def test_read_empty_array_via_path():
res = {'a': np.array([[], []])}
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn, path='a')
assert_array_equal(res, [[], []])
assert(np.shape(res) == (2, 0))
def test_store_and_load_quantities_array():
data = {'times': np.array([1, 2, 3]) * pq.ms, 'positions':
np.array([1, 2, 3]) * pq.cm}
h5w.save(fn, data, overwrite_dataset=True)
# loading the whole data
res = h5w.load(fn)
assert(res['times'].dimensionality == data['times'].dimensionality)
def test_write_empty_array():
res = {'a': [], 'b': np.array([])}
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
assert_array_equal(res['a'], [])
assert_array_equal(res['b'], [])
def test_load_lazy_simple():
res = _construct_simpledata()
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn, lazy=True)
for key, obj in res.items():
assert(obj is None)
def test_old_store_and_load_simpledata():
res = _construct_simpledata()
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
for key, val in zip(simpledata_str, simpledata_val):
assert(res[key] == val)
def test_write_nested_empty_array():
res = {'a': [[], []], 'b': np.array([[], []])}
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
assert_array_equal(res['a'], [[], []])
assert(np.shape(res['a']) == (2, 0))
assert_array_equal(res['b'], [[], []])
assert(np.shape(res['b']) == (2, 0))
def test_store_and_load_numpy_datatypes():
res = {}
res['float64'] = np.float64(f0)
res['int64'] = np.int64(i0)
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
assert(isinstance(res['float64'], np.float64))
assert(isinstance(res['int64'], np.int64))
def test_store_and_test_key_types():
data = {'a': 1, (1, 2): {4: 2.}, 4.: 3.}
h5w.save(fn, data, write_mode='w')
res = h5w.load(fn)
keys = ['a', (1, 2), 4.]
for k in keys:
assert(k in res)
assert(4 in res[(1, 2)])
def test_load_lazy_nested():
res = {'a': 1, 'test1': {'b': 2}, 'test2': {
'test3': {'c': np.array([1, 2, 3])}}}
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn, lazy=True)
assert(res['a'] is None)
assert(res['test1']['b'] is None)
assert(res['test2']['test3']['c'] is None)
def test_store_and_load_arraydata():
res = {}
for key, val in zip(arraydata_str, arraydata_val):
res[key] = val
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
for key, val in zip(arraydata_str, arraydata_val):
assert_array_equal(res[key], val)
def test_store_and_load_dictdata():
res = {}
for key, val in zip(dictdata_str, dictdata_val):
res[key] = val
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
for dkey, dval in zip(dictdata_str, dictdata_val):
for key, val in dval.items():
assert(res[dkey][key] == val)
def test_store_and_load_tupledata():
res = {}
for key, val in zip(tupledata_str, tupledata_val):
res[key] = val
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
for key, val in zip(tupledata_str, tupledata_val):
assert(isinstance(res[key], tuple))
assert_array_equal(res[key], np.array(val))
def test_store_and_load_custom_array():
a = np.array([[1, 2, 3, 4], [6, 7]])
h5w.save(fn, {'a': a}, overwrite_dataset=True)
# loading the whole data
res = h5w.load(fn)
for i in range(len(a)):
assert_array_equal(a[i], res['a'][i])
# loading path directly
res = h5w.load(fn, path='a/')
for i in range(len(a)):
assert_array_equal(a[i], res[i])
def test_handle_nonexisting_path():
res = {}
stest = 'this is a test'
h5w.save(fn, res, write_mode='w')
try:
res = h5w.load(fn, path='test/')
raise Exception() # should not get until here
except KeyError:
res['test'] = stest
h5w.save(fn, res)
res.clear()
res = h5w.load(fn, path='test/')
assert(res == stest)
def test_store_and_rehash_h5py():
d0 = {
'a': 'asd',
'b': 0.12,
'c': [3, 4, 5],
'd': np.array([[3, 4, 5], [3, 4, 5]]),
'e': True
}
hash0 = dicthash.generate_hash_from_dict(d0)
h5w.save('store_and_rehash_h5py.h5', {'d0': d0}, 'w')
d1 = h5w.load('store_and_rehash_h5py.h5', 'd0')
hash1 = dicthash.generate_hash_from_dict(d1)
assert(hash0 == hash1)
def test_store_and_load_listdata():
res = {}
for key, val in zip(listdata_str, listdata_val):
res[key] = val
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
for key, val in zip(listdata_str, listdata_val):
if isinstance(val[0], list):
for ii in range(len(val)):
