs [0/1]\n\n**Options:**\n0=hourly first year,1=hourly lifetime\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nTrue"), NULL}, diff --git a/modules/LinearFresnelDsgIph.c b/modules/LinearFresnelDsgIph.c index b66d2ab2..7daddcb3 100644 --- a/modules/LinearFresnelDsgIph.c +++ b/modules/LinearFresnelDsgIph.c @@ -2534,6 +2534,25 @@ LinearFresnelDsgIphModule_exec(PyObject *m) LinearFresnelDsgIph_Type.tp_dict = PyDict_New(); if (!LinearFresnelDsgIph_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to LinearFresnelDsgIph_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(LinearFresnelDsgIph_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to LinearFresnelDsgIph_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(LinearFresnelDsgIph_Type.tp_dict, diff --git a/modules/MhkWave.c b/modules/MhkWave.c index 119eb954..8d81efdf 100644 --- a/modules/MhkWave.c +++ b/modules/MhkWave.c @@ -1166,6 +1166,10 @@ newMhkWaveObject(void* data_ptr) PyDict_SetItemString(attr_dict, "MHKWave", MHKWave_obj); Py_DECREF(MHKWave_obj); + PyObject* Lifetime_obj = Lifetime_new(self->data_ptr); + PyDict_SetItemString(attr_dict, "Lifetime", Lifetime_obj); + Py_DECREF(Lifetime_obj); + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1181,10 +1185,6 @@ newMhkWaveObject(void* data_ptr) PyDict_SetItemString(attr_dict, "AdjustmentFactors", Adjust_obj); Py_DECREF(Adjust_obj); - PyObject* Lifetime_obj = Lifetime_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Lifetime", Lifetime_obj); - Py_DECREF(Lifetime_obj); - PyObject* Outputs_obj = Outputs_new(self->data_ptr); PyDict_SetItemString(attr_dict, "Outputs", Outputs_obj); Py_DECREF(Outputs_obj); @@ -1466,6 +1466,25 @@ MhkWaveModule_exec(PyObject *m) MhkWave_Type.tp_dict = PyDict_New(); if (!MhkWave_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to MhkWave_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(MhkWave_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the MHKWave type object to MhkWave_Type if (PyType_Ready(&MHKWave_Type) < 0) { goto fail; } PyDict_SetItemString(MhkWave_Type.tp_dict, diff --git a/modules/Pvsamv1.c b/modules/Pvsamv1.c index 6b87d576..4ff17172 100644 --- a/modules/Pvsamv1.c +++ b/modules/Pvsamv1.c @@ -2085,7 +2085,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Enable mismatched subarray Vmax calculation\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, {"inverter_count", (getter)SystemDesign_get_inverter_count,(setter)SystemDesign_set_inverter_count, - PyDoc_STR("*float*: Number of inverters\n\n**Constraints:**\nINTEGER,POSITIVE\n\n**Required:**\nTrue\n\nThe value of ``inverter_count`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Number of inverters\n\n**Constraints:**\nINTEGER,POSITIVE\n\n**Required:**\nTrue\n\nThe value of ``inverter_count`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"measured_temp_array", (getter)SystemDesign_get_measured_temp_array,(setter)SystemDesign_set_measured_temp_array, PyDoc_STR("*sequence*: Measured module temperature [C]\n\n**Required:**\nRequired if use_measured_temp=1"), @@ -2100,7 +2100,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Sub-array 1 Ground coverage ratio [0..1]\n\n**Constraints:**\nMIN=0.01,MAX=0.99\n\n**Required:**\nFalse. Automatically set to 0.3 if not assigned explicitly or loaded from defaults."), NULL}, {"subarray1_modules_per_string", (getter)SystemDesign_get_subarray1_modules_per_string,(setter)SystemDesign_set_subarray1_modules_per_string, - PyDoc_STR("*float*: Sub-array 1 Modules per string\n\n**Constraints:**\nINTEGER,POSITIVE\n\n**Required:**\nTrue\n\nThe value of the following variables depends on ``subarray1_modules_per_string``:\n\n\t - system_capacity\n\n\nThe value of ``subarray1_modules_per_string`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Sub-array 1 Modules per string\n\n**Constraints:**\nINTEGER,POSITIVE\n\n**Required:**\nTrue\n\nThe value of the following variables depends on ``subarray1_modules_per_string``:\n\n\t - system_capacity\n\n\nThe value of ``subarray1_modules_per_string`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"subarray1_monthly_tilt", (getter)SystemDesign_get_subarray1_monthly_tilt,(setter)SystemDesign_set_subarray1_monthly_tilt, PyDoc_STR("*sequence*: Sub-array 1 monthly tilt input [degrees]\n\n**Constraints:**\nLENGTH=12\n\n**Required:**\nRequired if subarray1_track_mode=4"), @@ -2109,7 +2109,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Sub-array 1 Inverter MPPT input number\n\n**Constraints:**\nINTEGER,POSITIVE\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), NULL}, {"subarray1_nstrings", (getter)SystemDesign_get_subarray1_nstrings,(setter)SystemDesign_set_subarray1_nstrings, - PyDoc_STR("*float*: Sub-array 1 Number of parallel strings\n\n**Constraints:**\nINTEGER\n\nThe value of the following variables depends on ``subarray1_nstrings``:\n\n\t - system_capacity\n\n\nThe value of ``subarray1_nstrings`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Sub-array 1 Number of parallel strings\n\n**Constraints:**\nINTEGER\n\nThe value of the following variables depends on ``subarray1_nstrings``:\n\n\t - system_capacity\n\n\nThe value of ``subarray1_nstrings`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"subarray1_rotlim", (getter)SystemDesign_get_subarray1_rotlim,(setter)SystemDesign_set_subarray1_rotlim, PyDoc_STR("*float*: Sub-array 1 Tracker rotation limit [degrees]\n\n**Constraints:**\nMIN=0,MAX=85\n\n**Required:**\nFalse. Automatically set to 45 if not assigned explicitly or loaded from defaults."), @@ -2136,7 +2136,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Sub-array 2 Backtracking enabled\n\n**Options:**\n0=no backtracking,1=backtrack\n\n**Constraints:**\nBOOLEAN"), NULL}, {"subarray2_enable", (getter)SystemDesign_get_subarray2_enable,(setter)SystemDesign_set_subarray2_enable, - PyDoc_STR("*float*: Sub-array 2 Enable [0/1]\n\n**Options:**\n0=disabled,1=enabled\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``subarray2_enable``:\n\n\t - system_capacity\n\n\nThe value of ``subarray2_enable`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Sub-array 2 Enable [0/1]\n\n**Options:**\n0=disabled,1=enabled\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``subarray2_enable``:\n\n\t - system_capacity\n\n\nThe value of ``subarray2_enable`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"subarray2_gcr", (getter)SystemDesign_get_subarray2_gcr,(setter)SystemDesign_set_subarray2_gcr, PyDoc_STR("*float*: Sub-array 2 Ground coverage ratio [0..1]\n\n**Constraints:**\nMIN=0.01,MAX=0.99\n\n**Required:**\nFalse. Automatically set to 0.3 if not assigned explicitly or loaded from defaults."), @@ -2178,7 +2178,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Sub-array 3 Backtracking enabled\n\n**Options:**\n0=no backtracking,1=backtrack\n\n**Constraints:**\nBOOLEAN"), NULL}, {"subarray3_enable", (getter)SystemDesign_get_subarray3_enable,(setter)SystemDesign_set_subarray3_enable, - PyDoc_STR("*float*: Sub-array 3 Enable [0/1]\n\n**Options:**\n0=disabled,1=enabled\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``subarray3_enable``:\n\n\t - system_capacity\n\n\nThe value of ``subarray3_enable`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Sub-array 3 Enable [0/1]\n\n**Options:**\n0=disabled,1=enabled\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``subarray3_enable``:\n\n\t - system_capacity\n\n\nThe value of ``subarray3_enable`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"subarray3_gcr", (getter)SystemDesign_get_subarray3_gcr,(setter)SystemDesign_set_subarray3_gcr, PyDoc_STR("*float*: Sub-array 3 Ground coverage ratio [0..1]\n\n**Constraints:**\nMIN=0.01,MAX=0.99\n\n**Required:**\nFalse. Automatically set to 0.3 if not assigned explicitly or loaded from defaults."), @@ -2220,7 +2220,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Sub-array 4 Backtracking enabled\n\n**Options:**\n0=no backtracking,1=backtrack\n\n**Constraints:**\nBOOLEAN"), NULL}, {"subarray4_enable", (getter)SystemDesign_get_subarray4_enable,(setter)SystemDesign_set_subarray4_enable, - PyDoc_STR("*float*: Sub-array 4 Enable [0/1]\n\n**Options:**\n0=disabled,1=enabled\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``subarray4_enable``:\n\n\t - system_capacity\n\n\nThe value of ``subarray4_enable`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Sub-array 4 Enable [0/1]\n\n**Options:**\n0=disabled,1=enabled\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``subarray4_enable``:\n\n\t - system_capacity\n\n\nThe value of ``subarray4_enable`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"subarray4_gcr", (getter)SystemDesign_get_subarray4_gcr,(setter)SystemDesign_set_subarray4_gcr, PyDoc_STR("*float*: Sub-array 4 Ground coverage ratio [0..1]\n\n**Constraints:**\nMIN=0.01,MAX=0.99\n\n**Required:**\nFalse. Automatically set to 0.3 if not assigned explicitly or loaded from defaults."), @@ -2256,7 +2256,7 @@ static PyGetSetDef SystemDesign_getset[] = { PyDoc_STR("*float*: Sub-array 4 Tracking mode\n\n**Options:**\n0=fixed,1=1axis,2=2axis,3=azi,4=monthly\n\n**Constraints:**\nINTEGER,MIN=0,MAX=4\n\n**Required:**\nRequired if subarray4_enable=1"), NULL}, {"system_capacity", (getter)SystemDesign_get_system_capacity,(setter)SystemDesign_set_system_capacity, - PyDoc_STR("*float*: DC Nameplate capacity [kWdc]\n\n**Required:**\nTrue\n\nThe value of ``system_capacity`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray2_modules_per_string\n\t - subarray2_nstrings\n\t - subarray3_enable\n\t - subarray3_modules_per_string\n\t - subarray3_nstrings\n\t - subarray4_enable\n\t - subarray4_modules_per_string\n\t - subarray4_nstrings\n"), + PyDoc_STR("*float*: DC Nameplate capacity [kWdc]\n\n**Required:**\nTrue\n\nThe value of ``system_capacity`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray2_modules_per_string\n\t - subarray2_nstrings\n\t - subarray3_enable\n\t - subarray3_modules_per_string\n\t - subarray3_nstrings\n\t - subarray4_enable\n\t - subarray4_modules_per_string\n\t - subarray4_nstrings\n"), NULL}, {"use_measured_temp", (getter)SystemDesign_get_use_measured_temp,(setter)SystemDesign_set_use_measured_temp, PyDoc_STR("*float*: Use measured temperatures [0/1]\n\n**Constraints:**\nINTEGER,MIN=0,MAX=1\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), @@ -2418,66 +2418,6 @@ Shading_set_subarray1_shading_diff(VarGroupObject *self, PyObject *value, void * return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray1_shading_diff_nset, self->data_ptr); } -static PyObject * -Shading_get_subarray1_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray1_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_subarray1_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray1_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray1_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray1_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_subarray1_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray1_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray1_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray1_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_subarray1_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray1_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray1_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray1_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_subarray1_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray1_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray1_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray1_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_subarray1_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray1_shading_en_timestep_nset, self->data_ptr); -} - static PyObject * Shading_get_subarray1_shading_mxh(VarGroupObject *self, void *closure) { @@ -2550,66 +2490,6 @@ Shading_set_subarray2_shading_diff(VarGroupObject *self, PyObject *value, void * return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray2_shading_diff_nset, self->data_ptr); } -static PyObject * -Shading_get_subarray2_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray2_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_subarray2_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray2_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray2_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray2_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_subarray2_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray2_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray2_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray2_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_subarray2_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray2_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray2_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray2_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_subarray2_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray2_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray2_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray2_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_subarray2_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray2_shading_en_timestep_nset, self->data_ptr); -} - static PyObject * Shading_get_subarray2_shading_mxh(VarGroupObject *self, void *closure) { @@ -2682,66 +2562,6 @@ Shading_set_subarray3_shading_diff(VarGroupObject *self, PyObject *value, void * return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray3_shading_diff_nset, self->data_ptr); } -static PyObject * -Shading_get_subarray3_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray3_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_subarray3_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray3_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray3_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray3_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_subarray3_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray3_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray3_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray3_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_subarray3_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray3_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray3_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray3_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_subarray3_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray3_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray3_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray3_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_subarray3_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray3_shading_en_timestep_nset, self->data_ptr); -} - static PyObject * Shading_get_subarray3_shading_mxh(VarGroupObject *self, void *closure) { @@ -2814,66 +2634,6 @@ Shading_set_subarray4_shading_diff(VarGroupObject *self, PyObject *value, void * return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray4_shading_diff_nset, self->data_ptr); } -static PyObject * -Shading_get_subarray4_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray4_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_subarray4_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray4_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray4_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray4_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_subarray4_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray4_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray4_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray4_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_subarray4_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray4_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray4_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray4_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_subarray4_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray4_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_subarray4_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvsamv1_Shading_subarray4_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_subarray4_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvsamv1_Shading_subarray4_shading_en_timestep_nset, self->data_ptr); -} - static PyObject * Shading_get_subarray4_shading_mxh(VarGroupObject *self, void *closure) { @@ -2920,21 +2680,6 @@ static PyGetSetDef Shading_getset[] = { {"subarray1_shading_diff", (getter)Shading_get_subarray1_shading_diff,(setter)Shading_set_subarray1_shading_diff, PyDoc_STR("*float*: Sub-array 1 Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, -{"subarray1_shading_en_azal", (getter)Shading_get_subarray1_shading_en_azal,(setter)Shading_set_subarray1_shading_en_azal, - PyDoc_STR("*float*: Enable Sub-array 1 Azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray1_shading_en_diff", (getter)Shading_get_subarray1_shading_en_diff,(setter)Shading_set_subarray1_shading_en_diff, - PyDoc_STR("*float*: Enable Sub-array 1 Diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray1_shading_en_mxh", (getter)Shading_get_subarray1_shading_en_mxh,(setter)Shading_set_subarray1_shading_en_mxh, - PyDoc_STR("*float*: Enable Sub-array 1 Month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray1_shading_en_string_option", (getter)Shading_get_subarray1_shading_en_string_option,(setter)Shading_set_subarray1_shading_en_string_option, - PyDoc_STR("*float*: Enable Sub-array 1 shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray1_shading_en_timestep", (getter)Shading_get_subarray1_shading_en_timestep,(setter)Shading_set_subarray1_shading_en_timestep, - PyDoc_STR("*float*: Enable Sub-array 1 timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"subarray1_shading_mxh", (getter)Shading_get_subarray1_shading_mxh,(setter)Shading_set_subarray1_shading_mxh, PyDoc_STR("*sequence[sequence]*: Sub-array 1 Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, @@ -2953,29 +2698,14 @@ static PyGetSetDef Shading_getset[] = { {"subarray2_shading_diff", (getter)Shading_get_subarray2_shading_diff,(setter)Shading_set_subarray2_shading_diff, PyDoc_STR("*float*: Sub-array 2 Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, -{"subarray2_shading_en_azal", (getter)Shading_get_subarray2_shading_en_azal,(setter)Shading_set_subarray2_shading_en_azal, - PyDoc_STR("*float*: Enable Sub-array 2 Azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray2_shading_en_diff", (getter)Shading_get_subarray2_shading_en_diff,(setter)Shading_set_subarray2_shading_en_diff, - PyDoc_STR("*float*: Enable Sub-array 2 Diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray2_shading_en_mxh", (getter)Shading_get_subarray2_shading_en_mxh,(setter)Shading_set_subarray2_shading_en_mxh, - PyDoc_STR("*float*: Enable Sub-array 2 Month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray2_shading_en_string_option", (getter)Shading_get_subarray2_shading_en_string_option,(setter)Shading_set_subarray2_shading_en_string_option, - PyDoc_STR("*float*: Enable Sub-array 2 shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray2_shading_en_timestep", (getter)Shading_get_subarray2_shading_en_timestep,(setter)Shading_set_subarray2_shading_en_timestep, - PyDoc_STR("*float*: Enable Sub-array 2 timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"subarray2_shading_mxh", (getter)Shading_get_subarray2_shading_mxh,(setter)Shading_set_subarray2_shading_mxh, PyDoc_STR("*sequence[sequence]*: Sub-array 2 Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, {"subarray2_shading_string_option", (getter)Shading_get_subarray2_shading_string_option,(setter)Shading_set_subarray2_shading_string_option, - PyDoc_STR("*float*: Sub-array 2 shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), + PyDoc_STR("*float*: Sub-array 2 Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), NULL}, {"subarray2_shading_timestep", (getter)Shading_get_subarray2_shading_timestep,(setter)Shading_set_subarray2_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Sub-array 2 timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + PyDoc_STR("*sequence[sequence]*: Sub-array 2 Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, {"subarray3_shade_mode", (getter)Shading_get_subarray3_shade_mode,(setter)Shading_set_subarray3_shade_mode, PyDoc_STR("*float*: Sub-array 3 Shading mode (fixed tilt or 1x tracking) [0/1/2]\n\n**Options:**\n0=none,1=standard(non-linear),2=thin film(linear)\n\n**Constraints:**\nINTEGER,MIN=0,MAX=2\n\n**Required:**\nRequired if subarray3_enable=1"), @@ -2986,29 +2716,14 @@ static PyGetSetDef Shading_getset[] = { {"subarray3_shading_diff", (getter)Shading_get_subarray3_shading_diff,(setter)Shading_set_subarray3_shading_diff, PyDoc_STR("*float*: Sub-array 3 Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, -{"subarray3_shading_en_azal", (getter)Shading_get_subarray3_shading_en_azal,(setter)Shading_set_subarray3_shading_en_azal, - PyDoc_STR("*float*: Enable Sub-array 3 Azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray3_shading_en_diff", (getter)Shading_get_subarray3_shading_en_diff,(setter)Shading_set_subarray3_shading_en_diff, - PyDoc_STR("*float*: Enable Sub-array 3 Diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray3_shading_en_mxh", (getter)Shading_get_subarray3_shading_en_mxh,(setter)Shading_set_subarray3_shading_en_mxh, - PyDoc_STR("*float*: Enable Sub-array 3 Month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray3_shading_en_string_option", (getter)Shading_get_subarray3_shading_en_string_option,(setter)Shading_set_subarray3_shading_en_string_option, - PyDoc_STR("*float*: Enable Sub-array 3 shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray3_shading_en_timestep", (getter)Shading_get_subarray3_shading_en_timestep,(setter)Shading_set_subarray3_shading_en_timestep, - PyDoc_STR("*float*: Enable Sub-array 3 timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"subarray3_shading_mxh", (getter)Shading_get_subarray3_shading_mxh,(setter)Shading_set_subarray3_shading_mxh, PyDoc_STR("*sequence[sequence]*: Sub-array 3 Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, {"subarray3_shading_string_option", (getter)Shading_get_subarray3_shading_string_option,(setter)Shading_set_subarray3_shading_string_option, - PyDoc_STR("*float*: Sub-array 3 shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), + PyDoc_STR("*float*: Sub-array 3 Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), NULL}, {"subarray3_shading_timestep", (getter)Shading_get_subarray3_shading_timestep,(setter)Shading_set_subarray3_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Sub-array 3 timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + PyDoc_STR("*sequence[sequence]*: Sub-array 3 Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, {"subarray4_shade_mode", (getter)Shading_get_subarray4_shade_mode,(setter)Shading_set_subarray4_shade_mode, PyDoc_STR("*float*: Sub-array 4 shading mode (fixed tilt or 1x tracking) [0/1/2]\n\n**Options:**\n0=none,1=standard(non-linear),2=thin film(linear)\n\n**Constraints:**\nINTEGER,MIN=0,MAX=2\n\n**Required:**\nRequired if subarray4_enable=1"), @@ -3019,29 +2734,14 @@ static PyGetSetDef Shading_getset[] = { {"subarray4_shading_diff", (getter)Shading_get_subarray4_shading_diff,(setter)Shading_set_subarray4_shading_diff, PyDoc_STR("*float*: Sub-array 4 Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, -{"subarray4_shading_en_azal", (getter)Shading_get_subarray4_shading_en_azal,(setter)Shading_set_subarray4_shading_en_azal, - PyDoc_STR("*float*: Enable Sub-array 4 Azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray4_shading_en_diff", (getter)Shading_get_subarray4_shading_en_diff,(setter)Shading_set_subarray4_shading_en_diff, - PyDoc_STR("*float*: Enable Sub-array 4 Diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray4_shading_en_mxh", (getter)Shading_get_subarray4_shading_en_mxh,(setter)Shading_set_subarray4_shading_en_mxh, - PyDoc_STR("*float*: Enable Sub-array 4 Month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray4_shading_en_string_option", (getter)Shading_get_subarray4_shading_en_string_option,(setter)Shading_set_subarray4_shading_en_string_option, - PyDoc_STR("*float*: Enable Sub-array 4 shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"subarray4_shading_en_timestep", (getter)Shading_get_subarray4_shading_en_timestep,(setter)Shading_set_subarray4_shading_en_timestep, - PyDoc_STR("*float*: Enable Sub-array 4 timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"subarray4_shading_mxh", (getter)Shading_get_subarray4_shading_mxh,(setter)Shading_set_subarray4_shading_mxh, PyDoc_STR("*sequence[sequence]*: Sub-array 4 Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, {"subarray4_shading_string_option", (getter)Shading_get_subarray4_shading_string_option,(setter)Shading_set_subarray4_shading_string_option, - PyDoc_STR("*float*: Sub-array 4 shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), + PyDoc_STR("*float*: Sub-array 4 Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), NULL}, {"subarray4_shading_timestep", (getter)Shading_get_subarray4_shading_timestep,(setter)Shading_set_subarray4_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Sub-array 4 timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + PyDoc_STR("*sequence[sequence]*: Sub-array 4 Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, {NULL} /* Sentinel */ }; @@ -7565,16 +7265,16 @@ static PyGetSetDef Inverter_getset[] = { PyDoc_STR("*float*: Inverter Sandia Maximum AC Power [Wac]\n\nThe value of the following variables depends on ``inv_snl_paco``:\n\n\t - inv_snl_eff_cec\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), NULL}, {"inverter_count", (getter)Inverter_get_inverter_count,(setter)Inverter_set_inverter_count, - PyDoc_STR("*float*: Number of inverters\n\nThe value of ``inverter_count`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_cec_cg_vdcmax\n\t - inv_ds_paco\n\t - inv_ds_vdcmax\n\t - inv_pd_paco\n\t - inv_pd_vdcmax\n\t - inv_snl_paco\n\t - inv_snl_vdcmax\n\t - inverter_model\n\t - module_model\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), + PyDoc_STR("*float*: Number of inverters\n\nThe value of ``inverter_count`` depends on the following variables:\n\n\t - 6par_imp\n\t - 6par_vmp\n\t - 6par_voc\n\t - cec_i_mp_ref\n\t - cec_v_mp_ref\n\t - cec_v_oc_ref\n\t - inv_cec_cg_paco\n\t - inv_ds_paco\n\t - inv_pd_paco\n\t - inv_snl_paco\n\t - inverter_model\n\t - module_model\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - sd11par_Vmp0\n\t - sd11par_Voc0\n\t - snl_a\n\t - snl_a0\n\t - snl_a1\n\t - snl_a2\n\t - snl_a3\n\t - snl_a4\n\t - snl_aimp\n\t - snl_aisc\n\t - snl_area\n\t - snl_b\n\t - snl_b0\n\t - snl_b1\n\t - snl_b2\n\t - snl_b3\n\t - snl_b4\n\t - snl_b5\n\t - snl_bvmpo\n\t - snl_bvoco\n\t - snl_c0\n\t - snl_c1\n\t - snl_c2\n\t - snl_c3\n\t - snl_dtc\n\t - snl_fd\n\t - snl_impo\n\t - snl_isco\n\t - snl_mbvmp\n\t - snl_mbvoc\n\t - snl_module_structure\n\t - snl_n\n\t - snl_series_cells\n\t - snl_vmpo\n\t - snl_voco\n\t - spe_area\n\t - spe_eff0\n\t - spe_eff1\n\t - spe_eff2\n\t - spe_eff3\n\t - spe_eff4\n\t - spe_rad0\n\t - spe_rad1\n\t - spe_rad2\n\t - spe_rad3\n\t - spe_rad4\n\t - spe_reference\n\t - spe_vmp\n\t - spe_voc\n"), NULL}, {"inverter_model", (getter)Inverter_get_inverter_model,(setter)Inverter_set_inverter_model, - PyDoc_STR("*float*: Inverter model specifier\n\n**Options:**\n0=cec,1=datasheet,2=partload,3=coefficientgenerator,4=PVYield\n\n**Constraints:**\nINTEGER,MIN=0,MAX=4\n\n**Required:**\nTrue\n\nThe value of the following variables depends on ``inverter_model``:\n\n\t - inv_num_mppt\n\t - inverter_count\n\t - mppt_hi_inverter\n\t - mppt_low_inverter\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), + PyDoc_STR("*float*: Inverter model specifier\n\n**Options:**\n0=cec,1=datasheet,2=partload,3=coefficientgenerator,4=PVYield\n\n**Constraints:**\nINTEGER,MIN=0,MAX=4\n\n**Required:**\nTrue\n\nThe value of the following variables depends on ``inverter_model``:\n\n\t - inv_num_mppt\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), NULL}, {"mppt_hi_inverter", (getter)Inverter_get_mppt_hi_inverter,(setter)Inverter_set_mppt_hi_inverter, - PyDoc_STR("*float*: Maximum inverter MPPT voltage window [Vdc]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of ``mppt_hi_inverter`` depends on the following variables:\n\n\t - inverter_model\n"), + PyDoc_STR("*float*: Maximum inverter MPPT voltage window [Vdc]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``mppt_hi_inverter``:\n\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), NULL}, {"mppt_low_inverter", (getter)Inverter_get_mppt_low_inverter,(setter)Inverter_set_mppt_low_inverter, - PyDoc_STR("*float*: Minimum inverter MPPT voltage window [Vdc]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of ``mppt_low_inverter`` depends on the following variables:\n\n\t - inverter_model\n"), + PyDoc_STR("*float*: Minimum inverter MPPT voltage window [Vdc]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults.\n\nThe value of the following variables depends on ``mppt_low_inverter``:\n\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), NULL}, {NULL} /* Sentinel */ }; @@ -7855,7 +7555,7 @@ static PyGetSetDef InverterCECDatabase_getset[] = { PyDoc_STR("*float*: DC power required to enable the inversion process [Wdc]\n\n**Required:**\nRequired if inverter_model=0\n\nThe value of the following variables depends on ``inv_snl_pso``:\n\n\t - inv_snl_eff_cec\n"), NULL}, {"inv_snl_vdcmax", (getter)InverterCECDatabase_get_inv_snl_vdcmax,(setter)InverterCECDatabase_set_inv_snl_vdcmax, - PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=0\n\nThe value of the following variables depends on ``inv_snl_vdcmax``:\n\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), + PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=0"), NULL}, {"inv_snl_vdco", (getter)InverterCECDatabase_get_inv_snl_vdco,(setter)InverterCECDatabase_set_inv_snl_vdco, PyDoc_STR("*float*: DC input voltage for the rated AC power rating [Vdc]\n\n**Required:**\nRequired if inverter_model=0\n\nThe value of the following variables depends on ``inv_snl_vdco``:\n\n\t - inv_snl_eff_cec\n"), @@ -8142,7 +7842,7 @@ static PyGetSetDef InverterCECCoefficientGenerator_getset[] = { PyDoc_STR("*float*: DC power required to enable the inversion process [Wdc]\n\n**Required:**\nRequired if inverter_model=3\n\nThe value of the following variables depends on ``inv_cec_cg_psco``:\n\n\t - inv_cec_cg_eff_cec\n"), NULL}, {"inv_cec_cg_vdcmax", (getter)InverterCECCoefficientGenerator_get_inv_cec_cg_vdcmax,(setter)InverterCECCoefficientGenerator_set_inv_cec_cg_vdcmax, - PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=3\n\nThe value of the following variables depends on ``inv_cec_cg_vdcmax``:\n\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), + PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=3"), NULL}, {"inv_cec_cg_vdco", (getter)InverterCECCoefficientGenerator_get_inv_cec_cg_vdco,(setter)InverterCECCoefficientGenerator_set_inv_cec_cg_vdco, PyDoc_STR("*float*: DC input voltage for the rated AC power rating [Vdc]\n\n**Required:**\nRequired if inverter_model=3\n\nThe value of the following variables depends on ``inv_cec_cg_vdco``:\n\n\t - inv_cec_cg_eff_cec\n"), @@ -8369,7 +8069,7 @@ static PyGetSetDef InverterDatasheet_getset[] = { PyDoc_STR("*float*: DC power required to enable the inversion process [Wdc]\n\n**Required:**\nRequired if inverter_model=1"), NULL}, {"inv_ds_vdcmax", (getter)InverterDatasheet_get_inv_ds_vdcmax,(setter)InverterDatasheet_set_inv_ds_vdcmax, - PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=1\n\nThe value of the following variables depends on ``inv_ds_vdcmax``:\n\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), + PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=1"), NULL}, {"inv_ds_vdco", (getter)InverterDatasheet_get_inv_ds_vdco,(setter)InverterDatasheet_set_inv_ds_vdco, PyDoc_STR("*float*: DC input voltage for the rated AC power rating [Vdc]\n\n**Required:**\nRequired if inverter_model=1"), @@ -8611,7 +8311,7 @@ static PyGetSetDef InverterPartLoadCurve_getset[] = { PyDoc_STR("*float*: AC power consumed by inverter at night [Wac]\n\n**Required:**\nRequired if inverter_model=2"), NULL}, {"inv_pd_vdcmax", (getter)InverterPartLoadCurve_get_inv_pd_vdcmax,(setter)InverterPartLoadCurve_set_inv_pd_vdcmax, - PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=2\n\nThe value of the following variables depends on ``inv_pd_vdcmax``:\n\n\t - inverter_count\n\t - subarray1_modules_per_string\n\t - subarray1_nstrings\n\t - subarray2_enable\n\t - subarray3_enable\n\t - subarray4_enable\n\t - system_capacity\n"), + PyDoc_STR("*float*: Maximum DC input operating voltage [Vdc]\n\n**Required:**\nRequired if inverter_model=2"), NULL}, {"inv_pd_vdco", (getter)InverterPartLoadCurve_get_inv_pd_vdco,(setter)InverterPartLoadCurve_set_inv_pd_vdco, PyDoc_STR("*float*: DC input voltage for the rated AC power rating [Vdc]\n\n**Required:**\nRequired if inverter_model=2"), @@ -17256,21 +16956,6 @@ newPvsamv1Object(void* data_ptr) PyDict_SetItemString(attr_dict, "Load", Load_obj); Py_DECREF(Load_obj); - PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); - - PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); - PyObject* Adjust_obj = PyObject_CallMethod(AdjustmentFactorsModule, "new", "(O)", data_cap); - Py_XDECREF(data_cap); - Py_XDECREF(AdjustmentFactorsModule); - - if (!Adjust_obj){ - PyErr_SetString(PyExc_Exception, "Couldn't create AdjustmentFactorsObject\n"); - return NULL; - } - - PyDict_SetItemString(attr_dict, "AdjustmentFactors", Adjust_obj); - Py_DECREF(Adjust_obj); - PyObject* BatteryCell_obj = BatteryCell_new(self->data_ptr); PyDict_SetItemString(attr_dict, "BatteryCell", BatteryCell_obj); Py_DECREF(BatteryCell_obj); @@ -17303,6 +16988,21 @@ newPvsamv1Object(void* data_ptr) PyDict_SetItemString(attr_dict, "GridLimits", GridLimits_obj); Py_DECREF(GridLimits_obj); + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + + PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); + PyObject* Adjust_obj = PyObject_CallMethod(AdjustmentFactorsModule, "new", "(O)", data_cap); + Py_XDECREF(data_cap); + Py_XDECREF(AdjustmentFactorsModule); + + if (!Adjust_obj){ + PyErr_SetString(PyExc_Exception, "Couldn't create AdjustmentFactorsObject\n"); + return NULL; + } + + PyDict_SetItemString(attr_dict, "AdjustmentFactors", Adjust_obj); + Py_DECREF(Adjust_obj); + PyObject* Outputs_obj = Outputs_new(self->data_ptr); PyDict_SetItemString(attr_dict, "Outputs", Outputs_obj); Py_DECREF(Outputs_obj); @@ -17586,6 +17286,25 @@ Pvsamv1Module_exec(PyObject *m) Pvsamv1_Type.tp_dict = PyDict_New(); if (!Pvsamv1_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Pvsamv1_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Pvsamv1_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to Pvsamv1_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(Pvsamv1_Type.tp_dict, diff --git a/modules/Pvwattsv1.c b/modules/Pvwattsv1.c index 73268b5d..8b39280b 100644 --- a/modules/Pvwattsv1.c +++ b/modules/Pvwattsv1.c @@ -406,6 +406,54 @@ PVWatts_set_shade_mode_1x(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_Pvwattsv1_PVWatts_shade_mode_1x_nset, self->data_ptr); } +static PyObject * +PVWatts_get_shading_azal(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv1_PVWatts_shading_azal_mget, self->data_ptr); +} + +static int +PVWatts_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv1_PVWatts_shading_azal_mset, self->data_ptr); +} + +static PyObject * +PVWatts_get_shading_diff(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Pvwattsv1_PVWatts_shading_diff_nget, self->data_ptr); +} + +static int +PVWatts_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Pvwattsv1_PVWatts_shading_diff_nset, self->data_ptr); +} + +static PyObject * +PVWatts_get_shading_mxh(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv1_PVWatts_shading_mxh_mget, self->data_ptr); +} + +static int +PVWatts_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv1_PVWatts_shading_mxh_mset, self->data_ptr); +} + +static PyObject * +PVWatts_get_shading_timestep(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv1_PVWatts_shading_timestep_mget, self->data_ptr); +} + +static int +PVWatts_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv1_PVWatts_shading_timestep_mset, self->data_ptr); +} + static PyObject * PVWatts_get_system_size(VarGroupObject *self, void *closure) { @@ -563,6 +611,18 @@ static PyGetSetDef PVWatts_getset[] = { {"shade_mode_1x", (getter)PVWatts_get_shade_mode_1x,(setter)PVWatts_set_shade_mode_1x, PyDoc_STR("*float*: Tracker self-shading mode [0/1/2]\n\n**Options:**\n0=shading,1=backtrack,2=none\n\n**Constraints:**\nINTEGER,MIN=0,MAX=2\n\n**Required:**\nFalse. Automatically set to 2 if not assigned explicitly or loaded from defaults."), NULL}, +{"shading_azal", (getter)PVWatts_get_shading_azal,(setter)PVWatts_set_shading_azal, + PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading factors\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_diff", (getter)PVWatts_get_shading_diff,(setter)PVWatts_set_shading_diff, + PyDoc_STR("*float*: Diffuse shading factor\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_mxh", (getter)PVWatts_get_shading_mxh,(setter)PVWatts_set_shading_mxh, + PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading factors\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_timestep", (getter)PVWatts_get_shading_timestep,(setter)PVWatts_set_shading_timestep, + PyDoc_STR("*sequence[sequence]*: Time step beam shading factors\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, {"system_size", (getter)PVWatts_get_system_size,(setter)PVWatts_set_system_size, PyDoc_STR("*float*: Nameplate capacity [kW]\n\n**Required:**\nTrue"), NULL}, @@ -640,278 +700,6 @@ static PyTypeObject PVWatts_Type = { }; -/* - * Shading Group - */ - -static PyTypeObject Shading_Type; - -static PyObject * -Shading_new(SAM_Pvwattsv1 data_ptr) -{ - PyObject* new_obj = Shading_Type.tp_alloc(&Shading_Type,0); - - VarGroupObject* Shading_obj = (VarGroupObject*)new_obj; - - Shading_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* Shading methods */ - -static PyObject * -Shading_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "Pvwattsv1", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &Shading_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "Pvwattsv1", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &Shading_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef Shading_methods[] = { - {"assign", (PyCFunction)Shading_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``Shading_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)Shading_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``Shading_vals = { var: val, ...