ENH : added a method to the Function Class named "data_preprocessing"…

… to clear the CSV file and save a CSV without header

rocketpy/mathutils/function.py

@@ -10,6 +10,7 @@
 
 import matplotlib.pyplot as plt
 import numpy as np
+import csv
 from scipy import integrate, linalg, optimize
 
 try:
@@ -1117,6 +1118,49 @@ def low_pass_filter(self, alpha):
             interpolation=self.__interpolation__,
             extrapolation=self.__extrapolation__,
         )
+
+    def data_preprocessing(self, source):
+        """Clear data (in particular NaN objects) and returns a CSV file without header and its name.
+
+        Parameters
+        ----------
+        source : string
+            The file path to the CSV file.
+
+        Returns
+        -------
+        Function
+            The function with the incoming cleared CSV
+        """
+        output_path = 'cleared_data.csv'
+
+        with open(source, 'r') as file:
+            reader = csv.reader(file)
+            header = next(reader)  # Read the header
+
+            data = [row for row in reader]
+
+        # Create a new list without the headers
+        data_no_headers = []
+
+        for row in data[1:]:
+            # Check if the row is not empty and if all values in the row can be converted to float
+            if row and all(self.is_float(value) for value in row):
+                data_no_headers.append(row)
+
+        # Save the processed data to a new CSV file
+        with open(output_path, 'w', newline='') as output_file:
+            writer = csv.writer(output_file, delimiter=',')
+            writer.writerows(data_no_headers)
+
+        return Function(
+            source=output_path,
+            interpolation=self.__interpolation__,
+            extrapolation=self.__extrapolation__,
+        )
+
+
+
 
     # Define all presentation methods
     def __call__(self, *args):
@@ -2987,6 +3031,72 @@ def _check_user_input(
                     + f"and output dimension ({in_out_dim})."
                 )
         return inputs, outputs, interpolation, extrapolation
+
+    def is_float(self, element):
+        """
+        Returns a boolean indicating us if an element is convertible to a float or not.
+        True : the element is convertible to a float
+        False : the element is not convertible to a float
+
+        Parameters
+        ----------
+        element : any
+            This is the element to test.
+
+        Returns
+        -------
+        result : boolean
+            The element is convertible or not.
+        """
+        if element is None: 
+            return False
+        try:
+            float(element)
+            return True
+        except ValueError:
+            return False
+
+    def return_first_data(self, source):
+        """
+        Returns the first data of a CSV file.
+
+        Parameters
+        ----------
+        source : string
+            This is the file path to the csv.
+
+        Returns
+        -------
+        result : any
+            The first data of the CSV file.
+        """
+        native_data = open(source)
+        for row in native_data : 
+            for value in row :
+                return value
+
+
+    def if_header(self, source):
+        """
+        Returns if a CSV file has a header or not.
+        True : The CSV file has a header
+        False : The CSV file has no header
+
+        Parameters
+        ----------
+        source : string
+            This is the file path to the csv.
+
+        Returns
+        -------
+        result : boolean
+            The result of the CSV file containing a header or not.
+        """
+        return not self.is_float(self.return_first_data(source))
+
+
+
+
 
 
 class PiecewiseFunction(Function):