Commit 10eab075 authored by Andrei Roibu's avatar Andrei Roibu
Browse files

commented out calls to matplotlib.plt to prevent cluster errors

parent 76c6a42a
...@@ -9,7 +9,6 @@ setup( ...@@ -9,7 +9,6 @@ setup(
maintainer_email='andrei-claudiu.roibu@dtc.ox.ac.uk', maintainer_email='andrei-claudiu.roibu@dtc.ox.ac.uk',
install_requires=[ install_requires=[
'pip', 'pip',
'matplotlib',
'numpy', 'numpy',
'pandas', 'pandas',
'torch==1.4', 'torch==1.4',
......
...@@ -17,7 +17,6 @@ Usage: ...@@ -17,7 +17,6 @@ Usage:
import numpy as np import numpy as np
from fsl.data.image import Image from fsl.data.image import Image
from fsl.utils.image.resample import resampleToPixdims from fsl.utils.image.resample import resampleToPixdims
import matplotlib.pyplot as plt
from preprocessor import directory_reader, regression_weight_calculator from preprocessor import directory_reader, regression_weight_calculator
from tempfile import TemporaryFile from tempfile import TemporaryFile
from datetime import datetime from datetime import datetime
......
...@@ -21,7 +21,6 @@ import torch ...@@ -21,7 +21,6 @@ import torch
import logging import logging
import utils.data_utils as data_utils import utils.data_utils as data_utils
from utils.common_utils import create_folder from utils.common_utils import create_folder
import matplotlib.pyplot as plt
import pandas as pd import pandas as pd
from fsl.data.image import Image from fsl.data.image import Image
from fsl.utils.image.roi import roi from fsl.utils.image.roi import roi
...@@ -511,39 +510,3 @@ def _pearson_correlation(volume, target): ...@@ -511,39 +510,3 @@ def _pearson_correlation(volume, target):
np.sum(np.power(np.subtract(volume, volume.mean()), 2)), np.sum(np.power(np.subtract(target, target.mean()), 2)))) np.sum(np.power(np.subtract(volume, volume.mean()), 2)), np.sum(np.power(np.subtract(target, target.mean()), 2))))
return r return r
def _generate_correlation_matrix(correlation_matrix, title, prediction_output_path, normalize=False):
"""Visual correlation matrix generator
This function generates a visual representation of the correlation matrix
Args:
correaltion_matrix (np.array): Array containing the correlation matrix
title (str): Title of the correlation matrix figure (also the experiment name)
normalize (bool): Flag indicating if the values of the correlation matrix should be normalized
prediction_output_path (str): Output prediction path
"""
# THIS FUNCTION NEEDS TO BE VERIFIED!
if normalize:
correlation_matrix = correlation_matrix.astype(
'float') / correlation_matrix.sum(axis=1)[:, np.newaxis]
plt.imshow(correlation_matrix, interpolation='nearest', cmap=plt.cm.Blues)
plt.title(title)
plt.colorbar()
tick_marks = np.arange(len(correlation_matrix))
plt.xticks(tick_marks, correlation_matrix)
plt.yticks(tick_marks, correlation_matrix)
threshold = correlation_matrix.max() / 2.0
for i, j in itertools.product(range(correlation_matrix.shape[0]), range(correlation_matrix.shape[1])):
plt.text(j, i, format(correlation_matrix[i, j], '.4f'), horizontalalignment='center',
color="white" if correlation_matrix[i, j] > threshold else "black")
plt.tight_layout()
plt.ylabel('Predicted')
plt.xlabel('Targets')
plt.savefig(prediction_output_path + '/' + title + '.png')
...@@ -13,8 +13,6 @@ Usage: ...@@ -13,8 +13,6 @@ Usage:
""" """
import os import os
import matplotlib
import matplotlib.pyplot as plt
import shutil import shutil
import logging import logging
import numpy as np import numpy as np
...@@ -24,11 +22,8 @@ import torch ...@@ -24,11 +22,8 @@ import torch
# More here: https://tensorboardx.readthedocs.io/en/latest/tensorboard.html # More here: https://tensorboardx.readthedocs.io/en/latest/tensorboard.html
from tensorboardX import SummaryWriter from tensorboardX import SummaryWriter
import utils.data_evaluation_utils as evaluation import utils.data_evaluation_utils as evaluation
plt.axis('scaled')
class LogWriter(): class LogWriter():
...@@ -46,7 +41,7 @@ class LogWriter(): ...@@ -46,7 +41,7 @@ class LogWriter():
confusion_matrix_cmap (class): Colour Map to be used for the Conusion Matrix confusion_matrix_cmap (class): Colour Map to be used for the Conusion Matrix
""" """
def __init__(self, number_of_classes, logs_directory, experiment_name, use_last_checkpoint=False, labels=None, confusion_matrix_cmap=plt.cm.Blues): def __init__(self, number_of_classes, logs_directory, experiment_name, use_last_checkpoint=False, labels=None):
self.number_of_classes = number_of_classes self.number_of_classes = number_of_classes
training_logs_directory = os.path.join( training_logs_directory = os.path.join(
...@@ -66,8 +61,6 @@ class LogWriter(): ...@@ -66,8 +61,6 @@ class LogWriter():
'validation': SummaryWriter(logdir=validation_logs_directory) 'validation': SummaryWriter(logdir=validation_logs_directory)
} }
self.confusion_matrix_color_map = confusion_matrix_cmap
self.current_iteration = 1 self.current_iteration = 1
self.labels = ['rsfMRI'] self.labels = ['rsfMRI']
......
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