Exemplo n.º 1
0
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)
Exemplo n.º 2
0
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
Exemplo n.º 3
0
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