analyse different things

src/pyVertexModel/analysis/analyse_results_excel.py

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+import numpy as np
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+from scipy.interpolate import griddata
+
+# Read excel into a pandas dataframe
+results_excel = pd.read_excel('data/simulations_results/all_files_features.xlsx')
+
+columns = ['visc', 'lt', 'ltExt', 'lS1', 'lS2', 'lS3', 'refA0', 'kSubs', 'lVol', 'eARBarrier']
+y_variables = ['recoiling_speed_apical', 'K']
+
+for y_variable in y_variables:
+    for column in columns:
+        # Plot in different ways the data
+        g = sns.lmplot(
+            data=results_excel,
+            x=column,
+            y=y_variable,
+        )
+
+        # Plot a graph with two values
+
+
+        # Use more informative axis labels than are provided by default
+        g.set_axis_labels(column, y_variable)
+
+        # Save the plot
+        plt.savefig(f'data/simulations_results/0_scatter_plot_{column}_{y_variable}.png')
+        plt.close('all')
+
+        # load plot
+
+
+        # for column2 in columns:
+        #     if column == column2:
+        #         continue
+        #
+        #     fig = plt.figure(facecolor='w')
+        #     X = results_excel[column].values
+        #     Y = results_excel[column2].values
+        #     Z = results_excel[y_variable].values
+        #
+        #     # Scatter plot with hue as the third dimension color
+        #     g = sns.scatterplot(
+        #         x=X,
+        #         y=Y,
+        #         hue=Z,
+        #         palette='RdBu_r',
+        #     )
+        #     plt.savefig(f'data/simulations_results/1_scatter_plot_{column}_{column2}_{y_variable}.png')
+        #     plt.close('all')