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csv_2_plot: refine Y-axis major tick interval calculation for better alignment with data ranges

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Signed-off-by: YoungSoo Shin <shinys000114@gmail.com>
This commit is contained in:
YoungSoo Shin
2025-12-11 14:16:24 +09:00
parent 1f35c52261
commit 222de64932
1 changed files with 22 additions and 4 deletions
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26
example/logger/csv_2_plot.py
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@@ -6,6 +6,7 @@ import matplotlib.pyplot as plt
import pandas as pd
from dateutil.tz import gettz
from matplotlib.ticker import MultipleLocator, FuncFormatter
import math
def plot_power_data(csv_path, output_path, plot_types, sources,
@@ -127,10 +128,27 @@ def plot_power_data(csv_path, output_path, plot_types, sources,
# --- Y-Grid and Tick Configuration ---
y_min, y_max = ax.get_ylim()
if plot_type == 'current' and y_max <= 2.5: major_interval = 0.5
elif y_max <= 10: major_interval = 2
elif y_max <= 25: major_interval = 5
else: major_interval = y_max / 5.0
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
elif y_max <= 10:
major_interval = 2.0 # Maintain current behavior for small ranges where 5-unit is too coarse
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
ax.yaxis.set_major_locator(MultipleLocator(major_interval))
ax.yaxis.set_minor_locator(MultipleLocator(1))