update logger README to include detailed usage instructions and examples

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

example/logger/csv_2_plot.py

@@ -1,53 +1,33 @@
 import argparse
-import matplotlib
-matplotlib.use('Agg')
+
 import matplotlib.dates as mdates
 import matplotlib.pyplot as plt
 import pandas as pd
 from dateutil.tz import gettz
-from matplotlib.ticker import MultipleLocator, FuncFormatter
-import math
+from matplotlib.ticker import MultipleLocator
 
 
-def plot_power_data(csv_path, output_path, plot_types, sources,
-                    voltage_y_max=None, current_y_max=None, power_y_max=None,
-                    relative_time=False, time_x_line=None, time_x_label=None):
+def plot_power_data(csv_path, output_path, plot_types, sources):
     """
     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.
-        sources (list): A list of strings indicating which power sources to plot.
-        voltage_y_max (float, optional): Maximum value for the voltage plot's Y-axis.
-        current_y_max (float, optional): Maximum value for the current plot's Y-axis.
-        power_y_max (float, optional): Maximum value for the power plot's Y-axis.
-        relative_time (bool): If True, the x-axis will show elapsed time from the start.
-        time_x_line (float, optional): Interval in seconds for x-axis grid lines.
-        time_x_label (float, optional): Interval in seconds for x-axis labels.
+        plot_types (list): A list of strings indicating which plots to generate
+                           (e.g., ['power', 'voltage', 'current']).
+        sources (list): A list of strings indicating which power sources to plot
+                        (e.g., ['vin', 'main', 'usb']).
     """
     try:
         # Read the CSV file into a pandas DataFrame
         df = pd.read_csv(csv_path, parse_dates=['timestamp'])
         print(f"Successfully loaded {len(df)} records from '{csv_path}'")
 
-        if df.empty:
-            print("CSV file is empty. Exiting.")
-            return
-
-        # --- Time Handling ---
-        x_axis_data = df['timestamp']
-        if relative_time:
-            start_time = df['timestamp'].iloc[0]
-            df.loc[:, 'elapsed_seconds'] = (df['timestamp'] - start_time).dt.total_seconds()
-            x_axis_data = df['elapsed_seconds']
-            print("X-axis set to relative time (elapsed seconds).")
-        else:
-            # --- Timezone Conversion for absolute time ---
-            local_tz = gettz()
-            df.loc[:, 'timestamp'] = df['timestamp'].dt.tz_convert(local_tz)
-            print(f"Timestamp converted to local timezone: {local_tz}")
+        # --- Timezone Conversion ---
+        local_tz = gettz()
+        df['timestamp'] = df['timestamp'].dt.tz_convert(local_tz)
+        print(f"Timestamp converted to local timezone: {local_tz}")
 
     except FileNotFoundError:
         print(f"Error: The file '{csv_path}' was not found.")
@@ -80,11 +60,6 @@ def plot_power_data(csv_path, output_path, plot_types, sources,
         'voltage': {'title': 'Voltage', 'ylabel': 'Voltage (V)', 'cols': [f'{s}_voltage' for s in sources]},
         'current': {'title': 'Current', 'ylabel': 'Current (A)', 'cols': [f'{s}_current' for s in sources]}
     }
-    y_max_options = {
-        'power': power_y_max,
-        'voltage': voltage_y_max,
-        'current': current_y_max
-    }
 
     channel_labels = [s.upper() for s in sources]
     color_map = {'vin': 'red', 'main': 'green', 'usb': 'blue'}
@@ -105,7 +80,7 @@ def plot_power_data(csv_path, output_path, plot_types, sources,
         max_data_value = 0
         for j, col_name in enumerate(config['cols']):
             if col_name in df.columns:
-                ax.plot(x_axis_data, df[col_name], label=channel_labels[j], color=channel_colors[j], zorder=2)
+                ax.plot(df['timestamp'], df[col_name], label=channel_labels[j], color=channel_colors[j], zorder=2)
                 max_col_value = df[col_name].max()
                 if max_col_value > max_data_value:
                     max_data_value = max_col_value
@@ -114,10 +89,7 @@ def plot_power_data(csv_path, output_path, plot_types, sources,
 
         # --- Dynamic Y-axis Scaling ---
         ax.set_ylim(bottom=0)
-        y_max_option = y_max_options.get(plot_type)
-        if y_max_option is not None:
-            ax.set_ylim(top=y_max_option)
-        elif plot_type in scale_config:
+        if plot_type in scale_config:
             steps = scale_config[plot_type]['steps']
             new_max = next((step for step in steps if step >= max_data_value), steps[-1])
             ax.set_ylim(top=new_max)
@@ -126,35 +98,27 @@ def plot_power_data(csv_path, output_path, plot_types, sources,
         ax.set_ylabel(config['ylabel'])
         ax.legend()
 
