Merge pull request #143 from asiaszmek/add_github_actions

Add GitHub actions

.github/workflows/python-package.yml

@@ -0,0 +1,42 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+
+name: Python package
+
+on:
+  push:
+    branches: [ "master" ]
+  pull_request:
+    branches: [ "master" ]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
+
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        python -m pip install flake8 pytest
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        pytest

figures/kCSD_properties/tutorial_basic_3d.py

@@ -71,7 +71,7 @@ def make_plots(fig_title,
     t_max = np.max(np.abs(true_csd))
     levels = np.linspace(-1*t_max, t_max, 16)
     ind_interest = np.mgrid[0:t_csd_z.shape[2]:np.complex(0,z_steps+2)]
-    ind_interest = np.array(ind_interest, dtype=np.int)[1:-1]
+    ind_interest = np.array(ind_interest, dtype=int)[1:-1]
     for ii, idx in enumerate(ind_interest):
         ax = plt.subplot(gs[ii, 0])
         im = plt.contourf(t_csd_x[:,:,idx], t_csd_y[:,:,idx], true_csd[:,:,idx], 
@@ -131,7 +131,7 @@ def make_plots(fig_title,
     t_max = np.max(np.abs(pre_cv[:,:,:,0]))
     levels_kcsd = np.linspace(-1*t_max, t_max, 16)
     ind_interest = np.mgrid[0:k_csd_z.shape[2]:np.complex(0,z_steps+2)]
-    ind_interest = np.array(ind_interest, dtype=np.int)[1:-1]
+    ind_interest = np.array(ind_interest, dtype=int)[1:-1]
     for ii, idx in enumerate(ind_interest):
         ax = plt.subplot(gs[ii, 2])
         im = plt.contourf(k_csd_x[:,:,idx], k_csd_y[:,:,idx], pre_cv[:,:,idx,0], 
@@ -159,7 +159,7 @@ def make_plots(fig_title,
     t_max = np.max(np.abs(est_csd[:,:,:,0]))
     levels_kcsd = np.linspace(-1*t_max, t_max, 16)
     ind_interest = np.mgrid[0:k_csd_z.shape[2]:np.complex(0,z_steps+2)]
-    ind_interest = np.array(ind_interest, dtype=np.int)[1:-1]
+    ind_interest = np.array(ind_interest, dtype=int)[1:-1]
     for ii, idx in enumerate(ind_interest):
         ax = plt.subplot(gs[ii, 3])
         im = plt.contourf(k_csd_x[:,:,idx], k_csd_y[:,:,idx], est_csd[:,:,idx,0], 

figures/npx/Neuropixels_with_fitted_dipoles_model.py

@@ -1,10 +1,12 @@
+from pathlib import Path
 import kCSD2D_reconstruction_from_npx as npx
 import matplotlib.pyplot as plt
 import matplotlib.cm as cm
 import scipy
 import numpy as np
+from numpy.linalg import LinAlgError
 from scipy.signal import filtfilt, butter
-
+import DemoReadSGLXData.readSGLX as readSGLX
 
 def set_axis(ax, x, y, letter=None):
     ax.text(
@@ -198,4 +200,4 @@ def gauss2d(x, y, p):
     make_plot(ax4, k.estm_x, k.estm_y, projection.reshape(true_csd.shape), ele_pos,
                   title='Projection', cmap='bwr')
     plt.tight_layout()
-    plt.savefig('Neuropixels_with_fitted_model.png', dpi=300)
+    plt.savefig('Neuropixels_with_fitted_model.png', dpi=300)

figures/npx/dan_kCSD_from_npx.py

@@ -93,7 +93,7 @@ def dan_fetch_electrodes(meta):
 def eles_to_rows(eles):
     rows = []
     for ele in eles:
-        rows.append(np.int(np.ceil(ele/2)))
+        rows.append(int(np.ceil(ele/2)))
     return rows
 
 def eles_to_ycoord(eles):

figures/npx/map_npx_ele.py

@@ -10,7 +10,7 @@
 def eles_to_rows(eles):
     rows = []
     for ele in eles:
-        rows.append(np.int(np.ceil(ele/2)))
+        rows.append(int(np.ceil(ele/2)))
     return rows
 
 def eles_to_ycoord(eles):

figures/npx/map_npx_ele_Daniel.py

@@ -8,7 +8,7 @@
 def eles_to_rows(eles):
     rows = []
     for ele in eles:
-        rows.append(np.int(np.ceil(ele/2)))
+        rows.append(int(np.ceil(ele/2)))
     return rows
 
