horizontal scaling of 10+ axes with figrid

[oliche]

Hello,

For multiple probe displays I get an issue trying to use figrid specifically, if I use many axes, some of them do not keep the same scale. It changes according to the number of axes, for example here with N=11 and 13.

At first I thought it was because of the labels, so I did plot the same insertion over and over again. Still the same.
The get_coords is also fine, the diffs are constant so I think the issue may lie with figrid.

Have you ever encountered this and found a fix ?

# %%
from pathlib import Path

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

from ibl_style.style import figure_style
from ibl_style.utils import MM_TO_INCH, get_coords
import figrid as fg


import ephys_atlas.data
import brainbox.ephys_plots
import iblatlas.atlas
import iblatlas.plots

ba = iblatlas.atlas.AllenAtlas()
regions = iblatlas.atlas.BrainRegions()
figure_style()
FIG_SIZE = (13, 6)


pids = ephys_atlas.data.BENCHMARK_PIDS
n_pids = len(pids)
path_features = Path('/Users/olivier/Documents/datadisk/Data/paper-ephys-atlas/ephys-atlas-decoding/features/2024_W50')  # mac
path_features = Path('/mnt/s0/ephys-atlas-decoding/features/2024_W50')  # parede
df_voltage = pd.read_parquet(path_features / 'raw_ephys_features_denoised.pqt')

ax_ratios =  np.r_[np.ones(n_pids), 2, 8]

# Make a double column figure
fig = plt.figure(figsize=FIG_SIZE)

# Get the dimensions of the figure in mm
width, height = fig.get_size_inches() / MM_TO_INCH
xspans = get_coords(width, ratios=ax_ratios, space=15, pad=5, span=(0, 1))
yspans = get_coords(height, ratios=[1], space=[20], pad=5, span=(0, 1))
ax = [fg.place_axes_on_grid(fig, xspan=xspans[i], yspan=yspans[0]) for i in range(len(ax_ratios))]

ba.plot_top(ax=ax[-1])

for i, pid in enumerate(pids):
    df_pid = df_voltage.loc[pids[0]]
    depth = df_pid.groupby('axial_um').agg(atlas_id=pd.NamedAgg(column='atlas_id', aggfunc='first')).reset_index()
    brainbox.ephys_plots.plot_brain_regions(
        depth['atlas_id'].values, channel_depths=depth['axial_um'].values,
        brain_regions=regions, display=True, ax=ax[i])
    ax[-1].plot(df_pid['x'].values * 1e6, df_pid['y'].values * 1e6, '.', color='r', markersize=2)
    ax[-1].plot(df_pid['x'].values[-1] * 1e6, df_pid['y'].values[-1] * 1e6, '*', color='k', markersize=2)


for i in range(13, 15):
    ax[i].axis('off')

def adjust_figure(fig):
    # Remove 7.5 mm of whitespace around figure in all directions
    adjust = 7.5
    # Depending on the location of axis labels leave a bit more space
    extra =  5
    width, height = fig.get_size_inches() / MM_TO_INCH
    fig.subplots_adjust(top=1-adjust/height, bottom=(adjust + extra)/height,
                        left=(adjust + extra)/width, right=1-adjust/width)
adjust_figure(fig)