def test_save_dicoms_realtime(tmp_path, dd=data_dict):
dd = dd.copy()
start_time = time.time()
dd['save_dicom'] = True
dd['save_realtime'] = True
# test when ROI files are not set
dd['ROI_A_file'] = None
dd['ROI_B_file'] = None
dd['template_path'] = None
dd['noise_dict_file'] = None
# Run the simulation
gen.generate_data(str(tmp_path), dd)
end_time = time.time()
# Check it took 2s per TR
assert (end_time - start_time) > 60, 'Realtime ran fast'
# Check correct file number
file_path = str(tmp_path / '*.dcm')
assert len(glob.glob(file_path)) == 30, "Wrong dicom file num"
def test_signal_size(tmp_path, dd=data_dict):
dd = dd.copy()
# Change it to only use ROI A
dd['different_ROIs'] = False
# Make the signal large
dd['scale_percentage'] = 100
# Run the simulation
gen.generate_data(str(tmp_path), dd)
# Load in the ROI masks
ROI_A = dd['ROI_A_file']
ROI_B = dd['ROI_B_file']
# Load in the data just simulated
ROI_A_mean = []
ROI_B_mean = []
for TR_counter in range(dd['numTRs']):
# Load the data
vol_name = 'rt_%03d.npy' % TR_counter
vol = np.load(tmp_path / vol_name)
# Mask the data
ROI_A_mean += [np.mean(vol[ROI_A == 1])]
ROI_B_mean += [np.mean(vol[ROI_B == 1])]
assert np.std(ROI_A_mean) > np.std(ROI_B_mean), 'Signal not scaling'
def test_save_dicoms_realtime(tmp_path, dd=data_dict):
dd['save_dicom'] = True
dd['save_realtime'] = True
start_time = time.time()
# Run the simulation
gen.generate_data(str(tmp_path), dd)
end_time = time.time()
# Check it took 2s per TR
assert (end_time - start_time) > 60, 'Realtime ran fast'
# Check correct file number
file_path = str(tmp_path / '*.dcm')
assert len(glob.glob(file_path)) == 30, "Wrong dicom file num"
def test_default(tmp_path, dd=data_dict):
# Run the simulation
gen.generate_data(str(tmp_path), dd)
# Check that there are 32 files where there should be (30 plus label and
# mask)
assert len(os.listdir(str(tmp_path))) == 32, "Incorrect file number"
# Check that the data is the right shape
input_template = dd['template_path']
input_shape = input_template.shape
output_vol = np.load(tmp_path / 'rt_000.npy')
output_shape = output_vol.shape
assert input_shape == output_shape, 'Output shape is incorrect'
# Check the labels have the correct count
labels = np.load(tmp_path / 'labels.npy')
assert np.sum(labels > 0) == 9, 'Incorrect number of events'
def test_multivariate(tmp_path, dd=data_dict):
dd['multivariate_pattern'] = True
dd['different_ROIs'] = False
# Make the signal large
dd['scale_percentage'] = 100
# Run the simulation
gen.generate_data(str(tmp_path), dd)
# Load in the ROI masks
ROI_A = dd['ROI_A_file']
ROI_B = dd['ROI_B_file']
# Test this volume
vol = np.load(str(tmp_path / 'rt_007.npy'))
ROI_A_std = np.std(vol[ROI_A == 1])
ROI_B_std = np.std(vol[ROI_B == 1])
assert ROI_A_std > ROI_B_std, 'Multivariate not making variable signal'
Authors: Cameron Ellis (Princeton) 2020
"""
import numpy as np
from brainiak.utils import fmrisim_real_time_generator as gen
import pytest
import os
import time
import glob
from pkg_resources import resource_stream
from typing import Dict
from nibabel.nifti1 import Nifti1Image
import gzip
# Test that it crashes without inputs
with pytest.raises(TypeError):
gen.generate_data() # type: ignore
data_dict = {} # type: Dict
vol = resource_stream(gen.__name__, "sim_parameters/ROI_A.nii.gz").read()
data_dict['ROI_A_file'] = Nifti1Image.from_bytes(
gzip.decompress(vol)).get_data()
vol = resource_stream(gen.__name__, "sim_parameters/ROI_B.nii.gz").read()
data_dict['ROI_B_file'] = Nifti1Image.from_bytes(
gzip.decompress(vol)).get_data()
vol = resource_stream(gen.__name__,
"sim_parameters/sub_template.nii.gz").read()
data_dict['template_path'] = Nifti1Image.from_bytes(
gzip.decompress(vol)).get_data()
noise_dict_file = resource_stream(gen.__name__,
"sim_parameters/sub_noise_dict.txt").read()
data_dict['noise_dict_file'] = noise_dict_file
if type(args.allowedDirs) is str:
args.allowedDirs = args.allowedDirs.split(',')
if type(args.allowedFileTypes) is str:
args.allowedFileTypes = args.allowedFileTypes.split(',')
addr, port = args.server.split(':')
# Check if the ssl certificate is valid for this server address
if checkSSLCertAltName(certFile, addr) is False:
# Addr not listed in sslCert, recreate ssl Cert
makeSSLCertFile(addr)
# if generate synthetic data
if args.synthetic_data:
# check if the dicoms are already created
if not os.path.exists("/tmp/synthetic_dicom/rt_199.dcm"):
datagen.generate_data("/tmp/synthetic_dicom", {'save_dicom': True})
print("Server: {}, interval {}".format(args.server, args.interval))
print("Allowed file types {}".format(args.allowedFileTypes))
print("Allowed directories {}".format(args.allowedDirs))
WsFileWatcher.runFileWatcher(args.server,
retryInterval=args.interval,
allowedDirs=args.allowedDirs,
allowedTypes=args.allowedFileTypes,
username=args.username,
password=args.password,
testMode=args.test)