Changeset 455 for trunk/src/analysis.py

Timestamp:

08/24/10 18:28:25 (21 months ago)

Author:

mpereira

Message:

removed dependency of signals/analogs.py on analysis. added support for SpikeTrain objects to analysis.crosscorrelate()

Files:

• trunk/src/analysis.py (modified) (4 diffs)

trunk/src/analysis.py

@@ -16 +16 @@
 
 ccf                       - fast cross correlation function based on fft
+crosscorrelate            - cross-correlation between two series of discrete
+                            events (e.g. spikes)
 simple_frequency_spectrum - Simple frequencxy spectrum
 arrays_almost_equal       - comparison of two arrays
+make_kernel               - creates kernel functions for convolution
 """
 
 import os, numpy
-from NeuroTools import check_dependency
+from NeuroTools import check_dependency, signals
 
 def arrays_almost_equal(a, b, threshold):
@@ -96 +99 @@
      
     Inputs:
-        sua1      - array of event times. Can be either a column/row vector.
-        sua2      - array of event times. Can be either a column/row vector.
+        sua1      - array of event times. Can be either a column/row vector or a
+                    member of the SpikeTrain class.
+        sua2      - array of event times. Can be either a column/row vector or a
+                    member of the SpikeTrain class.
                     If sua2 == sua1 the result is the
                     autocorrelogram.
@@ -134 +139 @@
     Examples:
         >> crosscorrelate(numpy_array1, numpy_array2)
-        >> crosscorrelate(spike_train1.spike_times, spike_train2.spike_times)
-        >> crosscorrelate(spike_train1.spike_times, spike_train2.spike_times,
-                          lag = 150.0)
-        >> crosscorrelate(spike_train1.spike_times, spike_train2.spike_times,
-                          display=True, kwargs={'bins':100})
+        >> crosscorrelate(spike_train1, spike_train2)
+        >> crosscorrelate(spike_train1, spike_train2, lag = 150.0)
+        >> crosscorrelate(spike_train1, spike_train2, display=True,
+                          kwargs={'bins':100})
             
     See also:
@@ -149 +153 @@
     sua = []
     for x in (sua1, sua2):
-        if x.ndim == 1:
+        if isinstance(x, signals.SpikeTrain):
+            sua.append(x.spike_times)
+        elif x.ndim == 1:
             sua.append(x)
         elif x.ndim == 2 and (x.shape[0] == 1 or x.shape[1] == 1):