}``")}, - {"export", (PyCFunction)Shading_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -Shading_get_shading_azal(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv1_Shading_shading_azal_mget, self->data_ptr); -} - -static int -Shading_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv1_Shading_shading_azal_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_en_timestep_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv1_Shading_shading_mxh_mget, self->data_ptr); -} - -static int -Shading_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv1_Shading_shading_mxh_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv1_Shading_shading_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv1_Shading_shading_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv1_Shading_shading_timestep_mget, self->data_ptr); -} - -static int -Shading_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv1_Shading_shading_timestep_mset, self->data_ptr); -} - -static PyGetSetDef Shading_getset[] = { -{"shading_azal", (getter)Shading_get_shading_azal,(setter)Shading_set_shading_azal, - PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_diff", (getter)Shading_get_shading_diff,(setter)Shading_set_shading_diff, - PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_en_azal", (getter)Shading_get_shading_en_azal,(setter)Shading_set_shading_en_azal, - PyDoc_STR("*float*: Enable azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_diff", (getter)Shading_get_shading_en_diff,(setter)Shading_set_shading_en_diff, - PyDoc_STR("*float*: Enable diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_mxh", (getter)Shading_get_shading_en_mxh,(setter)Shading_set_shading_en_mxh, - PyDoc_STR("*float*: Enable month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_string_option", (getter)Shading_get_shading_en_string_option,(setter)Shading_set_shading_en_string_option, - PyDoc_STR("*float*: Enable shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_timestep", (getter)Shading_get_shading_en_timestep,(setter)Shading_set_shading_en_timestep, - PyDoc_STR("*float*: Enable timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_mxh", (getter)Shading_get_shading_mxh,(setter)Shading_set_shading_mxh, - PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_string_option", (getter)Shading_get_shading_string_option,(setter)Shading_set_shading_string_option, - PyDoc_STR("*float*: Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_timestep", (getter)Shading_get_shading_timestep,(setter)Shading_set_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject Shading_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "Pvwattsv1.Shading", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - Shading_methods, /*tp_methods*/ - 0, /*tp_members*/ - Shading_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * Outputs Group */ @@ -1325,10 +1113,6 @@ newPvwattsv1Object(void* data_ptr) PyDict_SetItemString(attr_dict, "PVWatts", PVWatts_obj); Py_DECREF(PVWatts_obj); - PyObject* Shading_obj = Shading_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Shading", Shading_obj); - Py_DECREF(Shading_obj); - PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1625,6 +1409,25 @@ Pvwattsv1Module_exec(PyObject *m) Pvwattsv1_Type.tp_dict = PyDict_New(); if (!Pvwattsv1_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Pvwattsv1_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Pvwattsv1_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to Pvwattsv1_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv1_Type.tp_dict, @@ -1639,13 +1442,6 @@ Pvwattsv1Module_exec(PyObject *m) (PyObject*)&PVWatts_Type); Py_DECREF(&PVWatts_Type); - /// Add the Shading type object to Pvwattsv1_Type - if (PyType_Ready(&Shading_Type) < 0) { goto fail; } - PyDict_SetItemString(Pvwattsv1_Type.tp_dict, - "Shading", - (PyObject*)&Shading_Type); - Py_DECREF(&Shading_Type); - /// Add the Outputs type object to Pvwattsv1_Type if (PyType_Ready(&Outputs_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv1_Type.tp_dict, diff --git a/modules/Pvwattsv5.c b/modules/Pvwattsv5.c index 1c144fc4..cf8bd9c1 100644 --- a/modules/Pvwattsv5.c +++ b/modules/Pvwattsv5.c @@ -492,6 +492,54 @@ SystemDesign_set_module_type(VarGroupObject *self, PyObject *value, void *closur return PySAM_double_setter(value, SAM_Pvwattsv5_SystemDesign_module_type_nset, self->data_ptr); } +static PyObject * +SystemDesign_get_shading_azal(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv5_SystemDesign_shading_azal_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv5_SystemDesign_shading_azal_mset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_diff(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Pvwattsv5_SystemDesign_shading_diff_nget, self->data_ptr); +} + +static int +SystemDesign_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Pvwattsv5_SystemDesign_shading_diff_nset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_mxh(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv5_SystemDesign_shading_mxh_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv5_SystemDesign_shading_mxh_mset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_timestep(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv5_SystemDesign_shading_timestep_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv5_SystemDesign_shading_timestep_mset, self->data_ptr); +} + static PyObject * SystemDesign_get_system_capacity(VarGroupObject *self, void *closure) { @@ -541,6 +589,18 @@ static PyGetSetDef SystemDesign_getset[] = { {"module_type", (getter)SystemDesign_get_module_type,(setter)SystemDesign_set_module_type, PyDoc_STR("*float*: Module type [0/1/2]\n\n**Info:**\nStandard,Premium,Thin film\n\n**Constraints:**\nMIN=0,MAX=2,INTEGER\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, +{"shading_azal", (getter)SystemDesign_get_shading_azal,(setter)SystemDesign_set_shading_azal, + PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_diff", (getter)SystemDesign_get_shading_diff,(setter)SystemDesign_set_shading_diff, + PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_mxh", (getter)SystemDesign_get_shading_mxh,(setter)SystemDesign_set_shading_mxh, + PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_timestep", (getter)SystemDesign_get_shading_timestep,(setter)SystemDesign_set_shading_timestep, + PyDoc_STR("*sequence[sequence]*: Time step beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, {"system_capacity", (getter)SystemDesign_get_system_capacity,(setter)SystemDesign_set_system_capacity, PyDoc_STR("*float*: System size (DC nameplate) [kW]\n\n**Required:**\nTrue"), NULL}, @@ -597,278 +657,6 @@ static PyTypeObject SystemDesign_Type = { }; -/* - * Shading Group - */ - -static PyTypeObject Shading_Type; - -static PyObject * -Shading_new(SAM_Pvwattsv5 data_ptr) -{ - PyObject* new_obj = Shading_Type.tp_alloc(&Shading_Type,0); - - VarGroupObject* Shading_obj = (VarGroupObject*)new_obj; - - Shading_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* Shading methods */ - -static PyObject * -Shading_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "Pvwattsv5", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &Shading_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "Pvwattsv5", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &Shading_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef Shading_methods[] = { - {"assign", (PyCFunction)Shading_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``Shading_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)Shading_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``Shading_vals = { var: val, ...}``")}, - {"export", (PyCFunction)Shading_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -Shading_get_shading_azal(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv5_Shading_shading_azal_mget, self->data_ptr); -} - -static int -Shading_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv5_Shading_shading_azal_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_en_timestep_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv5_Shading_shading_mxh_mget, self->data_ptr); -} - -static int -Shading_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv5_Shading_shading_mxh_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv5_Shading_shading_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv5_Shading_shading_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv5_Shading_shading_timestep_mget, self->data_ptr); -} - -static int -Shading_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv5_Shading_shading_timestep_mset, self->data_ptr); -} - -static PyGetSetDef Shading_getset[] = { -{"shading_azal", (getter)Shading_get_shading_azal,(setter)Shading_set_shading_azal, - PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_diff", (getter)Shading_get_shading_diff,(setter)Shading_set_shading_diff, - PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_en_azal", (getter)Shading_get_shading_en_azal,(setter)Shading_set_shading_en_azal, - PyDoc_STR("*float*: Enable azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_diff", (getter)Shading_get_shading_en_diff,(setter)Shading_set_shading_en_diff, - PyDoc_STR("*float*: Enable diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_mxh", (getter)Shading_get_shading_en_mxh,(setter)Shading_set_shading_en_mxh, - PyDoc_STR("*float*: Enable month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_string_option", (getter)Shading_get_shading_en_string_option,(setter)Shading_set_shading_en_string_option, - PyDoc_STR("*float*: Enable shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_timestep", (getter)Shading_get_shading_en_timestep,(setter)Shading_set_shading_en_timestep, - PyDoc_STR("*float*: Enable timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_mxh", (getter)Shading_get_shading_mxh,(setter)Shading_set_shading_mxh, - PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_string_option", (getter)Shading_get_shading_string_option,(setter)Shading_set_shading_string_option, - PyDoc_STR("*float*: Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_timestep", (getter)Shading_get_shading_timestep,(setter)Shading_set_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject Shading_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "Pvwattsv5.Shading", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - Shading_methods, /*tp_methods*/ - 0, /*tp_members*/ - Shading_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * Outputs Group */ @@ -1340,10 +1128,6 @@ newPvwattsv5Object(void* data_ptr) PyDict_SetItemString(attr_dict, "SystemDesign", SystemDesign_obj); Py_DECREF(SystemDesign_obj); - PyObject* Shading_obj = Shading_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Shading", Shading_obj); - Py_DECREF(Shading_obj); - PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1640,6 +1424,25 @@ Pvwattsv5Module_exec(PyObject *m) Pvwattsv5_Type.tp_dict = PyDict_New(); if (!Pvwattsv5_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Pvwattsv5_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Pvwattsv5_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Lifetime type object to Pvwattsv5_Type if (PyType_Ready(&Lifetime_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv5_Type.tp_dict, @@ -1661,13 +1464,6 @@ Pvwattsv5Module_exec(PyObject *m) (PyObject*)&SystemDesign_Type); Py_DECREF(&SystemDesign_Type); - /// Add the Shading type object to Pvwattsv5_Type - if (PyType_Ready(&Shading_Type) < 0) { goto fail; } - PyDict_SetItemString(Pvwattsv5_Type.tp_dict, - "Shading", - (PyObject*)&Shading_Type); - Py_DECREF(&Shading_Type); - /// Add the Outputs type object to Pvwattsv5_Type if (PyType_Ready(&Outputs_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv5_Type.tp_dict, diff --git a/modules/Pvwattsv7.c b/modules/Pvwattsv7.c index 1e1efde8..a3d2c2fc 100644 --- a/modules/Pvwattsv7.c +++ b/modules/Pvwattsv7.c @@ -581,6 +581,54 @@ SystemDesign_set_rotlim(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_Pvwattsv7_SystemDesign_rotlim_nset, self->data_ptr); } +static PyObject * +SystemDesign_get_shading_azal(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv7_SystemDesign_shading_azal_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv7_SystemDesign_shading_azal_mset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_diff(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Pvwattsv7_SystemDesign_shading_diff_nget, self->data_ptr); +} + +static int +SystemDesign_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Pvwattsv7_SystemDesign_shading_diff_nset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_mxh(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv7_SystemDesign_shading_mxh_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv7_SystemDesign_shading_mxh_mset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_timestep(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv7_SystemDesign_shading_timestep_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv7_SystemDesign_shading_timestep_mset, self->data_ptr); +} + static PyObject * SystemDesign_get_soiling(VarGroupObject *self, void *closure) { @@ -708,6 +756,18 @@ static PyGetSetDef SystemDesign_getset[] = { {"rotlim", (getter)SystemDesign_get_rotlim,(setter)SystemDesign_set_rotlim, PyDoc_STR("*float*: Tracker rotation angle limit [deg]\n\n**Required:**\nFalse. Automatically set to 45.0 if not assigned explicitly or loaded from defaults."), NULL}, +{"shading_azal", (getter)SystemDesign_get_shading_azal,(setter)SystemDesign_set_shading_azal, + PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_diff", (getter)SystemDesign_get_shading_diff,(setter)SystemDesign_set_shading_diff, + PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_mxh", (getter)SystemDesign_get_shading_mxh,(setter)SystemDesign_set_shading_mxh, + PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_timestep", (getter)SystemDesign_get_shading_timestep,(setter)SystemDesign_set_shading_timestep, + PyDoc_STR("*sequence[sequence]*: Time step beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, {"soiling", (getter)SystemDesign_get_soiling,(setter)SystemDesign_set_soiling, PyDoc_STR("*sequence*: Soiling loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, @@ -779,278 +839,6 @@ static PyTypeObject SystemDesign_Type = { }; -/* - * Shading Group - */ - -static PyTypeObject Shading_Type; - -static PyObject * -Shading_new(SAM_Pvwattsv7 data_ptr) -{ - PyObject* new_obj = Shading_Type.tp_alloc(&Shading_Type,0); - - VarGroupObject* Shading_obj = (VarGroupObject*)new_obj; - - Shading_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* Shading methods */ - -static PyObject * -Shading_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "Pvwattsv7", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &Shading_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "Pvwattsv7", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &Shading_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef Shading_methods[] = { - {"assign", (PyCFunction)Shading_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``Shading_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)Shading_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``Shading_vals = { var: val, ...