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pretty printing of gradchecks
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3f01cbdbcc
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1 changed files with 31 additions and 12 deletions
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@ -308,9 +308,7 @@ class model(parameterised):
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numerical_gradient = (f1-f2)/(2*dx)
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ratio = (f1-f2)/(2*np.dot(dx,gradient))
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if verbose:
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#print "gradient = ",gradient
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#print "numerical gradient = ",numerical_gradient
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print " Gradient ratio = ", ratio, '\n'
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print "Gradient ratio = ", ratio, '\n'
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sys.stdout.flush()
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if (np.abs(1.-ratio)<tolerance) and not np.isnan(ratio):
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@ -319,10 +317,24 @@ class model(parameterised):
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else:
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if verbose:
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print "Global check failed. Testing individual gradients\n"
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try:
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names = self.extract_param_names()
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except NotImplementedError:
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names = ['Variable %i'%i for i in range(len(x))]
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try:
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names = self.extract_param_names()
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except NotImplementedError:
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names = ['Variable %i'%i for i in range(len(x))]
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# Prepare for pretty-printing
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header = ['Name', 'Ratio', 'Difference', 'Analytical', 'Numerical']
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max_names = max([len(names[i]) for i in range(len(names))] + [len(header[0])])
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float_len = 10
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cols = [max_names]
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cols.extend([max(float_len, len(header[i])) for i in range(1, len(header))])
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cols = np.array(cols) + 5
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header_string = ["{h:^{col}}".format(h = header[i], col = cols[i]) for i in range(len(cols))]
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header_string = map(lambda x: '|'.join(x), [header_string])
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separator = '-'*len(header_string[0])
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print '\n'.join([header_string[0], separator])
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for i in range(len(x)):
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xx = x.copy()
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xx[i] += step
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@ -338,13 +350,20 @@ class model(parameterised):
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numerical_gradient = (f1-f2)/(2*step)
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ratio = (f1-f2)/(2*step*gradient)
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difference = np.abs((f1-f2)/2/step - gradient)
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if verbose:
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if (np.abs(ratio-1)<tolerance):
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formatted_name = "\033[92m {0:10s} \033[0m".format(names[i])
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formatted_name = "\033[92m {0} \033[0m".format(names[i])
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else:
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formatted_name = "\033[91m {0:10s} \033[0m".format(names[i])
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print formatted_name + " ratio: {0:15f} difference: {1:15f} analytical: {2:15f} numerical: {3:15f}\n".format(float(ratio), float(difference), gradient, float(numerical_gradient)),
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formatted_name = "\033[91m {0} \033[0m".format(names[i])
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r = '%.6f' % float(ratio)
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d = '%.6f' % float(difference)
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g = '%.6f' % gradient
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ng = '%.6f' % float(numerical_gradient)
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grad_string = "{0:^{c0}}|{1:^{c1}}|{2:^{c2}}|{3:^{c3}}|{4:^{c4}}".format(formatted_name,r,d,g, ng, c0 = cols[0]+9, c1 = cols[1], c2 = cols[2], c3 = cols[3], c4 = cols[4])
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print grad_string
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print ''
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return False
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return True
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