Release v0.14.2

.github/workflows/conda-build.yml

@@ -0,0 +1,43 @@
+name: Build Conda Recipe
+
+on:
+  push:
+    branches:
+      - development  # You can change this to the branch you want to trigger on
+
+jobs:
+  build-linux:
+    name: CondaBuild (${{ matrix.python-version }}, ${{ matrix.os }})
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: ["ubuntu-latest", "macos-latest", "windows-latest"]
+        python-version: ["3.8", "3.11"]
+    steps:
+      - name: Checkout Repository
+        uses: actions/checkout@v2
+
+      - name: Set up Conda
+        uses: conda-incubator/setup-miniconda@v3
+        with:
+          auto-update-conda: true
+          python-version: ${{ matrix.python-version }}
+          mamba-version: "*"
+          channels: conda-forge,defaults
+          channel-priority: true
+
+      - name: Display Conda Settings
+        shell: bash -el {0}
+        run: |
+          conda info
+          conda list
+          conda config --show-sources
+          conda config --show
+          printenv | sort
+
+      - name: Build Conda Package
+        shell: bash -el {0}
+        run: |
+          mamba install conda-build boa
+          conda mambabuild conda-recipe

.github/workflows/gitlab-sync.yml

@@ -0,0 +1,22 @@
+name: GitlabSync
+
+on:
+  - push
+  - delete
+
+jobs:
+  sync:
+    runs-on: ubuntu-latest
+    name: Git Repo Sync
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+      - uses: wangchucheng/git-repo-sync@v0.1.0
+        with:
+          # Such as https://github.com/wangchucheng/git-repo-sync.git
+          target-url: ${{ secrets.TARGET_URL }}
+          # Such as wangchucheng
+          target-username: ${{ secrets.TARGET_USERNAME }}
+          # You can store token in your project's 'Setting > Secrets' and reference the name here. Such as ${{ secrets.ACCESS\_TOKEN }}
+          target-token: ${{ secrets.TARGET_TOKEN }}

CMakeLists.txt

@@ -1,7 +1,8 @@
-set (CMAKE_CXX_STANDARD 14)
-set(CMAKE_OSX_ARCHITECTURES "x86_64")
 # Are we running cmake from this directory (out of tree build) ?
 if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
+  set (CMAKE_CXX_STANDARD 14)
+  set(CMAKE_OSX_ARCHITECTURES "x86_64")
+
   cmake_minimum_required(VERSION 2.8.12)
   project(imp_module)
 

Setup.cmake

@@ -6,13 +6,13 @@ IF(NOT APPLE)
         INCLUDE(simd)
         IF(${AVX_FOUND})
             MESSAGE("BUILD WITH SIMD")
-            add_compile_definitions(WITH_AVX)
+            ADD_DEFINITIONS(-DWITH_AVX)
             IF (MSVC)
                 # https://devblogs.microsoft.com/cppblog/simd-extension-to-c-openmp-in-visual-studio/
                 # /Oi is for intrinsics
-                SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX -openmp:experimental /Oi")
+                SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX /Oi")
             ELSE(MSVC)
-                STRING(APPEND CMAKE_CXX_FLAGS " -Ofast -mavx -mfma -ffast-math -funroll-loops")
+                SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx -mfma")
             ENDIF (MSVC)
         ELSE(${AVX_FOUND})
             UNSET(WITH_AVX)

conda-recipe/meta.yaml

@@ -1,4 +1,4 @@
-{% set version = "0.14.0" %}
+{% set version = "0.14.2" %}
 
 package:
   name: imp.bff
@@ -32,7 +32,6 @@ requirements:
     - cereal
     - mpir  # [win]
     - msmpi  # [win]
-#    - libmongoc
     - imp
   run:
     - {{ pin_compatible('numpy') }}

include/AV.h

@@ -329,7 +329,7 @@ class IMPBFFEXPORT AV : public IMP::core::Gaussian {
      * @brief Get the mean position of the AV object.
      * @return The mean position as a Vector3D.
      */
-    IMP::algebra::Vector3D get_mean_position() const;
+    IMP::algebra::Vector3D get_mean_position(bool include_source=true) const;
 
     /**
      * @brief Get the source coordinates of the AV object.

include/DecayRoutines.h

@@ -19,20 +19,18 @@
 #include <algorithm> /* std::max */
 #include <string.h> /* strcmp */
 
