additional whitening functions (#24)

examples/config_sample.yaml

@@ -31,12 +31,12 @@ deconvolution:
   lam: 20
 
 neural_network_detector:
-  filename: detectnet1.ckpt
+  filename: detect_nn1.ckpt
   threshold_spike: 0.5
 
 neural_network_triage:
-  filename: triagenet1.ckpt
-  threshold_collision: 0.75
+  filename: triage_nn1.ckpt
+  threshold_collision: 0.9
 
 neural_network_autoencoder:
-  filename: ae_31.ckpt
+  filename: ae_nn1.ckpt

examples/config_sample_complete.yaml

@@ -59,22 +59,22 @@ neural_network_detector:
   # must be a yaml file with the number and size of the filters, the file
   # should be named exactly as your model but with yaml extension
   # see yass/src/assets/models/ for an example
-  filename: detectnet1.ckpt
+  filename: detect_nn1.ckpt
   # Threshold for spike event detection
   threshold_spike: 0.5
 
 
 neural_network_triage:
   # same rules apply as in neural_network_detector.filename but the
   # yaml file should only contain size (not number)
-  filename: triagenet1.ckpt
+  filename: triage_nn1.ckpt
   # Threshold for clear/collision detection
-  threshold_collision: 0.75
+  threshold_collision: 0.9
 
 neural_network_autoencoder:
   # same rules apply as in neural_network_detector.filename but no
   # yaml file is needed
-  filename: ae_31.ckpt
+  filename: ae_nn1.ckpt
 
 
 ############

src/yass/assets/models/ae_nn1.yaml

@@ -0,0 +1 @@
+{n_input: 31, n_features: 3}

src/yass/assets/models/detectnet1.yaml → src/yass/assets/models/detect_nn1.yaml

@@ -2,3 +2,5 @@
 filters: [16, 8]
 # temporal filter size
 size: 31
+# number of neighboring channels
+n_neighbors: 7

src/yass/assets/models/triage_nn1.yaml

@@ -0,0 +1,6 @@
+# num. of filters in each layer
+filters: [16, 8]
+# temporal filter size
+size: 31
+# number of neighboring channels
+n_neighbors: 7

src/yass/augment/__init__.py

@@ -0,0 +1,2 @@
+from .make import make_training_data
+from .util import save_detect_network_params, save_triage_network_params, save_ae_network_params

src/yass/augment/util.py

@@ -28,7 +28,7 @@ def seq_rep(dumper, data):
 CustomYAMLDumper.add_representer(seq_data, map_rep)
 
 
-def save_detect_network_params(filters, size, output_path):
+def save_detect_network_params(filters, size, n_neighbors, output_path):
     """Generate yaml file with parameters for a detect network
 
     Parameters
@@ -38,28 +38,57 @@ def save_detect_network_params(filters, size, output_path):
 
     size: int
         Temporal filter size
+        
+    n_neighbors: int
+        Number of neighboring channels       
 
     output_path: str
         Where to save the file
     """
-    d = dict(filters=filters, size=size)
+    d = dict(filters=filters, size=size, n_neighbors=n_neighbors)
 
     with open(output_path, 'w') as f:
         yaml.dump(d, f, CustomYAMLDumper)
 
 
-def save_triage_network_params(size, output_path):
+def save_triage_network_params(filters, size, n_neighbors, output_path):
     """Generate yaml file with parameters for a triage network
 
     Parameters
     ----------
-    size: list
+    filters: list
         List filters size
 
+    size: int
+        Temporal filter size
+        
+    n_neighbors: int
+        Number of neighboring channels        
+        
+    output_path: str
+        Where to save the file
+    """
+    d = dict(filters=filters, size=size, n_neighbors=n_neighbors)
+
+    with open(output_path, 'w') as f:
+        yaml.dump(d, f, CustomYAMLDumper)
+
+def save_ae_network_params(n_input, n_features, output_path):
+    """Generate yaml file with parameters for a ae network
+
+    Parameters
+    ----------
+    n_input: int
+        Dimension of input 
+        
+    n_features: int
+        Number of features
+
     output_path: str
         Where to save the file
     """
-    d = dict(size=size)
+    d = dict(n_input=n_input, n_features=n_features)
 
     with open(output_path, 'w') as f:
         yaml.dump(d, f, CustomYAMLDumper)
+

src/yass/command_line.py

@@ -6,7 +6,6 @@
 
 import yass
 from yass.preprocessing import Preprocessor
-from yass.neuralnet import NeuralNetDetector
 from yass.mainprocess import Mainprocessor
 from yass.deconvolute import Deconvolution