doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
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numpy.typename numpy.typename(char)[source]
Return a description for the given data type code. Parameters
charstr
Data type code. Returns
outstr
Description of the input data type code. See also
dtype, typecodes
Examples >>> typechars = ['S1', '?', 'B', 'D', 'G', 'F', 'I', 'H', 'L', 'O', 'Q'... | numpy.reference.generated.numpy.typename |
Typing (numpy.typing) New in version 1.20. Large parts of the NumPy API have PEP-484-style type annotations. In addition a number of type aliases are available to users, most prominently the two below:
ArrayLike: objects that can be converted to arrays
DTypeLike: objects that can be converted to dtypes Mypy plug... | numpy.reference.typing |
numpy.typing.DTypeLike = typing.Union[...]
A Union representing objects that can be coerced into a dtype. Among others this includes the likes of:
type objects. Character codes or the names of type objects. Objects with the .dtype attribute. New in version 1.20. See Also Specifying and constructing data types
... | numpy.reference.typing#numpy.typing.DTypeLike |
numpy.typing.NDArray = numpy.ndarray[typing.Any, numpy.dtype[+ScalarType]][source]
A generic version of np.ndarray[Any, np.dtype[+ScalarType]]. Can be used during runtime for typing arrays with a given dtype and unspecified shape. New in version 1.21. Examples >>> import numpy as np
>>> import numpy.typing as npt
... | numpy.reference.typing#numpy.typing.NDArray |
class numpy.ubyte[source]
Unsigned integer type, compatible with C unsigned char. Character code
'B' Alias on this platform (Linux x86_64)
numpy.uint8: 8-bit unsigned integer (0 to 255). | numpy.reference.arrays.scalars#numpy.ubyte |
numpy.ufunc class numpy.ufunc[source]
Functions that operate element by element on whole arrays. To see the documentation for a specific ufunc, use info. For example, np.info(np.sin). Because ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility, Python’s help() function finds this ... | numpy.reference.generated.numpy.ufunc |
class numpy.uint[source]
Unsigned integer type, compatible with C unsigned long. Character code
'L' Alias on this platform (Linux x86_64)
numpy.uint64: 64-bit unsigned integer (0 to 18_446_744_073_709_551_615). Alias on this platform (Linux x86_64)
numpy.uintp: Unsigned integer large enough to fit pointer, comp... | numpy.reference.arrays.scalars#numpy.uint |
numpy.uint8[source]
numpy.uint16
numpy.uint32
numpy.uint64
Alias for the unsigned integer types (one of numpy.ubyte, numpy.ushort, numpy.uintc, numpy.uint and numpy.ulonglong) with the specified number of bits. Compatible with the C99 uint8_t, uint16_t, uint32_t, and uint64_t, respectively. | numpy.reference.arrays.scalars#numpy.uint16 |
numpy.uint8[source]
numpy.uint16
numpy.uint32
numpy.uint64
Alias for the unsigned integer types (one of numpy.ubyte, numpy.ushort, numpy.uintc, numpy.uint and numpy.ulonglong) with the specified number of bits. Compatible with the C99 uint8_t, uint16_t, uint32_t, and uint64_t, respectively. | numpy.reference.arrays.scalars#numpy.uint32 |
numpy.uint8[source]
numpy.uint16
numpy.uint32
numpy.uint64
Alias for the unsigned integer types (one of numpy.ubyte, numpy.ushort, numpy.uintc, numpy.uint and numpy.ulonglong) with the specified number of bits. Compatible with the C99 uint8_t, uint16_t, uint32_t, and uint64_t, respectively. | numpy.reference.arrays.scalars#numpy.uint64 |
numpy.uint8[source]
numpy.uint16
numpy.uint32
numpy.uint64
Alias for the unsigned integer types (one of numpy.ubyte, numpy.ushort, numpy.uintc, numpy.uint and numpy.ulonglong) with the specified number of bits. Compatible with the C99 uint8_t, uint16_t, uint32_t, and uint64_t, respectively. | numpy.reference.arrays.scalars#numpy.uint8 |
class numpy.uintc[source]
Unsigned integer type, compatible with C unsigned int. Character code
'I' Alias on this platform (Linux x86_64)
numpy.uint32: 32-bit unsigned integer (0 to 4_294_967_295). | numpy.reference.arrays.scalars#numpy.uintc |
numpy.uintp[source]
Alias for the unsigned integer type (one of numpy.ubyte, numpy.ushort, numpy.uintc, numpy.uint and np.ulonglong) that is the same size as a pointer. Compatible with the C uintptr_t. Character code
'P' | numpy.reference.arrays.scalars#numpy.uintp |
class numpy.ulonglong[source]
Signed integer type, compatible with C unsigned long long. Character code
'Q' | numpy.reference.arrays.scalars#numpy.ulonglong |
numpy.unicode_[source]
alias of numpy.str_ | numpy.reference.arrays.scalars#numpy.unicode_ |
numpy.union1d numpy.union1d(ar1, ar2)[source]
Find the union of two arrays. Return the unique, sorted array of values that are in either of the two input arrays. Parameters
ar1, ar2array_like
Input arrays. They are flattened if they are not already 1D. Returns
union1dndarray
Unique, sorted union of th... | numpy.reference.generated.numpy.union1d |
