Changeset 101 for trunk/examples/retina/benchmark_noise.py

Timestamp:

01/15/08 17:44:22 (4 years ago)

Author:

LaurentPerrinet

Message:

Finished examples of use of NeuroTools: retina / renamd SpikeTrain.mean_firing_rate to SpikeTrain.mean_rate for consistency with SpikeList.mean_rate / bugfix in spikes.py for the definition of a range in SpikeTrain.mean_rate

Files:

• trunk/examples/retina/benchmark_noise.py (modified) (4 diffs)

trunk/examples/retina/benchmark_noise.py

@@ -35 +35 @@
     noise_std, CRF = numpy.zeros(len(experiments)), numpy.zeros(len(experiments))
     for count, experiment in enumerate(experiments):
-        out_ON_DATA = benchmark.get('out',experiment)['out_ON_DATA']#.as_list_id_list_time()
+        out_ON_DATA = benchmark.get('out',experiment)['out_ON_DATA']
         noise_std[count] = benchmark.get('experiments')[experiment]['noise_std']
-        CRF[count] = out_ON_DATA.mean_rate()#[0]) / N / N / simtime * 1000.0
+        CRF[count] = out_ON_DATA.mean_rate()
 
 
@@ -48 +48 @@
     #pylab.axes([Lmargin, dmargin , 1.0 - Rmargin- Lmargin,1.0-umargin-dmargin]) # [left, bottom, width, height]
 
-    #pylab.subplot(111)
     idx_ = numpy.argsort(noise_std) # extract lines
     pylab.plot(noise_std[idx_],CRF[idx_],'go-', label='line 1', linewidth=2)
@@ -65 +64 @@
     # create a Retina Model object that contains a method to init, to run, ...
     ret = model.Retina(10)
-    ret.params['simtime'] = 4000*0.1
 
-    tag = '07-02-21'
-    tag = '07-03-08' # worked fine for D25
-    tag = '07-04-12'
-    tag = '07-04-08' # new with multiple seeds for CNS07
-    tag = '07-05-14' # no
-    tag = '07-05-16' # going OO
-    tag = 'test' # going OO
+    tag = 'test'
 
     name = 'results/' + tag + '_benchmark_noise'
 
     # create the list of experiments as all possibilities accross parameter vectors
-    run = benchmark.get_experiment_dict({'noise_std':numpy.linspace(.10,10.0,20), 'snr' : [ 0.0 ]})
+    span, N_exp = 5, 2*7+1
+    #range = 10.**(numpy.linspace(-span,span,N_exp))
+    range = numpy.linspace(1/span,span,N_exp)
+    run = benchmark.get_experiment_dict({'noise_std': ret.params['noise_std']* range, 'snr' : [ 0.0 ]})
 
     # create benchmark (or open it if it exists)
@@ -86 +81 @@
 
     show(B)
-
+    #B.reset_all() # erase experimental data