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benchmark.py
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benchmark.py
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import time
import random
import collections
import math
random.seed(1)
#
# Testing with importing module each round
#
def test1(n):
def old_with_import():
from PySAM.PySSC import PySSC
ssc = PySSC()
# ssc.module_exec_set_print(0)
data = ssc.data_create()
ssc.data_set_number(data, b'spec_mode', 0)
ssc.data_set_number(data, b'derate', 4)
ssc.data_set_number(data, b'system_capacity', 100000)
ssc.data_set_number(data, b'user_capacity_factor', 43.599998474121094)
ssc.data_set_number(data, b'heat_rate', 10)
ssc.data_set_number(data, b'conv_eff', 34.118049621582031)
energy_output_array = [-0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.52636, 1.74917, 2.57383, 3.08427, 3.29984, 3.25021, 2.9358, 2.29411, 1.30634, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.524721, 1.71983, 2.57684, 3.08387, 3.30457, 3.25023, 2.92098, 2.26371, 1.28647, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.503479, 1.65889, 2.47494, 2.99021, 2.48259, 0.510929, 1.04024, 2.26393, 1.31871, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.513209, 1.74414, 2.57435, 3.05368, 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3.2222, 3.14679, 2.84115, 1.03333, 0.25087, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.0636998, 1.67104, 2.51978, 3.0768, 3.28817, 3.22333, 2.80386, 2.07904, 1.00767, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.0815454, 1.01058, 1.78157, 1.7197, 1.24068, 2.40172, 1.30105, 1.07336, 0.374479, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.148857, 1.13614, 1.86606, 2.03174, 2.22745, 2.2896, 2.94836, 2.24891, 1.18077, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.246482, 0.948695, 1.003, 2.2162, 3.31216, 2.01502, 2.93412, 2.25897, 1.22909, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.560853, 1.79087, 2.65201, 3.1555, 3.38399, 3.31805, 2.95418, 2.30422, 1.29319, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.566142, 1.76016, 2.62077, 3.09306, 3.27856, 1.95121, 1.74831, 1.26689, 0.564247, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.0143551, 0.448986, 0.308584, 0.864957, 1.57937, 0.889275, 0.856908, 0.474296, 0.0548501, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.459376, 1.65454, 2.54893, 3.08557, 3.33411, 3.29802, 1.93637, 2.28859, 1.25743, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655,]
ssc.data_set_array(data, b'energy_output_array', energy_output_array)
ssc.data_set_matrix(data, b'adjust:periods', [[1, 2, 3], [1, 2, 3], [1, 2, 3]])
ssc.data_free(data)
def new_with_import():
import PySAM.GenericSystem as GenericSystem
gs = GenericSystem.new()
a = gs.Plant
a.spec_mode = 0
a.derate = 4
a.system_capacity = 100000
a.user_capacity_factor = 43.599998474121094
a.heat_rate = 10
a.conv_eff = 34.118049621582031
a. energy_output_array = [-0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.52636, 1.74917, 2.57383, 3.08427, 3.29984, 3.25021, 2.9358, 2.29411, 1.30634, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.524721, 1.71983, 2.57684, 3.08387, 3.30457, 3.25023, 2.92098, 2.26371, 1.28647, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.503479, 1.65889, 2.47494, 2.99021, 2.48259, 0.510929, 1.04024, 2.26393, 1.31871, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.513209, 1.74414, 2.57435, 3.05368, 3.29414, 3.25901, 2.91821, 2.30584, 1.34467, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.50639, 1.70426, 2.53805, 3.04629, 3.29337, 3.2652, 2.93712, 2.33058, 1.36273, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.478388, 1.66943, 2.48534, 3.00258, 3.22182, 3.18345, 2.88544, 2.2917, 1.34554, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.461687, 1.64942, 2.47643, 3.03336, 3.26762, 3.23499, 2.91823, 2.27365, 1.289, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.438143, 1.66177, 2.5714, 