Fixed json bug

setup.py

@@ -2,7 +2,7 @@
 
 # Package information
 name = 'madml'
-version = '2.6.2'  # Need to increment every time to push to PyPI
+version = '2.6.3'  # Need to increment every time to push to PyPI
 description = 'Application domain of machine learning in materials science.'
 url = 'https://github.com/leschultz/'\
       'materials_application_domain_machine_learning.git'

src/madml/models.py

@@ -276,7 +276,7 @@ def predict(self, d, d_input=None):
 
             key = 'Domain Prediction from {} (p={},r={})'.format(key, p, r)
             cut = value['Threshold']
-            do_pred[key] = np.where(d <= cut, 'ID', 'OD')
+            do_pred[key] = np.where(d < cut, 'ID', 'OD')
 
         if d_input is not None:
             do_pred['d_input'] = np.where(d <= d_input, 'ID', 'OD')
@@ -349,16 +349,16 @@ def assign_ground_truth(data_cv, bin_cv):
         bin_cv.loc[row, 'gt_area'] = group[3]
 
     # Make labels
-    absres = data_cv['absres/mad_y'] <= data_cv['gt_absres']
-    rmse = data_cv['rmse/std_y'] <= data_cv['gt_rmse']
-    area = data_cv['cdf_area'] <= data_cv['gt_area']
+    absres = data_cv['absres/mad_y'] < data_cv['gt_absres']
+    rmse = data_cv['rmse/std_y'] < data_cv['gt_rmse']
+    area = data_cv['cdf_area'] < data_cv['gt_area']
 
     data_cv['domain_absres/mad_y'] = np.where(absres, 'ID', 'OD')
     data_cv['domain_rmse/std_y'] = np.where(rmse, 'ID', 'OD')
     data_cv['domain_cdf_area'] = np.where(area, 'ID', 'OD')
 
-    rmse = bin_cv['rmse/std_y'] <= bin_cv['gt_rmse']
-    area = bin_cv['cdf_area'] <= bin_cv['gt_area']
+    rmse = bin_cv['rmse/std_y'] < bin_cv['gt_rmse']
+    area = bin_cv['cdf_area'] < bin_cv['gt_area']
 
     bin_cv['domain_rmse/std_y'] = np.where(rmse, 'ID', 'OD')
     bin_cv['domain_cdf_area'] = np.where(area, 'ID', 'OD')

src/madml/plots.py

@@ -118,7 +118,12 @@ def sub(x, y, ylabel, key, gt, gtlabel, metric, color):
         ax_sub.set_xlabel(f'Included {key}')
         ax_sub.set_ylabel(ylabel)
 
-        dat = {'x': x, 'y': y, 'gt': gt}
+        dat = {
+               'x': list(map(float, x)),
+               'y': list(map(float, y)),
+               'gt': float(gt),
+               }
+
         plot_dump(
                   dat,
                   fig_sub,