Config, Lots of docs, Format

Added a config validator and documented code that was previously
undocumented, for the plot_generator scripts, documented them.

plot_generator/fit.py

@@ -6,53 +6,85 @@ n = int(input("Sensor number to be printed: "))
 
 file = ""
 
+
 def generate_plot():
-    reader = csv.reader(file, delimiter=',')
+    # Read data using the CSV library
+    reader = csv.reader(file, delimiter=",")
+
+    # Create a list from the data
     data = list(reader)
-    data.sort(key=lambda imp: float(imp[2]))
-    lenght = len(data)
+
+    # Sort the list using a lambda sort descriptor
+    # A lambda function is an anonymous function (= an unnamed function),
+    # which makes it convenient. A sort descriptor is a function that
+    # (usually, but not here) returns a value indicating which of two values
+    # come before or after in the ordering.
+    # Here, instead we simply return a floating point value for each data point
+    data.sort(key=lambda data_point: float(data_point[2]))
+
+    # Store the x and y coordinates in two arrays
     x = []
     y = []
 
-    for _ in range(lenght):
-        extract = data.pop(0)
-        sensor = int(extract.pop(0))
+    for _ in range(len(data)):
+        # Extract the data point
+        data_point = data.pop(0)
+        sensor = int(data_point.pop(0))
         if sensor == n:
-            ye = extract.pop(0)
-            xe = extract.pop(0)
-            y.append(float(ye))
-            x.append(float(xe))
+            y.append(float(data_point.pop(0)))
+            x.append(float(data_point.pop(0)))
 
+    # Use Numpy's polyfit function to fit a 2nd degree polynomial to the points using quadratic regression
+    # This function returns an array with the coefficients
     fit = np.polyfit(x, y, 2)
 
+    # The formula to output to the plot
     formula = f"F(U) = {round(float(fit[0]), 4)}U^2+{round(float(fit[1]), 4)}U+{round(float(fit[2]), 4)}"
 
-    fit_fn = np.poly1d(fit)
+    # Create a fit function from the previously determined coefficients
+    fit_fn = np.poly1d(fit) # Returns a function that takes a list of x-coordinate as argument
 
+    # Plot the line on the graph
     plt.plot(x, fit_fn(x), color="BLUE", label="T(U)")
 
+    # Scatter Plot the data points that we have
     plt.scatter(x, y, color="MAGENTA", marker="o", label="Data")
+
+    # Label the graph
     plt.ylabel("Temperature")
     plt.xlabel("Voltage")
-    title = 'Sensor MCP9701A #{}'.format(n)
-    plt.title(title)
+    plt.title("Sensor MCP9701A #{}".format(n))
+
+    # Scale the axis appropriately
     plt.axis((0.6, 2.0, 15.0, 70.0))
+
+    # Print a legend and set the graph to be annotated
     plt.legend(loc="lower right")
     plt.annotate(formula, xy=(0.85, 60))
+
+    # Enable the background grid
     plt.grid(True)
+
+    # Finally, show the graph
     plt.show()
 
+    # Get user input whether to save the plot or not
     saveit = input("Do you wish to save the plot? (y/N) ").lower()
 
     if saveit == "y":
-        plt.savefig("Sensor"+str(n)+".png")
-        plt.savefig("Sensor"+str(n)+".pdf", format="pdf")
-        plt.savefig("Sensor"+str(n)+".svg", format="svg")
+        # Save the plot as Sensor[Number] (e.g. Sensor9) as png, pdf and svg
+        plt.savefig("Sensor" + str(n) + ".png")
+        plt.savefig("Sensor" + str(n) + ".pdf", format="pdf")
+        plt.savefig("Sensor" + str(n) + ".svg", format="svg")
         print("==> Images saved")
     else:
         print("==> Images discarded")
 
+
+# Since we have defined a function above as a function, this here is executed first
 filename = input("Please enter a file path to the csv file to be plotted: ")
+
+# Try to open the file
 try:
     file = open(filename, "r")
     generate_plot()

plot_generator/plot_generator.py

@@ -4,29 +4,36 @@ import matplotlib.pyplot as plt
 import csv
 import os
 
+# Get user input for various data
 path = input("Path to csv-file to be plotted: ")
+print("For the below, it is recommended to enter data in this format: yyyy-mm-dd-hh-mm")
 date = input("Date & time at which the measurement was taken (approx.): ")
 group = input("Group-name: ")
 saveit = input("Should the graph be saved? (y/n) ").lower()
 
 imp = open(path, "r")
-reader = csv.reader(imp, delimiter=',')
-rohdaten = list(reader)
-lenght = len(rohdaten)
+reader = csv.reader(imp, delimiter=",")
+data = list(reader)
 x = []
 y = []
-for i in range(lenght):
-    extract = rohdaten.pop(0)
+for i in range(len(data)):
+    # Extract the data
+    extract = data.pop(0)
     x.append(float(extract.pop(0)))
     y.append(float(extract.pop(0)))
 
+# Set up plot
 plt.plot(x, y, color="MAGENTA")
 plt.xlabel("Time")
 plt.ylabel("Voltage")
-title = f"GC - Biogasanlage {date}"
-plt.title(title)
+
+plt.title(f"GC - Biogasanlage {date}")
 plt.grid(True)
-if saveit == "y":
+
+# Check if user wants to save the image
+if saveit == "n":
+    print("didn't save images")
+else:
     pos = 0
     for letter in path[::-1]:
         if letter == "/":
@@ -40,11 +47,7 @@ if saveit == "y":
         os.mkdir(save_path)
     except FileExistsError:
         pass
-    plt.savefig(save_path)
-    os.rename(f"{save_path}/.png", f"{save_path}/GC-{date}-{group}.png")
-    print(f"saved images to {save_path}")
-else:
-    print("didn't save images")
+    plt.savefig(f"{save_path}/GC-{date}-{group}.png")
+
+    print(f"Saved images to {save_path}")
 plt.show()
-
-