}``")}, - {"export", (PyCFunction)Shading_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -Shading_get_shading_azal(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv7_Shading_shading_azal_mget, self->data_ptr); -} - -static int -Shading_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv7_Shading_shading_azal_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_en_timestep_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv7_Shading_shading_mxh_mget, self->data_ptr); -} - -static int -Shading_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv7_Shading_shading_mxh_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv7_Shading_shading_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv7_Shading_shading_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv7_Shading_shading_timestep_mget, self->data_ptr); -} - -static int -Shading_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv7_Shading_shading_timestep_mset, self->data_ptr); -} - -static PyGetSetDef Shading_getset[] = { -{"shading_azal", (getter)Shading_get_shading_azal,(setter)Shading_set_shading_azal, - PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_diff", (getter)Shading_get_shading_diff,(setter)Shading_set_shading_diff, - PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_en_azal", (getter)Shading_get_shading_en_azal,(setter)Shading_set_shading_en_azal, - PyDoc_STR("*float*: Enable azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_diff", (getter)Shading_get_shading_en_diff,(setter)Shading_set_shading_en_diff, - PyDoc_STR("*float*: Enable diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_mxh", (getter)Shading_get_shading_en_mxh,(setter)Shading_set_shading_en_mxh, - PyDoc_STR("*float*: Enable month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_string_option", (getter)Shading_get_shading_en_string_option,(setter)Shading_set_shading_en_string_option, - PyDoc_STR("*float*: Enable shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_timestep", (getter)Shading_get_shading_en_timestep,(setter)Shading_set_shading_en_timestep, - PyDoc_STR("*float*: Enable timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_mxh", (getter)Shading_get_shading_mxh,(setter)Shading_set_shading_mxh, - PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_string_option", (getter)Shading_get_shading_string_option,(setter)Shading_set_shading_string_option, - PyDoc_STR("*float*: Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_timestep", (getter)Shading_get_shading_timestep,(setter)Shading_set_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject Shading_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "Pvwattsv7.Shading", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - Shading_methods, /*tp_methods*/ - 0, /*tp_members*/ - Shading_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * Outputs Group */ @@ -1558,10 +1346,6 @@ newPvwattsv7Object(void* data_ptr) PyDict_SetItemString(attr_dict, "SystemDesign", SystemDesign_obj); Py_DECREF(SystemDesign_obj); - PyObject* Shading_obj = Shading_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Shading", Shading_obj); - Py_DECREF(Shading_obj); - PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1860,6 +1644,25 @@ Pvwattsv7Module_exec(PyObject *m) Pvwattsv7_Type.tp_dict = PyDict_New(); if (!Pvwattsv7_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Pvwattsv7_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Pvwattsv7_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to Pvwattsv7_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv7_Type.tp_dict, @@ -1881,13 +1684,6 @@ Pvwattsv7Module_exec(PyObject *m) (PyObject*)&SystemDesign_Type); Py_DECREF(&SystemDesign_Type); - /// Add the Shading type object to Pvwattsv7_Type - if (PyType_Ready(&Shading_Type) < 0) { goto fail; } - PyDict_SetItemString(Pvwattsv7_Type.tp_dict, - "Shading", - (PyObject*)&Shading_Type); - Py_DECREF(&Shading_Type); - /// Add the Outputs type object to Pvwattsv7_Type if (PyType_Ready(&Outputs_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv7_Type.tp_dict, diff --git a/modules/Pvwattsv8.c b/modules/Pvwattsv8.c index f13b26ae..4f6ecf9a 100644 --- a/modules/Pvwattsv8.c +++ b/modules/Pvwattsv8.c @@ -614,6 +614,54 @@ SystemDesign_set_rotlim(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_Pvwattsv8_SystemDesign_rotlim_nset, self->data_ptr); } +static PyObject * +SystemDesign_get_shading_azal(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv8_SystemDesign_shading_azal_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv8_SystemDesign_shading_azal_mset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_diff(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Pvwattsv8_SystemDesign_shading_diff_nget, self->data_ptr); +} + +static int +SystemDesign_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Pvwattsv8_SystemDesign_shading_diff_nset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_mxh(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv8_SystemDesign_shading_mxh_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv8_SystemDesign_shading_mxh_mset, self->data_ptr); +} + +static PyObject * +SystemDesign_get_shading_timestep(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Pvwattsv8_SystemDesign_shading_timestep_mget, self->data_ptr); +} + +static int +SystemDesign_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Pvwattsv8_SystemDesign_shading_timestep_mset, self->data_ptr); +} + static PyObject * SystemDesign_get_soiling(VarGroupObject *self, void *closure) { @@ -738,6 +786,18 @@ static PyGetSetDef SystemDesign_getset[] = { {"rotlim", (getter)SystemDesign_get_rotlim,(setter)SystemDesign_set_rotlim, PyDoc_STR("*float*: Tracker rotation angle limit [degrees]\n\n**Required:**\nFalse. Automatically set to 45.0 if not assigned explicitly or loaded from defaults."), NULL}, +{"shading_azal", (getter)SystemDesign_get_shading_azal,(setter)SystemDesign_set_shading_azal, + PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_diff", (getter)SystemDesign_get_shading_diff,(setter)SystemDesign_set_shading_diff, + PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_mxh", (getter)SystemDesign_get_shading_mxh,(setter)SystemDesign_set_shading_mxh, + PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_timestep", (getter)SystemDesign_get_shading_timestep,(setter)SystemDesign_set_shading_timestep, + PyDoc_STR("*sequence[sequence]*: Time step beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, {"soiling", (getter)SystemDesign_get_soiling,(setter)SystemDesign_set_soiling, PyDoc_STR("*sequence*: Soiling loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), NULL}, @@ -809,278 +869,6 @@ static PyTypeObject SystemDesign_Type = { }; -/* - * Shading Group - */ - -static PyTypeObject Shading_Type; - -static PyObject * -Shading_new(SAM_Pvwattsv8 data_ptr) -{ - PyObject* new_obj = Shading_Type.tp_alloc(&Shading_Type,0); - - VarGroupObject* Shading_obj = (VarGroupObject*)new_obj; - - Shading_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* Shading methods */ - -static PyObject * -Shading_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "Pvwattsv8", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &Shading_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "Pvwattsv8", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &Shading_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef Shading_methods[] = { - {"assign", (PyCFunction)Shading_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``Shading_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)Shading_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``Shading_vals = { var: val, ...}``")}, - {"export", (PyCFunction)Shading_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -Shading_get_shading_azal(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv8_Shading_shading_azal_mget, self->data_ptr); -} - -static int -Shading_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv8_Shading_shading_azal_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_en_timestep_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv8_Shading_shading_mxh_mget, self->data_ptr); -} - -static int -Shading_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv8_Shading_shading_mxh_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Pvwattsv8_Shading_shading_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Pvwattsv8_Shading_shading_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Pvwattsv8_Shading_shading_timestep_mget, self->data_ptr); -} - -static int -Shading_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Pvwattsv8_Shading_shading_timestep_mset, self->data_ptr); -} - -static PyGetSetDef Shading_getset[] = { -{"shading_azal", (getter)Shading_get_shading_azal,(setter)Shading_set_shading_azal, - PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_diff", (getter)Shading_get_shading_diff,(setter)Shading_set_shading_diff, - PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_en_azal", (getter)Shading_get_shading_en_azal,(setter)Shading_set_shading_en_azal, - PyDoc_STR("*float*: Enable azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_diff", (getter)Shading_get_shading_en_diff,(setter)Shading_set_shading_en_diff, - PyDoc_STR("*float*: Enable diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_mxh", (getter)Shading_get_shading_en_mxh,(setter)Shading_set_shading_en_mxh, - PyDoc_STR("*float*: Enable month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_string_option", (getter)Shading_get_shading_en_string_option,(setter)Shading_set_shading_en_string_option, - PyDoc_STR("*float*: Enable shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_timestep", (getter)Shading_get_shading_en_timestep,(setter)Shading_set_shading_en_timestep, - PyDoc_STR("*float*: Enable timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_mxh", (getter)Shading_get_shading_mxh,(setter)Shading_set_shading_mxh, - PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_string_option", (getter)Shading_get_shading_string_option,(setter)Shading_set_shading_string_option, - PyDoc_STR("*float*: Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_timestep", (getter)Shading_get_shading_timestep,(setter)Shading_set_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject Shading_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "Pvwattsv8.Shading", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - Shading_methods, /*tp_methods*/ - 0, /*tp_members*/ - Shading_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * Outputs Group */ @@ -1642,10 +1430,6 @@ newPvwattsv8Object(void* data_ptr) PyDict_SetItemString(attr_dict, "SystemDesign", SystemDesign_obj); Py_DECREF(SystemDesign_obj); - PyObject* Shading_obj = Shading_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Shading", Shading_obj); - Py_DECREF(Shading_obj); - PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1944,6 +1728,25 @@ Pvwattsv8Module_exec(PyObject *m) Pvwattsv8_Type.tp_dict = PyDict_New(); if (!Pvwattsv8_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Pvwattsv8_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Pvwattsv8_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to Pvwattsv8_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv8_Type.tp_dict, @@ -1965,13 +1768,6 @@ Pvwattsv8Module_exec(PyObject *m) (PyObject*)&SystemDesign_Type); Py_DECREF(&SystemDesign_Type); - /// Add the Shading type object to Pvwattsv8_Type - if (PyType_Ready(&Shading_Type) < 0) { goto fail; } - PyDict_SetItemString(Pvwattsv8_Type.tp_dict, - "Shading", - (PyObject*)&Shading_Type); - Py_DECREF(&Shading_Type); - /// Add the Outputs type object to Pvwattsv8_Type if (PyType_Ready(&Outputs_Type) < 0) { goto fail; } PyDict_SetItemString(Pvwattsv8_Type.tp_dict, diff --git a/modules/Saleleaseback.c b/modules/Saleleaseback.c index 6b2604e6..fda8890d 100644 --- a/modules/Saleleaseback.c +++ b/modules/Saleleaseback.c @@ -77,54 +77,6 @@ static PyMethodDef Revenue_methods[] = { {NULL, NULL} /* sentinel */ }; -static PyObject * -Revenue_get_dispatch_factors_ts(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Saleleaseback_Revenue_dispatch_factors_ts_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Saleleaseback_Revenue_dispatch_factors_ts_aset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Saleleaseback_Revenue_dispatch_sched_weekday_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Saleleaseback_Revenue_dispatch_sched_weekday_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Saleleaseback_Revenue_dispatch_sched_weekend_mget, self->data_ptr); -} - -static int -Revenue_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Saleleaseback_Revenue_dispatch_sched_weekend_mset, self->data_ptr); -} - -static PyObject * -Revenue_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Saleleaseback_Revenue_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Saleleaseback_Revenue_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * Revenue_get_ppa_escalation(VarGroupObject *self, void *closure) { @@ -137,18 +89,6 @@ Revenue_set_ppa_escalation(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_Saleleaseback_Revenue_ppa_escalation_nset, self->data_ptr); } -static PyObject * -Revenue_get_ppa_multiplier_model(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Saleleaseback_Revenue_ppa_multiplier_model_nget, self->data_ptr); -} - -static int -Revenue_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Saleleaseback_Revenue_ppa_multiplier_model_nset, self->data_ptr); -} - static PyObject * Revenue_get_ppa_price_input(VarGroupObject *self, void *closure) { @@ -222,24 +162,9 @@ Revenue_set_ppa_soln_tolerance(VarGroupObject *self, PyObject *value, void *clos } static PyGetSetDef Revenue_getset[] = { -{"dispatch_factors_ts", (getter)Revenue_get_dispatch_factors_ts,(setter)Revenue_set_dispatch_factors_ts, - PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), - NULL}, -{"dispatch_sched_weekday", (getter)Revenue_get_dispatch_sched_weekday,(setter)Revenue_set_dispatch_sched_weekday, - PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_sched_weekend", (getter)Revenue_get_dispatch_sched_weekend,(setter)Revenue_set_dispatch_sched_weekend, - PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, -{"dispatch_tod_factors", (getter)Revenue_get_dispatch_tod_factors,(setter)Revenue_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, {"ppa_escalation", (getter)Revenue_get_ppa_escalation,(setter)Revenue_set_ppa_escalation, PyDoc_STR("*float*: PPA escalation rate [%/year]\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, -{"ppa_multiplier_model", (getter)Revenue_get_ppa_multiplier_model,(setter)Revenue_set_ppa_multiplier_model, - PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, {"ppa_price_input", (getter)Revenue_get_ppa_price_input,(setter)Revenue_set_ppa_price_input, PyDoc_STR("*sequence*: PPA price in first year input [$/kWh]\n\n**Required:**\nTrue"), NULL}, @@ -4766,6 +4691,323 @@ static PyTypeObject SaleLeaseback_Type = { }; +/* + * TimeOfDelivery Group + */ + +static PyTypeObject TimeOfDelivery_Type; + +static PyObject * +TimeOfDelivery_new(SAM_Saleleaseback data_ptr) +{ + PyObject* new_obj = TimeOfDelivery_Type.tp_alloc(&TimeOfDelivery_Type,0); + + VarGroupObject* TimeOfDelivery_obj = (VarGroupObject*)new_obj; + + TimeOfDelivery_obj->data_ptr = (SAM_table)data_ptr; + + return new_obj; +} + +/* TimeOfDelivery methods */ + +static PyObject * +TimeOfDelivery_assign(VarGroupObject *self, PyObject *args) +{ + PyObject* dict; + if (!PyArg_ParseTuple(args, "O:assign", &dict)){ + return NULL; + } + + if (!PySAM_assign_from_dict(self->data_ptr, dict, "Saleleaseback", "TimeOfDelivery")){ + return NULL; + } + + Py_INCREF(Py_None); + return Py_None; +} + +static PyObject * +TimeOfDelivery_replace(VarGroupObject *self, PyObject *args) +{ + PyObject* dict; + if (!PyArg_ParseTuple(args, "O:assign", &dict)){ + return NULL; + } + PyTypeObject* tp = &TimeOfDelivery_Type; + + if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "Saleleaseback", "TimeOfDelivery")){ + return NULL; + } + + Py_INCREF(Py_None); + return Py_None; +} + +static PyObject * +TimeOfDelivery_export(VarGroupObject *self, PyObject *args) +{ + PyTypeObject* tp = &TimeOfDelivery_Type; + PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); + return dict; +} + +static PyMethodDef TimeOfDelivery_methods[] = { + {"assign", (PyCFunction)TimeOfDelivery_assign, METH_VARARGS, + PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``TimeOfDelivery_vals = { var: val, ...}``")}, + {"replace", (PyCFunction)TimeOfDelivery_replace, METH_VARARGS, + PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``TimeOfDelivery_vals = { var: val, ...}``")}, + {"export", (PyCFunction)TimeOfDelivery_export, METH_VARARGS, + PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, + {NULL, NULL} /* sentinel */ +}; + +static PyObject * +TimeOfDelivery_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factor9_nset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_factors_ts(VarGroupObject *self, void *closure) +{ + return PySAM_array_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_factors_ts_aget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_factors_ts(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_array_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_factors_ts_aset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekday(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_sched_weekday_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekday(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_sched_weekday_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_dispatch_sched_weekend(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Saleleaseback_TimeOfDelivery_dispatch_sched_weekend_mget, self->data_ptr); +} + +static int +TimeOfDelivery_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Saleleaseback_TimeOfDelivery_dispatch_sched_weekend_mset, self->data_ptr); +} + +static PyObject * +TimeOfDelivery_get_ppa_multiplier_model(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Saleleaseback_TimeOfDelivery_ppa_multiplier_model_nget, self->data_ptr); +} + +static int +TimeOfDelivery_set_ppa_multiplier_model(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Saleleaseback_TimeOfDelivery_ppa_multiplier_model_nset, self->data_ptr); +} + +static PyGetSetDef TimeOfDelivery_getset[] = { +{"dispatch_factor1", (getter)TimeOfDelivery_get_dispatch_factor1,(setter)TimeOfDelivery_set_dispatch_factor1, + PyDoc_STR("*float*: TOD factor for period 1\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDelivery_get_dispatch_factor2,(setter)TimeOfDelivery_set_dispatch_factor2, + PyDoc_STR("*float*: TOD factor for period 2\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDelivery_get_dispatch_factor3,(setter)TimeOfDelivery_set_dispatch_factor3, + PyDoc_STR("*float*: TOD factor for period 3\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDelivery_get_dispatch_factor4,(setter)TimeOfDelivery_set_dispatch_factor4, + PyDoc_STR("*float*: TOD factor for period 4\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDelivery_get_dispatch_factor5,(setter)TimeOfDelivery_set_dispatch_factor5, + PyDoc_STR("*float*: TOD factor for period 5\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDelivery_get_dispatch_factor6,(setter)TimeOfDelivery_set_dispatch_factor6, + PyDoc_STR("*float*: TOD factor for period 6\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDelivery_get_dispatch_factor7,(setter)TimeOfDelivery_set_dispatch_factor7, + PyDoc_STR("*float*: TOD factor for period 7\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDelivery_get_dispatch_factor8,(setter)TimeOfDelivery_set_dispatch_factor8, + PyDoc_STR("*float*: TOD factor for period 8\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDelivery_get_dispatch_factor9,(setter)TimeOfDelivery_set_dispatch_factor9, + PyDoc_STR("*float*: TOD factor for period 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factors_ts", (getter)TimeOfDelivery_get_dispatch_factors_ts,(setter)TimeOfDelivery_set_dispatch_factors_ts, + PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), + NULL}, +{"dispatch_sched_weekday", (getter)TimeOfDelivery_get_dispatch_sched_weekday,(setter)TimeOfDelivery_set_dispatch_sched_weekday, + PyDoc_STR("*sequence[sequence]*: Diurnal weekday TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_sched_weekend", (getter)TimeOfDelivery_get_dispatch_sched_weekend,(setter)TimeOfDelivery_set_dispatch_sched_weekend, + PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"ppa_multiplier_model", (getter)TimeOfDelivery_get_ppa_multiplier_model,(setter)TimeOfDelivery_set_ppa_multiplier_model, + PyDoc_STR("*float*: PPA multiplier model [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), + NULL}, + {NULL} /* Sentinel */ +}; + +static PyTypeObject TimeOfDelivery_Type = { + /* The ob_type field must be initialized in the module init function + * to be portable to Windows without using C++. */ + PyVarObject_HEAD_INIT(NULL, 0) + "Saleleaseback.TimeOfDelivery", /*tp_name*/ + sizeof(VarGroupObject), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + /* methods */ + 0, /*tp_dealloc*/ + 0, /*tp_print*/ + (getattrfunc)0, /*tp_getattr*/ + 0, /*tp_setattr*/ + 0, /*tp_reserved*/ + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistofnset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + TimeOfDelivery_methods, /*tp_methods*/ + 0, /*tp_members*/ + TimeOfDelivery_getset, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictofnset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + 0, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ +}; + + /* * UtilityBill Group */ @@ -11179,6 +11421,10 @@ newSaleleasebackObject(void* data_ptr) PyDict_SetItemString(attr_dict, "SaleLeaseback", SaleLeaseback_obj); Py_DECREF(SaleLeaseback_obj); + PyObject* TimeOfDelivery_obj = TimeOfDelivery_new(self->data_ptr); + PyDict_SetItemString(attr_dict, "TimeOfDelivery", TimeOfDelivery_obj); + Py_DECREF(TimeOfDelivery_obj); + PyObject* UtilityBill_obj = UtilityBill_new(self->data_ptr); PyDict_SetItemString(attr_dict, "UtilityBill", UtilityBill_obj); Py_DECREF(UtilityBill_obj); @@ -11550,6 +11796,13 @@ SaleleasebackModule_exec(PyObject *m) (PyObject*)&SaleLeaseback_Type); Py_DECREF(&SaleLeaseback_Type); + /// Add the TimeOfDelivery type object to Saleleaseback_Type + if (PyType_Ready(&TimeOfDelivery_Type) < 0) { goto fail; } + PyDict_SetItemString(Saleleaseback_Type.tp_dict, + "TimeOfDelivery", + (PyObject*)&TimeOfDelivery_Type); + Py_DECREF(&TimeOfDelivery_Type); + /// Add the UtilityBill type object to Saleleaseback_Type if (PyType_Ready(&UtilityBill_Type) < 0) { goto fail; } PyDict_SetItemString(Saleleaseback_Type.tp_dict, diff --git a/modules/Sco2CspSystem.c b/modules/Sco2CspSystem.c index f8cea839..88529ac2 100644 --- a/modules/Sco2CspSystem.c +++ b/modules/Sco2CspSystem.c @@ -1136,10 +1136,10 @@ static PyGetSetDef Common_getset[] = { PyDoc_STR("*sequence[sequence]*: Columns: 0) T_htf_C, 1) m_dot_htf_ND, 2) T_amb_C, 3) f_N_rc (=1 use design, =0 optimize, <0, frac_des = abs(input)), 4) f_N_mc (=1 use design, =0 optimize, <0, frac_des = abs(input)), 5) f_N_pc (=1 use design, =0 optimize, <0, frac_des = abs(input)), 6) PHX_f_dP (=1 use design, <0 = abs(input), Rows: cases"), NULL}, {"od_generate_udpc", (getter)Common_get_od_generate_udpc,(setter)Common_set_od_generate_udpc, - PyDoc_STR("*sequence*: Columns 0) True/False,1) f_N_rc (=1 use design, =0 optimize, <0, frac_des = abs(input),2) f_N_mc (=1 use design, =0 optimize, <0, frac_des = abs(input),3) PHX_f_dP (=1 use design, <0 = abs(input)"), + PyDoc_STR("*sequence*: True/False, f_N_rc (=1 use design, =0 optimize, <0, frac_des = abs(input), f_N_mc (=1 use design, =0 optimize, <0, frac_des = abs(input), PHX_f_dP (=1 use design, <0 = abs(input)"), NULL}, {"od_max_htf_m_dot", (getter)Common_get_od_max_htf_m_dot,(setter)Common_set_od_max_htf_m_dot, - PyDoc_STR("*sequence[sequence]*: Columns: 0) T_htf_C, 1) T_amb_C,2) f_N_rc (=1 use design, <0, frac_des = abs(input),3) f_N_mc (=1 use design, <0, frac_des = abs(input),4) PHX_f_dP (=1 use design, <0 = abs(input), Rows: cases"), + PyDoc_STR("*sequence[sequence]*: Columns: T_htf_C, T_amb_C, f_N_rc (=1 use design, <0, frac_des = abs(input), f_N_mc (=1 use design, <0, frac_des = abs(input), PHX_f_dP (=1 use design, <0 = abs(input), Rows: cases"), NULL}, {"od_opt_objective", (getter)Common_get_od_opt_objective,(setter)Common_set_od_opt_objective, PyDoc_STR("*float*: 0: find P_LP_in to achieve target power, optimize efficiency 1: find P_LP_in to achieve T_HTF_cold, optimize efficiency\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), @@ -1824,12 +1824,6 @@ Outputs_get_PHX_cost_equipment(VarGroupObject *self, void *closure) return PySAM_double_getter(SAM_Sco2CspSystem_Outputs_PHX_cost_equipment_nget, self->data_ptr); } -static PyObject * -Outputs_get_PHX_min_dT(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Sco2CspSystem_Outputs_PHX_min_dT_nget, self->data_ptr); -} - static PyObject * Outputs_get_P_co2_PHX_in(VarGroupObject *self, void *closure) { @@ -3325,9 +3319,6 @@ static PyGetSetDef Outputs_getset[] = { {"PHX_cost_equipment", (getter)Outputs_get_PHX_cost_equipment,(setter)0, PyDoc_STR("*float*: PHX cost equipment [M$]"), NULL}, -{"PHX_min_dT", (getter)Outputs_get_PHX_min_dT,(setter)0, - PyDoc_STR("*float*: PHX min temperature difference [C]"), - NULL}, {"P_co2_PHX_in", (getter)Outputs_get_P_co2_PHX_in,(setter)0, PyDoc_STR("*float*: CO2 pressure at PHX inlet [MPa]"), NULL}, diff --git a/modules/Sco2CspUdPcTables.c b/modules/Sco2CspUdPcTables.c index decee470..aef391dc 100644 --- a/modules/Sco2CspUdPcTables.c +++ b/modules/Sco2CspUdPcTables.c @@ -1785,12 +1785,6 @@ Outputs_get_PHX_cost_equipment(VarGroupObject *self, void *closure) return PySAM_double_getter(SAM_Sco2CspUdPcTables_Outputs_PHX_cost_equipment_nget, self->data_ptr); } -static PyObject * -Outputs_get_PHX_min_dT(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Sco2CspUdPcTables_Outputs_PHX_min_dT_nget, self->data_ptr); -} - static PyObject * Outputs_get_P_co2_PHX_in(VarGroupObject *self, void *closure) { @@ -2731,9 +2725,6 @@ static PyGetSetDef Outputs_getset[] = { {"PHX_cost_equipment", (getter)Outputs_get_PHX_cost_equipment,(setter)0, PyDoc_STR("*float*: PHX cost equipment [M$]"), NULL}, -{"PHX_min_dT", (getter)Outputs_get_PHX_min_dT,(setter)0, - PyDoc_STR("*float*: PHX min temperature difference [C]"), - NULL}, {"P_co2_PHX_in", (getter)Outputs_get_P_co2_PHX_in,(setter)0, PyDoc_STR("*float*: CO2 pressure at PHX inlet [MPa]"), NULL}, diff --git a/modules/Singleowner.c b/modules/Singleowner.c index 0bd2bc01..9559ac20 100644 --- a/modules/Singleowner.c +++ b/modules/Singleowner.c @@ -77,6 +77,114 @@ static PyMethodDef Revenue_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +Revenue_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor1_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor2_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor3_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor4_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor5_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor6_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor7_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor8_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +Revenue_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Singleowner_Revenue_dispatch_factor9_nget, self->data_ptr); +} + +static int +Revenue_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Singleowner_Revenue_dispatch_factor9_nset, self->data_ptr); +} + static PyObject * Revenue_get_dispatch_factors_ts(VarGroupObject *self, void *closure) { @@ -113,18 +221,6 @@ Revenue_set_dispatch_sched_weekend(VarGroupObject *self, PyObject *value, void * return PySAM_matrix_setter(value, SAM_Singleowner_Revenue_dispatch_sched_weekend_mset, self->data_ptr); } -static PyObject * -Revenue_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_Singleowner_Revenue_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -Revenue_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_Singleowner_Revenue_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * Revenue_get_flip_target_percent(VarGroupObject *self, void *closure) { @@ -246,6 +342,33 @@ Revenue_set_ppa_soln_tolerance(VarGroupObject *self, PyObject *value, void *clos } static PyGetSetDef Revenue_getset[] = { +{"dispatch_factor1", (getter)Revenue_get_dispatch_factor1,(setter)Revenue_set_dispatch_factor1, + PyDoc_STR("*float*: TOD factor for period 1\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor2", (getter)Revenue_get_dispatch_factor2,(setter)Revenue_set_dispatch_factor2, + PyDoc_STR("*float*: TOD factor for period 2\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor3", (getter)Revenue_get_dispatch_factor3,(setter)Revenue_set_dispatch_factor3, + PyDoc_STR("*float*: TOD factor for period 3\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor4", (getter)Revenue_get_dispatch_factor4,(setter)Revenue_set_dispatch_factor4, + PyDoc_STR("*float*: TOD factor for period 4\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor5", (getter)Revenue_get_dispatch_factor5,(setter)Revenue_set_dispatch_factor5, + PyDoc_STR("*float*: TOD factor for period 5\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor6", (getter)Revenue_get_dispatch_factor6,(setter)Revenue_set_dispatch_factor6, + PyDoc_STR("*float*: TOD factor for period 6\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor7", (getter)Revenue_get_dispatch_factor7,(setter)Revenue_set_dispatch_factor7, + PyDoc_STR("*float*: TOD factor for period 7\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor8", (getter)Revenue_get_dispatch_factor8,(setter)Revenue_set_dispatch_factor8, + PyDoc_STR("*float*: TOD factor for period 8\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, +{"dispatch_factor9", (getter)Revenue_get_dispatch_factor9,(setter)Revenue_set_dispatch_factor9, + PyDoc_STR("*float*: TOD factor for period 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), + NULL}, {"dispatch_factors_ts", (getter)Revenue_get_dispatch_factors_ts,(setter)Revenue_set_dispatch_factors_ts, PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), NULL}, @@ -255,9 +378,6 @@ static PyGetSetDef Revenue_getset[] = { {"dispatch_sched_weekend", (getter)Revenue_get_dispatch_sched_weekend,(setter)Revenue_set_dispatch_sched_weekend, PyDoc_STR("*sequence[sequence]*: Diurnal weekend TOD periods [1..9]\n\n**Info:**\n12 x 24 matrix\n\n**Required:**\nRequired if ppa_multiplier_model=0"), NULL}, -{"dispatch_tod_factors", (getter)Revenue_get_dispatch_tod_factors,(setter)Revenue_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Required:**\nRequired if ppa_multiplier_model=0"), - NULL}, {"flip_target_percent", (getter)Revenue_get_flip_target_percent,(setter)Revenue_set_flip_target_percent, PyDoc_STR("*float*: After-tax IRR target [%]\n\n**Constraints:**\nMIN=0,MAX=100\n\n**Required:**\nFalse. Automatically set to 11 if not assigned explicitly or loaded from defaults."), NULL}, diff --git a/modules/Swh.c b/modules/Swh.c index f66cdbcf..118d96a0 100644 --- a/modules/Swh.c +++ b/modules/Swh.c @@ -553,6 +553,54 @@ SWH_set_scaled_draw(VarGroupObject *self, PyObject *value, void *closure) return PySAM_array_setter(value, SAM_Swh_SWH_scaled_draw_aset, self->data_ptr); } +static PyObject * +SWH_get_shading_azal(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Swh_SWH_shading_azal_mget, self->data_ptr); +} + +static int +SWH_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Swh_SWH_shading_azal_mset, self->data_ptr); +} + +static PyObject * +SWH_get_shading_diff(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_Swh_SWH_shading_diff_nget, self->data_ptr); +} + +static int +SWH_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_Swh_SWH_shading_diff_nset, self->data_ptr); +} + +static PyObject * +SWH_get_shading_mxh(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Swh_SWH_shading_mxh_mget, self->data_ptr); +} + +static int +SWH_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Swh_SWH_shading_mxh_mset, self->data_ptr); +} + +static PyObject * +SWH_get_shading_timestep(VarGroupObject *self, void *closure) +{ + return PySAM_matrix_getter(SAM_Swh_SWH_shading_timestep_mget, self->data_ptr); +} + +static int +SWH_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_matrix_setter(value, SAM_Swh_SWH_shading_timestep_mset, self->data_ptr); +} + static PyObject * SWH_get_sky_model(VarGroupObject *self, void *closure) { @@ -731,6 +779,18 @@ static PyGetSetDef SWH_getset[] = { {"scaled_draw", (getter)SWH_get_scaled_draw,(setter)SWH_set_scaled_draw, PyDoc_STR("*sequence*: Hot water draw [kg/hr]\n\n**Constraints:**\nLENGTH=8760\n\n**Required:**\nTrue"), NULL}, +{"shading_azal", (getter)SWH_get_shading_azal,(setter)SWH_set_shading_azal, + PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_diff", (getter)SWH_get_shading_diff,(setter)SWH_set_shading_diff, + PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_mxh", (getter)SWH_get_shading_mxh,(setter)SWH_set_shading_mxh, + PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, +{"shading_timestep", (getter)SWH_get_shading_timestep,(setter)SWH_set_shading_timestep, + PyDoc_STR("*sequence[sequence]*: Time step beam shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), + NULL}, {"sky_model", (getter)SWH_get_sky_model,(setter)SWH_set_sky_model, PyDoc_STR("*float*: Tilted surface irradiance model [0/1/2]\n\n**Info:**\nIsotropic,HDKR,Perez\n\n**Constraints:**\nINTEGER,MIN=0,MAX=2\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), NULL}, @@ -805,278 +865,6 @@ static PyTypeObject SWH_Type = { }; -/* - * Shading Group - */ - -static PyTypeObject Shading_Type; - -static PyObject * -Shading_new(SAM_Swh data_ptr) -{ - PyObject* new_obj = Shading_Type.tp_alloc(&Shading_Type,0); - - VarGroupObject* Shading_obj = (VarGroupObject*)new_obj; - - Shading_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* Shading methods */ - -static PyObject * -Shading_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "Swh", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &Shading_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "Swh", "Shading")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -Shading_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &Shading_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef Shading_methods[] = { - {"assign", (PyCFunction)Shading_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``Shading_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)Shading_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``Shading_vals = { var: val, ...}``")}, - {"export", (PyCFunction)Shading_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -Shading_get_shading_azal(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Swh_Shading_shading_azal_mget, self->data_ptr); -} - -static int -Shading_set_shading_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Swh_Shading_shading_azal_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_azal(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_en_azal_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_azal(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_en_azal_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_diff(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_en_diff_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_diff(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_en_diff_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_en_mxh_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_en_mxh_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_en_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_en_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_en_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_en_timestep_nget, self->data_ptr); -} - -static int -Shading_set_shading_en_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_en_timestep_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_mxh(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Swh_Shading_shading_mxh_mget, self->data_ptr); -} - -static int -Shading_set_shading_mxh(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Swh_Shading_shading_mxh_mset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_string_option(VarGroupObject *self, void *closure) -{ - return PySAM_double_getter(SAM_Swh_Shading_shading_string_option_nget, self->data_ptr); -} - -static int -Shading_set_shading_string_option(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_double_setter(value, SAM_Swh_Shading_shading_string_option_nset, self->data_ptr); -} - -static PyObject * -Shading_get_shading_timestep(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_Swh_Shading_shading_timestep_mget, self->data_ptr); -} - -static int -Shading_set_shading_timestep(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_matrix_setter(value, SAM_Swh_Shading_shading_timestep_mset, self->data_ptr); -} - -static PyGetSetDef Shading_getset[] = { -{"shading_azal", (getter)Shading_get_shading_azal,(setter)Shading_set_shading_azal, - PyDoc_STR("*sequence[sequence]*: Azimuth x altitude beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_diff", (getter)Shading_get_shading_diff,(setter)Shading_set_shading_diff, - PyDoc_STR("*float*: Diffuse shading loss [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_en_azal", (getter)Shading_get_shading_en_azal,(setter)Shading_set_shading_en_azal, - PyDoc_STR("*float*: Enable azimuth x altitude beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_diff", (getter)Shading_get_shading_en_diff,(setter)Shading_set_shading_en_diff, - PyDoc_STR("*float*: Enable diffuse shading loss [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_mxh", (getter)Shading_get_shading_en_mxh,(setter)Shading_set_shading_en_mxh, - PyDoc_STR("*float*: Enable month x Hour beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_string_option", (getter)Shading_get_shading_en_string_option,(setter)Shading_set_shading_en_string_option, - PyDoc_STR("*float*: Enable shading string option [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_en_timestep", (getter)Shading_get_shading_en_timestep,(setter)Shading_set_shading_en_timestep, - PyDoc_STR("*float*: Enable timestep beam shading losses [0/1]\n\n**Options:**\n0=false,1=true\n\n**Constraints:**\nBOOLEAN\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_mxh", (getter)Shading_get_shading_mxh,(setter)Shading_set_shading_mxh, - PyDoc_STR("*sequence[sequence]*: Month x Hour beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, -{"shading_string_option", (getter)Shading_get_shading_string_option,(setter)Shading_set_shading_string_option, - PyDoc_STR("*float*: Shading string option\n\n**Options:**\n0=shadingdb,1=average,2=maximum,3=minimum\n\n**Constraints:**\nINTEGER,MIN=-1,MAX=4\n\n**Required:**\nFalse. Automatically set to -1 if not assigned explicitly or loaded from defaults."), - NULL}, -{"shading_timestep", (getter)Shading_get_shading_timestep,(setter)Shading_set_shading_timestep, - PyDoc_STR("*sequence[sequence]*: