MultiTaskMPN/leison_plot.py at main · AllenInstitute/MultiTaskMPN · GitHub

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import numpy as np
import pandas as pd

import pickle

import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.ticker import MaxNLocator

import leison as leison_helper

mpl.rcParams.update({
    "font.family": "sans-serif",
    "font.sans-serif": ["Arial", "Helvetica", "DejaVu Sans"],
    "font.size": 8,
    "axes.labelsize": 8,
    "axes.titlesize": 8,
    "xtick.labelsize": 7,
    "ytick.labelsize": 7,
    "pdf.fonttype": 42,
    "ps.fonttype": 42,
})

if __name__ == "__main__":
    aname = "everything_seed749_L21e4+hidden300+batch128+angle"

    pickle_name = f"./multiple_tasks_perf/lesion_prune_results_{aname}.pkl"
    with open(pickle_name, 'rb') as f:
        results = pickle.load(f)

    all_comb_names_leison = results["leison"]["all_comb_names_leison"]
    all_comb_names_leison_ = [k for k in all_comb_names_leison if k not in ("pre_cNone", "post_cNone")]
    all_tasks = results["leison"]["all_tasks"]
    ihtask_accs = np.asarray(results["leison"]["ihtask_accs"], dtype=float)
    ihrandomtask_accs = np.asarray(results["random_leison"]["ihrandomtask_accs"], dtype=float)

    select_props = []
    for key_idx, key in enumerate(all_comb_names_leison):
        if key not in ("pre_cNone", "post_cNone"):
            leison = ihtask_accs[:, key_idx]
            random_leison = ihrandomtask_accs[:, key_idx]
            noleison = ihtask_accs[:,0]
            leison_diff = noleison - leison
            random_leison_diff = noleison - random_leison
            normalized_leison_diff = random_leison - leison
            select_props.append(normalized_leison_diff)

    select_props = np.array(select_props).T

    leison_helper.plot_heatmap(select_props, all_comb_names_leison_, all_tasks,
                               xlabel="Lesion Condition", ylabel="Task", savename="normalized_leison",
                               aname=aname, label="Normalized Accuracy")