-#if defined(_MSC_VER)
-/* Microsoft C/C++-compatible compiler */
-  #include <intrin.h>
-  #include <immintrin.h>
-#endif
-
 #if defined(__AVX__)
-#if (defined(__GNUC__) || defined(__clang__))
-#include <immintrin.h>
-#include <avxintrin.h>
-#endif
-#if !defined(__FMA__)
-#define __FMA__ 1
-#endif
+ #if defined(_MSC_VER)
+   /* Microsoft C/C++-compatible compiler */
+   #include <intrin.h>
+   #include <immintrin.h>
+ #endif
+ #if (defined(__GNUC__) || defined(__clang__))
+   #include <immintrin.h>
+ #endif
+ #if !defined(__FMA__)
+   #define __FMA__ 1
+ #endif
 #endif //__AVX__
 
 IMPBFF_BEGIN_NAMESPACE

pyext/swig.i-in

@@ -5,20 +5,6 @@
 
 %include "numpy.i"
 
-//%{
-//    #include <mongoc.h>
-//    void cleanup()
-//    {
-////        printf("cleanup!\n");
-//        mongoc_cleanup();
-//    }
-//%}
-//%init %{
-//    import_array();
-//    mongoc_init();
-//    atexit(cleanup);
-//%}
-
 %pythoncode %{
 import numpy as np
 %}

src/AV.cpp

@@ -31,17 +31,15 @@ std::string AVPairDistanceMeasurement::get_json(){
 
 
 double AVPairDistanceMeasurement::score_model(double model){
-    auto ev = [](auto f, auto m, auto en, auto ep){
-        auto dev = m - f;
-        auto w = (dev < 0) ? 1. / en : 1. / ep;
+    auto ev = [](double f, double m, double en, double ep){
+        double dev = m - f;
+        double w = (dev < 0) ? 1. / en : 1. / ep;
         return .5 * algebra::get_squared(dev * w);
     };
     if(std::isnan(model)){
         return std::numeric_limits<double>::infinity();
     }
-    else{
-        return 0.5 * ev(model, distance, error_neg, error_pos);
-    }
+    return 0.5 * ev(model, distance, error_neg, error_pos);
 }
 
 
@@ -114,9 +112,13 @@ IMP::bff::PathMap* AV::get_map() const{
     return av_map_;
 }
 
-IMP::algebra::Vector3D AV::get_mean_position() const{
+IMP::algebra::Vector3D AV::get_mean_position(bool include_source) const{
     IMP::algebra::Vector3D r = {0.0, 0.0, 0.0};
-    double sum = 0.0;
+    double sum = 1.0;
+    if(include_source){
+        r += get_source_coordinates();
+        sum += 1.0;
+    }
     auto xyzd = get_map()->get_xyz_density();
     for(auto &a: xyzd){
         if(a[3] <= 0.0f) continue;

src/AVNetworkRestraint.cpp

@@ -103,7 +103,7 @@ double AVNetworkRestraint::unprotected_evaluate(
                 distance.position_2,
                 distance.forster_radius,
                 distance.distance_type
-                );
+        );
         score += distance.score_model(model);
     }
     return score;

test/test_AVNetworkRestraint.py

@@ -60,8 +60,6 @@ def test_decorate_particle(self):
         # fps.json files can contain multiple sets of distances for scoring
         # structures.
         fps_json_path = IMP.bff.get_example_path("structure/T4L/fret.fps.json")
-        with open(fps_json_path) as fp:
-            fps_json = json.load(fp)
         score_set_c1 = "chi2_C2_33p"
         fret_restraint = IMP.bff.AVNetworkRestraint(
             hier, str(fps_json_path), 
@@ -74,8 +72,8 @@ def test_decorate_particle(self):
 
         model_ref = np.array(
             [
-                49. , 38. , 41.7, 52.6, 38.8, 38.7, 44.3, 52. , 60.3, 50.3, 52.7,
-                30. , 49.7, 46. , 46.7, 61.5, 56.2, 51.6, 35.4, 57.2, 53.5, 43.2,
+                49.0, 38.0, 41.7, 52.6, 38.8, 38.7, 44.3, 52.0, 60.3, 50.3, 52.7,
+                30.0, 49.7, 46.0, 46.7, 61.5, 56.2, 51.6, 35.4, 57.2, 53.5, 43.2,
                 52.2, 43.4, 47.5, 47.4, 35.3, 37.9, 41.3, 50.8, 45.9, 33.1, 47.4
             ]
         )

test/test_DecayConvolution.py

@@ -1,16 +1,26 @@
 from __future__ import division
 import unittest
-from sys import platform
+import platform
 
 import numpy as np
 import numpy.testing
-import scipy.stats
 import IMP.bff
 
 x = np.linspace(0, 20, 32)
 irf_position = 2.0
 irf_width = 0.1
-irf_y = scipy.stats.norm.pdf(x, loc=irf_position, scale=irf_width)
+
+
+def norm_pdf(x, mu, sigma):
+    variance = sigma**2
+    num = x - mu
+    denom = 2*variance
+    pdf = ((1/(np.sqrt(2*np.pi)*sigma))*np.exp(-(num**2)/denom))
+    return pdf
+
+
+
+irf_y = norm_pdf(x, irf_position, irf_width)
 