Timestep beam shading losses [%]\n\n**Required:**\nFalse for configuration with default inputs. May be required if a variable dependent on its value changes. Example: For the Detailed PV - Single Owner configuration, only Subarray 1 is enabled in the configuration defaults, so Subarray 2 inputs would not be required; if Subarray 2 is enabled, then Subarray 2 inputs is required."), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject Shading_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "Swh.Shading", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - Shading_methods, /*tp_methods*/ - 0, /*tp_members*/ - Shading_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * Outputs Group */ @@ -1544,10 +1332,6 @@ newSwhObject(void* data_ptr) PyDict_SetItemString(attr_dict, "SWH", SWH_obj); Py_DECREF(SWH_obj); - PyObject* Shading_obj = Shading_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Shading", Shading_obj); - Py_DECREF(Shading_obj); - PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1844,6 +1628,25 @@ SwhModule_exec(PyObject *m) Swh_Type.tp_dict = PyDict_New(); if (!Swh_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Swh_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Swh_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to Swh_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(Swh_Type.tp_dict, @@ -1858,13 +1661,6 @@ SwhModule_exec(PyObject *m) (PyObject*)&SWH_Type); Py_DECREF(&SWH_Type); - /// Add the Shading type object to Swh_Type - if (PyType_Ready(&Shading_Type) < 0) { goto fail; } - PyDict_SetItemString(Swh_Type.tp_dict, - "Shading", - (PyObject*)&Shading_Type); - Py_DECREF(&Shading_Type); - /// Add the Outputs type object to Swh_Type if (PyType_Ready(&Outputs_Type) < 0) { goto fail; } PyDict_SetItemString(Swh_Type.tp_dict, diff --git a/modules/TcsMSLF.c b/modules/TcsMSLF.c index 329ff5aa..da63b8a6 100644 --- a/modules/TcsMSLF.c +++ b/modules/TcsMSLF.c @@ -4820,6 +4820,25 @@ TcsMSLFModule_exec(PyObject *m) TcsMSLF_Type.tp_dict = PyDict_New(); if (!TcsMSLF_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TcsMSLF_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TcsMSLF_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TcsMSLF_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TcsMSLF_Type.tp_dict, diff --git a/modules/TcsgenericSolar.c b/modules/TcsgenericSolar.c index b0b11a7c..fd80ece9 100644 --- a/modules/TcsgenericSolar.c +++ b/modules/TcsgenericSolar.c @@ -2495,6 +2495,25 @@ TcsgenericSolarModule_exec(PyObject *m) TcsgenericSolar_Type.tp_dict = PyDict_New(); if (!TcsgenericSolar_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TcsgenericSolar_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TcsgenericSolar_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TcsgenericSolar_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TcsgenericSolar_Type.tp_dict, diff --git a/modules/TcslinearFresnel.c b/modules/TcslinearFresnel.c index 02b80f9e..182c6d38 100644 --- a/modules/TcslinearFresnel.c +++ b/modules/TcslinearFresnel.c @@ -3758,6 +3758,25 @@ TcslinearFresnelModule_exec(PyObject *m) TcslinearFresnel_Type.tp_dict = PyDict_New(); if (!TcslinearFresnel_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TcslinearFresnel_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TcslinearFresnel_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TcslinearFresnel_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TcslinearFresnel_Type.tp_dict, diff --git a/modules/TcsmoltenSalt.c b/modules/TcsmoltenSalt.c index bb4df41c..e8952db2 100644 --- a/modules/TcsmoltenSalt.c +++ b/modules/TcsmoltenSalt.c @@ -5383,6 +5383,114 @@ static PyMethodDef TimeOfDeliveryFactors_methods[] = { {NULL, NULL} /* sentinel */ }; +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor1_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor2_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor3_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor4_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor5_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor6_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor7_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor8_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +TimeOfDeliveryFactors_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor9_nget, self->data_ptr); +} + +static int +TimeOfDeliveryFactors_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_factor9_nset, self->data_ptr); +} + static PyObject * TimeOfDeliveryFactors_get_dispatch_factors_ts(VarGroupObject *self, void *closure) { @@ -5419,18 +5527,6 @@ TimeOfDeliveryFactors_set_dispatch_sched_weekend(VarGroupObject *self, PyObject return PySAM_matrix_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_sched_weekend_mset, self->data_ptr); } -static PyObject * -TimeOfDeliveryFactors_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -TimeOfDeliveryFactors_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_TcsmoltenSalt_TimeOfDeliveryFactors_dispatch_tod_factors_aset, self->data_ptr); -} - static PyObject * TimeOfDeliveryFactors_get_ppa_multiplier_model(VarGroupObject *self, void *closure) { @@ -5444,6 +5540,33 @@ TimeOfDeliveryFactors_set_ppa_multiplier_model(VarGroupObject *self, PyObject *v } static PyGetSetDef TimeOfDeliveryFactors_getset[] = { +{"dispatch_factor1", (getter)TimeOfDeliveryFactors_get_dispatch_factor1,(setter)TimeOfDeliveryFactors_set_dispatch_factor1, + PyDoc_STR("*float*: Dispatch payment factor 1\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor2", (getter)TimeOfDeliveryFactors_get_dispatch_factor2,(setter)TimeOfDeliveryFactors_set_dispatch_factor2, + PyDoc_STR("*float*: Dispatch payment factor 2\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor3", (getter)TimeOfDeliveryFactors_get_dispatch_factor3,(setter)TimeOfDeliveryFactors_set_dispatch_factor3, + PyDoc_STR("*float*: Dispatch payment factor 3\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor4", (getter)TimeOfDeliveryFactors_get_dispatch_factor4,(setter)TimeOfDeliveryFactors_set_dispatch_factor4, + PyDoc_STR("*float*: Dispatch payment factor 4\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor5", (getter)TimeOfDeliveryFactors_get_dispatch_factor5,(setter)TimeOfDeliveryFactors_set_dispatch_factor5, + PyDoc_STR("*float*: Dispatch payment factor 5\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor6", (getter)TimeOfDeliveryFactors_get_dispatch_factor6,(setter)TimeOfDeliveryFactors_set_dispatch_factor6, + PyDoc_STR("*float*: Dispatch payment factor 6\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor7", (getter)TimeOfDeliveryFactors_get_dispatch_factor7,(setter)TimeOfDeliveryFactors_set_dispatch_factor7, + PyDoc_STR("*float*: Dispatch payment factor 7\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor8", (getter)TimeOfDeliveryFactors_get_dispatch_factor8,(setter)TimeOfDeliveryFactors_set_dispatch_factor8, + PyDoc_STR("*float*: Dispatch payment factor 8\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, +{"dispatch_factor9", (getter)TimeOfDeliveryFactors_get_dispatch_factor9,(setter)TimeOfDeliveryFactors_set_dispatch_factor9, + PyDoc_STR("*float*: Dispatch payment factor 9\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), + NULL}, {"dispatch_factors_ts", (getter)TimeOfDeliveryFactors_get_dispatch_factors_ts,(setter)TimeOfDeliveryFactors_set_dispatch_factors_ts, PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1&csp_financial_model<5&is_dispatch=1&sim_type=1"), NULL}, @@ -5453,9 +5576,6 @@ static PyGetSetDef TimeOfDeliveryFactors_getset[] = { {"dispatch_sched_weekend", (getter)TimeOfDeliveryFactors_get_dispatch_sched_weekend,(setter)TimeOfDeliveryFactors_set_dispatch_sched_weekend, PyDoc_STR("*sequence[sequence]*: PPA pricing weekend schedule, 12x24\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), NULL}, -{"dispatch_tod_factors", (getter)TimeOfDeliveryFactors_get_dispatch_tod_factors,(setter)TimeOfDeliveryFactors_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Info:**\nWe added this array input after SAM 2022.12.21 to replace the functionality of former single value inputs dispatch_factor1 through dispatch_factor9\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), - NULL}, {"ppa_multiplier_model", (getter)TimeOfDeliveryFactors_get_ppa_multiplier_model,(setter)TimeOfDeliveryFactors_set_ppa_multiplier_model, PyDoc_STR("*float*: PPA multiplier model 0: dispatch factors dispatch_factorX, 1: hourly multipliers dispatch_factors_ts [0/1]\n\n**Options:**\n0=diurnal,1=timestep\n\n**Constraints:**\nINTEGER,MIN=0\n\n**Required:**\nFalse. Automatically set to 0 if not assigned explicitly or loaded from defaults."), NULL}, @@ -7033,12 +7153,6 @@ Outputs_get_annual_energy(VarGroupObject *self, void *closure) return PySAM_double_getter(SAM_TcsmoltenSalt_Outputs_annual_energy_nget, self->data_ptr); } -static PyObject * -Outputs_get_annual_energy_distribution_time(VarGroupObject *self, void *closure) -{ - return PySAM_matrix_getter(SAM_TcsmoltenSalt_Outputs_annual_energy_distribution_time_mget, self->data_ptr); -} - static PyObject * Outputs_get_annual_eta_rec_th(VarGroupObject *self, void *closure) { @@ -8417,9 +8531,6 @@ static PyGetSetDef Outputs_getset[] = { {"annual_energy", (getter)Outputs_get_annual_energy,(setter)0, PyDoc_STR("*float*: Annual total electric power to grid [kWhe]"), NULL}, -{"annual_energy_distribution_time", (getter)Outputs_get_annual_energy_distribution_time,(setter)0, - PyDoc_STR("*sequence[sequence]*: Annual energy production as function of time [kW]"), - NULL}, {"annual_eta_rec_th", (getter)Outputs_get_annual_eta_rec_th,(setter)0, PyDoc_STR("*float*: Annual receiver thermal efficiency ignoring rec reflective loss"), NULL}, @@ -9426,7 +9537,7 @@ static PyMethodDef TcsmoltenSaltModule_methods[] = { {"new", TcsmoltenSalt_new, METH_VARARGS, PyDoc_STR("new() -> TcsmoltenSalt")}, {"default", TcsmoltenSalt_default, METH_VARARGS, - PyDoc_STR("default(config) -> TcsmoltenSalt\n\nLoad defaults for the configuration ``config``. Available configurations are:\n\n - *\"MSPTAllEquityPartnershipFlip\"*\n\n - *\"MSPTLeveragedPartnershipFlip\"*\n\n - *\"MSPTMerchantPlant\"*\n\n - *\"MSPTNone\"*\n\n - *\"MSPTSaleLeaseback\"*\n\n - *\"MSPTSingleOwner\"*\n\n.. note::\n\n Some inputs do not have default values and may be assigned a value from the variable's **Required** attribute. See variable attribute descriptions below.")}, + PyDoc_STR("default(config) -> TcsmoltenSalt\n\nLoad defaults for the configuration ``config``. Available configurations are:\n\n - *\"MSPTAllEquityPartnershipFlip\"*\n\n - *\"MSPTLeveragedPartnershipFlip\"*\n\n - *\"MSPTMerchantPlant\"*\n\n - *\"MSPTSaleLeaseback\"*\n\n - *\"MSPTSingleOwner\"*\n\n.. note::\n\n Some inputs do not have default values and may be assigned a value from the variable's **Required** attribute. See variable attribute descriptions below.")}, {"wrap", TcsmoltenSalt_wrap, METH_VARARGS, PyDoc_STR("wrap(ssc_data_t) -> TcsmoltenSalt\n\nLoad data from a PySSC object.\n\n.. warning::\n\n Do not call PySSC.data_free on the ssc_data_t provided to ``wrap()``")}, {"from_existing", TcsmoltenSalt_from_existing, METH_VARARGS, @@ -9449,6 +9560,25 @@ TcsmoltenSaltModule_exec(PyObject *m) TcsmoltenSalt_Type.tp_dict = PyDict_New(); if (!TcsmoltenSalt_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TcsmoltenSalt_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TcsmoltenSalt_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the SolarResource type object to TcsmoltenSalt_Type if (PyType_Ready(&SolarResource_Type) < 0) { goto fail; } PyDict_SetItemString(TcsmoltenSalt_Type.tp_dict, diff --git a/modules/TcstroughEmpirical.c b/modules/TcstroughEmpirical.c index 4eea9bcd..7e981b67 100644 --- a/modules/TcstroughEmpirical.c +++ b/modules/TcstroughEmpirical.c @@ -3971,6 +3971,25 @@ TcstroughEmpiricalModule_exec(PyObject *m) TcstroughEmpirical_Type.tp_dict = PyDict_New(); if (!TcstroughEmpirical_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TcstroughEmpirical_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TcstroughEmpirical_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TcstroughEmpirical_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TcstroughEmpirical_Type.tp_dict, diff --git a/modules/TcstroughPhysical.c b/modules/TcstroughPhysical.c index 50497715..f6e84bf7 100644 --- a/modules/TcstroughPhysical.c +++ b/modules/TcstroughPhysical.c @@ -5570,6 +5570,25 @@ TcstroughPhysicalModule_exec(PyObject *m) TcstroughPhysical_Type.tp_dict = PyDict_New(); if (!TcstroughPhysical_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TcstroughPhysical_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TcstroughPhysical_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TcstroughPhysical_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TcstroughPhysical_Type.tp_dict, diff --git a/modules/TroughPhysical.c b/modules/TroughPhysical.c index 0db0fa8f..d6fa2386 100644 --- a/modules/TroughPhysical.c +++ b/modules/TroughPhysical.c @@ -3001,6 +3001,114 @@ Tou_set_disp_timeout(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_TroughPhysical_Tou_disp_timeout_nset, self->data_ptr); } +static PyObject * +Tou_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor1_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor2_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor3_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor4_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor5_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor6_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor7_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor8_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysical_Tou_dispatch_factor9_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysical_Tou_dispatch_factor9_nset, self->data_ptr); +} + static PyObject * Tou_get_dispatch_factors_ts(VarGroupObject *self, void *closure) { @@ -3272,6 +3380,33 @@ static PyGetSetDef Tou_getset[] = { {"disp_timeout", (getter)Tou_get_disp_timeout,(setter)Tou_set_disp_timeout, PyDoc_STR("*float*: Max. dispatch optimization solve duration [s]\n\n**Required:**\nRequired if is_dispatch=1"), NULL}, +{"dispatch_factor1", (getter)Tou_get_dispatch_factor1,(setter)Tou_set_dispatch_factor1, + PyDoc_STR("*float*: Dispatch payment factor 1\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor2", (getter)Tou_get_dispatch_factor2,(setter)Tou_set_dispatch_factor2, + PyDoc_STR("*float*: Dispatch payment factor 2\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor3", (getter)Tou_get_dispatch_factor3,(setter)Tou_set_dispatch_factor3, + PyDoc_STR("*float*: Dispatch payment factor 3\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor4", (getter)Tou_get_dispatch_factor4,(setter)Tou_set_dispatch_factor4, + PyDoc_STR("*float*: Dispatch payment factor 4\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor5", (getter)Tou_get_dispatch_factor5,(setter)Tou_set_dispatch_factor5, + PyDoc_STR("*float*: Dispatch payment factor 5\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor6", (getter)Tou_get_dispatch_factor6,(setter)Tou_set_dispatch_factor6, + PyDoc_STR("*float*: Dispatch payment factor 6\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor7", (getter)Tou_get_dispatch_factor7,(setter)Tou_set_dispatch_factor7, + PyDoc_STR("*float*: Dispatch payment factor 7\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor8", (getter)Tou_get_dispatch_factor8,(setter)Tou_set_dispatch_factor8, + PyDoc_STR("*float*: Dispatch payment factor 8\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, +{"dispatch_factor9", (getter)Tou_get_dispatch_factor9,(setter)Tou_set_dispatch_factor9, + PyDoc_STR("*float*: Dispatch payment factor 9\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1"), + NULL}, {"dispatch_factors_ts", (getter)Tou_get_dispatch_factors_ts,(setter)Tou_set_dispatch_factors_ts, PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1&csp_financial_model<5&is_dispatch=1"), NULL}, @@ -3954,143 +4089,6 @@ static PyTypeObject ElectricityRates_Type = { }; -/* - * TimeOfDeliveryFactors Group - */ - -static PyTypeObject TimeOfDeliveryFactors_Type; - -static PyObject * -TimeOfDeliveryFactors_new(SAM_TroughPhysical data_ptr) -{ - PyObject* new_obj = TimeOfDeliveryFactors_Type.tp_alloc(&TimeOfDeliveryFactors_Type,0); - - VarGroupObject* TimeOfDeliveryFactors_obj = (VarGroupObject*)new_obj; - - TimeOfDeliveryFactors_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* TimeOfDeliveryFactors methods */ - -static PyObject * -TimeOfDeliveryFactors_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "TroughPhysical", "TimeOfDeliveryFactors")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -TimeOfDeliveryFactors_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &TimeOfDeliveryFactors_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "TroughPhysical", "TimeOfDeliveryFactors")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -TimeOfDeliveryFactors_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &TimeOfDeliveryFactors_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef TimeOfDeliveryFactors_methods[] = { - {"assign", (PyCFunction)TimeOfDeliveryFactors_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``TimeOfDeliveryFactors_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)TimeOfDeliveryFactors_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``TimeOfDeliveryFactors_vals = { var: val, ...