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-rw-r--r--numpy/lib/financial.py8
-rw-r--r--numpy/lib/function_base.py33
-rw-r--r--numpy/lib/io.py6
-rw-r--r--numpy/lib/polynomial.py4
-rw-r--r--numpy/lib/scimath.py63
-rw-r--r--numpy/lib/shape_base.py70
-rw-r--r--numpy/lib/twodim_base.py8
7 files changed, 93 insertions, 99 deletions
diff --git a/numpy/lib/financial.py b/numpy/lib/financial.py
index a3552ebc0..9c5d2753a 100644
--- a/numpy/lib/financial.py
+++ b/numpy/lib/financial.py
@@ -69,7 +69,7 @@ What is the future value after 10 years of saving $100 now, with
an additional monthly savings of $100. Assume the interest rate is
5% (annually) compounded monthly?
->>> fv(0.05/12, 10*12, -100, -100)
+>>> np.fv(0.05/12, 10*12, -100, -100)
15692.928894335748
By convention, the negative sign represents cash flow out (i.e. money not
@@ -94,7 +94,7 @@ Examples
What would the monthly payment need to be to pay off a $200,000 loan in 15
years at an annual interest rate of 7.5%?
->>> pmt(0.075/12, 12*15, 200000)
+>>> np.pmt(0.075/12, 12*15, 200000)
-1854.0247200054619
In order to pay-off (i.e. have a future-value of 0) the $200,000 obtained
@@ -122,7 +122,7 @@ Examples
If you only had $150 to spend as payment, how long would it take to pay-off
a loan of $8,000 at 7% annual interest?
->>> nper(0.07/12, -150, 8000)
+>>> np.nper(0.07/12, -150, 8000)
64.073348770661852
So, over 64 months would be required to pay off the loan.
@@ -130,7 +130,7 @@ So, over 64 months would be required to pay off the loan.
The same analysis could be done with several different interest rates and/or
payments and/or total amounts to produce an entire table.
->>> nper(*(ogrid[0.06/12:0.071/12:0.01/12, -200:-99:100, 6000:7001:1000]))
+>>> np.nper(*(np.ogrid[0.06/12:0.071/12:0.01/12, -200:-99:100, 6000:7001:1000]))
array([[[ 32.58497782, 38.57048452],
[ 71.51317802, 86.37179563]],
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index fe6e67903..e8df0b439 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -471,7 +471,7 @@ def average(a, axis=None, weights=None, returned=False):
Examples
--------
- >>> average(range(1,11), weights=range(10,0,-1))
+ >>> np.average(range(1,11), weights=range(10,0,-1))
4.0
Raises
@@ -893,7 +893,7 @@ def trim_zeros(filt, trim='fb'):
Examples
--------
- >>> a = array((0, 0, 0, 1, 2, 3, 2, 1, 0))
+ >>> a = np.array((0, 0, 0, 1, 2, 3, 2, 1, 0))
>>> np.trim_zeros(a)
array([1, 2, 3, 2, 1])
@@ -1069,7 +1069,7 @@ class vectorize(object):
... else:
... return a+b
- >>> vfunc = vectorize(myfunc)
+ >>> vfunc = np.vectorize(myfunc)
>>> vfunc([1, 2, 3, 4], 2)
array([3, 4, 1, 2])
@@ -1486,29 +1486,28 @@ def median(a, axis=0, out=None, overwrite_input=False):
Examples
--------
- >>> from numpy import median
>>> a = np.array([[10, 7, 4], [3, 2, 1]])
>>> a
array([[10, 7, 4],
[ 3, 2, 1]])
- >>> median(a)
+ >>> np.median(a)
array([ 6.5, 4.5, 2.5])
- >>> median(a, axis=None)
+ >>> np.median(a, axis=None)
3.5
- >>> median(a, axis=1)
+ >>> np.median(a, axis=1)
array([ 7., 2.])
- >>> m = median(a)
+ >>> m = np.median(a)
>>> out = np.zeros_like(m)
- >>> median(a, out=m)
+ >>> np.median(a, out=m)
array([ 6.5, 4.5, 2.5])
>>> m
array([ 6.5, 4.5, 2.5])
>>> b = a.copy()
- >>> median(b, axis=1, overwrite_input=True)
+ >>> np.median(b, axis=1, overwrite_input=True)
array([ 7., 2.])
