def compute_coverage(self, all_channels):
start = time.time()
cvol = np.zeros(self.ba.image.shape, dtype=np.float)
val, counts = np.unique(self.ba._lookup(all_channels), return_counts=True)
#cvol[np.unravel_index(val, cvol.shape)] = counts
cvol[np.unravel_index(val, cvol.shape)] = 1
DIST_FCN = np.array([100, 150]) / 1e6
dx = self.ba.bc.dx
template = np.arange(- np.max(DIST_FCN) - dx, np.max(DIST_FCN) + 2 * dx, dx) ** 2
kernel = sum(np.meshgrid(template, template, template))
kernel = 1 - fcn_cosine(DIST_FCN)(np.sqrt(kernel))
#
cvol = fftconvolve(cvol, kernel, mode='same')
end = time.time()
print(end-start)
self.cvol = cvol
self.cvol_flat = cvol.flatten()
return cvol
def test_dsp_cosine_func(self):
x = np.linspace(0, 40)
fcn = fcn_cosine(bounds=[20, 30])
y = fcn(x)
self.assertTrue(y[0] == 0 and y[-1] == 1 and np.all(np.diff(y) >= 0))
import numpy as np
from ibllib.dsp import fcn_cosine
import ibllib.atlas as atlas
from ibllib.pipes.histology import coverage
from oneibl.one import ONE
one = ONE()
ba = atlas.AllenAtlas()
# trajs = one.alyx.rest('trajectories', 'list', provenance='Ephys aligned histology track')
trajs = one.alyx.rest('trajectories', 'list', provenance='Micro-manipulator',
django='probe_insertion__session__project__name__icontains,'
'ibl_neuropixel_brainwide_01,'
'probe_insertion__session__qc__lt,40')
full_coverage = coverage(trajs)
fig, axs = plt.subplots(2, 2)
ax = ba.plot_hslice(-4000 * 1e-6, volume=full_coverage, ax=axs[0, 0])
ax.set_title("horizontal slice at dv=-4mm")
ax = ba.plot_sslice(ml_coordinate=-0.002, volume=full_coverage, ax=axs[0, 1])
ax.set_title("sagittal slice at ml=-2mm")
ax = ba.plot_cslice(ap_coordinate=-0.003, volume=full_coverage, ax=axs[1, 1])
ax.set_title("coronal slice at ap=-3mm")
axs[1, 0].plot(np.linspace(0, 200), 1 - fcn_cosine([100, 150])(np.linspace(0, 200)))
axs[1, 0].set_xlabel('distance from nearest active site (um)')
axs[1, 0].set_ylabel('weight')