Creating a PDF from an experiment

This example shows how to loop through folders in an experimental project, adding the driftplot for each session to a PDF file. This allows you to get a quick overview of the drift within and across sessions in an experiment.

You can extend this example to use the same scaling for the amplitudes across sessions, using the consistent amplitudes example.

from pathlib import Path

import matplotlib.pyplot as plt
import spikeinterface as si
from matplotlib.backends.backend_pdf import PdfPages

from driftplots import DriftPlotter

# Set up paths
project_path = Path("/path/to/my/project")
derivatives_path = project_path / "derivatives"
output_path = project_path / "output" / "all_drift_maps.pdf"
output_path.parent.mkdir(parents=True, exist_ok=True)

# Iterate through every subject and session, adding
# the generated matplotlib plot to the PDF

with PdfPages(output_path) as pdf:
    for sub_dir in sorted(derivatives_path.glob("sub-*")):
        for ses_dir in sorted(sub_dir.glob("ses-*")):
            analyzer_path = ses_dir / "ephys" / "sorting_analyzer.zarr"

            analyzer = si.load_sorting_analyzer(analyzer_path)

            plotter = DriftPlotter(analyzer)

            fig = plotter.drift_map_plot_matplotlib(
                add_histogram_plot=True,
                weight_histogram_by_amplitude=True,
            )

            fig.suptitle(f"{sub_dir.name}  /  {ses_dir.name}", fontsize=14)

            pdf.savefig(fig, bbox_inches="tight")
            plt.close(fig)

            print(f"  Added {sub_dir.name}/{ses_dir.name}")

print(f"\nSaved multi-page PDF to {output_path}")