def test_rate_map():
box_size = [1., 1.]
rate = 5.
bin_size = [.01, .01]
n_step=10**4
step_size=.1
sigma=0.1
spacing=0.3
smoothing = .03
rate_map_true, pos_fields, xbins, ybins = make_test_grid_rate_map(
sigma=sigma, spacing=spacing, amplitude=rate, box_size=box_size,
bin_size=bin_size)
x, y, t, spikes = make_test_spike_map(
pos_fields=pos_fields, box_size=box_size, rate=rate,
n_step=n_step, step_size=step_size, sigma=sigma)
smap = SpatialMap(
x, y, t, spikes, box_size=box_size, bin_size=bin_size)
rate_map = smap.rate_map(smoothing)
diff = rate_map_true - rate_map
X, Y = np.meshgrid(xbins, ybins)
samples = []
for p in pos_fields:
mask = np.sqrt((X - p[0])**2 + (Y - p[1])**2) < .1
samples.append(diff[mask])
peak_diff = np.abs(np.mean([s.min() for s in samples if s.size > 0]))
assert peak_diff < 0.5
def test_gridness():
box_size = np.array([1., 1.])
rate = 5.
bin_size = [.01, .01]
spacing_true = 0.3
rate_map, pos_fields, xbins, ybins = make_test_grid_rate_map(
sigma=0.05,
spacing=spacing_true,
amplitude=rate,
offset=0,
box_size=box_size,
bin_size=bin_size)
g = gridness(rate_map)
assert round(g, 1) == 1.3
def test_spacing_and_orientation_from_true_peaks():
box_size = np.array([1., 1.])
rate = 5.
bin_size = [.01, .01]
spacing_true = 0.3
rate_map, pos_fields, xbins, ybins = make_test_grid_rate_map(
sigma=0.05,
spacing=spacing_true,
amplitude=rate,
offset=0,
box_size=box_size,
bin_size=bin_size)
spacing, orientation = spacing_and_orientation(pos_fields, box_size)
assert spacing == spacing_true
assert round(orientation * 180 / np.pi) == 30
def test_separate_fields_by_distance():
box_size = [1., 1.]
rate = 1.
bin_size = [.01, .01]
rate_map, pos_true, xbins, ybins = make_test_grid_rate_map(
sigma=0.05,
spacing=0.3,
amplitude=rate,
offset=0,
box_size=box_size,
bin_size=bin_size)
peaks, radius = separate_fields_by_distance(rate_map)
bump_centers = np.array([xbins[peaks[:, 0]], ybins[peaks[:, 1]]])
# The position of a 2D bin is defined to be its center
for p in pos_true:
assert np.isclose(p, pos_true).prod(axis=1).any()
def test_separate_fields_by_laplace():
box_size = [1., 1.]
rate = 1.
bin_size = [.01, .01]
sigma = 0.05
spacing = 0.3
rate_map, pos_true, xbins, ybins = make_test_grid_rate_map(
sigma=sigma,
spacing=spacing,
amplitude=rate,
offset=0.1,
box_size=box_size,
bin_size=bin_size,
orientation=0.1)
labels = separate_fields_by_laplace(rate_map, threshold=0)
peaks = calculate_field_centers(rate_map, labels)
bump_centers = np.array([xbins[peaks[:, 0]], ybins[peaks[:, 1]]])
# The position of a 2D bin is defined to be its center
for p in pos_true:
assert np.isclose(p, pos_true).prod(axis=1).any()
def test_find_peaks():
box_size = np.array([1., 1.])
rate = 5.
bin_size = [.01, .01]
sigma = 0.05
spacing = 0.3
rate_map, pos_fields, xbins, ybins = make_test_grid_rate_map(
sigma=sigma,
spacing=spacing,
amplitude=rate,
offset=0,
box_size=box_size,
bin_size=bin_size,
repeat=0)
peaks = find_peaks(rate_map)
pos_peaks = np.array([xbins[peaks[:, 1]], ybins[peaks[:, 0]]]).T
print(pos_peaks)
assert all([
np.isclose(p, pos_peaks, rtol=1e-3).prod(axis=1).any()
for p in pos_fields
])
def test_spacing_and_orientation_from_autocorr():
box_size = np.array([1., 1.])
rate = 5.
bin_size = [.01, .01]
spacing_true = 0.3
orientation_true = .3
rate_map, pos_fields, xbins, ybins = make_test_grid_rate_map(
sigma=0.05,
spacing=spacing_true,
amplitude=rate,
offset=0,
box_size=box_size,
bin_size=bin_size,
orientation=orientation_true)
autocorrelogram = autocorrelation(rate_map)
peaks = find_peaks(autocorrelogram)
real_peaks = peaks * bin_size
autocorrelogram_box_size = box_size * autocorrelogram.shape[
0] / rate_map.shape[0]
spacing, orientation = spacing_and_orientation(real_peaks,
autocorrelogram_box_size)
assert round(spacing, 1) == spacing_true
assert round(orientation, 1) == orientation_true