 
 class Tests(unittest.TestCase):
@@ -39,15 +49,15 @@ def test_DecayConvolution_init(self):
                         6.68957600e-02, 5.69312992e-02, 4.84510951e-02, 4.12340602e-02,
                         3.50920390e-02, 2.98649029e-02, 2.54163750e-02, 2.16304778e-02,
                         1.84085090e-02, 1.56664688e-02, 1.33328693e-02, 1.13468712e-02])
-        self.assertEqual(np.allclose(decay.y, ref), True)
+        np.testing.assert_allclose(decay.y, ref)
         ref = np.array([ 0.        ,  0.64516129,  1.29032258,  1.93548387,  2.58064516,
                          3.22580645,  3.87096774,  4.51612903,  5.16129032,  5.80645161,
                          6.4516129 ,  7.09677419,  7.74193548,  8.38709677,  9.03225806,
                          9.67741935, 10.32258065, 10.96774194, 11.61290323, 12.25806452,
                          12.90322581, 13.5483871 , 14.19354839, 14.83870968, 15.48387097,
                          16.12903226, 16.77419355, 17.41935484, 18.06451613, 18.70967742,
                          19.35483871, 20.        ])
-        self.assertEqual(np.allclose(decay.x, ref), True)
+        np.testing.assert_allclose(decay.x, ref)
 
     def test_DecayConvolution_init(self):
         irf = IMP.bff.DecayCurve(x, irf_y)
@@ -80,18 +90,12 @@ def test_DecayConvolution_init(self):
             IMP.bff.DecayConvolution.FAST_AVX,
             IMP.bff.DecayConvolution.FAST_PERIODIC_AVX
         ]
-
-        if platform == "linux" or platform == "linux2":
-            # linux
-            conv_methods += conv_methods_fast
-        elif platform == "win32":
-            # Windows...
-            conv_methods += conv_methods_fast
-        elif platform == "darwin":
-            # OS X
-            conv_methods = conv_methods
+        if "AMD64" in platform.machine():
+            if platform.system() == "Linux":
+                conv_methods += conv_methods_fast
+            elif platform.system() == "Windows":
+                conv_methods += conv_methods_fast
         for i in conv_methods:
-            print(i)
             settings["convolution_method"] = i
             dc = IMP.bff.DecayConvolution(**settings)
             decay = IMP.bff.DecayCurve(x)

test/test_DecayCurve.py

@@ -3,18 +3,25 @@
 
 import numpy as np
 import numpy.testing
-import scipy.stats
 import math
 import IMP.bff
 
 
+def norm_pdf(x, mu, sigma):
+    variance = sigma**2
+    num = x - mu
+    denom = 2*variance
+    pdf = ((1/(np.sqrt(2*np.pi)*sigma))*np.exp(-(num**2)/denom))
+    return pdf
+
+
 class Tests(unittest.TestCase):
 
     def test_shift(self):
         time_axis = np.linspace(0, 12, 25)
         irf_position = 6.0
         irf_width = 1.0
-        irf = scipy.stats.norm.pdf(time_axis, loc=irf_position, scale=irf_width)
+        irf = norm_pdf(time_axis, irf_position, irf_width)
         shifts = [2.1, 1.1, 0.5, 0.0, -0.5, -1.1, -2.1, 26.0, -26.2]
         for shift in shifts:
             shifted_irf_ip = IMP.bff.DecayCurve.shift_array(

test/test_DecayLifetimeHandler.py

@@ -2,7 +2,6 @@
 import unittest
 
 import numpy as np
-import scipy.stats
 import IMP.bff
 
 

test/test_DecayLinearization.py

@@ -2,7 +2,6 @@
 import unittest
 
 import numpy as np
-import pandas as pd
 
 import IMP.bff
 
@@ -11,14 +10,14 @@ class Tests(unittest.TestCase):
 
     def test_lin(self):
         dt = 0.0141
-        df = pd.read_csv(
+        x, y = np.genfromtxt(
             IMP.bff.get_example_path("spectroscopy/hgbp1/eTCSPC_whitelight.txt"),
-            skiprows=6,
-            sep='\t'
-        )
-        lin_data = IMP.bff.DecayCurve(x=df['Chan'] * dt, y=df['Data'])
+            skip_header=9,
+            delimiter='\t'
+        ).T
+        lin_data = IMP.bff.DecayCurve(x * dt, y)
         model = IMP.bff.DecayCurve(
-            x=df['Chan'] * dt,
+            x=x * dt,
             y=np.ones_like(lin_data.y)
         )
         dl = IMP.bff.DecayLinearization(