-        # --- Y-Grid and Tick Configuration ---
+        # --- Grid and Tick Configuration ---
         y_min, y_max = ax.get_ylim()
-        
-        if y_max <= 0:
-            major_interval = 1.0 # Default for very small or zero range
-        elif plot_type == 'current' and y_max <= 2.5:
-            major_interval = 0.5 # Maintain current behavior for very small current values
+
+        # Keep the dynamic major_interval logic for tick LABELS
+        if plot_type == 'current' and y_max <= 2.5:
+            major_interval = 0.5
         elif y_max <= 10:
-            major_interval = 2.0 # Maintain current behavior for small ranges where 5-unit is too coarse
+            major_interval = 2
         elif y_max <= 25:
-            major_interval = 5.0 # Already a multiple of 5
-        else: # y_max > 25
-            # Aim for major ticks that are multiples of 5.
-            # Calculate a rough interval to get around 5 major ticks.
-            rough_interval = y_max / 5.0
-            
-            # Find the smallest multiple of 5 that is greater than or equal to rough_interval.
-            # This ensures labels are multiples of 5.
-            major_interval = math.ceil(rough_interval / 5.0) * 5.0
-            
-            # Ensure major_interval is not 0 if y_max is small but positive.
-            if major_interval == 0 and y_max > 0:
-                major_interval = 5.0
+            major_interval = 5
+        else:
+            major_interval = y_max / 5.0
 
         ax.yaxis.set_major_locator(MultipleLocator(major_interval))
         ax.yaxis.set_minor_locator(MultipleLocator(1))
+
+        # Disable the default major grid, but keep the minor one
         ax.yaxis.grid(False, which='major')
         ax.yaxis.grid(True, which='minor', linestyle='--', linewidth=0.6, zorder=0)
 
+        # Draw custom lines for 5 and 10 multiples, which are now the only major grid lines
         for y_val in range(int(y_min), int(y_max) + 1):
             if y_val == 0: continue
             if y_val % 10 == 0:
@@ -162,60 +126,43 @@ def plot_power_data(csv_path, output_path, plot_types, sources,
             elif y_val % 5 == 0:
                 ax.axhline(y=y_val, color='midnightblue', linestyle='--', linewidth=1.2, zorder=1)
 
-        # --- X-Grid Configuration ---
+        # Keep the x-axis grid
         ax.xaxis.grid(True, which='major', linestyle='--', linewidth=0.8)
-        if time_x_line is not None:
-            ax.xaxis.grid(True, which='minor', linestyle=':', linewidth=0.6)
 
-
-    # --- Formatting the x-axis ---
+    # --- Formatting the x-axis (Time) ---
+    local_tz = gettz()
     last_ax = axes[-1]
+
     if not df.empty:
-        last_ax.set_xlim(x_axis_data.iloc[0], x_axis_data.iloc[-1])
-
-    if relative_time:
-        plt.xlabel('Elapsed Time (seconds)')
-        if time_x_label is not None:
-            last_ax.xaxis.set_major_locator(MultipleLocator(time_x_label))
-        else:
-            last_ax.xaxis.set_major_locator(plt.MaxNLocator(15))
-        if time_x_line is not None:
-            last_ax.xaxis.set_minor_locator(MultipleLocator(time_x_line))
-    else:
-        local_tz = gettz()
-        plt.xlabel(f'Time ({local_tz.tzname(df["timestamp"].iloc[-1])})')
-        last_ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S', tz=local_tz))
-        if time_x_label is not None:
-            last_ax.xaxis.set_major_locator(mdates.SecondLocator(interval=int(time_x_label)))
-        else:
-            last_ax.xaxis.set_major_locator(plt.MaxNLocator(15))
-        if time_x_line is not None:
-            last_ax.xaxis.set_minor_locator(mdates.SecondLocator(interval=int(time_x_line)))
+        last_ax.set_xlim(df['timestamp'].iloc[0], df['timestamp'].iloc[-1])
 
+    last_ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S', tz=local_tz))
+    last_ax.xaxis.set_major_locator(plt.MaxNLocator(15))
+    plt.xlabel(f'Time ({local_tz.tzname(df["timestamp"].iloc[-1])})')
     plt.xticks(rotation=45)
 
     # --- Add a main title and subtitle ---
-    if relative_time:
-        main_title = 'PowerMate Log'
-    else:
-        start_time_str = df['timestamp'].iloc[0].strftime('%Y-%m-%d %H:%M:%S')
-        end_time_str = df['timestamp'].iloc[-1].strftime('%H:%M:%S')
-        main_title = f'PowerMate Log ({start_time_str} to {end_time_str})'
-
+    start_time = df['timestamp'].iloc[0].strftime('%Y-%m-%d %H:%M:%S')
+    end_time = df['timestamp'].iloc[-1].strftime('%H:%M:%S')
+    main_title = f'PowerMate Log ({start_time} to {end_time})'
 
     subtitle_parts = []
     if avg_interval_ms > 0:
         subtitle_parts.append(f'Avg. Interval: {avg_interval_ms:.2f} ms')
+
     voltage_strings = [f'{source.upper()} Avg: {avg_v:.2f} V' for source, avg_v in avg_voltages.items()]
     if voltage_strings:
         subtitle_parts.extend(voltage_strings)
+
     subtitle = ' | '.join(subtitle_parts)
 
     full_title = main_title
     if subtitle:
         full_title += f'\n{subtitle}'
+
     fig.suptitle(full_title, fontsize=14)
 
