def grid3D(self, z_min, z_max, drift_corrected=False):
z_scale = float(self.z_bins) / (z_max - z_min)
image = numpy.zeros(self.im_shape_3D, dtype=numpy.int32)
for locs in self.locsInFrameRangeIterator(self.fmin, self.fmax,
["x", "y", "z"]):
# Create z value filter.
#
# We filter here rather than just relying on gridC.grid3D as application
# of z drift correction could move out of z range peaks into the acceptable
# range.
#
mask = (locs["z"] > z_min) & (locs["z"] < z_max)
if (numpy.count_nonzero(mask) == 0):
continue
# Remove localizations that are out of range.
locs["x"] = locs["x"][mask]
locs["y"] = locs["y"][mask]
locs["z"] = locs["z"][mask]
# Apply drift correction if requested.
if drift_corrected:
locs["x"] += self.dx
locs["y"] += self.dy
locs["z"] += self.dz
# Add to image.
i_x = numpy.floor(locs["x"] * self.scale).astype(numpy.int32)
i_y = numpy.floor(locs["y"] * self.scale).astype(numpy.int32)
i_z = numpy.floor(
(locs["z"] - z_min) * z_scale).astype(numpy.int32)
gridC.grid3D(i_x, i_y, i_z, image)
return image
def grid3D(self, z_min, z_max, drift_corrected = False):
z_scale = float(self.z_bins)/(z_max - z_min)
image = numpy.zeros(self.im_shape_3D, dtype = numpy.int32)
for locs in self.locsInFrameRangeIterator(self.fmin, self.fmax, ["x", "y", "z"]):
# Create z value filter.
#
# We filter here rather than just relying on gridC.grid3D as application
# of z drift correction could move out of z range peaks into the acceptable
# range.
#
mask = (locs["z"] > z_min) & (locs["z"] < z_max)
if (numpy.count_nonzero(mask) == 0):
continue
# Remove localizations that are out of range.
locs["x"] = locs["x"][mask]
locs["y"] = locs["y"][mask]
locs["z"] = locs["z"][mask]
# Apply drift correction if requested.
if drift_corrected:
locs["x"] += self.dx
locs["y"] += self.dy
locs["z"] += self.dz
# Add to image.
i_x = numpy.floor(locs["x"]*self.scale).astype(numpy.int32)
i_y = numpy.floor(locs["y"]*self.scale).astype(numpy.int32)
i_z = numpy.floor((locs["z"] - z_min)*z_scale).astype(numpy.int32)
gridC.grid3D(i_x, i_y, i_z, image)
return image
def gridTracks3D(self, z_min, z_max, dx = 0.0, dy = 0.0, verbose = False):
z_scale = float(self.z_bins)/(z_max - z_min)
image = numpy.zeros(self.im_shape_3D, dtype = numpy.int32)
for locs in self.tracksIterator(fields = ["x", "y", "z"]):
if verbose:
sys.stdout.write(".")
sys.stdout.flush()
# Add to image.
f_x = locs["x"] + dx
f_y = locs["y"] + dy
f_z = (locs["z"] - z_min)*z_scale
i_x = numpy.floor(f_x*self.scale).astype(numpy.int32)
i_y = numpy.floor(f_y*self.scale).astype(numpy.int32)
i_z = numpy.floor(f_z.astype(numpy.int32))
gridC.grid3D(i_x, i_y, i_z, image)
if verbose:
sys.stdout.write("\n")
return image
def i3To3DGrid(self, z_bins, fmin = 0, fmax = 500000, zmin = -1000.0, zmax = 1000.0, uncorrected = False, verbose = True):
if uncorrected:
[x, y, z] = [self.i3data['x'],
self.i3data['y'],
self.i3data['z']]
else:
[x, y, z] = [self.i3data['xc'],
self.i3data['yc'],
self.i3data['zc']]
cat = self.i3data['c']
f = self.i3data['fr']
[image_x, image_y] = self.im_size
xy_scale = int(self.scale)
z_bins = int(z_bins)
z_range = zmax - zmin
max_max = 0.0
max_counts = []
image_data = []
for channel in self.channels:
mask = (cat == channel) & (f >= fmin) & (f < fmax) & (z > zmin) & (z < zmax)
i_x = numpy.floor(x[mask] * xy_scale).astype(int)
i_y = numpy.floor(y[mask] * xy_scale).astype(int)
i_z = numpy.floor((z[mask] - zmin) * float(z_bins)/z_range).astype(int)
if (i_x.shape[0] > 0):
channel_data = grid_c.grid3D(i_x, i_y, i_z, (image_x*xy_scale, image_y*xy_scale, z_bins))
else:
channel_data = numpy.zeros((image_x*xy_scale, image_y*xy_scale, z_bins))
image_data.append(channel_data.astype(numpy.float32))
max_count = numpy.max(channel_data)
if max_count > max_max:
max_max = max_count
max_counts.append(max_count)
return [image_data, self.channels, max_counts, max_max]
def i3To3DGrid(self, z_bins, fmin = 0, fmax = 500000, zmin = -1000.0, zmax = 1000.0, uncorrected = False, verbose = True):
if uncorrected:
[x, y, z] = [self.i3data['x'],
self.i3data['y'],
self.i3data['z']]
else:
[x, y, z] = [self.i3data['xc'],
self.i3data['yc'],
self.i3data['zc']]
cat = self.i3data['c']
f = self.i3data['fr']
[image_x, image_y] = self.im_size
xy_scale = int(self.scale)
z_bins = int(z_bins)
z_range = zmax - zmin
max_max = 0.0
max_counts = []
image_data = []
for channel in self.channels:
mask = (cat == channel) & (f >= fmin) & (f < fmax) & (z > zmin) & (z < zmax)
i_x = numpy.floor(x[mask] * xy_scale).astype(int)
i_y = numpy.floor(y[mask] * xy_scale).astype(int)
i_z = numpy.floor((z[mask] - zmin) * float(z_bins)/z_range).astype(int)
if (i_x.shape[0] > 0):
channel_data = grid_c.grid3D(i_x, i_y, i_z, (image_x*xy_scale, image_y*xy_scale, z_bins))
else:
channel_data = numpy.zeros((image_x*xy_scale, image_y*xy_scale, z_bins))
image_data.append(channel_data.astype(numpy.float32))
max_count = numpy.max(channel_data)
if max_count > max_max:
max_max = max_count
max_counts.append(max_count)
return [image_data, self.channels, max_counts, max_max]