numpy.unique numpy.unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None)[source]
Find the unique elements of an array. Returns the sorted unique elements of an array. There are three optional outputs in addition to the unique elements: the indices of the input array that give the uni... | numpy.reference.generated.numpy.unique |
numpy.unpackbits numpy.unpackbits(a, /, axis=None, count=None, bitorder='big')
Unpacks elements of a uint8 array into a binary-valued output array. Each element of a represents a bit-field that should be unpacked into a binary-valued output array. The shape of the output array is either 1-D (if axis is None) or the... | numpy.reference.generated.numpy.unpackbits |
numpy.unravel_index numpy.unravel_index(indices, shape, order='C')
Converts a flat index or array of flat indices into a tuple of coordinate arrays. Parameters
indicesarray_like
An integer array whose elements are indices into the flattened version of an array of dimensions shape. Before version 1.6.0, this f... | numpy.reference.generated.numpy.unravel_index |
numpy.unwrap numpy.unwrap(p, discont=None, axis=- 1, *, period=6.283185307179586)[source]
Unwrap by taking the complement of large deltas with respect to the period. This unwraps a signal p by changing elements which have an absolute difference from their predecessor of more than max(discont, period/2) to their per... | numpy.reference.generated.numpy.unwrap |
class numpy.ushort[source]
Unsigned integer type, compatible with C unsigned short. Character code
'H' Alias on this platform (Linux x86_64)
numpy.uint16: 16-bit unsigned integer (0 to 65_535). | numpy.reference.arrays.scalars#numpy.ushort |
numpy.vander numpy.vander(x, N=None, increasing=False)[source]
Generate a Vandermonde matrix. The columns of the output matrix are powers of the input vector. The order of the powers is determined by the increasing boolean argument. Specifically, when increasing is False, the i-th output column is the input vector ... | numpy.reference.generated.numpy.vander |
numpy.var numpy.var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>, *, where=<no value>)[source]
Compute the variance along the specified axis. Returns the variance of the array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwi... | numpy.reference.generated.numpy.var |
numpy.vdot numpy.vdot(a, b, /)
Return the dot product of two vectors. The vdot(a, b) function handles complex numbers differently than dot(a, b). If the first argument is complex the complex conjugate of the first argument is used for the calculation of the dot product. Note that vdot handles multidimensional array... | numpy.reference.generated.numpy.vdot |
numpy.vectorize class numpy.vectorize(pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None)[source]
Generalized function class. Define a vectorized function which takes a nested sequence of objects or numpy arrays as inputs and returns a single numpy array or a tuple of numpy arrays. The vector... | numpy.reference.generated.numpy.vectorize |
class numpy.void[source]
Either an opaque sequence of bytes, or a structure. >>> np.void(b'abcd')
void(b'\x61\x62\x63\x64')
Structured void scalars can only be constructed via extraction from Structured arrays: >>> arr = np.array((1, 2), dtype=[('x', np.int8), ('y', np.int8)])
>>> arr[()]
(1, 2) # looks like a tupl... | numpy.reference.arrays.scalars#numpy.void |
numpy.vsplit numpy.vsplit(ary, indices_or_sections)[source]
Split an array into multiple sub-arrays vertically (row-wise). Please refer to the split documentation. vsplit is equivalent to split with axis=0 (default), the array is always split along the first axis regardless of the array dimension. See also split
... | numpy.reference.generated.numpy.vsplit |
numpy.vstack numpy.vstack(tup)[source]
Stack arrays in sequence vertically (row wise). This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided by vsplit. This function makes most sense for arrays with up to 3 dimensions. For instan... | numpy.reference.generated.numpy.vstack |
numpy.where numpy.where(condition, [x, y, ]/)
Return elements chosen from x or y depending on condition. Note When only condition is provided, this function is a shorthand for np.asarray(condition).nonzero(). Using nonzero directly should be preferred, as it behaves correctly for subclasses. The rest of this docum... | numpy.reference.generated.numpy.where |
numpy.who numpy.who(vardict=None)[source]
Print the NumPy arrays in the given dictionary. If there is no dictionary passed in or vardict is None then returns NumPy arrays in the globals() dictionary (all NumPy arrays in the namespace). Parameters
vardictdict, optional
A dictionary possibly containing ndarrays... | numpy.reference.generated.numpy.who |
numpy.zeros numpy.zeros(shape, dtype=float, order='C', *, like=None)
Return a new array of given shape and type, filled with zeros. Parameters
shapeint or tuple of ints
Shape of the new array, e.g., (2, 3) or 2.
