def search_one_asymmetry(**kwargs):
sess = PINGDataSession() # username/password stored in an env variable for me.
sess.login()
return sess.regress_multistep(X='MRI_cort_area_ctx_supramarginal_AI',
Y='MRI_cort_area_ctx_rostralmiddlefrontal_AI',
**kwargs)
def search_all_pairwise(plot=True, **kwargs):
"""For each pair of variables, look for a significant regression slope."""
sess = PINGDataSession() # username/password stored in an env variable for me.
sess.login()
all_data = compute_all_asymmetries(prefix=['MRI_cort_area', 'MRI_cort_thick',
'MRI_subcort_vol', 'DTI_fiber_vol'])
results = []
keys = list(set(all_data.keys()) - set(('SubjID',)))
for ki in range(len(keys)):
key1 = keys[ki]
if skip_key(key1):
continue
for ii in range(ki + 1, len(keys)):
key2 = keys[ii]
if skip_key(key2) or skip_pairing(key1, key2):
continue
try:
result = sess.regress_multistep(key1, key2, plot=plot, **kwargs)
results.append(result)
except Exception as e:
print("Exception: %s" % str(e)) # force print
else:
if plot:
if result is None:
plt.close()
plt.close()
else:
plt.show()
def search_all_vs_one(key, plot=False, **kwargs):
"""For each pair of variables, look for a significant regression slope."""
sess = PINGDataSession() # username/password stored in an env variable for me.
sess.login()
all_data = compute_all_asymmetries(prefix=['MRI_cort_area', 'MRI_cort_thick',
'MRI_subcort_vol', 'DTI_fiber_vol'])
results = []
keys = list(set(all_data.keys()) - set(('SubjID',)))
for loop_key in keys:
results.append(sess.regress(key, loop_key, plot=plot, **kwargs))
if plot:
plt.show()
def search_all_vs_itself(covariates, plot=False, **kwargs):
"""For each pair of variables, look for a significant regression slope."""
def add_subplot(fh, *args):
return fh.add_subplot(*args) if plot else None
sess = PINGDataSession() # username/password stored in an env variable for me.
sess.login()
all_data = compute_all_asymmetries(prefix=['MRI_cort_area', 'MRI_cort_thick',
'MRI_subcort_vol', 'DTI_fiber_vol'])
results = []
keys = list(set(all_data.keys()) - set(('SubjID',)))
for X in keys:
# Get relevant covariates
try:
added_covariates = sess.AI2flds(X)
# Then regress on each side
fh2 = plt.figure(figsize=(18, 6)) if plot else None
sess.regress(X.replace('_AI', '_LH_PLUS_RH'),
X,
covariates=covariates, plot=add_subplot(fh2, 1, 3, 1),
**kwargs)
sess.regress(added_covariates[1],
X,
covariates=covariates + ['MRI_cort_area_ctx_total_LH_PLUS_RH'],
plot=add_subplot(fh2, 1, 3, 2),
**kwargs)
sess.regress('MRI_cort_area_ctx_total_LH_PLUS_RH',
X,
covariates=covariates,
plot=add_subplot(fh2, 1, 3, 3),
**kwargs)
except Exception as e:
print("Failed for %s (%s); moving on..." % (X, e))
if plot:
plt.show()
