34, 36, 38, 41, 42, 46, 47, 49, 61, 62, 63, 69, 71, 74,
75, 79, 94, 95, 96, 97, 104, 105, 108, 115, 116, 120, 136, 137,
143]
areas_notdeg2 = np.zeros(NUM_AREAS)
areas_notdeg2[areas_notdeg2_idx] = 1
"""
PCA
"""
"""
R1
"""
data_t1, y_t1, subs_t1 = load_cort(measure = 'r1', cort='midgray')
dataset = 'reading'
data_matrix_reading, age_reading, subs_reading, _ = load_dataset(dataset,
cortical_parc='midgray',
measure_type = 'r1')
no_preterm =['s016', 's088', 's114', 's027', 's041',
's121', 's132', 's143', 's057',
's061', 's079', 's070', 's067',
's080', 's148', 's112', 's117', 's160', 's113', ]
#
# # ringing
# 's007','s034','s037','s045','s046','s064','s078','s082',
# 's083','s083_2','s092_dti30','s097_2','s101','s109','s111','s116',
# 's120','s123','s126','s126_2','s127','s129','s133','s137',
# 's141','s142','s144','s145','s146','s147','s153','s154',
143]
areas_notdeg2 = np.zeros(NUM_AREAS)
areas_notdeg2[areas_notdeg2_idx] = 1
"""
R2
"""
"""
PCA
"""
"""
R1
"""
data_t1, y_t1, subs_t1 = load_cort(measure = 'r1', cort='midgray')
dataset = 'stanford_ms_run1'
cortical_mat_ms1_t1, age_ms1, subs, _ = load_dataset(dataset, cortical_parc='midgray',
measure_type='r1_les')
dataset = 'stanford_ms_run2'
cortical_mat_ms2_t1, age_ms2, subs, _ = load_dataset(dataset, cortical_parc='midgray',
measure_type='r1_les')
NUM_REPS = 1000
X = data_t1.T
youngsters = np.where(y_t1<=AGE)
y_old = np.delete(y_t1, youngsters)
data_old = np.delete(X, youngsters, axis=0)
data_old = np.delete(data_old, np.where(areas_notdeg2==1), axis=1)
xp = np.linspace(8, 42, 35)
plt.plot(xp, p(xp))
plt.scatter(y1, data1[desc_num, :])
plt.scatter(y2, data2[desc_num, :])
plt.xlabel('Age of subject')
plt.ylabel('qMRI value')
plt.legend(['1st deg fit', 'Con', 'MS'])
plt.title((area_names[desc_num], str(desc_num)))
return
"""
CT
"""
data_t1, y_t1, subs_t1 = load_cort(measure='t1', cort='volume')
dataset = 'stanford_ms_run1'
cortical_mat_ms1, age_ms1, subs, _ = load_dataset(dataset,
cortical_parc='volume',
measure_type='t1')
dataset = 'stanford_ms_run2'
cortical_mat_ms2, age_ms2, subs, _ = load_dataset(dataset,
cortical_parc='volume',
measure_type='t1')
cortical_mat_ms1 = np.delete(cortical_mat_ms1, 74, axis=0)
cortical_mat_ms2 = np.delete(cortical_mat_ms2, 74, axis=0)
#data_t1 = np.delete(data_t1, areas_to_remove_idx, axis=0)
#cortical_mat_ms1 = np.delete(cortical_mat_ms1, areas_to_remove_idx, axis=0)
#cortical_mat_ms2 = np.delete(cortical_mat_ms2, areas_to_remove_idx, axis=0)
