remove matplotlib based tests

sappelhoff · Nov 26, 2024 · 50823e3 · 50823e3
1 parent 9667c46
commit 50823e3
Showing 1 changed file with 0 additions and 202 deletions.
diff --git a/tests/test_prep_pipeline.py b/tests/test_prep_pipeline.py
@@ -3,216 +3,14 @@
 # Authors: The PyPREP developers
 # SPDX-License-Identifier: MIT
 
-import matplotlib.pyplot as plt
 import numpy as np
 import pytest
-import scipy.io as sio
 
 from pyprep.prep_pipeline import PrepPipeline
 
 from .conftest import make_random_mne_object
 
 
-@pytest.mark.usefixtures("raw", "montage")
-def test_prep_pipeline(raw, montage):
-    """Test prep pipeline."""
-    eeg_index = np.array(
-        [idx for idx, typ in enumerate(raw.get_channel_types()) if typ == "eeg"]
-    )
-    raw_copy = raw.copy()
-    ch_names = raw_copy.info["ch_names"]
-    ch_names_eeg = list(np.asarray(ch_names)[eeg_index])
-    sample_rate = raw_copy.info["sfreq"]
-    prep_params = {
-        "ref_chs": ch_names_eeg,
-        "reref_chs": ch_names_eeg,
-        "line_freqs": np.arange(60, sample_rate / 2, 60),
-    }
-    prep = PrepPipeline(raw_copy, prep_params, montage, random_state=42)
-    prep.fit()
-
-    EEG_raw = raw_copy.get_data(picks="eeg") * 1e6
-    EEG_raw_max = np.max(abs(EEG_raw), axis=None)
-    EEG_raw_matlab = sio.loadmat("./examples/matlab_results/EEG_raw.mat")
-    EEG_raw_matlab = EEG_raw_matlab["save_data"]
-    EEG_raw_diff = EEG_raw - EEG_raw_matlab
-    # EEG_raw_mse = (EEG_raw_diff / EEG_raw_max ** 2).mean(axis=None)
-
-    fig, axs = plt.subplots(5, 3, sharex="all")
-    plt.setp(fig, facecolor=[1, 1, 1])
-    fig.suptitle("Python versus Matlab PREP results", fontsize=16)
-
-    im = axs[0, 0].imshow(
-        EEG_raw / EEG_raw_max,
-        aspect="auto",
-        extent=[0, (EEG_raw.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[0, 0].set_title("Python", fontsize=14)
-    axs[0, 1].imshow(
-        EEG_raw_matlab / EEG_raw_max,
-        aspect="auto",
-        extent=[0, (EEG_raw_matlab.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[0, 1].set_title("Matlab", fontsize=14)
-    axs[0, 2].imshow(
-        EEG_raw_diff / EEG_raw_max,
-        aspect="auto",
-        extent=[0, (EEG_raw_diff.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[0, 2].set_title("Difference", fontsize=14)
-    # axs[0, 0].set_title('Original EEG', loc='left', fontsize=14)
-    # axs[0, 0].set_ylabel('Channel Number', fontsize=14)
-    cb = fig.colorbar(im, ax=axs, fraction=0.05, pad=0.04)
-    cb.set_label("\u03bcVolt", fontsize=14)
-
-    EEG_new_matlab = sio.loadmat("./examples/matlab_results/EEGNew.mat")
-    EEG_new_matlab = EEG_new_matlab["save_data"]
-    EEG_new = prep.EEG_new
-    EEG_new_max = np.max(abs(EEG_new), axis=None)
-    EEG_new_diff = EEG_new - EEG_new_matlab
-    # EEG_new_mse = ((EEG_new_diff / EEG_new_max) ** 2).mean(axis=None)
-    axs[1, 0].imshow(
-        EEG_new / EEG_new_max,
-        aspect="auto",
-        extent=[0, (EEG_new.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[1, 1].imshow(
-        EEG_new_matlab / EEG_new_max,
-        aspect="auto",
-        extent=[0, (EEG_new_matlab.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[1, 2].imshow(
-        EEG_new_diff / EEG_new_max,
-        aspect="auto",
-        extent=[0, (EEG_new_diff.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    # axs[1, 0].set_title('High pass filter', loc='left', fontsize=14)