}``")}, - {"export", (PyCFunction)TimeOfDeliveryFactors_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -TimeOfDeliveryFactors_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_TroughPhysical_TimeOfDeliveryFactors_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -TimeOfDeliveryFactors_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_TroughPhysical_TimeOfDeliveryFactors_dispatch_tod_factors_aset, self->data_ptr); -} - -static PyGetSetDef TimeOfDeliveryFactors_getset[] = { -{"dispatch_tod_factors", (getter)TimeOfDeliveryFactors_get_dispatch_tod_factors,(setter)TimeOfDeliveryFactors_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Info:**\nWe added this array input after SAM 2022.12.21 to replace the functionality of former single value inputs dispatch_factor1 through dispatch_factor9\n\n**Required:**\nRequired if ppa_multiplier_model=0&csp_financial_model<5&is_dispatch=1&sim_type=1"), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject TimeOfDeliveryFactors_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "TroughPhysical.TimeOfDeliveryFactors", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - TimeOfDeliveryFactors_methods, /*tp_methods*/ - 0, /*tp_members*/ - TimeOfDeliveryFactors_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * Revenue Group */ @@ -6505,10 +6503,6 @@ newTroughPhysicalObject(void* data_ptr) PyDict_SetItemString(attr_dict, "ElectricityRates", ElectricityRates_obj); Py_DECREF(ElectricityRates_obj); - PyObject* TimeOfDeliveryFactors_obj = TimeOfDeliveryFactors_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "TimeOfDeliveryFactors", TimeOfDeliveryFactors_obj); - Py_DECREF(TimeOfDeliveryFactors_obj); - PyObject* Revenue_obj = Revenue_new(self->data_ptr); PyDict_SetItemString(attr_dict, "Revenue", Revenue_obj); Py_DECREF(Revenue_obj); @@ -6821,6 +6815,25 @@ TroughPhysicalModule_exec(PyObject *m) TroughPhysical_Type.tp_dict = PyDict_New(); if (!TroughPhysical_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TroughPhysical_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TroughPhysical_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TroughPhysical_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TroughPhysical_Type.tp_dict, @@ -6884,13 +6897,6 @@ TroughPhysicalModule_exec(PyObject *m) (PyObject*)&ElectricityRates_Type); Py_DECREF(&ElectricityRates_Type); - /// Add the TimeOfDeliveryFactors type object to TroughPhysical_Type - if (PyType_Ready(&TimeOfDeliveryFactors_Type) < 0) { goto fail; } - PyDict_SetItemString(TroughPhysical_Type.tp_dict, - "TimeOfDeliveryFactors", - (PyObject*)&TimeOfDeliveryFactors_Type); - Py_DECREF(&TimeOfDeliveryFactors_Type); - /// Add the Revenue type object to TroughPhysical_Type if (PyType_Ready(&Revenue_Type) < 0) { goto fail; } PyDict_SetItemString(TroughPhysical_Type.tp_dict, diff --git a/modules/TroughPhysicalCspSolver.c b/modules/TroughPhysicalCspSolver.c index 1123f1d5..b4353fef 100644 --- a/modules/TroughPhysicalCspSolver.c +++ b/modules/TroughPhysicalCspSolver.c @@ -4850,6 +4850,25 @@ TroughPhysicalCspSolverModule_exec(PyObject *m) TroughPhysicalCspSolver_Type.tp_dict = PyDict_New(); if (!TroughPhysicalCspSolver_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TroughPhysicalCspSolver_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TroughPhysicalCspSolver_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TroughPhysicalCspSolver_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TroughPhysicalCspSolver_Type.tp_dict, diff --git a/modules/TroughPhysicalProcessHeat.c b/modules/TroughPhysicalProcessHeat.c index 1186ee88..6e3d2669 100644 --- a/modules/TroughPhysicalProcessHeat.c +++ b/modules/TroughPhysicalProcessHeat.c @@ -2906,6 +2906,114 @@ Tou_set_disp_timeout(VarGroupObject *self, PyObject *value, void *closure) return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_disp_timeout_nset, self->data_ptr); } +static PyObject * +Tou_get_dispatch_factor1(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor1_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor1(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor1_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor2(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor2_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor2(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor2_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor3(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor3_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor3(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor3_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor4(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor4_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor4(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor4_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor5(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor5_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor5(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor5_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor6(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor6_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor6(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor6_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor7(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor7_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor7(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor7_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor8(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor8_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor8(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor8_nset, self->data_ptr); +} + +static PyObject * +Tou_get_dispatch_factor9(VarGroupObject *self, void *closure) +{ + return PySAM_double_getter(SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor9_nget, self->data_ptr); +} + +static int +Tou_set_dispatch_factor9(VarGroupObject *self, PyObject *value, void *closure) +{ + return PySAM_double_setter(value, SAM_TroughPhysicalProcessHeat_Tou_dispatch_factor9_nset, self->data_ptr); +} + static PyObject * Tou_get_dispatch_factors_ts(VarGroupObject *self, void *closure) { @@ -3171,8 +3279,35 @@ static PyGetSetDef Tou_getset[] = { {"disp_timeout", (getter)Tou_get_disp_timeout,(setter)Tou_set_disp_timeout, PyDoc_STR("*float*: Max. dispatch optimization solve duration [s]\n\n**Required:**\nRequired if is_dispatch=1"), NULL}, +{"dispatch_factor1", (getter)Tou_get_dispatch_factor1,(setter)Tou_set_dispatch_factor1, + PyDoc_STR("*float*: Dispatch payment factor 1\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor2", (getter)Tou_get_dispatch_factor2,(setter)Tou_set_dispatch_factor2, + PyDoc_STR("*float*: Dispatch payment factor 2\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor3", (getter)Tou_get_dispatch_factor3,(setter)Tou_set_dispatch_factor3, + PyDoc_STR("*float*: Dispatch payment factor 3\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor4", (getter)Tou_get_dispatch_factor4,(setter)Tou_set_dispatch_factor4, + PyDoc_STR("*float*: Dispatch payment factor 4\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor5", (getter)Tou_get_dispatch_factor5,(setter)Tou_set_dispatch_factor5, + PyDoc_STR("*float*: Dispatch payment factor 5\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor6", (getter)Tou_get_dispatch_factor6,(setter)Tou_set_dispatch_factor6, + PyDoc_STR("*float*: Dispatch payment factor 6\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor7", (getter)Tou_get_dispatch_factor7,(setter)Tou_set_dispatch_factor7, + PyDoc_STR("*float*: Dispatch payment factor 7\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor8", (getter)Tou_get_dispatch_factor8,(setter)Tou_set_dispatch_factor8, + PyDoc_STR("*float*: Dispatch payment factor 8\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, +{"dispatch_factor9", (getter)Tou_get_dispatch_factor9,(setter)Tou_set_dispatch_factor9, + PyDoc_STR("*float*: Dispatch payment factor 9\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), + NULL}, {"dispatch_factors_ts", (getter)Tou_get_dispatch_factors_ts,(setter)Tou_set_dispatch_factors_ts, - PyDoc_STR("*sequence*: Dispatch payment factor array"), + PyDoc_STR("*sequence*: Dispatch payment factor array\n\n**Required:**\nRequired if ppa_multiplier_model=1"), NULL}, {"dispatch_sched_weekday", (getter)Tou_get_dispatch_sched_weekday,(setter)Tou_set_dispatch_sched_weekday, PyDoc_STR("*sequence[sequence]*: 12x24 PPA pricing Weekday schedule\n\n**Required:**\nFalse. Automatically set to 1 if not assigned explicitly or loaded from defaults."), @@ -3412,143 +3547,6 @@ static PyTypeObject SystemControl_Type = { }; -/* - * TimeOfDeliveryFactors Group - */ - -static PyTypeObject TimeOfDeliveryFactors_Type; - -static PyObject * -TimeOfDeliveryFactors_new(SAM_TroughPhysicalProcessHeat data_ptr) -{ - PyObject* new_obj = TimeOfDeliveryFactors_Type.tp_alloc(&TimeOfDeliveryFactors_Type,0); - - VarGroupObject* TimeOfDeliveryFactors_obj = (VarGroupObject*)new_obj; - - TimeOfDeliveryFactors_obj->data_ptr = (SAM_table)data_ptr; - - return new_obj; -} - -/* TimeOfDeliveryFactors methods */ - -static PyObject * -TimeOfDeliveryFactors_assign(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - - if (!PySAM_assign_from_dict(self->data_ptr, dict, "TroughPhysicalProcessHeat", "TimeOfDeliveryFactors")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -TimeOfDeliveryFactors_replace(VarGroupObject *self, PyObject *args) -{ - PyObject* dict; - if (!PyArg_ParseTuple(args, "O:assign", &dict)){ - return NULL; - } - PyTypeObject* tp = &TimeOfDeliveryFactors_Type; - - if (!PySAM_replace_from_dict(tp, self->data_ptr, dict, "TroughPhysicalProcessHeat", "TimeOfDeliveryFactors")){ - return NULL; - } - - Py_INCREF(Py_None); - return Py_None; -} - -static PyObject * -TimeOfDeliveryFactors_export(VarGroupObject *self, PyObject *args) -{ - PyTypeObject* tp = &TimeOfDeliveryFactors_Type; - PyObject* dict = PySAM_export_to_dict((PyObject *) self, tp); - return dict; -} - -static PyMethodDef TimeOfDeliveryFactors_methods[] = { - {"assign", (PyCFunction)TimeOfDeliveryFactors_assign, METH_VARARGS, - PyDoc_STR("assign(dict) -> None\n Assign attributes from dictionary, overwriting but not removing values.\n\n``TimeOfDeliveryFactors_vals = { var: val, ...}``")}, - {"replace", (PyCFunction)TimeOfDeliveryFactors_replace, METH_VARARGS, - PyDoc_STR("replace(dict) -> None\n Replace attributes from dictionary, unassigning values not present in input ``dict``.\n\n``TimeOfDeliveryFactors_vals = { var: val, ...}``")}, - {"export", (PyCFunction)TimeOfDeliveryFactors_export, METH_VARARGS, - PyDoc_STR("export() -> dict\n Export attributes into dictionary.")}, - {NULL, NULL} /* sentinel */ -}; - -static PyObject * -TimeOfDeliveryFactors_get_dispatch_tod_factors(VarGroupObject *self, void *closure) -{ - return PySAM_array_getter(SAM_TroughPhysicalProcessHeat_TimeOfDeliveryFactors_dispatch_tod_factors_aget, self->data_ptr); -} - -static int -TimeOfDeliveryFactors_set_dispatch_tod_factors(VarGroupObject *self, PyObject *value, void *closure) -{ - return PySAM_array_setter(value, SAM_TroughPhysicalProcessHeat_TimeOfDeliveryFactors_dispatch_tod_factors_aset, self->data_ptr); -} - -static PyGetSetDef TimeOfDeliveryFactors_getset[] = { -{"dispatch_tod_factors", (getter)TimeOfDeliveryFactors_get_dispatch_tod_factors,(setter)TimeOfDeliveryFactors_set_dispatch_tod_factors, - PyDoc_STR("*sequence*: TOD factors for periods 1 through 9\n\n**Info:**\nWe added this array input after SAM 2022.12.21 to replace the functionality of former single value inputs dispatch_factor1 through dispatch_factor9\n\n**Required:**\nRequired if is_dispatch=1&sim_type=1"), - NULL}, - {NULL} /* Sentinel */ -}; - -static PyTypeObject TimeOfDeliveryFactors_Type = { - /* The ob_type field must be initialized in the module init function - * to be portable to Windows without using C++. */ - PyVarObject_HEAD_INIT(NULL, 0) - "TroughPhysicalProcessHeat.TimeOfDeliveryFactors", /*tp_name*/ - sizeof(VarGroupObject), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - /* methods */ - 0, /*tp_dealloc*/ - 0, /*tp_print*/ - (getattrfunc)0, /*tp_getattr*/ - 0, /*tp_setattr*/ - 0, /*tp_reserved*/ - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT, /*tp_flags*/ - 0, /*tp_doc*/ - 0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistofnset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - TimeOfDeliveryFactors_methods, /*tp_methods*/ - 0, /*tp_members*/ - TimeOfDeliveryFactors_getset, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictofnset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - 0, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ -}; - - /* * System Group */ @@ -4695,10 +4693,6 @@ newTroughPhysicalProcessHeatObject(void* data_ptr) PyDict_SetItemString(attr_dict, "SystemControl", SystemControl_obj); Py_DECREF(SystemControl_obj); - PyObject* TimeOfDeliveryFactors_obj = TimeOfDeliveryFactors_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "TimeOfDeliveryFactors", TimeOfDeliveryFactors_obj); - Py_DECREF(TimeOfDeliveryFactors_obj); - PyObject* System_obj = System_new(self->data_ptr); PyDict_SetItemString(attr_dict, "System", System_obj); Py_DECREF(System_obj); @@ -5003,6 +4997,25 @@ TroughPhysicalProcessHeatModule_exec(PyObject *m) TroughPhysicalProcessHeat_Type.tp_dict = PyDict_New(); if (!TroughPhysicalProcessHeat_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to TroughPhysicalProcessHeat_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(TroughPhysicalProcessHeat_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Weather type object to TroughPhysicalProcessHeat_Type if (PyType_Ready(&Weather_Type) < 0) { goto fail; } PyDict_SetItemString(TroughPhysicalProcessHeat_Type.tp_dict, @@ -5059,13 +5072,6 @@ TroughPhysicalProcessHeatModule_exec(PyObject *m) (PyObject*)&SystemControl_Type); Py_DECREF(&SystemControl_Type); - /// Add the TimeOfDeliveryFactors type object to TroughPhysicalProcessHeat_Type - if (PyType_Ready(&TimeOfDeliveryFactors_Type) < 0) { goto fail; } - PyDict_SetItemString(TroughPhysicalProcessHeat_Type.tp_dict, - "TimeOfDeliveryFactors", - (PyObject*)&TimeOfDeliveryFactors_Type); - Py_DECREF(&TimeOfDeliveryFactors_Type); - /// Add the System type object to TroughPhysicalProcessHeat_Type if (PyType_Ready(&System_Type) < 0) { goto fail; } PyDict_SetItemString(TroughPhysicalProcessHeat_Type.tp_dict, diff --git a/modules/Windpower.c b/modules/Windpower.c index a580638a..4695793a 100644 --- a/modules/Windpower.c +++ b/modules/Windpower.c @@ -1689,6 +1689,10 @@ newWindpowerObject(void* data_ptr) PyDict_SetItemString(attr_dict, "Losses", Losses_obj); Py_DECREF(Losses_obj); + PyObject* Uncertainty_obj = Uncertainty_new(self->data_ptr); + PyDict_SetItemString(attr_dict, "Uncertainty", Uncertainty_obj); + Py_DECREF(Uncertainty_obj); + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); PyObject* data_cap = PyCapsule_New(self->data_ptr, NULL, NULL); @@ -1704,10 +1708,6 @@ newWindpowerObject(void* data_ptr) PyDict_SetItemString(attr_dict, "AdjustmentFactors", Adjust_obj); Py_DECREF(Adjust_obj); - PyObject* Uncertainty_obj = Uncertainty_new(self->data_ptr); - PyDict_SetItemString(attr_dict, "Uncertainty", Uncertainty_obj); - Py_DECREF(Uncertainty_obj); - PyObject* Outputs_obj = Outputs_new(self->data_ptr); PyDict_SetItemString(attr_dict, "Outputs", Outputs_obj); Py_DECREF(Outputs_obj); @@ -1989,6 +1989,25 @@ WindpowerModule_exec(PyObject *m) Windpower_Type.tp_dict = PyDict_New(); if (!Windpower_Type.tp_dict) { goto fail; } + /// Add the AdjustmentFactors type object to Windpower_Type + PyObject* AdjustmentFactorsModule = PyImport_ImportModule("AdjustmentFactors"); + if (!AdjustmentFactorsModule){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors module."), NULL, NULL); + } + + PyTypeObject* AdjustmentFactors_Type = (PyTypeObject*)PyObject_GetAttrString(AdjustmentFactorsModule, "AdjustmentFactors"); + if (!AdjustmentFactors_Type){ + PyErr_SetImportError(PyUnicode_FromString("Could not import AdjustmentFactors type."), NULL, NULL); + } + Py_XDECREF(AdjustmentFactorsModule); + + if (PyType_Ready(AdjustmentFactors_Type) < 0) { goto fail; } + PyDict_SetItemString(Windpower_Type.tp_dict, + "AdjustmentFactors", + (PyObject*)AdjustmentFactors_Type); + Py_DECREF(&AdjustmentFactors_Type); + Py_XDECREF(AdjustmentFactors_Type); + /// Add the Resource type object to Windpower_Type if (PyType_Ready(&Resource_Type) < 0) { goto fail; } PyDict_SetItemString(Windpower_Type.tp_dict, diff --git a/src/AdjustmentFactors.c b/src/AdjustmentFactors.c index f0d38598..6a9deaae 100644 --- a/src/AdjustmentFactors.c +++ b/src/AdjustmentFactors.c @@ -84,7 +84,6 @@ AdjustmentFactors_set_hourly(AdjustmentFactorsObject *self, PyObject *value, voi return PySAM_array_setter(value, SAM_AdjustmentFactors_adjust_hourly_aset, self->data_ptr); } - static PyObject * AdjustmentFactors_get_periods(AdjustmentFactorsObject *self, void *closure) { @@ -169,24 +168,24 @@ AdjustmentFactors_set_sf_periods(AdjustmentFactorsObject *self, PyObject *value, } static PyGetSetDef AdjustmentFactors_getset[] = { - {"adjust_constant", (getter)AdjustmentFactors_get_constant, (setter)AdjustmentFactors_set_constant, + {"constant", (getter)AdjustmentFactors_get_constant, (setter)AdjustmentFactors_set_constant, "type: float", NULL}, - {"adjust_hourly", (getter)AdjustmentFactors_get_hourly, (setter)AdjustmentFactors_set_hourly, - "AC Hourly Adjustment Factors [%]", NULL}, - {"adjust_periods", (getter)AdjustmentFactors_get_periods, (setter)AdjustmentFactors_set_periods, + {"hourly", (getter)AdjustmentFactors_get_hourly, (setter)AdjustmentFactors_set_hourly, + "AC Hourly Adjustment Factors [%]", NULL}, + {"periods", (getter)AdjustmentFactors_get_periods, (setter)AdjustmentFactors_set_periods, "AC Period-based Adjustment Factors [%]", NULL}, - {"dc_adjust_constant", (getter)AdjustmentFactors_get_dc_constant, (setter)AdjustmentFactors_set_dc_constant, + {"dc_constant", (getter)AdjustmentFactors_get_dc_constant, (setter)AdjustmentFactors_set_dc_constant, + "DC Constant loss adjustment [%]", NULL}, + {"dc_hourly", (getter)AdjustmentFactors_get_dc_hourly, (setter)AdjustmentFactors_set_dc_hourly, + "DC Hourly Adjustment Factors [%]", NULL}, + {"dc_periods", (getter)AdjustmentFactors_get_dc_periods, (setter)AdjustmentFactors_set_dc_periods, + "DC Period-based Adjustment Factors [%]", NULL}, + {"sf_constant", (getter)AdjustmentFactors_get_sf_constant, (setter)AdjustmentFactors_set_sf_constant, "DC Constant loss adjustment [%]", NULL}, - {"dc_adjust_hourly", (getter)AdjustmentFactors_get_dc_hourly, (setter)AdjustmentFactors_set_dc_hourly, + {"sf_hourly", (getter)AdjustmentFactors_get_sf_hourly, (setter)AdjustmentFactors_set_sf_hourly, "DC Hourly Adjustment Factors [%]", NULL}, - {"dc_adjust_periods", (getter)AdjustmentFactors_get_dc_periods, (setter)AdjustmentFactors_set_dc_periods, + {"sf_periods", (getter)AdjustmentFactors_get_sf_periods, (setter)AdjustmentFactors_set_sf_periods, "DC Period-based Adjustment Factors [%]", NULL}, - {"sf_adjust_constant", (getter)AdjustmentFactors_get_sf_constant, (setter)AdjustmentFactors_set_sf_constant, - "SF Constant loss adjustment [%]", NULL}, - {"sf_adjust_hourly", (getter)AdjustmentFactors_get_sf_hourly, (setter)AdjustmentFactors_set_sf_hourly, - "SF Hourly Adjustment Factors [%]", NULL}, - {"sf_adjust_periods", (getter)AdjustmentFactors_get_sf_periods, (setter)AdjustmentFactors_set_sf_periods, - "SF Period-based Adjustment Factors [%]", NULL}, {NULL} /* Sentinel */ }; diff --git a/stubs/stubs/Equpartflip.pyi b/stubs/stubs/Equpartflip.pyi index 40aa5ff8..9c1c41ad 100644 --- a/stubs/stubs/Equpartflip.pyi +++ b/stubs/stubs/Equpartflip.pyi @@ -31,12 +31,7 @@ class Equpartflip(object): pass - dispatch_factors_ts = tuple - dispatch_sched_weekday = tuple - dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple ppa_escalation = float - ppa_multiplier_model = float ppa_price_input = tuple ppa_soln_max = float ppa_soln_max_iterations = float @@ -388,6 +383,19 @@ class Equpartflip(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float + dispatch_factors_ts = tuple + dispatch_sched_weekday = tuple + dispatch_sched_weekend = tuple + ppa_multiplier_model = float system_use_lifetime_output = float diff --git a/stubs/stubs/EtesElectricResistance.pyi b/stubs/stubs/EtesElectricResistance.pyi index 438bb402..805f5047 100644 --- a/stubs/stubs/EtesElectricResistance.pyi +++ b/stubs/stubs/EtesElectricResistance.pyi @@ -220,10 +220,18 @@ class EtesElectricResistance(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float dispatch_factors_ts = tuple dispatch_sched_weekday = tuple dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple ppa_multiplier_model = float diff --git a/stubs/stubs/EtesPtes.pyi b/stubs/stubs/EtesPtes.pyi index 6f005e42..d4f4388f 100644 --- a/stubs/stubs/EtesPtes.pyi +++ b/stubs/stubs/EtesPtes.pyi @@ -218,10 +218,18 @@ class EtesPtes(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float dispatch_factors_ts = tuple dispatch_sched_weekday = tuple dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple ppa_multiplier_model = float @@ -438,9 +446,6 @@ class EtesPtes(object): op_mode_1 = tuple op_mode_2 = tuple op_mode_3 = tuple - operating_modes_a = tuple - operating_modes_b = tuple - operating_modes_c = tuple ppa_soln_mode = float q_balance = tuple q_dot_CT_tes_heater = tuple diff --git a/stubs/stubs/HostDeveloper.pyi b/stubs/stubs/HostDeveloper.pyi index 36b6a444..1f56a6bc 100644 --- a/stubs/stubs/HostDeveloper.pyi +++ b/stubs/stubs/HostDeveloper.pyi @@ -31,14 +31,9 @@ class HostDeveloper(object): pass - dispatch_factors_ts = tuple - dispatch_sched_weekday = tuple - dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple flip_target_percent = float flip_target_year = float ppa_escalation = float - ppa_multiplier_model = float ppa_price_input = tuple ppa_soln_max = float ppa_soln_max_iterations = float @@ -461,6 +456,19 @@ class HostDeveloper(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float + dispatch_factors_ts = tuple + dispatch_sched_weekday = tuple + dispatch_sched_weekend = tuple + ppa_multiplier_model = float system_use_lifetime_output = float diff --git a/stubs/stubs/Levpartflip.pyi b/stubs/stubs/Levpartflip.pyi index 351c2f9a..8bf9052f 100644 --- a/stubs/stubs/Levpartflip.pyi +++ b/stubs/stubs/Levpartflip.pyi @@ -31,14 +31,9 @@ class Levpartflip(object): pass - dispatch_factors_ts = tuple - dispatch_sched_weekday = tuple - dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple flip_target_percent = float flip_target_year = float ppa_escalation = float - ppa_multiplier_model = float ppa_price_input = tuple ppa_soln_max = float ppa_soln_max_iterations = float @@ -422,6 +417,19 @@ class Levpartflip(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float + dispatch_factors_ts = tuple + dispatch_sched_weekday = tuple + dispatch_sched_weekend = tuple + ppa_multiplier_model = float system_use_lifetime_output = float diff --git a/stubs/stubs/MhkWave.pyi b/stubs/stubs/MhkWave.pyi index 278e3cc0..aa86af80 100644 --- a/stubs/stubs/MhkWave.pyi +++ b/stubs/stubs/MhkWave.pyi @@ -59,6 +59,22 @@ class MhkWave(object): year = tuple + class Lifetime(object): + def assign(self): + pass + + def export(self) -> dict: + pass + + def __init__(self, *args, **kwargs): + pass + + + analysis_period = float + generic_degradation = tuple + system_use_lifetime_output = float + + class AdjustmentFactors(object): def assign(self): pass @@ -79,22 +95,6 @@ class MhkWave(object): sf_hourly = tuple sf_periods = tuple - class Lifetime(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - analysis_period = float - generic_degradation = tuple - system_use_lifetime_output = float - - class Outputs(object): def assign(self): pass diff --git a/stubs/stubs/Pvsamv1.pyi b/stubs/stubs/Pvsamv1.pyi index 81ea45bd..496f0728 100644 --- a/stubs/stubs/Pvsamv1.pyi +++ b/stubs/stubs/Pvsamv1.pyi @@ -209,44 +209,24 @@ class Pvsamv1(object): subarray1_shade_mode = float subarray1_shading_azal = tuple subarray1_shading_diff = float - subarray1_shading_en_azal = float - subarray1_shading_en_diff = float - subarray1_shading_en_mxh = float - subarray1_shading_en_string_option = float - subarray1_shading_en_timestep = float subarray1_shading_mxh = tuple subarray1_shading_string_option = float subarray1_shading_timestep = tuple subarray2_shade_mode = float subarray2_shading_azal = tuple subarray2_shading_diff = float - subarray2_shading_en_azal = float - subarray2_shading_en_diff = float - subarray2_shading_en_mxh = float - subarray2_shading_en_string_option = float - subarray2_shading_en_timestep = float subarray2_shading_mxh = tuple subarray2_shading_string_option = float subarray2_shading_timestep = tuple subarray3_shade_mode = float subarray3_shading_azal = tuple subarray3_shading_diff = float - subarray3_shading_en_azal = float - subarray3_shading_en_diff = float - subarray3_shading_en_mxh = float - subarray3_shading_en_string_option = float - subarray3_shading_en_timestep = float subarray3_shading_mxh = tuple subarray3_shading_string_option = float subarray3_shading_timestep = tuple subarray4_shade_mode = float subarray4_shading_azal = tuple subarray4_shading_diff = float - subarray4_shading_en_azal = float - subarray4_shading_en_diff = float - subarray4_shading_en_mxh = float - subarray4_shading_en_string_option = float - subarray4_shading_en_timestep = float subarray4_shading_mxh = tuple subarray4_shading_string_option = float subarray4_shading_timestep = tuple @@ -797,26 +777,6 @@ class Pvsamv1(object): run_resiliency_calcs = float - class AdjustmentFactors(object): - def assign(self): - pass - - def export(self): - return {} - - def __init__(self, *args, **kwargs): # real signature unknown - pass - - constant = float - dc_constant = float - dc_hourly = tuple - dc_periods = tuple - hourly = tuple - periods = tuple - sf_constant = float - sf_hourly = tuple - sf_periods = tuple - class BatteryCell(object): def assign(self): pass @@ -1067,6 +1027,26 @@ class Pvsamv1(object): grid_interconnection_limit_kwac = float + class AdjustmentFactors(object): + def assign(self): + pass + + def export(self): + return {} + + def __init__(self, *args, **kwargs): # real signature unknown + pass + + constant = float + dc_constant = float + dc_hourly = tuple + dc_periods = tuple + hourly = tuple + periods = tuple + sf_constant = float + sf_hourly = tuple + sf_periods = tuple + class Outputs(object): def assign(self): pass diff --git a/stubs/stubs/Pvwattsv1.pyi b/stubs/stubs/Pvwattsv1.pyi index 212fc00e..3d162c9b 100644 --- a/stubs/stubs/Pvwattsv1.pyi +++ b/stubs/stubs/Pvwattsv1.pyi @@ -61,6 +61,10 @@ class Pvwattsv1(object): poa_cutin = float rotlim = float shade_mode_1x = float + shading_azal = tuple + shading_diff = float + shading_mxh = tuple + shading_timestep = tuple system_size = float tilt = float tilt_eq_lat = float @@ -72,29 +76,6 @@ class Pvwattsv1(object): w_stow = float - class Shading(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - shading_azal = tuple - shading_diff = float - shading_en_azal = float - shading_en_diff = float - shading_en_mxh = float - shading_en_string_option = float - shading_en_timestep = float - shading_mxh = tuple - shading_string_option = float - shading_timestep = tuple - - class AdjustmentFactors(object): def assign(self): pass diff --git a/stubs/stubs/Pvwattsv5.pyi b/stubs/stubs/Pvwattsv5.pyi index 39099d38..934d17fe 100644 --- a/stubs/stubs/Pvwattsv5.pyi +++ b/stubs/stubs/Pvwattsv5.pyi @@ -70,31 +70,12 @@ class Pvwattsv5(object): inv_eff = float losses = float module_type = float - system_capacity = float - tilt = float - - - class Shading(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - shading_azal = tuple shading_diff = float - shading_en_azal = float - shading_en_diff = float - shading_en_mxh = float - shading_en_string_option = float - shading_en_timestep = float shading_mxh = tuple - shading_string_option = float shading_timestep = tuple + system_capacity = float + tilt = float class AdjustmentFactors(object): diff --git a/stubs/stubs/Pvwattsv7.pyi b/stubs/stubs/Pvwattsv7.pyi index 1cdcbbb1..8020ef8f 100644 --- a/stubs/stubs/Pvwattsv7.pyi +++ b/stubs/stubs/Pvwattsv7.pyi @@ -79,6 +79,10 @@ class Pvwattsv7(object): losses = float module_type = float rotlim = float + shading_azal = tuple + shading_diff = float + shading_mxh = tuple + shading_timestep = tuple soiling = tuple stow_wspd = float system_capacity = float @@ -88,29 +92,6 @@ class Pvwattsv7(object): xfmr_nll = float - class Shading(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - shading_azal = tuple - shading_diff = float - shading_en_azal = float - shading_en_diff = float - shading_en_mxh = float - shading_en_string_option = float - shading_en_timestep = float - shading_mxh = tuple - shading_string_option = float - shading_timestep = tuple - - class AdjustmentFactors(object): def assign(self): pass diff --git a/stubs/stubs/Pvwattsv8.pyi b/stubs/stubs/Pvwattsv8.pyi index c9eec3e1..4bd1c305 100644 --- a/stubs/stubs/Pvwattsv8.pyi +++ b/stubs/stubs/Pvwattsv8.pyi @@ -81,6 +81,10 @@ class Pvwattsv8(object): losses = float module_type = float rotlim = float + shading_azal = tuple + shading_diff = float + shading_mxh = tuple + shading_timestep = tuple soiling = tuple stow_wspd = float system_capacity = float @@ -90,29 +94,6 @@ class Pvwattsv8(object): xfmr_nll = float - class Shading(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - shading_azal = tuple - shading_diff = float - shading_en_azal = float - shading_en_diff = float - shading_en_mxh = float - shading_en_string_option = float - shading_en_timestep = float - shading_mxh = tuple - shading_string_option = float - shading_timestep = tuple - - class AdjustmentFactors(object): def assign(self): pass diff --git a/stubs/stubs/Saleleaseback.pyi b/stubs/stubs/Saleleaseback.pyi index 1464be58..083beb09 100644 --- a/stubs/stubs/Saleleaseback.pyi +++ b/stubs/stubs/Saleleaseback.pyi @@ -31,12 +31,7 @@ class Saleleaseback(object): pass - dispatch_factors_ts = tuple - dispatch_sched_weekday = tuple - dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple ppa_escalation = float - ppa_multiplier_model = float ppa_price_input = tuple ppa_soln_max = float ppa_soln_max_iterations = float @@ -386,6 +381,32 @@ class Saleleaseback(object): total_installed_cost = float + class TimeOfDelivery(object): + def assign(self): + pass + + def export(self) -> dict: + pass + + def __init__(self, *args, **kwargs): + pass + + + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float + dispatch_factors_ts = tuple + dispatch_sched_weekday = tuple + dispatch_sched_weekend = tuple + ppa_multiplier_model = float + + class UtilityBill(object): def assign(self): pass diff --git a/stubs/stubs/Sco2CspSystem.pyi b/stubs/stubs/Sco2CspSystem.pyi index d5153fed..b6c9192f 100644 --- a/stubs/stubs/Sco2CspSystem.pyi +++ b/stubs/stubs/Sco2CspSystem.pyi @@ -191,7 +191,6 @@ class Sco2CspSystem(object): PHX_co2_deltaP_des = float PHX_cost_bare_erected = float PHX_cost_equipment = float - PHX_min_dT = float P_co2_PHX_in = float P_co2_PHX_in_od = tuple P_comp_in = float diff --git a/stubs/stubs/Sco2CspUdPcTables.pyi b/stubs/stubs/Sco2CspUdPcTables.pyi index 8a495491..40d2e964 100644 --- a/stubs/stubs/Sco2CspUdPcTables.pyi +++ b/stubs/stubs/Sco2CspUdPcTables.pyi @@ -183,7 +183,6 @@ class Sco2CspUdPcTables(object): PHX_co2_deltaP_des = float PHX_cost_bare_erected = float PHX_cost_equipment = float - PHX_min_dT = float P_co2_PHX_in = float P_comp_in = float P_comp_out = float diff --git a/stubs/stubs/Singleowner.pyi b/stubs/stubs/Singleowner.pyi index f6bc9b39..a94f0af0 100644 --- a/stubs/stubs/Singleowner.pyi +++ b/stubs/stubs/Singleowner.pyi @@ -31,10 +31,18 @@ class Singleowner(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float dispatch_factors_ts = tuple dispatch_sched_weekday = tuple dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple flip_target_percent = float flip_target_year = float ppa_escalation = float diff --git a/stubs/stubs/Swh.pyi b/stubs/stubs/Swh.pyi index 2541c3ea..6620442c 100644 --- a/stubs/stubs/Swh.pyi +++ b/stubs/stubs/Swh.pyi @@ -73,6 +73,10 @@ class Swh(object): pump_eff = float pump_power = float scaled_draw = tuple + shading_azal = tuple + shading_diff = float + shading_mxh = tuple + shading_timestep = tuple sky_model = float system_capacity = float tank_h2d_ratio = float @@ -83,29 +87,6 @@ class Swh(object): use_custom_set = float - class Shading(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - shading_azal = tuple - shading_diff = float - shading_en_azal = float - shading_en_diff = float - shading_en_mxh = float - shading_en_string_option = float - shading_en_timestep = float - shading_mxh = tuple - shading_string_option = float - shading_timestep = tuple - - class AdjustmentFactors(object): def assign(self): pass diff --git a/stubs/stubs/TcsmoltenSalt.pyi b/stubs/stubs/TcsmoltenSalt.pyi index f7f39aa3..d5650275 100644 --- a/stubs/stubs/TcsmoltenSalt.pyi +++ b/stubs/stubs/TcsmoltenSalt.pyi @@ -448,10 +448,18 @@ class TcsmoltenSalt(object): pass + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float dispatch_factors_ts = tuple dispatch_sched_weekday = tuple dispatch_sched_weekend = tuple - dispatch_tod_factors = tuple ppa_multiplier_model = float @@ -645,7 +653,6 @@ class TcsmoltenSalt(object): annual_W_cooling_tower = float annual_W_cycle_gross = float annual_energy = float - annual_energy_distribution_time = tuple annual_eta_rec_th = float annual_eta_rec_th_incl_refl = float annual_q_rec_inc = float diff --git a/stubs/stubs/TroughPhysical.pyi b/stubs/stubs/TroughPhysical.pyi index 35309459..10f09808 100644 --- a/stubs/stubs/TroughPhysical.pyi +++ b/stubs/stubs/TroughPhysical.pyi @@ -249,6 +249,15 @@ class TroughPhysical(object): disp_steps_per_hour = float disp_time_weighting = float disp_timeout = float + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float dispatch_factors_ts = tuple dispatch_sched_weekday = tuple dispatch_sched_weekend = tuple @@ -327,20 +336,6 @@ class TroughPhysical(object): en_electricity_rates = float - class TimeOfDeliveryFactors(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - dispatch_tod_factors = tuple - - class Revenue(object): def assign(self): pass diff --git a/stubs/stubs/TroughPhysicalProcessHeat.pyi b/stubs/stubs/TroughPhysicalProcessHeat.pyi index b3c8a08f..d443e99f 100644 --- a/stubs/stubs/TroughPhysicalProcessHeat.pyi +++ b/stubs/stubs/TroughPhysicalProcessHeat.pyi @@ -252,6 +252,15 @@ class TroughPhysicalProcessHeat(object): disp_steps_per_hour = float disp_time_weighting = float disp_timeout = float + dispatch_factor1 = float + dispatch_factor2 = float + dispatch_factor3 = float + dispatch_factor4 = float + dispatch_factor5 = float + dispatch_factor6 = float + dispatch_factor7 = float + dispatch_factor8 = float + dispatch_factor9 = float dispatch_factors_ts = tuple dispatch_sched_weekday = tuple dispatch_sched_weekend = tuple @@ -286,20 +295,6 @@ class TroughPhysicalProcessHeat(object): disp_inventory_incentive = float - class TimeOfDeliveryFactors(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - dispatch_tod_factors = tuple - - class System(object): def assign(self): pass diff --git a/stubs/stubs/Windpower.pyi b/stubs/stubs/Windpower.pyi index 2c98e7e8..df9d0e63 100644 --- a/stubs/stubs/Windpower.pyi +++ b/stubs/stubs/Windpower.pyi @@ -118,6 +118,20 @@ class Windpower(object): wake_int_loss = float + class Uncertainty(object): + def assign(self): + pass + + def export(self) -> dict: + pass + + def __init__(self, *args, **kwargs): + pass + + + total_uncert = float + + class AdjustmentFactors(object): def assign(self): pass @@ -138,20 +152,6 @@ class Windpower(object): sf_hourly = tuple sf_periods = tuple - class Uncertainty(object): - def assign(self): - pass - - def export(self) -> dict: - pass - - def __init__(self, *args, **kwargs): - pass - - - total_uncert = float - - class Outputs(object): def assign(self): pass diff --git a/tests/test_pysam_all.py b/tests/test_pysam_all.py index a92f21d1..5a95af13 100644 --- a/tests/test_pysam_all.py +++ b/tests/test_pysam_all.py @@ -102,44 +102,44 @@ def test_functionality(): # Test shared module (AdjustmentFactors) d = a.AdjustmentFactors - d.adjust_constant = 1 - assert(d.adjust_constant == 1) + d.constant = 1 + assert(d.constant == 1) n_tests_passed += 1 - d.adjust_hourly = (1, 2) - assert(d.adjust_hourly == (1, 2)) + d.hourly = (1, 2) + assert(d.hourly == (1, 2)) n_tests_passed += 1 - d.adjust_periods = ((1, 2), (3, 4)) - assert(d.adjust_periods == ((1, 2), (3, 4))) + d.periods = ((1, 2), (3, 4)) + assert(d.periods == ((1, 2), (3, 4))) n_tests_passed += 1 try: - d.adjust_periods = ((1, 2)) + d.periods = ((1, 2)) except: n_tests_passed += 1 ValDict = d.export() - assert(ValDict['adjust_constant'] == 1 and ValDict['adjust_hourly'] == (1, 2) and ValDict['adjust_periods'] == ((1, 2), (3, 4))) + assert(ValDict['constant'] == 1 and ValDict['hourly'] == (1, 2) and ValDict['periods'] == ((1, 2), (3, 4))) n_tests_passed += 1 - ValDict = {'adjust_constant': 10, 'adjust_hourly': (10, 20), 'adjust_periods': ((10, 20), (30, 40))} + ValDict = {'constant': 10, "hourly": (10, 20), "periods": ((10, 20), (30, 40))} d.assign(ValDict) - assert(ValDict['adjust_constant'] == 10 and ValDict['adjust_hourly'] == (10, 20) and ValDict['adjust_periods'] == ((10, 20), (30, 40))) + assert(ValDict['constant'] == 10 and ValDict['hourly'] == (10, 20) and ValDict['periods'] == ((10, 20), (30, 40))) n_tests_passed += 1 # Test nested dictionary assignment and export TechDict = {'Plant': {'derate': 100, 'energy_output_array': (100, 200)}, - 'AdjustmentFactors': {'adjust_constant': 100, 'adjust_hourly': (100, 200), 'adjust_periods': ((100, 200), (300, 400))}} + 'AdjustmentFactors': {'constant': 100, "hourly": (100, 200), "periods": ((100, 200), (300, 400))}} a.assign(TechDict) ValDict = a.Plant.export() assert (ValDict['derate'] == 100 and ValDict['energy_output_array'] == (100, 200)) n_tests_passed += 1 ValDict = a.AdjustmentFactors.export() - assert (ValDict['adjust_constant'] == 100 and ValDict['adjust_hourly'] == (100, 200) and ValDict['adjust_periods'] == ( + assert (ValDict['constant'] == 100 and ValDict['hourly'] == (100, 200) and ValDict['periods'] == ( (100, 200), (300, 400))) n_tests_passed += 1