dtypedata-type, optional
The desired data-type for the array, e.g., numpy.int8. Default is num... | numpy.reference.generated.numpy.zeros |
numpy.zeros_like numpy.zeros_like(a, dtype=None, order='K', subok=True, shape=None)[source]
Return an array of zeros with the same shape and type as a given array. Parameters
aarray_like
The shape and data-type of a define these same attributes of the returned array.
dtypedata-type, optional
Overrides the... | numpy.reference.generated.numpy.zeros_like |
Packaging (numpy.distutils) NumPy provides enhanced distutils functionality to make it easier to build and install sub-packages, auto-generate code, and extension modules that use Fortran-compiled libraries. To use features of NumPy distutils, use the setup command from numpy.distutils.core. A useful Configuration clas... | numpy.reference.distutils |
paths(*paths, **kws)[source]
Apply glob to paths and prepend local_path if needed. Applies glob.glob(…) to each path in the sequence (if needed) and pre-pends the local_path if needed. Because this is called on all source lists, this allows wildcard characters to be specified in lists of sources for extension modules... | numpy.reference.distutils#numpy.distutils.misc_util.Configuration.paths |
Performance Recommendation The recommended generator for general use is PCG64 or its upgraded variant PCG64DXSM for heavily-parallel use cases. They are statistically high quality, full-featured, and fast on most platforms, but somewhat slow when compiled for 32-bit processes. See Upgrading PCG64 with PCG64DXSM for de... | numpy.reference.random.performance |
Poly1d Basics
poly1d(c_or_r[, r, variable]) A one-dimensional polynomial class.
polyval(p, x) Evaluate a polynomial at specific values.
poly(seq_of_zeros) Find the coefficients of a polynomial with the given sequence of roots.
roots(p) Return the roots of a polynomial with coefficients given in p. Fitting ... | numpy.reference.routines.polynomials.poly1d |
numpy.poly1d.__call__ method poly1d.__call__(val)[source]
Call self as a function. | numpy.reference.generated.numpy.poly1d.__call__ |
numpy.poly1d.deriv method poly1d.deriv(m=1)[source]
Return a derivative of this polynomial. Refer to polyder for full documentation. See also polyder
equivalent function | numpy.reference.generated.numpy.poly1d.deriv |
numpy.poly1d.integ method poly1d.integ(m=1, k=0)[source]
Return an antiderivative (indefinite integral) of this polynomial. Refer to polyint for full documentation. See also polyint
equivalent function | numpy.reference.generated.numpy.poly1d.integ |
numpy.polynomial.chebyshev.cheb2poly polynomial.chebyshev.cheb2poly(c)[source]
Convert a Chebyshev series to a polynomial. Convert an array representing the coefficients of a Chebyshev series, ordered from lowest degree to highest, to an array of the coefficients of the equivalent polynomial (relative to the “stand... | numpy.reference.generated.numpy.polynomial.chebyshev.cheb2poly |
numpy.polynomial.chebyshev.chebadd polynomial.chebyshev.chebadd(c1, c2)[source]
Add one Chebyshev series to another. Returns the sum of two Chebyshev series c1 + c2. The arguments are sequences of coefficients ordered from lowest order term to highest, i.e., [1,2,3] represents the series T_0 + 2*T_1 + 3*T_2. Param... | numpy.reference.generated.numpy.polynomial.chebyshev.chebadd |
numpy.polynomial.chebyshev.chebcompanion polynomial.chebyshev.chebcompanion(c)[source]
Return the scaled companion matrix of c. The basis polynomials are scaled so that the companion matrix is symmetric when c is a Chebyshev basis polynomial. This provides better eigenvalue estimates than the unscaled case and for ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebcompanion |
numpy.polynomial.chebyshev.chebder polynomial.chebyshev.chebder(c, m=1, scl=1, axis=0)[source]