>>> assert not np.all(a==b)
>>> b = a.copy()
- >>> median(b, axis=None, overwrite_input=True)
+ >>> np.median(b, axis=None, overwrite_input=True)
3.5
>>> assert not np.all(a==b)
"""
@@ -1632,11 +1631,11 @@ def delete(arr, obj, axis=None):
... [1,2,3],
... [6,7,8]]
- >>> delete(arr, 1, 1)
+ >>> np.delete(arr, 1, 1)
array([[3, 5],
[1, 3],
[6, 8]])
- >>> delete(arr, 1, 0)
+ >>> np.delete(arr, 1, 0)
array([[3, 4, 5],
[6, 7, 8]])
"""
@@ -1732,11 +1731,11 @@ def insert(arr, obj, values, axis=None):
Examples
--------
- >>> a = array([[1,2,3],
- ... [4,5,6],
- ... [7,8,9]])
+ >>> a = np.array([[1,2,3],
+ ... [4,5,6],
+ ... [7,8,9]])
- >>> insert(a, [1,2], [[4],[5]], axis=0)
+ >>> np.insert(a, [1,2], [[4],[5]], axis=0)
array([[1, 2, 3],
[4, 4, 4],
[4, 5, 6],
diff --git a/numpy/lib/io.py b/numpy/lib/io.py
index db4e73358..36723f1d8 100644
--- a/numpy/lib/io.py
+++ b/numpy/lib/io.py
@@ -344,9 +344,9 @@ def savetxt(fname, X, fmt='%.18e',delimiter=' '):
Examples
--------
- >>> savetxt('test.out', x, delimiter=',') # X is an array
- >>> savetxt('test.out', (x,y,z)) # x,y,z equal sized 1D arrays
- >>> savetxt('test.out', x, fmt='%1.4e') # use exponential notation
+ >>> np.savetxt('test.out', x, delimiter=',') # X is an array
+ >>> np.savetxt('test.out', (x,y,z)) # x,y,z equal sized 1D arrays
+ >>> np.savetxt('test.out', x, fmt='%1.4e') # use exponential notation
Notes on fmt
------------
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py
index 303cdb13c..8fb0337dc 100644
--- a/numpy/lib/polynomial.py
+++ b/numpy/lib/polynomial.py
@@ -52,8 +52,8 @@ def poly(seq_of_zeros):
Example:
- >>> b = roots([1,3,1,5,6])
- >>> poly(b)
+ >>> b = np.roots([1,3,1,5,6])
+ >>> np.poly(b)
array([ 1., 3., 1., 5., 6.])
"""
diff --git a/numpy/lib/scimath.py b/numpy/lib/scimath.py
index d3965668d..2a951135a 100644
--- a/numpy/lib/scimath.py
+++ b/numpy/lib/scimath.py
@@ -50,8 +50,8 @@ def _tocomplex(arr):
>>> a = np.array([1,2,3],np.short)
- >>> ac = _tocomplex(a); ac
- array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64)
+ >>> ac = np.lib.scimath._tocomplex(a); ac
+ array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=np.complex64)
>>> ac.dtype
dtype('complex64')
@@ -61,7 +61,7 @@ def _tocomplex(arr):
>>> b = np.array([1,2,3],np.double)
- >>> bc = _tocomplex(b); bc
+ >>> bc = np.lib.scimath._tocomplex(b); bc
array([ 1.+0.j, 2.+0.j, 3.+0.j])
>>> bc.dtype
@@ -72,7 +72,7 @@ def _tocomplex(arr):
>>> c = np.array([1,2,3],np.csingle)
- >>> cc = _tocomplex(c); cc
+ >>> cc = np.lib.scimath._tocomplex(c); cc
array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64)
>>> c *= 2; c
@@ -102,10 +102,10 @@ def _fix_real_lt_zero(x):
Examples
--------
- >>> _fix_real_lt_zero([1,2])
+ >>> np.lib.scimath._fix_real_lt_zero([1,2])
array([1, 2])
- >>> _fix_real_lt_zero([-1,2])
+ >>> np.lib.scimath._fix_real_lt_zero([-1,2])
array([-1.+0.j, 2.+0.j])
"""
x = asarray(x)
@@ -128,10 +128,10 @@ def _fix_int_lt_zero(x):
Examples
--------
- >>> _fix_int_lt_zero([1,2])
+ >>> np.lib.scimath._fix_int_lt_zero([1,2])
array([1, 2])
- >>> _fix_int_lt_zero([-1,2])
+ >>> np.lib.scimath._fix_int_lt_zero([-1,2])
array([-1., 2.])
