Changeset 333

Timestamp:

11/13/08 14:20:47 (2 months ago)

Author:

LaurentPerrinet

Message:

little clean-up in the wiki:examples scripts to get near to real-world scripts

Files:

• trunk/examples/retina/benchmark_linear.py (modified) (4 diffs)
• trunk/examples/retina/benchmark_noise.py (modified) (2 diffs)
• trunk/examples/retina/benchmark_retina.py (modified) (3 diffs)
• trunk/examples/retina/make_all.py (deleted)
• trunk/examples/retina/results/fig-benchmark_linear.png (modified) (previous)
• trunk/examples/retina/results/fig-benchmark_noise.png (modified) (previous)
• trunk/examples/retina/test_parallel.py (deleted)

trunk/examples/retina/benchmark_linear.py

@@ -15 +15 @@
-
-import os, sys, numpy, pylab, shelve
-import progressbar # see http://projects.scipy.org/pipermail/scipy-dev/2008-January/008200.html
-from NeuroTools.parameters import *
-
-N, N_exp = 1000, 6
-t_smooth = 100. # width (in ms) of the integration window
-from retina import *
-retina = Retina(N)
-retina.params['amplitude'] = 1
-snr  = retina.params['snr']* numpy.linspace(0.1,2.0,N_exp)
-p =  ParameterSpace({'snr' : ParameterRange(list(snr))})
-
-
@@ -34 +24 @@
-    temporal_OFF = results['temporal_OFF']
-    lower_edges = results['lower_edges']
+    params = results['params']
+    #if (params == retina.params): raise('Parameters have changed')
-
-except:
+    N, N_exp = 1000, 6
+    t_smooth = 100. # width (in ms) of the integration window
+    from retina import *
+    retina = Retina(N)
+    retina.params['amplitude'] = numpy.ones(retina.params['amplitude'].shape)
+    snr  = retina.params['snr']* numpy.linspace(0.1,2.0,N_exp)
+    from NeuroTools.parameters import ParameterSpace
+    p = ParameterSpace({'snr' : ParameterRange(list(snr))})
-
-    # calculates the dimension of the parameter space
@@ -46 +46 @@
-    
-    temporal_ON, temporal_OFF = [],[]
-
+
-    pbar=progressbar.ProgressBar(widgets=[name, " ", progressbar.Percentage(), ' ',
-            progressbar.Bar(), ' ', progressbar.ETA()], maxval=N_exp)
@@ -65 +65 @@
-    results['temporal_ON'] = temporal_ON
-    results['temporal_OFF'] = temporal_OFF
+    results['params'] = params
-
-    pbar.finish()

trunk/examples/retina/benchmark_noise.py

@@ -19 +19 @@
-import os, sys, numpy, shelve
-
-from NeuroTools.parameters import *
-
-# this is not mandatory but just a "easy_install progressbar" away
-# else remove all corresponding lines in this code...
-import progressbar # see http://projects.scipy.org/pipermail/scipy-dev/2008-January/008200.html
-
-N, N_exp_noise = 1000, 22
-
-p =  ParameterSpace({'noise_std' : ParameterRange(list(10.**(numpy.linspace(-.50,1.,N_exp_noise))))})
-
-import retina as model
-retina = model.Retina(N) 
-retina.params['snr'] = 0 # no input
-
@@ -39 +27 @@
-    CRF = results['CRF']
-except:
-
+
+
+
+
+
+
+
+
+
+
+
+
+
-    # calculates the dimension of the parameter space
-    results_dim, results_label = p.parameter_space_dimension_labels()

trunk/examples/retina/benchmark_retina.py

@@ -25 +25 @@
-import os, sys, numpy, pylab, shelve, progressbar
-
-from NeuroTools.parameters import *
-
-N, N_snr, N_seeds = 1000, 5, 10
-from retina import *
-retina = Retina(N)
-
-t_smooth = 100. # ms.  integration time to show fiber activity
-
-p =  ParameterSpace({
-                'snr' : ParameterRange(list(numpy.linspace(0.1,2.0,N_snr))),
-                'kernelseed' : ParameterRange(list([retina.params['kernelseed'] + k for k in range(N_seeds)]))})
-
-
-name = sys.argv[0].split('.')[0] # name of the current script withpout the '.py' part
- MAKING THE SIMULATIONS 
+########## MAKING THE SIMULATIONS #####
-results = shelve.open('results/mat-' + name)
-try:
-    DATA = results['DATA']
-except:
+
+    from NeuroTools.parameters import *
+
+    N, N_snr, N_seeds = 1000, 5, 10
+    from retina import *
+    retina = Retina(N)
+
+    t_smooth = 100. # ms.  integration time to show fiber activity
+
+    p =  ParameterSpace({
+                    'snr' : ParameterRange(list(numpy.linspace(0.1,2.0,N_snr))),
+                    'kernelseed' : ParameterRange(list([retina.params['kernelseed'] + k for k in range(N_seeds)]))})
-
-    # calculates the dimension of the parameter space
@@ -67 +67 @@
-############## PRE-PROCESSING ###########################
-try:
-
+ the pre-processing stage
-    lower_edges = results['lower_edges']
-    temporal_ON = results['temporal_ON']
@@ -91 +91 @@
-    r2 = x**2 + y**2
-    r = numpy.sqrt(r2)
-
+[0]
-
-    # mean activity accross kernelseeds as a function of SNR