File displacement and fix for code imports from tools in examples

tools/movement_treatment.py → examples/movement_treatment.py

@@ -45,6 +45,7 @@ def explained_variance_ratio(obj, p: int):
 
     plt.ylabel("Variance explained in ratio and cumulation")
     plt.xlabel("Number of factors")
+    plt.title('Explained variance ratio by the components and cumulation')
     plt.show()
 
 def corelations_circle(Xraw:pd.DataFrame, Xtransform:np.ndarray, p:int) -> pd.DataFrame:
@@ -83,7 +84,7 @@ def corelations_circle(Xraw:pd.DataFrame, Xtransform:np.ndarray, p:int) -> pd.Da
     
     plt.xlabel('Component 1')
     plt.ylabel('Component 2')
-    
+    plt.title('Circle of the corelations between initial variables and components')
     plt.show() 
     
     return pd.DataFrame({'id': Xraw.columns, 'COR_1': corvar[:, 0], 'COR_2': corvar[:, 1]})
@@ -106,11 +107,12 @@ def scatter_points(Xtransform:np.ndarray, Group_vect : pd.Series, Add_points : n
     
     plt.xlabel('Component 1')
     plt.ylabel('Component 2')
+    plt.title('Scatter plot of the transformed points')
     plt.show()
     return fig
 
 # %% LDA per motors____________________________________________
-for Motor in range(1,7,1):
+for Motor in range(1,2,1):
     
     lda = LinearDiscriminantAnalysis()
     Movements_Data_Motor = Movements_Data_File.loc[Movements_Data_File['Motor'] == Motor].copy()
@@ -128,7 +130,7 @@ for Motor in range(1,7,1):
     explained_variance_ratio(lda, p)
     coef = corelations_circle(Movements_Data_Motor, Xlda, Movements_Data_Motor.shape[1])
     scatter_points(Xlda, Group_Data, New_points)
-    # print(coef)
+    print(coef)
 
 # %% ACP per motors (less revelating than LDA but still interesting) ____________________________________________
 for Motor in range(1,7,1):

examples/variable_by.py

@@ -6,6 +6,9 @@ import seaborn as sns
 import scipy.signal as scs
 from pathlib import Path
 
+import sys
+sys.path.append("../")
+# Must be ath te same level of main.py to work with regular execution
 from tools.database import Database
 from tools.utils import from_class_to_text
 from tools.plots import plot_all_axis, plot_grouped_load, plot_moving_axes

tools/movement_extractor.py

@@ -8,9 +8,8 @@ import seaborn as sns
 import matplotlib.pyplot as plt
 import scipy.signal as scs
 
-from tools.database import Database
-from tools.plots import Spectrogram_plot
-from tools.processing import RMS, FFT
+from .database import Database
+from .processing import RMS
 
 DB = Database(f"D:\VSB\Programs\DB\Robot2-LoadTest.sqlite")
 
@@ -245,12 +244,10 @@ class Movement_Extractor:
             plt.show()
         return DataMovementFile
     
-    
-# Example of uses : 
 if __name__ == "__main__":
     
 # %% Extract movement from exel file and store it in Data_Movements.xlsx
-    Extractor = Movement_Extractor(fr"D:\VSB\Programs\data-collection\data\[2024-06-18] 10h53 data [30%-80%] [4ms] [class 4] [10 10 10 10 10 10] - Robot 2_TRACE.xlsx")
+    Extractor = Movement_Extractor(fr"D:\VSB\Programs\data-collection\data\[2024-06-18] 10h53 data [30%-80%] [4ms] [class 0] [10 10 10 10 10 10] - Robot 2_TRACE.xlsx")
     Total_Data = Extractor.movements_from_file(plot = 'current') # plots the extracted current
     Total_Data.to_excel("Data_Movements.xlsx")