Plot Peakmap Binning Demonstration

This example demonstrates how different binning levels affect peak map visualization

import pandas as pd
import requests
from io import StringIO
import numpy as np
import matplotlib.pyplot as plt

pd.options.plotting.backend = "ms_matplotlib"

url = "https://github.com/OpenMS/pyopenms_viz/releases/download/v0.1.5/TestMSExperimentDf.tsv"
response = requests.get(url)
response.raise_for_status()
df = pd.read_csv(StringIO(response.text), sep="\t")


fig, axs = plt.subplots(3, 1, figsize=(5, 15), sharex=True, sharey=True)


binning_levels = [(10, 10), (40, 40), (100, 100)]

for ax, (num_x_bins, num_y_bins) in zip(axs, binning_levels):

    df.plot(
        kind="peakmap",
        x="RT",
        y="mz",
        z="inty",
        aggregate_duplicates=True,
        num_x_bins=num_x_bins,
        num_y_bins=num_y_bins,
        canvas=ax,
        title=f"Binning: {num_x_bins} x {num_y_bins}",
        title_font_size=12,
        show_plot = False,
        xaxis_label_font_size=10,
        yaxis_label_font_size=10,
        xaxis_tick_font_size=9,
        yaxis_tick_font_size=9,
    )

fig.subplots_adjust(top=0.95, hspace=0.3, bottom=0.13)
plt.show()