"""
x = asarray(x)
@@ -154,10 +154,10 @@ def _fix_real_abs_gt_1(x):
Examples
--------
- >>> _fix_real_abs_gt_1([0,1])
+ >>> np.lib.scimath._fix_real_abs_gt_1([0,1])
array([0, 1])
- >>> _fix_real_abs_gt_1([0,2])
+ >>> np.lib.scimath._fix_real_abs_gt_1([0,2])
array([ 0.+0.j, 2.+0.j])
"""
x = asarray(x)
@@ -180,17 +180,17 @@ def sqrt(x):
--------
For real, non-negative inputs this works just like numpy.sqrt():
- >>> sqrt(1)
+ >>> np.lib.scimath.sqrt(1)
1.0
- >>> sqrt([1,4])
+ >>> np.lib.scimath.sqrt([1,4])
array([ 1., 2.])
But it automatically handles negative inputs:
- >>> sqrt(-1)
+ >>> np.lib.scimath.sqrt(-1)
(0.0+1.0j)
- >>> sqrt([-1,4])
+ >>> np.lib.scimath.sqrt([-1,4])
array([ 0.+1.j, 2.+0.j])
"""
x = _fix_real_lt_zero(x)
@@ -213,14 +213,13 @@ def log(x):
Examples
--------
>>> import math
-
- >>> log(math.exp(1))
+ >>> np.lib.scimath.log(math.exp(1))
1.0
Negative arguments are correctly handled (recall that for negative
arguments, the identity exp(log(z))==z does not hold anymore):
- >>> log(-math.exp(1)) == (1+1j*math.pi)
+ >>> np.lib.scimath.log(-math.exp(1)) == (1+1j*math.pi)
True
"""
x = _fix_real_lt_zero(x)
@@ -246,11 +245,11 @@ def log10(x):
(We set the printing precision so the example can be auto-tested)
>>> np.set_printoptions(precision=4)
- >>> log10([10**1,10**2])
+ >>> np.lib.scimath.log10([10**1,10**2])
array([ 1., 2.])
- >>> log10([-10**1,-10**2,10**2])
+ >>> np.lib.scimath.log10([-10**1,-10**2,10**2])
array([ 1.+1.3644j, 2.+1.3644j, 2.+0.j ])
"""
x = _fix_real_lt_zero(x)
@@ -276,10 +275,10 @@ def logn(n, x):
(We set the printing precision so the example can be auto-tested)
>>> np.set_printoptions(precision=4)
- >>> logn(2,[4,8])
+ >>> np.lib.scimath.logn(2,[4,8])
array([ 2., 3.])
- >>> logn(2,[-4,-8,8])
+ >>> np.lib.scimath.logn(2,[-4,-8,8])
array([ 2.+4.5324j, 3.+4.5324j, 3.+0.j ])
"""
x = _fix_real_lt_zero(x)
@@ -306,10 +305,10 @@ def log2(x):
(We set the printing precision so the example can be auto-tested)
>>> np.set_printoptions(precision=4)
- >>> log2([4,8])
+ >>> np.lib.scimath.log2([4,8])
array([ 2., 3.])