 def eles_to_ycoord(eles):

figures/sKCSD_paper/make_fig_5.py

@@ -122,7 +122,8 @@
             utils.save_sim(path, ker)
             est_skcsd = ker.values(estimate='CSD')
         except NameError:
-            skcsd, pot, cell_obj = utils.load_sim(path)
+            skcsd, pot, morphology, ele_pos, n_src = utils.load_sim(path)
+            cell_obj =  sKCSDcell(morphology, ele_pos, n_src)
             est_skcsd = cell_itself[i].transform_to_3D(skcsd)
 
         xmin = cell_itself[i].xmin

figures/sKCSD_paper/make_fig_9.py

@@ -5,7 +5,7 @@
 import sys
 import os
 from kcsd import sKCSD, sKCSDcell
-from  kcsd import sKCSD_utils as utils
+from kcsd import sKCSD_utils as utils
 import kcsd.validation.plotting_functions as pl
 import sKCSD_utils
 import numpy.random
@@ -87,17 +87,18 @@
     L1 = []
 
     for i, nl in enumerate(noise_levels):
+        new_LFP = data.LFP
         if nl:
             noise = numpy.random.normal(scale=std/nl, size=shape)
             snr = np.round((new_LFP.var()**.5/noise.var()**.5))
 
         else:
             noise = 0
             snr = 0
-
+        new_LFP += noise    
         snrs.append(snr)
 
-        new_LFP = data.LFP + noise
+
 
 
 

kcsd/__init__.py

@@ -1,6 +1,6 @@
 import os
 kcsd_loc = os.path.dirname(os.path.abspath(__file__))
-sample_data_path = os.path.join(kcsd_loc, '..', 'data')
+sample_data_path = os.path.join(kcsd_loc, 'data')
 
 from .KCSD import KCSD1D, KCSD2D, KCSD3D, MoIKCSD, oKCSD1D, oKCSD2D, oKCSD3D
 from .sKCSD import sKCSD, sKCSDcell

kcsd/sKCSD.py

@@ -287,7 +287,8 @@ def points_in_between(self, p1, p0, last):
         # bresenhamline only works with 2D vectors with coordinates
         if p1[0] == p0[0] and p1[1] == p0[1] and p1[2] == p0[2]:
             return [np.array(p1)]
-        new_p1, new_p0 = np.ndarray((1, 3), dtype=np.int), np.ndarray((1, 3), dtype=np.int)
+        new_p1, new_p0 = np.ndarray((1, 3), dtype=int), np.ndarray((1, 3),
+                                                                   dtype=int)
         for i in range(3):
             new_p1[0, i], new_p0[0, i] = p1[i], p0[i]
         intermediate_points = utils.bresenhamline(new_p0, new_p1, -1)
@@ -337,7 +338,7 @@ def get_grid(self):
             [self.ymin, self.ymax],
             [self.zmin, self.zmax]
         ]
-        dims = np.ones((3, ), dtype=np.int)
+        dims = np.ones((3, ), dtype=int)
         for i, dx in enumerate(self.dxs):
             dims[i] = 1
             if dx:
@@ -365,7 +366,7 @@ def point_coordinates(self, morpho, dxs=None):
         minis = np.array([self.xmin, self.ymin, self.zmin])
         zero_coords = np.zeros((3, ), dtype=int)
         coor_3D = np.zeros((morpho.shape[0] - 1, morpho.shape[1]),
-                           dtype=np.int)
+                           dtype=int)
         if dxs is None:
             dxs = self.dxs
         for i, dx in enumerate(dxs):
@@ -634,6 +635,7 @@ def parameters(self, **kwargs):
         self.dim = 'skCSD'
         self.tolerance = kwargs.pop('tolerance', 2e-06)
         self.exact = kwargs.pop('exact', False)
+        self.est_xyz_auto =  False
         if kwargs:
             raise TypeError('Invalid keyword arguments:', kwargs.keys())
 

kcsd/sKCSD_utils.py

@@ -105,7 +105,7 @@ def load_sim(path):
     morphology = np.array(cell_data['morphology'])
     ele_pos = np.array(cell_data['ele_pos'])
     n_src = cell_data['n_src']
-    return est_csd, est_pot, cell_obj, morphology, ele_pos, n_src
+    return est_csd, est_pot, morphology, ele_pos, n_src
 
 
 def load_elpos(path):