diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 30bb0e7..0243f3d 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -3,6 +3,8 @@
+
+
@@ -321,7 +323,14 @@
1594770746301
-
+
+ 1594772074449
+
+
+
+ 1594772074449
+
+
@@ -352,7 +361,8 @@
-
+
+
@@ -376,11 +386,11 @@
-
-
+
+
-
-
+
+
diff --git a/docs/Examples/iterative_fitter.py b/docs/Examples/iterative_fitter.py
index 665d379..37d8218 100644
--- a/docs/Examples/iterative_fitter.py
+++ b/docs/Examples/iterative_fitter.py
@@ -2,7 +2,6 @@ from scipy.optimize import curve_fit
import llepe
import pandas as pd
import numpy as np
-import json
def linear(x, a, b):
diff --git a/docs/Examples/iterative_fitter_monitor.py b/docs/Examples/iterative_fitter_monitor.py
index b234b31..a6c2370 100644
--- a/docs/Examples/iterative_fitter_monitor.py
+++ b/docs/Examples/iterative_fitter_monitor.py
@@ -13,6 +13,25 @@ while go == 'y':
if parameter in col:
info_cols[parameter].append(col)
for parameter in parameters:
+ mini_df = df[info_cols[parameter]]
fig, ax = plt.subplots()
- ax.title
-
+ ax.set_title(parameter)
+ for col in info_cols[parameter]:
+ ax.plot(df['iters'].values,
+ df[col].values,
+ label=col,
+ linestyle='-',
+ marker='o')
+ ax.set_xlabel('iteration')
+ ax.set_ylabel('Value')
+ plt.legend()
+ plt.show()
+ fig, ax = plt.subplots()
+ ax.set_title('best_obj_value')
+ ax.plot(df['iters'].values,
+ df['best_obj'].values,
+ linestyle='-',
+ marker='o')
+ ax.set_xlabel('iteration')
+ ax.set_ylabel('Value')
+ plt.show()