- >>> log2([-4,-8,8])
+ >>> np.lib.scimath.log2([-4,-8,8])
array([ 2.+4.5324j, 3.+4.5324j, 3.+0.j ])
"""
x = _fix_real_lt_zero(x)
@@ -336,13 +335,13 @@ def power(x, p):
(We set the printing precision so the example can be auto-tested)
>>> np.set_printoptions(precision=4)
- >>> power([2,4],2)
+ >>> np.lib.scimath.power([2,4],2)
array([ 4, 16])
- >>> power([2,4],-2)
+ >>> np.lib.scimath.power([2,4],-2)
array([ 0.25 , 0.0625])
- >>> power([-2,4],2)
+ >>> np.lib.scimath.power([-2,4],2)
array([ 4.+0.j, 16.+0.j])
"""
x = _fix_real_lt_zero(x)
@@ -368,10 +367,10 @@ def arccos(x):
--------
>>> np.set_printoptions(precision=4)
- >>> arccos(1)
+ >>> np.lib.scimath.arccos(1)
0.0
- >>> arccos([1,2])
+ >>> np.lib.scimath.arccos([1,2])
array([ 0.-0.j , 0.+1.317j])
"""
x = _fix_real_abs_gt_1(x)
@@ -397,10 +396,10 @@ def arcsin(x):
(We set the printing precision so the example can be auto-tested)
>>> np.set_printoptions(precision=4)
- >>> arcsin(0)
+ >>> np.lib.scimath.arcsin(0)
0.0
- >>> arcsin([0,1])
+ >>> np.lib.scimath.arcsin([0,1])
array([ 0. , 1.5708])
"""
x = _fix_real_abs_gt_1(x)
@@ -426,10 +425,10 @@ def arctanh(x):
(We set the printing precision so the example can be auto-tested)
>>> np.set_printoptions(precision=4)
- >>> arctanh(0)
+ >>> np.lib.scimath.arctanh(0)
0.0
- >>> arctanh([0,2])
+ >>> np.lib.scimath.arctanh([0,2])
array([ 0.0000+0.j , 0.5493-1.5708j])
"""
x = _fix_real_abs_gt_1(x)
diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py
index 77f158eb3..afdb879e4 100644
--- a/numpy/lib/shape_base.py
+++ b/numpy/lib/shape_base.py
@@ -192,13 +192,13 @@ def vstack(tup):
tup -- sequence of arrays. All arrays must have the same
shape.
Examples:
- >>> a = array((1,2,3))
- >>> b = array((2,3,4))
+ >>> a = np.array((1,2,3))
+ >>> b = np.array((2,3,4))
>>> np.vstack((a,b))
array([[1, 2, 3],
[2, 3, 4]])
- >>> a = array([[1],[2],[3]])
- >>> b = array([[2],[3],[4]])
+ >>> a = np.array([[1],[2],[3]])
+ >>> b = np.array([[2],[3],[4]])
>>> np.vstack((a,b))
array([[1],
[2],
@@ -222,14 +222,13 @@ def hstack(tup):
tup -- sequence of arrays. All arrays must have the same
shape.
Examples:
- >>> import numpy
- >>> a = array((1,2,3))
- >>> b = array((2,3,4))
- >>> numpy.hstack((a,b))
+ >>> a = np.array((1,2,3))
+ >>> b = np.array((2,3,4))
+ >>> np.hstack((a,b))
array([1, 2, 3, 2, 3, 4])
- >>> a = array([[1],[2],[3]])
- >>> b = array([[2],[3],[4]])
- >>> numpy.hstack((a,b))
+ >>> a = np.array([[1],[2],[3]])
+ >>> b = np.array([[2],[3],[4]])
+ >>> np.hstack((a,b))
array([[1, 2],
[2, 3],
[3, 4]])
@@ -253,10 +252,9 @@ def column_stack(tup):
tup -- sequence of 1D or 2D arrays. All arrays must have the same
first dimension.
Examples:
- >>> import numpy
- >>> a = array((1,2,3))
- >>> b = array((2,3,4))
- >>> numpy.column_stack((a,b))
+ >>> a = np.array((1,2,3))
+ >>> b = np.array((2,3,4))
+ >>> np.column_stack((a,b))
array([[1, 2],
[2, 3],
[3, 4]])
@@ -283,16 +281,15 @@ def dstack(tup):
tup -- sequence of arrays. All arrays must have the same
shape.
