Merge pull request #3 from CINPLA/mask_unvisited

Mask unvisited

setup.py

@@ -21,7 +21,7 @@
 }
 
 setup(
-    name="spatialmaps",
+    name="spatial_maps",
     install_requires=install_requires,
     tests_require=install_requires,
     extras_require=extras_require,

spatialmaps/fields.py → spatial_maps/fields.py

@@ -8,11 +8,15 @@ def find_peaks(image):
     """
     Returns peaks sorted by distance from center of image.
     """
+    image = image.copy()
+    image[~np.isfinite(image)] = 0
     image_max = filters.maximum_filter(image, 3)
     is_maxima = (image == image_max)
     labels, num_objects = ndimage.label(is_maxima)
     indices = np.arange(1, num_objects+1)
     peaks = ndimage.maximum_position(image, labels=labels, index=indices)
+    # if len(peaks) == 0:
+    #     return None
     peaks = np.array(peaks)
     center = np.array(image.shape) / 2
     distances = np.linalg.norm(peaks - center, axis=1)

spatialmaps/gridcells.py → spatial_maps/gridcells.py

@@ -1,6 +1,6 @@
 import numpy as np
-from spatialmaps.tools import autocorrelation, fftcorrelate2d, masked_corrcoef2d
-from spatialmaps.fields import find_peaks
+from spatial_maps.tools import autocorrelation, fftcorrelate2d, masked_corrcoef2d
+from spatial_maps.fields import find_peaks
 
 
 def separate_fields_from_distance(rate_map):
@@ -108,7 +108,8 @@ def gridness(rate_map, return_mask=False):
     out : gridness
     '''
     import numpy.ma as ma
-
+    rate_map = rate_map.copy()
+    rate_map[~np.isfinite(rate_map)] = 0
     acorr = autocorrelation(rate_map, mode='full', normalize=True)
 
     acorr_maxima = find_peaks(acorr)

spatialmaps/maps.py → spatial_maps/maps.py

@@ -28,23 +28,23 @@ def _adjust_bin_size(box_size, bin_size=None, bin_count=None):
 
 def smooth_map(rate_map, bin_size, smoothing):
     std_dev_pixels = smoothing / bin_size
-    rate_map = rate_map.copy()  # do not modify the original!
-    rate_map[np.isnan(rate_map)] = 0.
     kernel = Gaussian2DKernel(std_dev_pixels[0], std_dev_pixels[1])
     return convolve_fft(rate_map, kernel)
 
 
 def _occupancy_map(x, y, t, xbins, ybins):
     t_ = np.append(t, t[-1] + np.median(np.diff(t)))
     time_in_bin = np.diff(t_)
-    values, _, _ = np.histogram2d(y, x, bins=[xbins, ybins], weights=time_in_bin)
+    values, _, _ = np.histogram2d(
+        y, x, bins=[xbins, ybins], weights=time_in_bin)
     return values
 
 
 def _spike_map(x, y, t, spike_times, xbins, ybins):
     t_ = np.append(t, t[-1] + np.median(np.diff(t)))
     spikes_in_bin, _ = np.histogram(spike_times, t_)
-    values, _, _ = np.histogram2d(y, x, bins=[xbins, ybins], weights=spikes_in_bin)
+    values, _, _ = np.histogram2d(
+        y, x, bins=[xbins, ybins], weights=spikes_in_bin)
     return values
 
 
@@ -56,6 +56,7 @@ def __init__(self, x, y, t, spike_times, box_size, bin_size, bin_count=None):
 
         self.spike_pos = _spike_map(x, y, t, spike_times, xbins, ybins)
         self.time_pos = _occupancy_map(x, y, t, xbins, ybins)
+        assert all(self.spike_pos[self.time_pos == 0] == 0)
 
         self.bin_size = bin_size
         self.box_size = box_size
@@ -72,5 +73,12 @@ def occupancy_map(self, smoothing):
 
         return smooth_map(self.time_pos, self.bin_size, smoothing)
 
-    def rate_map(self, smoothing):
-        return self.spike_map(smoothing) / self.occupancy_map(smoothing)
+    def rate_map(self, smoothing, mask_zero_occupancy=False):
+        spike_map = self.spike_map(smoothing)
+        occupancy_map = self.occupancy_map(smoothing)
+        if mask_zero_occupancy:
+            # to avoid infinity (x/0) we set zero occupancy to nan
+            # this can be handy when analyzing low occupancy maps
+            occupancy_map[self.time_pos == 0] = np.nan
+        rate_map = spike_map / occupancy_map
+        return rate_map

spatialmaps/tests/test_fields.py → spatial_maps/tests/test_fields.py

@@ -2,7 +2,7 @@
 import pytest
 import quantities as pq
 from tools import make_test_grid_rate_map, make_test_border_map
-from spatialmaps.fields import (
+from spatial_maps.fields import (
     separate_fields_from_laplace, find_peaks, calculate_field_centers,
     border_score)
 

spatialmaps/tests/test_gridcells.py → spatial_maps/tests/test_gridcells.py

@@ -1,9 +1,9 @@
 import numpy as np
 import pytest
-from spatialmaps import SpatialMap
+from spatial_maps import SpatialMap
 import quantities as pq
 from tools import make_test_grid_rate_map, make_test_spike_map
-from spatialmaps.gridcells import (
+from spatial_maps.gridcells import (
     gridness, spacing_and_orientation, separate_fields_from_distance)
 
 

spatialmaps/tests/test_maps.py → spatial_maps/tests/test_maps.py

@@ -1,6 +1,6 @@
 import numpy as np
 import pytest
-from spatialmaps.maps import SpatialMap
+from spatial_maps.maps import SpatialMap
 import quantities as pq
 from tools import make_test_grid_rate_map, make_test_spike_map
 

spatialmaps/tests/test_speed.py → spatial_maps/tests/test_speed.py

@@ -3,7 +3,7 @@
 import quantities as pq
 import neo
 from tools import random_walk
-from spatialmaps.speed import speed_correlation
+from spatial_maps.speed import speed_correlation
 # TODO need a better test, where we can set the corr beforehand
 
 def test_speed_random():

spatialmaps/tests/tools.py → spatial_maps/tests/tools.py

@@ -1,4 +1,4 @@
-from spatialmaps.tools import gaussian2D
+from spatial_maps.tools import gaussian2D
 import quantities as pq
 import numpy as np