-    # axs[1, 0].set_ylabel('Channel Number', fontsize=14)
-
-    EEG_clean_matlab = sio.loadmat("./examples/matlab_results/EEG.mat")
-    EEG_clean_matlab = EEG_clean_matlab["save_data"]
-    EEG_clean = prep.EEG
-    EEG_max = np.max(abs(EEG_clean), axis=None)
-    EEG_diff = EEG_clean - EEG_clean_matlab
-    # EEG_mse = ((EEG_diff / EEG_max) ** 2).mean(axis=None)
-    axs[2, 0].imshow(
-        EEG_clean / EEG_max,
-        aspect="auto",
-        extent=[0, (EEG_clean.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[2, 1].imshow(
-        EEG_clean_matlab / EEG_max,
-        aspect="auto",
-        extent=[0, (EEG_clean_matlab.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[2, 2].imshow(
-        EEG_diff / EEG_max,
-        aspect="auto",
-        extent=[0, (EEG_diff.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    # axs[2, 0].set_title('Line-noise removal', loc='left', fontsize=14)
-    axs[2, 0].set_ylabel("Channel Number", fontsize=14)
-
-    EEG = prep.EEG_before_interpolation
-    EEG_max = np.max(abs(EEG), axis=None)
-    EEG_ref_mat = sio.loadmat("./examples/matlab_results/EEGref.mat")
-    EEG_ref_matlab = EEG_ref_mat["save_EEG"]
-    # reference_matlab = EEG_ref_mat["save_reference"]
-    EEG_ref_diff = EEG - EEG_ref_matlab
-    # EEG_ref_mse = ((EEG_ref_diff / EEG_max) ** 2).mean(axis=None)
-    # reference_signal = prep.reference_before_interpolation
-    # reference_max = np.max(abs(reference_signal), axis=None)
-    # reference_diff = reference_signal - reference_matlab
-    # reference_mse = ((reference_diff / reference_max) ** 2).mean(axis=None)
-    axs[3, 0].imshow(
-        EEG / EEG_max,
-        aspect="auto",
-        extent=[0, (EEG.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[3, 1].imshow(
-        EEG_ref_matlab / EEG_max,
-        aspect="auto",
-        extent=[0, (EEG_ref_matlab.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[3, 2].imshow(
-        EEG_ref_diff / EEG_max,
-        aspect="auto",
-        extent=[0, (EEG_ref_diff.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    # axs[3, 0].set_title('Referencing', loc='left', fontsize=14)
-    # axs[3, 0].set_ylabel('Channel Number', fontsize=14)
-
-    EEG_final = prep.raw.get_data() * 1e6
-    EEG_final_max = np.max(abs(EEG_final), axis=None)
-    EEG_final_matlab = sio.loadmat("./examples/matlab_results/EEGinterp.mat")
-    EEG_final_matlab = EEG_final_matlab["save_data"]
-    EEG_final_diff = EEG_final - EEG_final_matlab
-    # EEG_final_mse = ((EEG_final_diff / EEG_final_max) ** 2).mean(axis=None)
-    axs[4, 0].imshow(
-        EEG_final / EEG_final_max,
-        aspect="auto",
-        extent=[0, (EEG_final.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[4, 1].imshow(
-        EEG_final_matlab / EEG_final_max,
-        aspect="auto",
-        extent=[0, (EEG_final_matlab.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    axs[4, 2].imshow(
-        EEG_final_diff / EEG_final_max,
-        aspect="auto",
-        extent=[0, (EEG_final_diff.shape[1] / sample_rate), 63, 0],
-        vmin=-1,
-        vmax=1,
-        cmap=plt.get_cmap("RdBu"),
-    )
-    # axs[4, 0].set_title('Interpolation', loc='left', fontsize=14)
-    # axs[4, 0].set_ylabel('Channel Number', fontsize=14)
-    axs[4, 1].set_xlabel("Time(s)", fontsize=14)
-
-
 @pytest.mark.usefixtures("raw", "montage")
 def test_prep_pipeline_non_eeg(raw, montage):
     """Test prep pipeline with non eeg channels."""