Examples:
- >>> import numpy
- >>> a = array((1,2,3))
- >>> b = array((2,3,4))
- >>> numpy.dstack((a,b))
+ >>> a = np.array((1,2,3))
+ >>> b = np.array((2,3,4))
+ >>> np.dstack((a,b))
array([[[1, 2],
[2, 3],
[3, 4]]])
- >>> a = array([[1],[2],[3]])
- >>> b = array([[2],[3],[4]])
- >>> numpy.dstack((a,b))
+ >>> a = np.array([[1],[2],[3]])
+ >>> b = np.array([[2],[3],[4]])
+ >>> np.dstack((a,b))
array([[[1, 2]],
<BLANKLINE>
[[2, 3]],
@@ -432,12 +429,11 @@ def hsplit(ary,indices_or_sections):
Related:
hstack, split, array_split, vsplit, dsplit.
Examples:
- >>> import numpy
- >>> a= array((1,2,3,4))
- >>> numpy.hsplit(a,2)
+ >>> a= np.array((1,2,3,4))
+ >>> np.hsplit(a,2)
[array([1, 2]), array([3, 4])]
- >>> a = array([[1,2,3,4],[1,2,3,4]])
- >>> hsplit(a,2)
+ >>> a = np.array([[1,2,3,4],[1,2,3,4]])
+ >>> np.hsplit(a,2)
[array([[1, 2],
[1, 2]]), array([[3, 4],
[3, 4]])]
@@ -482,9 +478,9 @@ def vsplit(ary,indices_or_sections):
vstack, split, array_split, hsplit, dsplit.
Examples:
import numpy
- >>> a = array([[1,2,3,4],
- ... [1,2,3,4]])
- >>> numpy.vsplit(a,2)
+ >>> a = np.array([[1,2,3,4],
+ ... [1,2,3,4]])
+ >>> np.vsplit(a,2)
[array([[1, 2, 3, 4]]), array([[1, 2, 3, 4]])]
"""
@@ -519,8 +515,8 @@ def dsplit(ary,indices_or_sections):
Related:
dstack, split, array_split, hsplit, vsplit.
Examples:
- >>> a = array([[[1,2,3,4],[1,2,3,4]]])
- >>> dsplit(a,2)
+ >>> a = np.array([[[1,2,3,4],[1,2,3,4]]])
+ >>> np.dsplit(a,2)
[array([[[1, 2],
[1, 2]]]), array([[[3, 4],
[3, 4]]])]
@@ -596,15 +592,15 @@ def tile(A, reps):
Examples:
- >>> a = array([0,1,2])
- >>> tile(a,2)
+ >>> a = np.array([0,1,2])
+ >>> np.tile(a,2)
array([0, 1, 2, 0, 1, 2])
- >>> tile(a,(1,2))
+ >>> np.tile(a,(1,2))
array([[0, 1, 2, 0, 1, 2]])
- >>> tile(a,(2,2))
+ >>> np.tile(a,(2,2))
array([[0, 1, 2, 0, 1, 2],
[0, 1, 2, 0, 1, 2]])
- >>> tile(a,(2,1,2))
+ >>> np.tile(a,(2,1,2))
array([[[0, 1, 2, 0, 1, 2]],
<BLANKLINE>
[[0, 1, 2, 0, 1, 2]]])
diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py
index 44082521c..ab1e5fcf0 100644
--- a/numpy/lib/twodim_base.py
+++ b/numpy/lib/twodim_base.py
@@ -88,13 +88,13 @@ def diagflat(v,k=0):
Examples
--------
- >>> diagflat([[1,2],[3,4]]])
+ >>> np.diagflat([[1,2],[3,4]])
array([[1, 0, 0, 0],
[0, 2, 0, 0],
[0, 0, 3, 0],
[0, 0, 0, 4]])
- >>> diagflat([1,2], 1)
+ >>> np.diagflat([1,2], 1)
array([[0, 1, 0],
[0, 0, 2],
[0, 0, 0]])
@@ -180,8 +180,8 @@ def histogram2d(x,y, bins=10, range=None, normed=False, weights=None):
- `xedges, yedges` : Arrays defining the bin edges.
Example:
- >>> x = random.randn(100,2)
- >>> hist2d, xedges, yedges = histogram2d(x, bins = (6, 7))
+ >>> x = np.random.randn(100,2)
+ >>> hist2d, xedges, yedges = np.lib.histogram2d(x, bins = (6, 7))
:SeeAlso: histogramdd
"""
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