Mercurial > hg > pycsalgos
changeset 23:c02eb33d2c54
Prepare to run whole script
| author | nikcleju |
|---|---|
| date | Wed, 09 Nov 2011 00:13:27 +0000 |
| parents | 2dd78e37b23a |
| children | c07440417bd8 |
| files | scripts/ABSapprox.py |
| diffstat | 1 files changed, 13 insertions(+), 13 deletions(-) [+] |
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--- a/scripts/ABSapprox.py Wed Nov 09 00:11:14 2011 +0000 +++ b/scripts/ABSapprox.py Wed Nov 09 00:13:27 2011 +0000 @@ -57,15 +57,15 @@ #Set up experiment parameters d = 50; sigma = 2.0 - #deltas = np.arange(0.05,0.95,0.05) - #rhos = np.arange(0.05,0.95,0.05) - deltas = np.array([0.05,0.95]) - rhos = np.array([0.05,0.95]) + deltas = np.arange(0.05,0.95,0.05) + rhos = np.arange(0.05,0.95,0.05) + #deltas = np.array([0.05,0.95]) + #rhos = np.array([0.05,0.95]) #deltas = np.array([0.05]) #rhos = np.array([0.05]) #delta = 0.8; #rho = 0.15; - numvects = 10; # Number of vectors to generate + numvects = 100; # Number of vectors to generate SNRdb = 20.; # This is norm(signal)/norm(noise), so power, not energy # Values for lambda #lambdas = [0 10.^linspace(-5, 4, 10)]; @@ -119,14 +119,14 @@ print "Oops, Type Error" raise # Show - for algotuple in algosN: - plt.figure() - plt.imshow(meanmatrix[algotuple[1]], cmap=cm.gray, interpolation='nearest') - for algotuple in algosL: - for ilbd in np.arange(lambdas.size): - plt.figure() - plt.imshow(meanmatrix[algotuple[1]][ilbd], cmap=cm.gray, interpolation='nearest') - plt.show() + # for algotuple in algosN: + # plt.figure() + # plt.imshow(meanmatrix[algotuple[1]], cmap=cm.gray, interpolation='nearest') + # for algotuple in algosL: + # for ilbd in np.arange(lambdas.size): + # plt.figure() + # plt.imshow(meanmatrix[algotuple[1]][ilbd], cmap=cm.gray, interpolation='nearest') + # plt.show() print "Finished." def genData(d,sigma,delta,rho,numvects,SNRdb):