Differentiate a Chebyshev series. Returns the Chebyshev series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl (the scaling factor is for use in a linear change of varia... | numpy.reference.generated.numpy.polynomial.chebyshev.chebder |
numpy.polynomial.chebyshev.chebdiv polynomial.chebyshev.chebdiv(c1, c2)[source]
Divide one Chebyshev series by another. Returns the quotient-with-remainder of two Chebyshev series c1 / c2. The arguments are sequences of coefficients from lowest order “term” to highest, e.g., [1,2,3] represents the series T_0 + 2*T_... | numpy.reference.generated.numpy.polynomial.chebyshev.chebdiv |
numpy.polynomial.chebyshev.chebdomain polynomial.chebyshev.chebdomain = array([-1, 1])
An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether... | numpy.reference.generated.numpy.polynomial.chebyshev.chebdomain |
numpy.polynomial.chebyshev.chebfit polynomial.chebyshev.chebfit(x, y, deg, rcond=None, full=False, w=None)[source]
Least squares fit of Chebyshev series to data. Return the coefficients of a Chebyshev series of degree deg that is the least squares fit to the data values y given at points x. If y is 1-D the returned... | numpy.reference.generated.numpy.polynomial.chebyshev.chebfit |
numpy.polynomial.chebyshev.chebfromroots polynomial.chebyshev.chebfromroots(roots)[source]
Generate a Chebyshev series with given roots. The function returns the coefficients of the polynomial \[p(x) = (x - r_0) * (x - r_1) * ... * (x - r_n),\] in Chebyshev form, where the r_n are the roots specified in roots. If ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebfromroots |
numpy.polynomial.chebyshev.chebgauss polynomial.chebyshev.chebgauss(deg)[source]
Gauss-Chebyshev quadrature. Computes the sample points and weights for Gauss-Chebyshev quadrature. These sample points and weights will correctly integrate polynomials of degree \(2*deg - 1\) or less over the interval \([-1, 1]\) with ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebgauss |
numpy.polynomial.chebyshev.chebgrid2d polynomial.chebyshev.chebgrid2d(x, y, c)[source]
Evaluate a 2-D Chebyshev series on the Cartesian product of x and y. This function returns the values: \[p(a,b) = \sum_{i,j} c_{i,j} * T_i(a) * T_j(b),\] where the points (a, b) consist of all pairs formed by taking a from x and... | numpy.reference.generated.numpy.polynomial.chebyshev.chebgrid2d |
numpy.polynomial.chebyshev.chebgrid3d polynomial.chebyshev.chebgrid3d(x, y, z, c)[source]
Evaluate a 3-D Chebyshev series on the Cartesian product of x, y, and z. This function returns the values: \[p(a,b,c) = \sum_{i,j,k} c_{i,j,k} * T_i(a) * T_j(b) * T_k(c)\] where the points (a, b, c) consist of all triples for... | numpy.reference.generated.numpy.polynomial.chebyshev.chebgrid3d |
numpy.polynomial.chebyshev.chebint polynomial.chebyshev.chebint(c, m=1, k=[], lbnd=0, scl=1, axis=0)[source]
Integrate a Chebyshev series. Returns the Chebyshev series coefficients c integrated m times from lbnd along axis. At each iteration the resulting series is multiplied by scl and an integration constant, k, ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebint |
numpy.polynomial.chebyshev.chebinterpolate polynomial.chebyshev.chebinterpolate(func, deg, args=())[source]
Interpolate a function at the Chebyshev points of the first kind. Returns the Chebyshev series that interpolates func at the Chebyshev points of the first kind in the interval [-1, 1]. The interpolating serie... | numpy.reference.generated.numpy.polynomial.chebyshev.chebinterpolate |
numpy.polynomial.chebyshev.chebline polynomial.chebyshev.chebline(off, scl)[source]
Chebyshev series whose graph is a straight line. Parameters
off, sclscalars
The specified line is given by off + scl*x. Returns
yndarray
