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All Samples(142)  |  Call(138)  |  Derive(0)  |  Import(4)
Return a new array with the same shape and type as a given array.

Parameters
----------
a : array_like
    The shape and data-type of `a` define these same attributes of the
    returned array.

Returns
-------(more...)

All Samples(96)  |  Call(66)  |  Derive(0)  |  Import(30)
subtract(x1, x2[, out])

Subtract arguments, element-wise.

Parameters
----------
x1, x2 : array_like
    The arrays to be subtracted from each other.

Returns(more...)

All Samples(142)  |  Call(108)  |  Derive(0)  |  Import(34)
Return the angle of the complex argument.

Parameters
----------
z : array_like
    A complex number or sequence of complex numbers.
deg : bool, optional
    Return angle in degrees if True, radians if False (default).

Returns(more...)

All Samples(139)  |  Call(123)  |  Derive(0)  |  Import(16)
log2(x[, out])

Base-2 logarithm of `x`.

Parameters
----------
x : array_like
    Input values.

Returns(more...)

All Samples(136)  |  Call(105)  |  Derive(0)  |  Import(31)
arcsin(x[, out])

Inverse sine, element-wise.

Parameters
----------
x : array_like
    `y`-coordinate on the unit circle.

out : ndarray, optional(more...)

All Samples(135)  |  Call(121)  |  Derive(0)  |  Import(14)
Return True if x is a complex type or an array of complex numbers.

The type of the input is checked, not the value. So even if the input
has an imaginary part equal to zero, `iscomplexobj` evaluates to True
if the data type is complex.

Parameters
----------
x : any
    The input can be of any type and shape.(more...)

All Samples(128)  |  Call(127)  |  Derive(0)  |  Import(1)
Roll the specified axis backwards, until it lies in a given position.

Parameters
----------
a : ndarray
    Input array.
axis : int
    The axis to roll backwards.  The positions of the other axes do not
    change relative to one another.
start : int, optional(more...)

All Samples(126)  |  Call(101)  |  Derive(0)  |  Import(25)
Flip array in the up/down direction.

Flip the entries in each column in the up/down direction.
Rows are preserved, but appear in a different order than before.

Parameters
----------
m : array_like
    Input array.
(more...)

All Samples(124)  |  Call(96)  |  Derive(0)  |  Import(28)
tanh(x[, out])

Compute hyperbolic tangent element-wise.

Equivalent to ``np.sinh(x)/np.cosh(x)`` or
``-1j * np.tan(1j*x)``.

Parameters
----------
x : array_like(more...)

All Samples(123)  |  Call(88)  |  Derive(0)  |  Import(35)
64-bit floating-point number. Character code 'd'. Python float compatible.

All Samples(122)  |  Call(122)  |  Derive(0)  |  Import(0)
No Document.

All Samples(120)  |  Call(0)  |  Derive(0)  |  Import(120)
No Document.

All Samples(117)  |  Call(0)  |  Derive(0)  |  Import(117)
No Document.

All Samples(116)  |  Call(106)  |  Derive(0)  |  Import(10)
Set printing options.

These options determine the way floating point numbers, arrays and
other NumPy objects are displayed.

Parameters
----------
precision : int, optional
    Number of digits of precision for floating point output (default 8).
threshold : int, optional(more...)

All Samples(113)  |  Call(95)  |  Derive(0)  |  Import(18)
greater_equal(x1, x2[, out])

Return the truth value of (x1 >= x2) element-wise.

Parameters
----------
x1, x2 : array_like
    Input arrays.  If ``x1.shape != x2.shape``, they must be
    broadcastable to a common shape (which may be the shape of one or
    the other).(more...)

All Samples(113)  |  Call(101)  |  Derive(0)  |  Import(12)
No Document.

All Samples(108)  |  Call(99)  |  Derive(0)  |  Import(9)
No Document.

All Samples(108)  |  Call(95)  |  Derive(0)  |  Import(13)
Least squares polynomial fit.

Fit a polynomial ``p(x) = p[0] * x**deg + ... + p[deg]`` of degree `deg`
to points `(x, y)`. Returns a vector of coefficients `p` that minimises
the squared error.

Parameters
----------
x : array_like, shape (M,)
    x-coordinates of the M sample points ``(x[i], y[i])``.(more...)

All Samples(106)  |  Call(101)  |  Derive(0)  |  Import(5)
No Document.

All Samples(106)  |  Call(75)  |  Derive(0)  |  Import(31)
cosh(x[, out])

Hyperbolic cosine, element-wise.

Equivalent to ``1/2 * (np.exp(x) + np.exp(-x))`` and ``np.cos(1j*x)``.

Parameters
----------
x : array_like
    Input array.(more...)

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