using github workflow

environment.yml

@@ -0,0 +1,12 @@
+name: pyeit-environment
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - pylint
+  - pytest
+  - numpy
+  - scipy
+  - pandas
+  - matplotlib
+  - vispy

examples/eit_dynamic_jac3d.py

@@ -53,7 +53,8 @@
 
 """ 3. JAC solver """
 # number of stimulation lines/patterns
-eit = jac.JAC(mesh_obj, el_pos, ex_mat=ex_mat, step=step, perm=1., parser='std')
+eit = jac.JAC(mesh_obj, el_pos, ex_mat=ex_mat, step=step, perm=1.,
+              parser='std')
 eit.setup(p=0.50, lamb=1e-3, method='kotre')
 ds = eit.solve(f1.v, f0.v, normalize=False)
 node_ds = sim2pts(pts, tri, np.real(ds))

pyeit/io/daeger_eit.py

@@ -56,10 +56,10 @@ def read_header(fname, max_lines=50):
                     cell = line.split(':')
                     fmt = int(cell[1])
         # failed to find valid parameters
-        if fr==0:
+        if fr == 0:
             print('Frame rate could not be read, setting to 20')
             fr = 20
-        if fmt==0:
+        if fmt == 0:
             print('Format could not be read, setting to 51')
             fmt = 51
 
@@ -119,7 +119,7 @@ def to_df(self):
         raise NotImplementedError()
 
 
-if __name__=="__main__":
+if __name__ == "__main__":
     file_name = r"./ID_SC_10_001.eit"
     model = DAEGER_EIT(fname=file_name)
     print(model.info)

pyeit/io/et3.py

@@ -210,10 +210,10 @@ def to_dp(self, resample=None, rel_date=None, fps=1, aux_filter=False):
         if aux_filter:
             # filter auxillary sampled data
             # correct temperature (temperature cannot be 0)
-            dp.loc[dp['tleft']==0, 'tleft'] = np.nan
-            dp.loc[dp['tright']==0, 'tright'] = np.nan
-            dp.loc[dp['nt_s']==0, 'nt_s'] = np.nan
-            dp.loc[dp['rt_s']==0, 'rt_s'] = np.nan
+            dp.loc[dp['tleft'] == 0, 'tleft'] = np.nan
+            dp.loc[dp['tright'] == 0, 'tright'] = np.nan
+            dp.loc[dp['nt_s'] == 0, 'nt_s'] = np.nan
+            dp.loc[dp['rt_s'] == 0, 'rt_s'] = np.nan
 
             dp.tleft = med_outlier(dp.tleft)
             dp.tright = med_outlier(dp.tright)
@@ -240,7 +240,7 @@ def med_outlier(d, window=17):
     """ filter outliers using median filter """
     med = d.rolling(window, center=False).median()
     std = d.rolling(window, center=False).std()
-    std[std==np.nan] = 0.0
+    std[std == np.nan] = 0.0
     # replace med with d for outlier removal
     df = med[(d <= med+3*std) & (d >= med-3*std)]
     return df

pyeit/mesh/utils.py

@@ -73,7 +73,7 @@ def edge_grad(p, fd, h0=1.0):
     d_eps = 1e-8 * h0
 
     # get dimensions
-    if np.ndim(p)==1:
+    if np.ndim(p) == 1:
         p = p[:, np.newaxis]
 
     # distance

tests/test_simple.py

@@ -16,4 +16,3 @@ def test_multiplication():
 
 def test_floating_addition():
     assert_allclose(0.1 + 0.2, 0.3)
-