3.18626, 3.4756, 3.46643, 3.11831, 2.4423, 1.4207, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.298492, 1.68528, 2.51258, 3.03752, 3.31718, 2.1765, 2.95705, 2.32783, 1.12005, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.483602, 1.66018, 2.48754, 2.9683, 3.19167, 2.36438, 2.93213, 1.37819, 1.38927, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.316576, 1.21371, 1.3103, 1.82015, 2.57998, 2.08484, 2.09217, 1.78869, 0.541045, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.380346, 1.52474, 2.33225, 0.856755, 1.30386, 0.998001, 1.24023, 1.44021, 0.124894, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.558542, 1.82135, 2.69572, 3.21381, 3.47379, 3.44851, 3.13781, 2.50507, 1.56649, 0.232529, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.311779, 0.996716, 2.60037, 2.29834, 2.73789, 2.9751, 1.94711, 0.421591, 0.0710252, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.00224862, 0.445546, 0.345022, 0.825553, 0.266927, 1.0904, 0.672061, 0.481642, 0.0950679, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.240926, 1.62411, 2.47447, 2.0444, 2.5267, 2.26256, 1.79363, 2.29987, 1.34117, 0.135846, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.508528, 1.66769, 2.54565, 3.06244, 3.32937, 3.30558, 2.95337, 2.35875, 1.42108, 0.181567, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.524927, 1.68492, 2.54151, 3.01945, 3.28101, 3.26167, 2.99119, 2.39038, 1.46373, 0.221781, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.510989, 1.68143, 2.52696, 3.02763, 3.26424, 3.22114, 2.9847, 2.44102, 1.54647, 0.288087, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.540859, 1.70569, 2.53931, 3.02322, 3.29016, 3.28014, 3.02828, 2.44568, 1.5324, 0.29973, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.321143, 0.789351, 1.39186, 0.883055, 0.889167, 0.706776, 2.22093, 2.34842, 1.34074, 0.0477816, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.588618, 1.14896, 1.72947, 1.80565, 2.51988, 1.91514, 1.58317, 0.584762, 0.660672, 0.0306318, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.418603, 1.70638, 1.76756, 1.40892, 1.5738, 1.70824, 1.99692, 0.48402, 0.264152, 0.0312964, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.580285, 1.73606, 2.65915, 3.25576, 3.54728, 3.55361, 3.24764, 2.62033, 1.64736, 0.383405, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.606766, 1.80304, 2.7184, 3.30877, 3.61885, 3.61622, 3.29848, 2.6806, 1.71975, 0.444532, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 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gs.AdjustmentFactors.periods = [[1, 2, 3], [1, 2, 3], [1, 2, 3]]
# time old version
t1 = time.process_time()
for i in range(n):
old_with_import()
t2 = time.process_time()
t_old = t2 - t1
# time new version
t1 = time.process_time()
for i in range(n):
new_with_import()
t2 = time.process_time()
t_new = t2 - t1
if math.isclose(0, t_new, rel_tol=1e-5):
factor = None
else:
factor = round(t_old / t_new, 5)
print("Time with importing module:\t", round(t_old, 5), "\t", round(t_new, 5), "\t", factor)
#
# Testing without importing module each round
#
def test2(n):
from PySAM.PySSC import PySSC
ssc = PySSC()
import PySAM.GenericSystem as GenericSystem
def old_no_import():
# ssc.module_exec_set_print(0)
data = ssc.data_create()
ssc.data_set_number(data, b'spec_mode', 0)
ssc.data_set_number(data, b'derate', 4)
ssc.data_set_number(data, b'system_capacity', 100000)
ssc.data_set_number(data, b'user_capacity_factor', 43.599998474121094)
ssc.data_set_number(data, b'heat_rate', 10)
ssc.data_set_number(data, b'conv_eff', 34.118049621582031)
