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

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import pandas as pd
import requests
import zipfile
import numpy as np
from plotly.subplots import make_subplots

###### Load/Download Data #######

# URL of the zip file
url = 'https://github.com/OpenMS/pyopenms_viz/releases/download/v0.1.3/spyogenes.zip'
zip_filename = 'spyogenes.zip'

# Download the zip file
try:
    print(f"Downloading {zip_filename}...")
    response = requests.get(url)
    response.raise_for_status()  # Check for any HTTP errors

    # Save the zip file to the current directory
    with open(zip_filename, 'wb') as out:
        out.write(response.content)
    print(f"Downloaded {zip_filename} successfully.")
except requests.RequestException as e:
    print(f"Error downloading zip file: {e}")
except IOError as e:
    print(f"Error writing zip file: {e}")

# Unzipping the file
try:
    with zipfile.ZipFile(zip_filename, 'r') as zip_ref:
        # Extract all files to the current directory
        zip_ref.extractall()
        print("Unzipped files successfully.")
except zipfile.BadZipFile as e:
    print(f"Error unzipping file: {e}")

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={'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