diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/matlib.py | 8 | ||||
| -rw-r--r-- | numpy/polynomial/polynomial.py | 2 | ||||
| -rw-r--r-- | numpy/random/_generator.pyx | 9 | ||||
| -rw-r--r-- | numpy/random/mtrand.pyx | 17 |
4 files changed, 23 insertions, 13 deletions
diff --git a/numpy/matlib.py b/numpy/matlib.py index bd6b63289..e929fd9b1 100644 --- a/numpy/matlib.py +++ b/numpy/matlib.py @@ -300,9 +300,10 @@ def randn(*args): Notes ----- - For random samples from :math:`N(\\mu, \\sigma^2)`, use: + For random samples from the normal distribution with mean ``mu`` and + standard deviation ``sigma``, use:: - ``sigma * np.matlib.randn(...) + mu`` + sigma * np.matlib.randn(...) + mu Examples -------- @@ -314,7 +315,8 @@ def randn(*args): matrix([[ 0.99734545, 0.2829785 , -1.50629471], [-0.57860025, 1.65143654, -2.42667924]]) - Two-by-four matrix of samples from :math:`N(3, 6.25)`: + Two-by-four matrix of samples from the normal distribution with + mean 3 and standard deviation 2.5: >>> 2.5 * np.matlib.randn((2, 4)) + 3 matrix([[1.92771843, 6.16484065, 0.83314899, 1.30278462], diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py index 8e2c6f002..d102f5a30 100644 --- a/numpy/polynomial/polynomial.py +++ b/numpy/polynomial/polynomial.py @@ -1339,7 +1339,7 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None): >>> np.random.seed(123) >>> from numpy.polynomial import polynomial as P >>> x = np.linspace(-1,1,51) # x "data": [-1, -0.96, ..., 0.96, 1] - >>> y = x**3 - x + np.random.randn(len(x)) # x^3 - x + N(0,1) "noise" + >>> y = x**3 - x + np.random.randn(len(x)) # x^3 - x + Gaussian noise >>> c, stats = P.polyfit(x,y,3,full=True) >>> np.random.seed(123) >>> c # c[0], c[2] should be approx. 0, c[1] approx. -1, c[3] approx. 1 diff --git a/numpy/random/_generator.pyx b/numpy/random/_generator.pyx index 0019c4bcd..8092c8e7a 100644 --- a/numpy/random/_generator.pyx +++ b/numpy/random/_generator.pyx @@ -1001,7 +1001,8 @@ cdef class Generator: Notes ----- - For random samples from :math:`N(\\mu, \\sigma^2)`, use one of:: + For random samples from the normal distribution with mean ``mu`` and + standard deviation ``sigma``, use one of:: mu + sigma * rng.standard_normal(size=...) rng.normal(mu, sigma, size=...) @@ -1022,7 +1023,8 @@ cdef class Generator: >>> s.shape (3, 4, 2) - Two-by-four array of samples from :math:`N(3, 6.25)`: + Two-by-four array of samples from the normal distribution with + mean 3 and standard deviation 2.5: >>> 3 + 2.5 * rng.standard_normal(size=(2, 4)) array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], # random @@ -1126,7 +1128,8 @@ cdef class Generator: ... linewidth=2, color='r') >>> plt.show() - Two-by-four array of samples from N(3, 6.25): + Two-by-four array of samples from the normal distribution with + mean 3 and standard deviation 2.5: >>> np.random.default_rng().normal(3, 2.5, size=(2, 4)) array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], # random diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx index 408d5a332..19d23f6a8 100644 --- a/numpy/random/mtrand.pyx +++ b/numpy/random/mtrand.pyx @@ -1224,16 +1224,18 @@ cdef class RandomState: Notes ----- - For random samples from :math:`N(\\mu, \\sigma^2)`, use: + For random samples from the normal distribution with mean ``mu`` and + standard deviation ``sigma``, use:: - ``sigma * np.random.randn(...) + mu`` + sigma * np.random.randn(...) + mu Examples -------- >>> np.random.randn() 2.1923875335537315 # random - Two-by-four array of samples from N(3, 6.25): + Two-by-four array of samples from the normal distribution with + mean 3 and standard deviation 2.5: >>> 3 + 2.5 * np.random.randn(2, 4) array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], # random @@ -1373,7 +1375,8 @@ cdef class RandomState: Notes ----- - For random samples from :math:`N(\\mu, \\sigma^2)`, use one of:: + For random samples from the normal distribution with mean ``mu`` and + standard deviation ``sigma``, use one of:: mu + sigma * np.random.standard_normal(size=...) np.random.normal(mu, sigma, size=...) @@ -1393,7 +1396,8 @@ cdef class RandomState: >>> s.shape (3, 4, 2) - Two-by-four array of samples from :math:`N(3, 6.25)`: + Two-by-four array of samples from the normal distribution with + mean 3 and standard deviation 2.5: >>> 3 + 2.5 * np.random.standard_normal(size=(2, 4)) array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], # random @@ -1500,7 +1504,8 @@ cdef class RandomState: ... linewidth=2, color='r') >>> plt.show() - Two-by-four array of samples from N(3, 6.25): + Two-by-four array of samples from the normal distribution with + mean 3 and standard deviation 2.5: >>> np.random.normal(3, 2.5, size=(2, 4)) array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], # random |