Fixing FilterNet behavior for frame_rate != 1000.0

bmtk/simulator/filternet/lgnmodel/cursor.py

@@ -76,6 +76,8 @@ def evaluate(self, t_min=None, t_max=None, downsample=1):
 
         t_range = convert_tmin_tmax_framerate_to_trange(t_min, t_max, self.movie.frame_rate)[::int(downsample)]
         y_vals = np.array([self(t) for t in t_range])
+        # normalize by the frame rate
+        y_vals = y_vals * 1000.0 / self.movie.frame_rate
 
         return t_range, y_vals  
 
@@ -246,6 +248,8 @@ def evaluate(self, threshold=0):
         sig_tmp = np.zeros(len(full_temporal_kernel) + len(convolution_answer_sep_spatial) - 1)
         sig_tmp[len(full_temporal_kernel)-1:] = convolution_answer_sep_spatial
         convolution_answer_sep = spsig.convolve(sig_tmp, full_temporal_kernel[::-1], mode='valid')
+        # normalize by the frame rate
+        convolution_answer_sep = convolution_answer_sep * 1000.0 / self.movie.frame_rate
         t = np.arange(len(convolution_answer_sep))/self.movie.frame_rate
 
         return t, convolution_answer_sep

bmtk/simulator/filternet/lgnmodel/movie.py

@@ -271,7 +271,7 @@ def create_movie(self, t_min=0, t_max=1, gray_screen_dur=0, cpd=0.05, temporal_f
         :return: Movie object of grating with desired parameters
         """
         assert contrast <= 1, "Contrast must be <= 1"
-        assert contrast > 0, "Contrast must be > 0"
+        assert contrast >= 0, "Contrast must be >= 0"
 
         if degrees_per_pixel is None:  # default behavior when not specified
             degrees_per_pixel = 1.0 / (float(cpd) * 10)  # To make sure no aliasing occurs

bmtk/tests/simulator/filternet/lgnmodel/test_units.py

@@ -10,9 +10,13 @@
 from bmtk.simulator.filternet.lgnmodel.lgnmodel1 import LGNModel
 from bmtk.simulator.filternet.lgnmodel import movie
 
+# FilterNet now correctly normalize the rate other than 1000 Hz.
+# The tests below were made before the change, so we correctionso on the
+# firing rates.
+norm_factor = 1000.0 / 24.0
 
 def test_onunit():
-    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7)
+    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7, frame_rate=24.0)
     mv = ffm.full(t_max=2.0)
 
     spatial_filter = GaussianSpatialFilter(translate=(120.0, 60.0), sigma=(0.615, 0.615), origin=(0.0, 0.0))
@@ -29,11 +33,11 @@ def test_onunit():
     rates = np.array(results[0][1], dtype=np.float64)
 
     assert(np.allclose(times, [0.0, 0.41666, 0.83333, 1.250, 1.6666], atol=1.0e-4))
-    assert(np.allclose(rates, [1.05, 0.8635, 1.05, 1.05, 1.05], atol=1.0e-3))
+    assert(np.allclose(rates / norm_factor, [1.05, 0.8635, 1.05, 1.05, 1.05], atol=1.0e-3))
 
 
 def test_offunit():
-    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7)
+    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7, frame_rate=24.0)
     mv = ffm.full(t_max=2.0)
 
     spatial_filter = GaussianSpatialFilter(translate=(120.0, 60.0), sigma=(0.615, 0.615), origin=(0.0, 0.0))
@@ -50,11 +54,11 @@ def test_offunit():
     rates = np.array(results[0][1], dtype=np.float64)
 
     assert(np.allclose(times, [0.0, 0.41666, 0.83333, 1.250, 1.6666], atol=1.0e-4))
-    assert(np.allclose(rates, [1.05, 1.2364, 1.05, 1.05, 1.05], atol=1.0e-3))
+    assert(np.allclose(rates / norm_factor, [1.05, 1.2364, 1.05, 1.05, 1.05], atol=1.0e-3))
 
 
 def test_lgnonoffcell():
-    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7)
+    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7, frame_rate=24.0)
     mv = ffm.full(t_max=2.0)
 
     temporal_filter = TemporalFilterCosineBump(weights=[3.441, -2.115], kpeaks=[8.269, 19.991], delays=[0.0, 0.0])
@@ -74,11 +78,11 @@ def test_lgnonoffcell():
     rates = np.array(results[0][1], dtype=np.float64)
 
     assert(np.allclose(times, [0.0, 0.41666, 0.83333, 1.250, 1.6666], atol=1.0e-4))
-    assert(np.allclose(rates, [0.0, 3.7286, 0.0, 0.0, 0.0], atol=1.0e-3))
+    assert(np.allclose(rates / norm_factor, [0.0, 3.7286, 0.0, 0.0, 0.0], atol=1.0e-3))
 
