plot_fibers_in_striatum_side_view.py

generates a side view of the striatum with the fiber tips

1. Import required packages

import pandas as pd
import numpy as np
from pathlib import Path
from brain_locations_visualizer import config_parser
from brain_locations_visualizer.plotting_functions import generate_side_figure

2. Get the configuration file and define variables

# use the default config file for the documentation
config_file = Path("config_for_documentation.json")

# variables are assigned in the config_parser function
config_parser.config_parser(config_file)

plot with a different marker the flat fibers and the tapered fibers (this is specified in the mouse name)

ff_marker = "_"
tf_marker = "|"

define the output directory as the parent of the config file

parent = Path(config_file).parent

read the file of points

coords = pd.read_csv(config_parser.file_path, header=0)
X = coords.x
Y = coords.y
Animal_Name = coords.Mouse_name

select only the fibers used in the analysis animals that are not included have a # in front of their name

animal_mask = [not an.startswith("#") for an in Animal_Name]
X = np.array(list(X[animal_mask])).astype(float)
Y = np.array(list(Y[animal_mask])).astype(float)
Animal_Name = np.array(list(Animal_Name[animal_mask]))

plot slices location evenly if the precise slices are not specified in the config file

if config_parser.sl_list == []:
    step = int(
        np.floor(
            (config_parser.z_limits[1] - config_parser.z_limits[0])
            / config_parser.n_images
        )
    )
    sl_list = list(
        range(config_parser.z_limits[0], config_parser.z_limits[1], step)
    )
    sl_list = sl_list[-config_parser.n_images :]

else:
    sl_list = config_parser.sl_list

separate animals

mask_1 = [x.startswith(config_parser.id_1) for x in Animal_Name]
mask_2 = [x.startswith(config_parser.id_2) for x in Animal_Name]
mask_other = np.logical_and(
    [not e for e in mask_1], [not e for e in mask_2]
)

ff_mask = [x.endswith("_flat") for x in Animal_Name]
tf_mask = [not x for x in ff_mask]

2. Generate the figure

generate_side_figure(
    config_parser,
    sl_list,
    X,
    Y,
    mask_1,
    mask_2,
    mask_other,
    ff_mask,
    tf_mask,
    ff_marker,
    tf_marker,
    parent,
)

/mnt/c/Users/herny/Documents/GitHub/brain-locations-visualizer/brain_locations_visualizer/plotting_functions.py:103: UserWarning: FixedFormatter should only be used together with FixedLocator
  ax.set_xticklabels(a, fontsize=18)
/mnt/c/Users/herny/Documents/GitHub/brain-locations-visualizer/brain_locations_visualizer/plotting_functions.py:106: UserWarning: FixedFormatter should only be used together with FixedLocator
  ax.set_yticklabels(a, fontsize=18)