energy_output_array = [-0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.52636, 1.74917, 2.57383, 3.08427, 3.29984, 3.25021, 2.9358, 2.29411, 1.30634, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.524721, 1.71983, 2.57684, 3.08387, 3.30457, 3.25023, 2.92098, 2.26371, 1.28647, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.503479, 1.65889, 2.47494, 2.99021, 2.48259, 0.510929, 1.04024, 2.26393, 1.31871, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.513209, 1.74414, 2.57435, 3.05368, 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2.04414, 0.999438, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.519289, 1.08241, 1.75449, 2.38685, 3.19444, 2.40605, 1.50775, 0.960027, 0.26022, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.81446, 1.84132, 2.60204, 3.05024, 3.22712, 3.12493, 2.7522, 2.03874, 0.991921, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.804229, 1.84434, 2.60739, 3.0537, 3.22158, 3.13457, 2.78295, 2.10898, 1.05493, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 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3.2222, 3.14679, 2.84115, 1.03333, 0.25087, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.0636998, 1.67104, 2.51978, 3.0768, 3.28817, 3.22333, 2.80386, 2.07904, 1.00767, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.0815454, 1.01058, 1.78157, 1.7197, 1.24068, 2.40172, 1.30105, 1.07336, 0.374479, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.148857, 1.13614, 1.86606, 2.03174, 2.22745, 2.2896, 2.94836, 2.24891, 1.18077, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 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-0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.459376, 1.65454, 2.54893, 3.08557, 3.33411, 3.29802, 1.93637, 2.28859, 1.25743, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655,]
ssc.data_set_array(data, b'energy_output_array', energy_output_array)
ssc.data_set_matrix(data, b'adjust:periods', [[1, 2, 3], [1, 2, 3], [1, 2, 3]])
ssc.data_free(data)
def new_no_import():
gs = GenericSystem.new()
a = gs.Plant
a.spec_mode = 0
a.derate = 4
a.system_capacity = 100000
a.user_capacity_factor = 43.599998474121094
a.heat_rate = 10
a.conv_eff = 34.118049621582031
a. energy_output_array = [-0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.52636, 1.74917, 2.57383, 3.08427, 3.29984, 3.25021, 2.9358, 2.29411, 1.30634, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.524721, 1.71983, 2.57684, 3.08387, 3.30457, 3.25023, 2.92098, 2.26371, 1.28647, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.503479, 1.65889, 2.47494, 2.99021, 2.48259, 0.510929, 1.04024, 2.26393, 1.31871, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.513209, 1.74414, 2.57435, 3.05368, 3.29414, 3.25901, 2.91821, 2.30584, 1.34467, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.50639, 1.70426, 2.53805, 3.04629, 3.29337, 3.2652, 2.93712, 2.33058, 1.36273, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.478388, 1.66943, 2.48534, 3.00258, 3.22182, 3.18345, 2.88544, 2.2917, 1.34554, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.461687, 1.64942, 2.47643, 3.03336, 3.26762, 3.23499, 2.91823, 2.27365, 1.289, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.438143, 1.66177, 2.5714, 3.18626, 3.4756, 3.46643, 3.11831, 2.4423, 1.4207, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.298492, 1.68528, 2.51258, 3.03752, 3.31718, 2.1765, 2.95705, 2.32783, 1.12005, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.483602, 1.66018, 2.48754, 2.9683, 3.19167, 2.36438, 2.93213, 1.37819, 1.38927, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, -0.00116655, 0.316576, 1.21371, 1.3103, 1.82015, 2.57998, 2.08484, 2.09217, 1.78869, 0.541045, -0.00116655, -0.00116655, 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gs.AdjustmentFactors.periods = [[1, 2, 3], [1, 2, 3], [1, 2, 3]]
# time old version
t1 = time.process_time()
for i in range(n):
old_no_import()
t2 = time.process_time()
t_old = t2 - t1
# time new version
t1 = time.process_time()
for i in range(n):
new_no_import()
t2 = time.process_time()
t_new = t2 - t1
if math.isclose(0, t_new, rel_tol=1e-5):
factor = None
else:
factor = round(t_old / t_new, 5)
print("Time w/o importing module:\t", round(t_old, 5), "\t", round(t_new, 5), "\t", factor)
#
# Testing with random values
#
def test3(n):
