example: add .gitignore

Signed-off-by: YoungSoo Shin <shinys000114@gmail.com>

example/logger/.gitignore

@@ -0,0 +1,5 @@
+/.venv/
+/venv/
+status_pb2.py
+test.csv
+plot.png

example/logger/README.md

@@ -35,7 +35,7 @@ python3 logger.py -u admin -p password -o test.csv 192.168.30.5
 #### Plot data
 
 ```shell
-python3 csv_2_plot.py test.csv plot.png
+python3 csv_2_plot.py test.csv plot.png [--type power voltage current]
 ```
 
 ![plot.png](plot.png)

example/logger/csv_2_plot.py

@@ -5,13 +5,15 @@ import os
 import pandas as pd
 
 
-def plot_power_data(csv_path, output_path):
+def plot_power_data(csv_path, output_path, plot_types):
     """
     Reads power data from a CSV file and generates a plot image.
 
     Args:
         csv_path (str): The path to the input CSV file.
         output_path (str): The path to save the output plot image.
+        plot_types (list): A list of strings indicating which plots to generate
+                           (e.g., ['power', 'voltage', 'current']).
     """
     try:
         # Read the CSV file into a pandas DataFrame
@@ -25,44 +27,47 @@ def plot_power_data(csv_path, output_path):
         print(f"An error occurred while reading the CSV file: {e}")
         return
 
-    # Create a figure and a set of subplots (3 rows, 1 column)
+    # --- Plotting Configuration ---
+    plot_configs = {
+        'power': {'title': 'Power Consumption', 'ylabel': 'Power (W)',
+                  'cols': ['vin_power', 'main_power', 'usb_power']},
+        'voltage': {'title': 'Voltage', 'ylabel': 'Voltage (V)',
+                    'cols': ['vin_voltage', 'main_voltage', 'usb_voltage']},
+        'current': {'title': 'Current', 'ylabel': 'Current (A)', 'cols': ['vin_current', 'main_current', 'usb_current']}
+    }
+    channel_labels = ['VIN', 'MAIN', 'USB']
+    channel_colors = ['red', 'green', 'blue']
+
+    num_plots = len(plot_types)
+    if num_plots == 0:
+        print("No plot types selected. Exiting.")
+        return
+
+    # Create a figure and a set of subplots based on the number of selected plot types.
     # sharex=True makes all subplots share the same x-axis (time)
-    fig, axes = plt.subplots(3, 1, figsize=(15, 18), sharex=True)
+    # squeeze=False ensures that 'axes' is always a 2D array, even if num_plots is 1.
+    fig, axes = plt.subplots(num_plots, 1, figsize=(15, 6 * num_plots), sharex=True, squeeze=False)
+    axes = axes.flatten()  # Flatten the 2D array to 1D for easier iteration
 
-    # --- Plot 1: Power (W) ---
-    ax1 = axes[0]
-    ax1.plot(df['timestamp'], df['vin_power'], label='VIN', color='red')
-    ax1.plot(df['timestamp'], df['main_power'], label='MAIN', color='green')
-    ax1.plot(df['timestamp'], df['usb_power'], label='USB', color='blue')
-    ax1.set_title('Power Consumption')
-    ax1.set_ylabel('Power (W)')
-    ax1.legend()
-    ax1.grid(True, which='both', linestyle='--', linewidth=0.5)
+    # --- Loop through selected plot types and generate plots ---
+    for i, plot_type in enumerate(plot_types):
+        ax = axes[i]
+        config = plot_configs[plot_type]
 
-    # --- Plot 2: Voltage (V) ---
-    ax2 = axes[1]
-    ax2.plot(df['timestamp'], df['vin_voltage'], label='VIN', color='red')
-    ax2.plot(df['timestamp'], df['main_voltage'], label='MAIN', color='green')
-    ax2.plot(df['timestamp'], df['usb_voltage'], label='USB', color='blue')
-    ax2.set_title('Voltage')
-    ax2.set_ylabel('Voltage (V)')
-    ax2.legend()
-    ax2.grid(True, which='both', linestyle='--', linewidth=0.5)
+        for j, col_name in enumerate(config['cols']):
+            ax.plot(df['timestamp'], df[col_name], label=channel_labels[j], color=channel_colors[j])
 
-    # --- Plot 3: Current (A) ---
-    ax3 = axes[2]
-    ax3.plot(df['timestamp'], df['vin_current'], label='VIN', color='red')
-    ax3.plot(df['timestamp'], df['main_current'], label='MAIN', color='green')
-    ax3.plot(df['timestamp'], df['usb_current'], label='USB', color='blue')
-    ax3.set_title('Current')
-    ax3.set_ylabel('Current (A)')
-    ax3.legend()
-    ax3.grid(True, which='both', linestyle='--', linewidth=0.5)
+        ax.set_title(config['title'])
+        ax.set_ylabel(config['ylabel'])
+        ax.legend()
+        ax.grid(True, which='both', linestyle='--', linewidth=0.5)
 
     # --- Formatting the x-axis (Time) ---
     # Improve date formatting on the x-axis
-    ax3.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
-    ax3.xaxis.set_major_locator(plt.MaxNLocator(15))  # Limit the number of ticks
+    # Apply formatting to the last subplot's x-axis
+    last_ax = axes[-1]
+    last_ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
+    last_ax.xaxis.set_major_locator(plt.MaxNLocator(15))  # Limit the number of ticks
     plt.xlabel('Time')
     plt.xticks(rotation=45)
 
@@ -83,12 +88,20 @@ def plot_power_data(csv_path, output_path):
 
 
 def main():
-    parser = argparse.ArgumentParser(description="Generate a plot from an Odroid PowerMate CSV log file.")
+    parser = argparse.ArgumentParser(description="Generate a plot from an Odroid Smart Power CSV log file.")
     parser.add_argument("input_csv", help="Path to the input CSV log file.")
     parser.add_argument("output_image", help="Path to save the output plot image (e.g., plot.png).")
+    parser.add_argument(
+        "-t", "--type",
+        nargs='+',
+        choices=['power', 'voltage', 'current'],
+        default=['power', 'voltage', 'current'],
+        help="Types of plots to generate. Choose from 'power', 'voltage', 'current'. "
+             "Default is to generate all three."
+    )
     args = parser.parse_args()
 
-    plot_power_data(args.input_csv, args.output_image)
+    plot_power_data(args.input_csv, args.output_image, args.type)
 
 
 if __name__ == "__main__":