diff options
Diffstat (limited to 'numpy/oldnumeric')
| -rw-r--r-- | numpy/oldnumeric/random_array.py | 16 | ||||
| -rw-r--r-- | numpy/oldnumeric/rng_stats.py | 4 |
2 files changed, 10 insertions, 10 deletions
diff --git a/numpy/oldnumeric/random_array.py b/numpy/oldnumeric/random_array.py index c5d163196..550af720c 100644 --- a/numpy/oldnumeric/random_array.py +++ b/numpy/oldnumeric/random_array.py @@ -166,7 +166,7 @@ def multinomial(trials, probs, shape=[]): trials is the number of trials in each multinomial distribution. probs is a one dimensional array. There are len(prob)+1 events. prob[i] is the probability of the i-th event, 0<=i<len(prob). - The probability of event len(prob) is 1.-Numeric.sum(prob). + The probability of event len(prob) is 1.-Numeric.sum(prob,axis=0). The first form returns a single 1-D array containing one multinomially distributed vector. @@ -188,14 +188,14 @@ def poisson(mean, shape=[]): def mean_var_test(x, type, mean, var, skew=[]): n = len(x) * 1.0 - x_mean = Numeric.sum(x)/n + x_mean = Numeric.sum(x,axis=0)/n x_minus_mean = x - x_mean - x_var = Numeric.sum(x_minus_mean*x_minus_mean)/(n-1.0) + x_var = Numeric.sum(x_minus_mean*x_minus_mean,axis=0)/(n-1.0) print "\nAverage of ", len(x), type print "(should be about ", mean, "):", x_mean print "Variance of those random numbers (should be about ", var, "):", x_var if skew != []: - x_skew = (Numeric.sum(x_minus_mean*x_minus_mean*x_minus_mean)/9998.)/x_var**(3./2.) + x_skew = (Numeric.sum(x_minus_mean*x_minus_mean*x_minus_mean,axis=0)/9998.)/x_var**(3./2.) print "Skewness of those random numbers (should be about ", skew, "):", x_skew def test(): @@ -205,12 +205,12 @@ def test(): if (obj2[1] - obj[1]).any(): raise SystemExit, "Failed seed test." print "First random number is", random() - print "Average of 10000 random numbers is", Numeric.sum(random(10000))/10000. + print "Average of 10000 random numbers is", Numeric.sum(random(10000),axis=0)/10000. x = random([10,1000]) if len(x.shape) != 2 or x.shape[0] != 10 or x.shape[1] != 1000: raise SystemExit, "random returned wrong shape" x.shape = (10000,) - print "Average of 100 by 100 random numbers is", Numeric.sum(x)/10000. + print "Average of 100 by 100 random numbers is", Numeric.sum(x,axis=0)/10000. y = uniform(0.5,0.6, (1000,10)) if len(y.shape) !=2 or y.shape[0] != 1000 or y.shape[1] != 10: raise SystemExit, "uniform returned wrong shape" @@ -239,7 +239,7 @@ def test(): print x if x.shape != (4,3,2): raise SystemExit, "multivariate_normal returned wrong shape" x = multivariate_normal(Numeric.array([-100,0,100]), Numeric.array([[3,2,1],[2,2,1],[1,1,1]]), 10000) - x_mean = Numeric.sum(x)/10000. + x_mean = Numeric.sum(x,axis=0)/10000. print "Average of 10000 multivariate normals with mean [-100,0,100]" print x_mean x_minus_mean = x - x_mean @@ -262,7 +262,7 @@ def test(): print "\nEach row is the result of 16 multinomial trials with probabilities [0.1, 0.5, 0.1 0.3]:" x = multinomial(16, [0.1, 0.5, 0.1], 8) print x - print "Mean = ", Numeric.sum(x)/8. + print "Mean = ", Numeric.sum(x,axis=0)/8. if __name__ == '__main__': test() diff --git a/numpy/oldnumeric/rng_stats.py b/numpy/oldnumeric/rng_stats.py index 60248247e..8c7fec433 100644 --- a/numpy/oldnumeric/rng_stats.py +++ b/numpy/oldnumeric/rng_stats.py @@ -9,7 +9,7 @@ def average(data): def variance(data): data = Numeric.array(data) - return Numeric.add.reduce((data-average(data))**2)/(len(data)-1) + return Numeric.add.reduce((data-average(data,axis=0))**2)/(len(data)-1) def standardDeviation(data): data = Numeric.array(data) @@ -25,7 +25,7 @@ def histogram(data, nbins, range = None): data = Numeric.repeat(data, Numeric.logical_and(Numeric.less_equal(data, max), Numeric.greater_equal(data, - min))) + min)),axis=0) bin_width = (max-min)/nbins data = Numeric.floor((data - min)/bin_width).astype(Numeric.Int) histo = Numeric.add.reduce(Numeric.equal( |