Plot Spyogenes subplots ms_plotly

Here we show how we can plot multiple chromatograms across runs together. In this rendering the plot is slightly cut off

import pandas as pd
import numpy as np
from plotly.subplots import make_subplots
from pyopenms_viz.util import download_file, unzip_file

zip_filename = "spyogenes.zip"
zip_dir = "spyogenes"
url = "https://zenodo.org/records/17904512/files/spyogenes.zip?download=1"

download_file(url, zip_filename)
unzip_file(zip_filename, ".")  # Extract to current directory

annotation_bounds = pd.read_csv(
    "spyogenes/AADGQTVSGGSILYR3_manual_annotations.tsv", sep="\t"
)  # contain annotations across all runs
chrom_df = pd.read_csv(
    "spyogenes/chroms_AADGQTVSGGSILYR3.tsv", sep="\t"
)  # contains chromatogram for precursor across all runs

##### Set Plotting Variables #####
pd.options.plotting.backend = "ms_plotly"
RUN_NAMES = [
    "Run #0 Spyogenes 0% human plasma",
    "Run #1 Spyogenes 0% human plasma",
    "Run #2 Spyogenes 0% human plasma",
    "Run #3 Spyogenes 10% human plasma",
    "Run #4 Spyogenes 10% human plasma",
    "Run #5 Spyogenes 10% human plasma",
]

# For each run fill in the axs object with the corresponding chromatogram
plot_list = []
for i, run in enumerate(RUN_NAMES):
    run_df = chrom_df[chrom_df["run_name"] == run]
    current_bounds = annotation_bounds[annotation_bounds["run"] == run]

    plot_list.append(
        run_df.plot(
            kind="chromatogram",
            x="rt",
            y="int",
            grid=False,
            by="ion_annotation",
            width=700,
            xaxis_label_font_size=16,
            yaxis_label_font_size=16,
            xaxis_tick_font_size=14,
            yaxis_tick_font_size=14,
            relative_intensity=True,
            annotation_data=current_bounds,
            xlabel="Retention Time (sec)",
            ylabel="Relative\nIntensity",
            show_plot=False,
            legend_config={"show": True, "title": "Transition"},
        )
    )

# Combine all plots into plotly subplot
fig = make_subplots(rows=len(plot_list), cols=1, subplot_titles=RUN_NAMES)
for idx, f in enumerate(plot_list):
    for trace in f.data:
        fig.add_trace(trace, row=idx + 1, col=1)

fig