def test_natural_movie_one_a(nm1a, nwb_a, analysis_a_new):
nm1a_new = NaturalMovie.from_analysis_file(BODS(nwb_a), analysis_a_new, si.NATURAL_MOVIE_ONE)
#assert np.allclose(nm1a.sweep_response, nm1a_new.sweep_response)
assert np.allclose(nm1a.binned_cells_sp, nm1a_new.binned_cells_sp, equal_nan=True)
assert np.allclose(nm1a.binned_cells_vis, nm1a_new.binned_cells_vis, equal_nan=True)
assert np.allclose(nm1a.binned_dx_sp, nm1a_new.binned_dx_sp, equal_nan=True)
assert np.allclose(nm1a.binned_dx_vis, nm1a_new.binned_dx_vis, equal_nan=True)
def lsn(nwb_c, analysis_c):
# in order to work around 2/3 unicode compatibility, separate files are specified for python 2 and 3
# we need to look up a different key depending on python version
key = si.LOCALLY_SPARSE_NOISE_4DEG if sys.version_info < (
3, ) else si.LOCALLY_SPARSE_NOISE
return LocallySparseNoise.from_analysis_file(BODS(nwb_c), analysis_c, key)
def test_natural_scenes(ns, nwb_b, analysis_b_new):
ns_new = NaturalScenes.from_analysis_file(BODS(nwb_b), analysis_b_new)
#assert np.allclose(ns.sweep_response, ns_new.sweep_response)
assert np.allclose(ns.mean_sweep_response, ns_new.mean_sweep_response, equal_nan=True)
assert np.allclose(ns.noise_correlation, ns_new.noise_correlation, equal_nan=True)
assert np.allclose(ns.signal_correlation, ns_new.signal_correlation, equal_nan=True)
assert np.allclose(ns.representational_similarity, ns_new.representational_similarity, equal_nan=True)
def test_static_gratings(sg, nwb_b, analysis_b_new):
sg_new = StaticGratings.from_analysis_file(BODS(nwb_b), analysis_b_new)
#assert np.allclose(sg.sweep_response, sg_new.sweep_response)
assert np.allclose(sg.mean_sweep_response, sg_new.mean_sweep_response, equal_nan=True)
assert np.allclose(sg.response, sg_new.response, equal_nan=True)
assert np.allclose(sg.noise_correlation, sg_new.noise_correlation, equal_nan=True)
assert np.allclose(sg.signal_correlation, sg_new.signal_correlation, equal_nan=True)
assert np.allclose(sg.representational_similarity, sg_new.representational_similarity, equal_nan=True)
def test_drifting_gratings(dg, nwb_a, analysis_a_new):
logging.debug("reading outputs")
dg_new = DriftingGratings.from_analysis_file(BODS(nwb_a), analysis_a_new)
#assert np.allclose(dg.sweep_response, dg_new.sweep_response)
assert np.allclose(dg.mean_sweep_response, dg_new.mean_sweep_response, equal_nan=True)
assert np.allclose(dg.response, dg_new.response, equal_nan=True)
assert np.allclose(dg.noise_correlation, dg_new.noise_correlation, equal_nan=True)
assert np.allclose(dg.signal_correlation, dg_new.signal_correlation, equal_nan=True)
assert np.allclose(dg.representational_similarity, dg_new.representational_similarity, equal_nan=True)
def test_locally_sparse_noise(lsn, nwb_c, analysis_c_new):
ds = BODS(nwb_c)
session_type = ds.get_metadata()['session_type']
logging.debug(session_type)
if session_type == si.THREE_SESSION_C:
lsn_new = LocallySparseNoise.from_analysis_file(ds, analysis_c_new, si.LOCALLY_SPARSE_NOISE)
elif session_type == si.THREE_SESSION_C2:
lsn_new = LocallySparseNoise.from_analysis_file(ds, analysis_c_new, si.LOCALLY_SPARSE_NOISE_4DEG)
#assert np.allclose(lsn.sweep_response, lsn_new.sweep_response)
assert np.allclose(lsn.mean_sweep_response, lsn_new.mean_sweep_response, equal_nan=True)
def analysis_c_new(nwb_c, tmpdir_factory):
save_path = str(tmpdir_factory.mktemp("session_c") / "session_c_new.h5")
logging.debug("running analysis c")
session_analysis = SessionAnalysis(nwb_c, save_path)
session_type = BODS(nwb_c).get_metadata()['session_type']
if session_type == si.THREE_SESSION_C2:
session_analysis.session_c2(plot_flag=False, save_flag=True)
elif session_type == si.THREE_SESSION_C:
session_analysis.session_c(plot_flag=False, save_flag=True)
logging.debug("done running analysis c")
logging.debug(save_path)
yield save_path
def analysis_c_new(nwb_c):
with tempfile.NamedTemporaryFile(delete=True) as tf:
save_path = tf.name
logging.debug("running analysis c")
session_analysis = SessionAnalysis(nwb_c, save_path)
session_type = BODS(nwb_c).get_metadata()['session_type']
if session_type == si.THREE_SESSION_C2:
session_analysis.session_c2(plot_flag=False, save_flag=True)
elif session_type == si.THREE_SESSION_C:
session_analysis.session_c(plot_flag=False, save_flag=True)
logging.debug("done running analysis c")
logging.debug(save_path)
yield save_path
if os.path.exists(save_path):
os.remove(save_path)
def nm2(nwb_c, analysis_c):
return NaturalMovie.from_analysis_file(BODS(nwb_c), analysis_c, si.NATURAL_MOVIE_TWO)
def ns(nwb_b, analysis_b):
return NaturalScenes.from_analysis_file(BODS(nwb_b), analysis_b)
def nm1b(nwb_b, analysis_b):
return NaturalMovie.from_analysis_file(BODS(nwb_b), analysis_b, si.NATURAL_MOVIE_ONE)
def sg(nwb_b, analysis_b):
return StaticGratings.from_analysis_file(BODS(nwb_b), analysis_b)
def nm3(nwb_a, analysis_a):
return NaturalMovie.from_analysis_file(BODS(nwb_a), analysis_a, si.NATURAL_MOVIE_THREE)
def dg(nwb_a, analysis_a):
return DriftingGratings.from_analysis_file(BODS(nwb_a), analysis_a)
def lsn(nwb_c, analysis_c):
return LocallySparseNoise.from_analysis_file(BODS(nwb_c), analysis_c,
si.LOCALLY_SPARSE_NOISE_8DEG)
