def _compare(a, b):
"""Compare two python objects."""
global last_keys
skip_types = ['whitener', 'proj', 'reginv', 'noisenorm', 'nchan',
'command_line', 'working_dir', 'mri_file', 'mri_id']
try:
if isinstance(a, (dict, Info)):
assert_true(isinstance(b, (dict, Info)))
for k, v in six.iteritems(a):
if k not in b and k not in skip_types:
raise ValueError('First one had one second one didn\'t:\n'
'%s not in %s' % (k, b.keys()))
if k not in skip_types:
last_keys.pop()
last_keys = [k] + last_keys
_compare(v, b[k])
for k, v in six.iteritems(b):
if k not in a and k not in skip_types:
raise ValueError('Second one had one first one didn\'t:\n'
'%s not in %s' % (k, a.keys()))
elif isinstance(a, list):
assert_true(len(a) == len(b))
for i, j in zip(a, b):
_compare(i, j)
elif isinstance(a, sparse.csr.csr_matrix):
assert_array_almost_equal(a.data, b.data)
assert_equal(a.indices, b.indices)
assert_equal(a.indptr, b.indptr)
elif isinstance(a, np.ndarray):
assert_array_almost_equal(a, b)
else:
assert_equal(a, b)
except Exception:
print(last_keys)
raise
def _compare(a, b):
"""Compare two python objects."""
global last_keys
skip_types = ['whitener', 'proj', 'reginv', 'noisenorm', 'nchan',
'command_line', 'working_dir', 'mri_file', 'mri_id']
try:
if isinstance(a, (dict, Info)):
assert (isinstance(b, (dict, Info)))
for k, v in six.iteritems(a):
if k not in b and k not in skip_types:
raise ValueError('First one had one second one didn\'t:\n'
'%s not in %s' % (k, b.keys()))
if k not in skip_types:
last_keys.pop()
last_keys = [k] + last_keys
_compare(v, b[k])
for k, v in six.iteritems(b):
if k not in a and k not in skip_types:
raise ValueError('Second one had one first one didn\'t:\n'
'%s not in %s' % (k, a.keys()))
elif isinstance(a, list):
assert (len(a) == len(b))
for i, j in zip(a, b):
_compare(i, j)
elif isinstance(a, sparse.csr.csr_matrix):
assert_array_almost_equal(a.data, b.data)
assert_equal(a.indices, b.indices)
assert_equal(a.indptr, b.indptr)
elif isinstance(a, np.ndarray):
assert_array_almost_equal(a, b)
else:
assert_equal(a, b)
except Exception:
print(last_keys)
raise
def _pprint(params, offset=0, printer=repr):
"""Pretty print the dictionary 'params' (copied from sklearn)
Parameters
----------
params : dict
The dictionary to pretty print
offset : int
The offset in characters to add at the begin of each line.
printer : callable
The function to convert entries to strings, typically
the builtin str or repr
Returns
-------
lines : str
The pretty print of the dictionary as a string.
"""
# Do a multi-line justified repr:
options = np.get_printoptions()
np.set_printoptions(precision=5, threshold=64, edgeitems=2)
params_list = list()
this_line_length = offset
line_sep = ',\n' + (1 + offset // 2) * ' '
for i, (k, v) in enumerate(sorted(six.iteritems(params))):
if type(v) is float:
# use str for representing floating point numbers
# this way we get consistent representation across
# architectures and versions.
this_repr = '%s=%s' % (k, str(v))
else:
# use repr of the rest
this_repr = '%s=%s' % (k, printer(v))
if len(this_repr) > 500:
this_repr = this_repr[:300] + '...' + this_repr[-100:]
if i > 0:
if (this_line_length + len(this_repr) >= 75 or '\n' in this_repr):
params_list.append(line_sep)
this_line_length = len(line_sep)
else:
params_list.append(', ')
this_line_length += 2
params_list.append(this_repr)
this_line_length += len(this_repr)
np.set_printoptions(**options)
lines = ''.join(params_list)
# Strip trailing space to avoid nightmare in doctests
lines = '\n'.join(l.rstrip(' ') for l in lines.split('\n'))
return lines