 
 def test_twosubfieldlinearcell():
-    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7)
+    ffm = movie.FullFieldFlashMovie(range(120), range(240), 0.3, 0.7, frame_rate=24.0)
     mv = ffm.full(t_max=2.0)
 
     spatial_filter = GaussianSpatialFilter(translate=(120.0, 60.0), sigma=(0.615, 0.615), origin=(0.0, 0.0))
@@ -107,7 +111,10 @@ def test_twosubfieldlinearcell():
     rates = np.array(results[0][1], dtype=np.float64)
 
     assert(np.allclose(times, [0.0, 0.41666, 0.83333, 1.250, 1.6666], atol=1.0e-4))
-    assert(np.allclose(rates, [4.0, 3.26931, 3.885, 4.0, 4.0], atol=1.0e-3))
+    # for this example, the offset (2.0) of the transfer function breaks the
+    # compatibility. It makes sense to update the values.
+    # assert(np.allclose(rates, [4.0, 3.26931, 3.885, 4.0, 4.0], atol=1.0e-3))
+    assert(np.allclose(rates, [4.0, 18.929, 11.894, 4.0, 4.0], atol=1.0e-3))
 
 
 if __name__ == '__main__':

bmtk/tests/simulator/filternet/test_default_setters.py

@@ -55,6 +55,10 @@ def __contains__(self, item):
 
 np.set_printoptions(precision=4)
 
+# FilterNet now correctly normalize the rate other than 1000 Hz.
+# The tests below were made before the change, so we correctionso on the
+# firing rates.
+norm_factor = 1000.0 / 24.0
 
 @pytest.mark.parametrize("cell_type,expected_val", [
     ('tON_TF8', [2.6, 2.5502, 2.7221, 2.7718, 2.6497]),
@@ -77,7 +81,7 @@ def test_onunit(cell_type, expected_val):
     rates = np.array(results[0][1], dtype=np.float64)
 
     assert(np.allclose(times, [0.0, 0.2083, 0.4167, 0.6250, 0.8333], atol=1.0e-3))
-    assert(np.allclose(rates, expected_val, atol=1.0e-3))
+    assert(np.allclose(rates / norm_factor, expected_val, atol=1.0e-3))
 
 
 @pytest.mark.parametrize("cell_type,expected_val", [
@@ -105,12 +109,15 @@ def test_offunit(cell_type, expected_val):
     rates = np.array(results[0][1], dtype=np.float64)
 
     assert(np.allclose(times, [0.0, 0.2083, 0.4167, 0.6250, 0.8333], atol=1.0e-3))
-    assert(np.allclose(rates, expected_val, atol=1.0e-3))
+    assert(np.allclose(rates / norm_factor, expected_val, atol=1.0e-3))
 
 
 @pytest.mark.parametrize("cell_type,expected_val", [
     # ('sONsOFF_001', [4.0, 3.5654, 2.2956, 2.7437, 4.4480])
-    ('sONsOFF_001', [4.0, 3.0136, 3.335, 4.3349, 4.9999])  # updated value after OS bug fix. (issue, #339)
+    # ('sONsOFF_001', [4.0, 3.0136, 3.335, 4.3349, 4.9999])  # updated value after OS bug fix. (issue, #339)
+    # Again, due to the offset in the transfer function, the expected values
+    # won't nicely convert, so updating the values.
+    ('sONsOFF_001', [4.0, 20.1642, 0, 45.4373, 61.2649])  # updated value after OS bug fix. (issue, #339)
 ])
 def test_sONsOFF(cell_type, expected_val):
     gm = movie.GratingMovie(row_size=120, col_size=240, frame_rate=24.0)
@@ -130,7 +137,9 @@ def test_sONsOFF(cell_type, expected_val):
 
 @pytest.mark.parametrize("cell_type,expected_val", [
     # ('sONsOFF_001', [4.0, 3.5654, 2.2957, 2.7437, 4.4481])
-    ('sONsOFF_001', [4.0, 3.0136, 3.335, 4.3349, 4.9999])  # updated value after OS bug fix. (issue, #339)
+    # ('sONsOFF_001', [4.0, 3.0136, 3.335, 4.3349, 4.9999])  # updated value after OS bug fix. (issue, #339)
+    ('sONsOFF_001', [4.0, 20.1642, 0, 45.4373, 61.2649])  # updated value after OS bug fix. (issue, #339)
+
 ])
 def test_sONtOFF(cell_type, expected_val):
     gm = movie.GratingMovie(row_size=120, col_size=240, frame_rate=24.0)