Python load_paradigm_from_csv_file Examples

Example #1

File: tmin_statistic.py Project: GaelVaroquaux/nipy

hfcut = 128

# write directory
write_dir = path.join(getcwd(), 'results')
if not path.exists(write_dir):
    mkdir(write_dir)

print('Computation will be performed in directory: %s' % write_dir)

########################################
# Design matrix
########################################

print('Loading design matrix...')

paradigm = load_paradigm_from_csv_file(paradigm_file)['0']

design_matrix = make_dmtx(frametimes, paradigm, hrf_model=hrf_model,
                          drift_model=drift_model, hfcut=hfcut)

#########################################
# Specify the contrasts
#########################################

# simplest ones
contrasts = {}
n_columns = len(design_matrix.names)
for i in range(paradigm.n_conditions):
    contrasts['%s' % design_matrix.names[i]] = np.eye(n_columns)[i]

# and more complex/ interesting ones

Example #2

File: plot_auditory_analysis.py Project: takhs91/python-cogstats

hfcut = 128

# write directory
write_dir = path.join(getcwd(), 'results')
if not path.exists(write_dir):
    mkdir(write_dir)

print('Computation will be performed in directory: %s' % write_dir)

########################################
# Design matrix
########################################

print('Loading design matrix...')

paradigm = load_paradigm_from_csv_file(paradigm_file)['0']

design_matrix = make_dmtx(frametimes,
                          paradigm,
                          hrf_model=hrf_model,
                          drift_model=drift_model,
                          hfcut=hfcut)

ax = design_matrix.show()
ax.set_position([.05, .25, .9, .65])
ax.set_title('Design matrix')

plt.savefig(path.join(write_dir, 'design_matrix.png'))

#########################################
# Specify the contrasts

Example #3

File: localizer_glm_ar.py Project: satra/nipy

hfcut = 128

# write directory
write_dir = path.join(getcwd(), 'results')
if not path.exists(write_dir):
    mkdir(write_dir)

print 'Computation will be performed in directory: %s' % write_dir

########################################
# Design matrix
########################################

print 'Loading design matrix...'

paradigm = load_paradigm_from_csv_file(paradigm_file).values()[0]

design_matrix = make_dmtx(frametimes, paradigm, hrf_model=hrf_model,
                          drift_model=drift_model, hfcut=hfcut)

ax = design_matrix.show()
ax.set_position([.05, .25, .9, .65])
ax.set_title('Design matrix')

plt.savefig(path.join(write_dir, 'design_matrix.png'))

#########################################
# Specify the contrasts
#########################################

# simplest ones

Example #4

File: localizer_glm_ar.py Project: ofenlab/nipy

hfcut = 128

# write directory
write_dir = path.join(getcwd(), 'results')
if not path.exists(write_dir):
    mkdir(write_dir)

print 'Computation will be performed in directory: %s' % write_dir

########################################
# Design matrix
########################################

print 'Loading design matrix...'

paradigm = load_paradigm_from_csv_file(paradigm_file).values()[0]

design_matrix = make_dmtx(frametimes,
                          paradigm,
                          hrf_model=hrf_model,
                          drift_model=drift_model,
                          hfcut=hfcut)

ax = design_matrix.show()
ax.set_position([.05, .25, .9, .65])
ax.set_title('Design matrix')

plt.savefig(path.join(write_dir, 'design_matrix.png'))
# design_matrix.write_csv(...)

########################################

Example #5

File: glm.py Project: Solvi/pyhrf

    # Paradigm

    # Fix bug in nipy/modalities/fmri/experimental_paradigm.py
    # -> amplitudes are not converted to floats
    # @@ -187,7 +187,7 @@ def load_paradigm_from_csv_file(path, session=None):
    #          if len(row) > 3:
    #              duration.append(float(row[3]))
    #          if len(row) > 4:
    # -            amplitude.append(row[4])
    # +            amplitude.append(float(row[4]))

if 0:
    paradigm = load_paradigm_from_csv_file(paradigm_csv_file,
                                           session=str(session))
    if paradigm is None:
        raise Exception('Failed to load paradigm data from %s (session=%d)' \
                            %(paradigm_csv_file, session))
    pyhrf.verbose(1, 'Loaded paradigm: condition=%s, nb events=%d'
                  %(str(list(set(paradigm.con_id))),paradigm.n_events))

    assert op.exists(mask_file)
    # # Functional mask
    # if not op.exists(mask_file):
    #     pyhrf.verbose(1, 'Mask file does not exist. Computing mask from '\
    #                       'BOLD data')
    #     compute_mask_files(data_path, mask_file, False, 0.4, 0.9)
    #     mask_array = compute_mask_files(bold_file, mask_file,
    #                                     False, 0.4, 0.9)

Example #6

File: plot_permutation.py Project: NanoResearch/python-cogstats

# Data and analysis parameters
#######################################

# timing
n_scans = 128
tr = 2.4
# paradigm
frametimes = np.linspace(0.5 * tr, (n_scans - .5) * tr, n_scans)

fmri_data = nibabel.load('s12069_swaloc1_corr.nii.gz')

########################################
# Design matrix
########################################

paradigm = load_paradigm_from_csv_file('localizer_paradigm.csv')['0']

design_matrix = make_dmtx(frametimes, paradigm,
                          hrf_model='canonical with derivative',
                          drift_model="cosine", hfcut=128)

#########################################
# Specify the contrasts
#########################################

# simplest ones
contrasts = {}
n_columns = len(design_matrix.names)
for i in range(paradigm.n_conditions):
    contrasts['%s' % design_matrix.names[2 * i]] = np.eye(n_columns)[2 * i]

Example #7

File: plot_localizer_analysis.py Project: mo-jay/python-cogstats

# timing
n_scans = 128
tr = 2.4
# paradigm
frametimes = np.linspace(0.5 * tr, (n_scans - 0.5) * tr, n_scans)

# write directory
write_dir = "results"
if not path.exists(write_dir):
    mkdir(write_dir)

########################################
# Design matrix
########################################

paradigm = load_paradigm_from_csv_file("localizer_paradigm.csv")["0"]

design_matrix = make_dmtx(frametimes, paradigm, hrf_model="canonical with derivative", drift_model="cosine", hfcut=128)

# Plot the design matrix
ax = design_matrix.show()
ax.set_position([0.05, 0.25, 0.9, 0.65])
ax.set_title("Design matrix")
plt.savefig(path.join(write_dir, "design_matrix.png"))

#########################################
# Specify the contrasts
#########################################

# simplest ones
contrasts = {}

Example #8

File: plot_permutation.py Project: sohairzaki/python-cogstats

# Data and analysis parameters
#######################################

# timing
n_scans = 128
tr = 2.4
# paradigm
frametimes = np.linspace(0.5 * tr, (n_scans - .5) * tr, n_scans)

fmri_data = nibabel.load('s12069_swaloc1_corr.nii.gz')

########################################
# Design matrix
########################################

paradigm = load_paradigm_from_csv_file('localizer_paradigm.csv')['0']

design_matrix = make_dmtx(frametimes,
                          paradigm,
                          hrf_model='canonical with derivative',
                          drift_model="cosine",
                          hfcut=128)

#########################################
# Specify the contrasts
#########################################

# simplest ones
contrasts = {}
n_columns = len(design_matrix.names)
for i in range(paradigm.n_conditions):