def report_func2(epi,realignment_parameters_file,output_file): import gc, os import pylab as plt import nibabel as nb from matplotlib.backends.backend_pdf import PdfPages from mriqc.volumes import plot_mosaic, plot_distrbution_of_values from mriqc.motion import plot_frame_displacement report = PdfPages(output_file) epi_nii = nb.load(epi) mean_epi = epi_nii.get_data().mean(axis=3) fig = plot_mosaic(mean_epi, title="Mean EPI node output", figsize=(8.3, 11.7)) report.savefig(fig, dpi=300) fig.clf() epi_std = epi_nii.get_data().std(axis=3) epi_tsnr = mean_epi/epi_std fig = plot_mosaic(epi_tsnr, title="tSNR node output", figsize=(8.3, 11.7)) report.savefig(fig, dpi=300) fig.clf() fig = plot_frame_displacement(realignment_parameters_file, figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() report.close() gc.collect() plt.close() return os.path.abspath(output_file)
def create_report(subject_id, tsnr_file, realignment_parameters_file, mean_epi_file, mask_file, reg_file, fssubjects_dir, similarity_distribution, mean_FD_distribution, tsnr_distributions, output_file): import gc import pylab as plt from matplotlib.backends.backend_pdf import PdfPages from mriqc.volumes import plot_mosaic, plot_distrbution_of_values from mriqc.correlation import plot_epi_T1_corregistration from mriqc.motion import plot_frame_displacement report = PdfPages(output_file) fig = plot_mosaic(mean_epi_file, title="Mean EPI", figsize=(8.3, 11.7)) report.savefig(fig, dpi=300) fig.clf() fig = plot_mosaic(mean_epi_file, "EPI mask", mask_file, figsize=(8.3, 11.7)) report.savefig(fig, dpi=600) fig.clf() fig = plot_mosaic(tsnr_file, title="tSNR", figsize=(8.3, 11.7)) report.savefig(fig, dpi=300) fig.clf() fig = plot_distrbution_of_values( tsnr_file, mask_file, "Subjects %s tSNR inside the mask" % subject_id, tsnr_distributions, "Distribution of median tSNR of all subjects", figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() fig = plot_epi_T1_corregistration(mean_epi_file, reg_file, fssubjects_dir, subject_id, similarity_distribution, figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() fig = plot_frame_displacement(realignment_parameters_file, mean_FD_distribution, figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() report.close() gc.collect() plt.close() return output_file
def create_report(subject_id, tsnr_file, realignment_parameters_file, mean_epi_file, mask_file, reg_file, fssubjects_dir, similarity_distribution, mean_FD_distribution, tsnr_distributions, output_file): import gc import pylab as plt from matplotlib.backends.backend_pdf import PdfPages from mriqc.volumes import plot_mosaic, plot_distrbution_of_values from mriqc.correlation import plot_epi_T1_corregistration from mriqc.motion import plot_frame_displacement report = PdfPages(output_file) fig = plot_mosaic(mean_epi_file, title="Mean EPI", figsize=(8.3, 11.7)) report.savefig(fig, dpi=300) fig.clf() fig = plot_mosaic(mean_epi_file, "EPI mask", mask_file, figsize=(8.3, 11.7)) report.savefig(fig, dpi=600) fig.clf() fig = plot_mosaic(tsnr_file, title="tSNR", figsize=(8.3, 11.7)) report.savefig(fig, dpi=300) fig.clf() fig = plot_distrbution_of_values(tsnr_file, mask_file, "Subjects %s tSNR inside the mask" % subject_id, tsnr_distributions, "Distribution of median tSNR of all subjects", figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() fig = plot_epi_T1_corregistration(mean_epi_file, reg_file, fssubjects_dir, subject_id, similarity_distribution, figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() fig = plot_frame_displacement(realignment_parameters_file, mean_FD_distribution, figsize=(8.3, 8.3)) report.savefig(fig, dpi=300) fig.clf() plt.close() report.close() gc.collect() plt.close() return output_file