visualize.py f-string transformed to simple string for server correct display

src/utils/visualize.py

@@ -112,10 +112,10 @@ def reg_plot(meas, pred, train_idx, test_idx, trainplot=True):
 
     fig, ax = plt.subplots(figsize=(12, 4))
     if trainplot:
-        sns.regplot(x=meas[0], y=pred[0], color="#2C6B6F", label=f'Cal (Predicted = {
-                    a0[0]} + {a1[0]} x Measured)', scatter_kws={'edgecolor': 'black'})
-    sns.regplot(x=meas[1], y=pred[1], color='#d0f7be', label=f'Val (Predicted = {
-                a0[1]} + {a1[1]} x Measured)', scatter_kws={'edgecolor': 'black'})
+        sns.regplot(x=meas[0], y=pred[0], color="#2C6B6F", label='Cal (Predicted = '+
+                    a0[0] +' + '+ a1[0] +' x Measured)', scatter_kws={'edgecolor': 'black'})
+    sns.regplot(x=meas[1], y=pred[1], color='#d0f7be', label='Val (Predicted = '+
+                a0[1]+' + '+a1[1]+' x Measured)', scatter_kws={'edgecolor': 'black'})
     plt.plot([np.min(meas[0]) - 0.05, np.max([meas[0]]) + 0.05],
              [np.min(meas[0]) - 0.05, np.max([meas[0]]) + 0.05], color='black')
 
@@ -152,7 +152,7 @@ def resid_plot(meas, pred, train_idx, test_idx, trainplot=True):
         ec = np.subtract(meas[0], pred[0])
         ecc = np.array(ec).reshape(-1, 1)
         sns.scatterplot(x=pred[0], y=ec, color="#2C6B6F",
-                        label=f'Cal', edgecolor="black")
+                        label='Cal', edgecolor="black")
 
         for i, txt in enumerate(train_idx):
             if np.abs(ecc[i]) > np.mean(ecc) + 3*np.std(ecc):
@@ -161,7 +161,7 @@ def resid_plot(meas, pred, train_idx, test_idx, trainplot=True):
 
 
     sns.scatterplot(x=pred[1], y=et, color="#d0f7be",
-                    label=f'Val', edgecolor="black")
+                    label='Val', edgecolor="black")
     for i, txt in enumerate(test_idx):
         if np.abs(ett[i]) > np.mean(ett) + 3 * np.std(ett):
             plt.annotate(txt, (np.array(pred[1]).reshape(-1)[i], ett[i]))