assert(isinstance(res[key][ii], list))
assert_array_equal(res[key][ii], val[ii])
else:
assert(isinstance(res[key], type(val)))
assert_array_equal(res[key], val)
def test_file_close_on_exception():
res = {'a': 5}
h5w.save(fn, res, write_mode='w')
try:
h5w.save(fn, res, write_mode='a', overwrite_dataset=False)
except KeyError:
pass
h5w.save(fn, res, write_mode='w')
def test_overwrite_dataset():
res = {'a': 5}
h5w.save(fn, res, write_mode='w')
res.clear()
res = {'a': 6}
with pytest.raises(KeyError):
h5w.save(fn, res, write_mode='a', overwrite_dataset=False)
res.clear()
res = h5w.load(fn)
assert(res['a'] == 5) # dataset should still contain old value
res.clear()
res = {'a': 6}
h5w.save(
fn, res, write_mode='a', overwrite_dataset=True)
res.clear()
res = h5w.load(fn)
assert(res['a'] == 6) # dataset should contain new value
def test_write_and_load_with_label():
res = _construct_simpledata()
h5w.save(fn, res, write_mode='w', path='test_label')
for key, val in zip(simpledata_str, simpledata_val):
assert(h5w.load(fn, 'test_label/' + key) == val)
def test_raises_error_for_dictlabel_and_path():
res = {}
with pytest.raises(ValueError):
h5w.save(fn, res, dict_label='test', path='test')
def test_raises_error_for_dictlabel_and_path():
res = {}
with pytest.raises(ValueError):
h5w.save(fn, res, dict_label='test', path='test')
def test_store_and_load_with_compression():
data = {'a': 1, 'test1': {'b': 2}, 'test2': {
'test3': {'c': np.array([1, 2, 3])}}}
h5w.save(fn, data, write_mode='w', compression='gzip')
h5w.load(fn)
def test_write_and_load_with_label():
res = _construct_simpledata()
h5w.save(fn, res, write_mode='w', path='test_label')
for key, val in zip(simpledata_str, simpledata_val):
assert (h5w.load(fn, 'test_label/' + key) == val)
for i, trans_func in enumerate(transfer_function):
for j, value in enumerate(trans_func):
transfer_function_with_synaptic_filter[i, j] = (
value / complex(1., circ.omegas[j] * tau_s))
eigenvalue_spectra_freqs, eigenvalue_spectra = (
circ.create_eigenvalue_spectra('MH'))
h5.save(filename, {
'params': circ.params,
'omegas': circ.omegas,
'firing_rates': circ.th_rates,
'transfer_function': transfer_function,
'transfer_function_with_synaptic_filter':
transfer_function_with_synaptic_filter,
'power_spectra': power_spectra,
'H': H,
'MH': MH,
'delay_dist': delay_dist,
'eigenvalue_spectra': eigenvalue_spectra,
'exemplary_frequency_idx': exemplary_frequency_idx
},
overwrite_dataset=True)
# frequencies = [64, 241, 263, 267, 284]
#
# for f in frequencies:
#
# Z = circ.get_sensitivity_measure(f)
#
# eigc = eigs[eig_index][np.argmin(abs(eigs[eig_index]-1))]
def test_store_none():
res = {'a1': None}
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
assert (res['a1'] is None)
def test_store_and_load_dataset_directly():
res = _construct_simpledata()
h5w.save(fn, res, write_mode='w')
for key, val in zip(simpledata_str, simpledata_val):
assert(h5w.load(fn, '/' + key) == val)
def test_store_and_load_dataset_directly():
res = _construct_simpledata()
h5w.save(fn, res, write_mode='w')
for key, val in zip(simpledata_str, simpledata_val):
assert (h5w.load(fn, '/' + key) == val)
def test_store_none():
res = {'a1': None}
h5w.save(fn, res, write_mode='w')
res.clear()
res = h5w.load(fn)
assert(res['a1'] is None)
# sigma = 1.5, $\nu = 10, 30$ Hz
mean_input_2 = np.array([18.94, 20.96])
sigma_2 = 1.5
frequencies = np.logspace(-1, 2.8, num=500)
zero_freq = 0.06
fig, (axA, axB) = plt.subplots(1, 2, figsize=(15, 10))
Phi1 = Phi1_mpmath_pcfu
results_dict = plot_PRE_Schuecker_Fig4(frequencies, sigma_1, mean_input_1,
sigma_2, mean_input_2)
# fig.savefig(fix_path + 'PRE_Schuecker_Fig4.pdf')
# save output
h5.save(fix_path + 'Schuecker2015_data.h5',
results_dict,
overwrite_dataset=True)
# Phi1 = Phi1_U_Kummer_fortran
# plot_PRE_Schuecker_Fig4(['red', 'orange'], lw=2, markersize_cross=4)
# axA.set_ylim(0, 15)
# axB.set_ylim(-50, 10)
# fig.savefig(fix_path + 'PRE_Schuecker_Fig4_Kummer_fortran.png')
#
# Phi1 = Phi1_U_Kummer_mpmath
# plot_PRE_Schuecker_Fig4(['blue', 'green'], lw=2, markersize_cross=4)
# axA.set_ylim(0, 15)
# axB.set_ylim(-50, 10)
# fig.savefig(fix_path + 'PRE_Schuecker_Fig4_Kummer_python.png')