+    # Adjust layout to make space for the subtitle
     plt.tight_layout(rect=[0, 0, 1, 0.98])
 
     # --- Save the plot to a file ---
@@ -246,32 +193,9 @@ def main():
         help="Power sources to plot. Choose from 'vin', 'main', 'usb'. "
              "Default is to plot all three."
     )
-    parser.add_argument("--voltage_y_max", type=float, help="Maximum value for the voltage plot's Y-axis.")
-    parser.add_argument("--current_y_max", type=float, help="Maximum value for the current plot's Y-axis.")
-    parser.add_argument("--power_y_max", type=float, help="Maximum value for the power plot's Y-axis.")
-    parser.add_argument(
-        "-r", "--relative-time",
-        action='store_true',
-        help="Display the x-axis as elapsed time from the start (in seconds) instead of absolute time."
-    )
-    parser.add_argument("--time_x_line", type=float, help="Interval in seconds for x-axis grid lines.")
-    parser.add_argument("--time_x_label", type=float, help="Interval in seconds for x-axis labels.")
-
-
     args = parser.parse_args()
 
-    plot_power_data(
-        args.input_csv,
-        args.output_image,
-        args.type,
-        args.source,
-        voltage_y_max=args.voltage_y_max,
-        current_y_max=args.current_y_max,
-        power_y_max=args.power_y_max,
-        relative_time=args.relative_time,
-        time_x_line=args.time_x_line,
-        time_x_label=args.time_x_label
-    )
+    plot_power_data(args.input_csv, args.output_image, args.type, args.source)
 
 
 if __name__ == "__main__":

example/logger/logger.py

@@ -113,9 +113,9 @@ class OdroidPowerLogger:
                             ts_iso_csv = ts_dt.isoformat(timespec='milliseconds').replace('+00:00', 'Z')
                             row = [
                                 ts_iso_csv, sensor_data.uptime_ms,
-                                f"{sensor_data.vin.voltage:.3f}", f"{sensor_data.vin.current:.3f}", f"{sensor_data.vin.power:.3f}",
-                                f"{sensor_data.main.voltage:.3f}", f"{sensor_data.main.current:.3f}", f"{sensor_data.main.power:.3f}",
-                                f"{sensor_data.usb.voltage:.3f}", f"{sensor_data.usb.current:.3f}", f"{sensor_data.usb.power:.3f}"
+                                sensor_data.vin.voltage, sensor_data.vin.current, sensor_data.vin.power,
+                                sensor_data.main.voltage, sensor_data.main.current, sensor_data.main.power,
+                                sensor_data.usb.voltage, sensor_data.usb.current, sensor_data.usb.power
                             ]
                             csv_writer.writerow(row)
 

main/service/monitor.c

@@ -54,9 +54,9 @@ ina3221_t ina3221 = {
             .ch1 = true, // channel 1 enable
             .ch2 = true, // channel 2 enable
             .ch3 = true, // channel 3 enable
-            .avg = INA3221_AVG_16, // 16 samples average
-            .vbus = INA3221_CT_140, // 140us by channel (bus)
-            .vsht = INA3221_CT_1100, // 1.1ms by channel (shunt)
+            .avg = INA3221_AVG_64, // 64 samples average
+            .vbus = INA3221_CT_2116, // 2ms by channel (bus)
+            .vsht = INA3221_CT_2116, // 2ms by channel (shunt)
         },
 };
 
@@ -298,7 +298,7 @@ void init_status_monitor()
 
 esp_err_t update_sensor_period(int period)
 {
-    if (period < 100 || period > 10000) // 0.1 sec ~ 10 sec
+    if (period < 500 || period > 10000) // 0.5 sec ~ 10 sec
     {
         return ESP_ERR_INVALID_ARG;
     }

page/index.html

@@ -379,7 +379,7 @@
                         </div>
                         <div class="mb-3 p-3 border rounded">
                             <label for="period-slider" class="form-label">Sensor Period: <span class="fw-bold text-primary" id="period-value">...</span> ms</label>
-                            <input type="range" class="form-range" id="period-slider" min="100" max="5000" step="100">
+                            <input type="range" class="form-range" id="period-slider" min="500" max="5000" step="100">
                             <div class="d-flex justify-content-end mt-2">
                                 <button type="button" class="btn btn-primary btn-sm" id="period-apply-button">Apply</button>
                             </div>