from PySAM.PySSC import PySSC
import PySAM.GenericSystem as GenericSystem
ssc = PySSC()
def old_no_import_rand():
# ssc.module_exec_set_print(0)
data = ssc.data_create()
ssc.data_set_number(data, b'spec_mode', 0)
ssc.data_set_number(data, b'derate', random.randint(0, 10))
ssc.data_set_number(data, b'system_capacity', random.randint(50000, 100000))
ssc.data_set_number(data, b'user_capacity_factor', random.randint(40, 60))
ssc.data_set_number(data, b'heat_rate', random.randint(5, 15))
ssc.data_set_number(data, b'conv_eff', random.randint(25, 50))
energy_output_array = [random.random() for i in range(8760)]
ssc.data_set_array(data, b'energy_output_array', energy_output_array)
ssc.data_set_matrix(data, b'adjust:periods', [[random.randint(0, 4)] for i in range(3)])
ssc.data_free(data)
def new_no_import_rand():
gs = GenericSystem.new()
a = gs.Plant
a.spec_mode = 0
a.derate = random.randint(0, 10)
a.system_capacity = random.randint(50000, 100000)
a.user_capacity_factor = random.randint(40, 50)
a.heat_rate = random.randint(5, 15)
a.conv_eff = random.randint(25, 50)
a. energy_output_array = [random.random() for i in range(8760)]
gs.AdjustmentFactors.periods = [[random.randint(0, 4)] for i in range(3)]
# time old version
t1 = time.process_time()
for i in range(n):
old_no_import_rand()
t2 = time.process_time()
t_old = t2 - t1
# time new version
t1 = time.process_time()
for i in range(n):
new_no_import_rand()
t2 = time.process_time()
t_new = t2 - t1
if math.isclose(0, t_new, rel_tol=1e-5):
factor = None
else:
factor = round(t_old / t_new, 5)
print("Time w/o importing + rand:\t", round(t_old, 5), "\t", round(t_new, 5), "\t", factor)
#
# Testing with dictionary loading
#
def test4(n):
import PySAM.GenericSystem as GenericSystem
from PySAM.PySSC import PySSC
dict_old = {
'conv_eff': 34.11800003051758,
'derate': random.randint(0, 10),
'energy_output_array': [random.random() for i in range(8760)],
'heat_rate': random.randint(5, 15),
'spec_mode': 0.0,
'system_capacity': random.randint(0, 10),
'user_capacity_factor': random.randint(5, 15),
'adjust:periods': [[random.randint(0, 4)] for i in range(3)]}
dict_new = {'Plant': {
'conv_eff': 34.11800003051758,
'derate': random.randint(0, 10),
'energy_output_array': [random.random() for i in range(8760)],
'heat_rate': random.randint(5, 15),
'spec_mode': 0.0,
'system_capacity': random.randint(0, 10),
'user_capacity_factor': random.randint(5, 15)},
'AdjustmentFactors': {
'periods': [[random.randint(0, 4)] for i in range(3)]}}
def old_dict():
dict_old_types = {'conv_eff': 2,
'derate': 2,
'energy_output_array': 3,
'heat_rate': 2,
'spec_mode': 2,
'system_capacity': 2,
'user_capacity_factor': 2,
'adjust:periods': 4}
ssc = PySSC()
data = ssc.data_create()
for k, v in dict_old.items():
type = dict_old_types[k]
bytestr = k.encode()
if type == 1:
if isinstance(v, str):
ssc.data_set_string(data, bytestr, v)
else:
raise ValueError(k, "not str")
elif type == 2:
if isinstance(v, float) or isinstance(v, int):
ssc.data_set_number(data, bytestr, v)
else:
raise ValueError(k, "not float")
elif type == 3:
if isinstance(v, tuple) or isinstance(v, list):
ssc.data_set_array(data, bytestr, v)
else:
raise ValueError(k, "not array")
elif type == 2:
if isinstance(v, collections.Sequence):
ssc.data_set_matrix(data, bytestr, v)
else:
raise ValueError("not matrix")
ssc.data_free(data)
def new_dict():
gs = GenericSystem.new()
gs.assign(dict_new)
# time old version
t1 = time.process_time()
for i in range(n):
old_dict()
t2 = time.process_time()
t_old = t2 - t1
# time new version
t1 = time.process_time()
for i in range(n):
new_dict()
t2 = time.process_time()
t_new = t2 - t1
if math.isclose(0, t_new, rel_tol=1e-5):
factor = None
else:
factor = round(t_old / t_new, 5)
print("Time w/o importing w/ dict:\t", round(t_old, 5), "\t", round(t_new, 5), "\t", factor)
for n in (100, 1000):
print("Testing over", n, "loops:\t\t t_old\t\tt_new\t\tfactor")
test1(n)
test2(n)
test4(n)
print()