This module’s representation of the Chebyshev series for off + scl*x. See al... | numpy.reference.generated.numpy.polynomial.chebyshev.chebline |
numpy.polynomial.chebyshev.chebmul polynomial.chebyshev.chebmul(c1, c2)[source]
Multiply one Chebyshev series by another. Returns the product of two Chebyshev series c1 * c2. The arguments are sequences of coefficients, from lowest order “term” to highest, e.g., [1,2,3] represents the series T_0 + 2*T_1 + 3*T_2. P... | numpy.reference.generated.numpy.polynomial.chebyshev.chebmul |
numpy.polynomial.chebyshev.chebmulx polynomial.chebyshev.chebmulx(c)[source]
Multiply a Chebyshev series by x. Multiply the polynomial c by x, where x is the independent variable. Parameters
carray_like
1-D array of Chebyshev series coefficients ordered from low to high. Returns
outndarray
Array repre... | numpy.reference.generated.numpy.polynomial.chebyshev.chebmulx |
numpy.polynomial.chebyshev.chebone polynomial.chebyshev.chebone = array([1])
An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is an ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebone |
numpy.polynomial.chebyshev.chebpow polynomial.chebyshev.chebpow(c, pow, maxpower=16)[source]
Raise a Chebyshev series to a power. Returns the Chebyshev series c raised to the power pow. The argument c is a sequence of coefficients ordered from low to high. i.e., [1,2,3] is the series T_0 + 2*T_1 + 3*T_2. Parameter... | numpy.reference.generated.numpy.polynomial.chebyshev.chebpow |
numpy.polynomial.chebyshev.chebpts1 polynomial.chebyshev.chebpts1(npts)[source]
Chebyshev points of the first kind. The Chebyshev points of the first kind are the points cos(x), where x = [pi*(k + .5)/npts for k in range(npts)]. Parameters
nptsint
Number of sample points desired. Returns
ptsndarray
Th... | numpy.reference.generated.numpy.polynomial.chebyshev.chebpts1 |
numpy.polynomial.chebyshev.chebpts2 polynomial.chebyshev.chebpts2(npts)[source]
Chebyshev points of the second kind. The Chebyshev points of the second kind are the points cos(x), where x = [pi*k/(npts - 1) for k in range(npts)]. Parameters
nptsint
Number of sample points desired. Returns
ptsndarray
T... | numpy.reference.generated.numpy.polynomial.chebyshev.chebpts2 |
numpy.polynomial.chebyshev.chebroots polynomial.chebyshev.chebroots(c)[source]
Compute the roots of a Chebyshev series. Return the roots (a.k.a. “zeros”) of the polynomial \[p(x) = \sum_i c[i] * T_i(x).\] Parameters
c1-D array_like
1-D array of coefficients. Returns
outndarray
Array of the roots of t... | numpy.reference.generated.numpy.polynomial.chebyshev.chebroots |
numpy.polynomial.chebyshev.chebsub polynomial.chebyshev.chebsub(c1, c2)[source]
Subtract one Chebyshev series from another. Returns the difference of two Chebyshev series c1 - c2. The sequences of coefficients are from lowest order term to highest, i.e., [1,2,3] represents the series T_0 + 2*T_1 + 3*T_2. Parameter... | numpy.reference.generated.numpy.polynomial.chebyshev.chebsub |
numpy.polynomial.chebyshev.chebtrim polynomial.chebyshev.chebtrim(c, tol=0)[source]
Remove “small” “trailing” coefficients from a polynomial. “Small” means “small in absolute value” and is controlled by the parameter tol; “trailing” means highest order coefficient(s), e.g., in [0, 1, 1, 0, 0] (which represents 0 + ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebtrim |
numpy.polynomial.chebyshev.chebval polynomial.chebyshev.chebval(x, c, tensor=True)[source]
Evaluate a Chebyshev series at points x. If c is of length n + 1, this function returns the value: \[p(x) = c_0 * T_0(x) + c_1 * T_1(x) + ... + c_n * T_n(x)\] The parameter x is converted to an array only if it is a tuple or... | numpy.reference.generated.numpy.polynomial.chebyshev.chebval |
numpy.polynomial.chebyshev.chebval2d polynomial.chebyshev.chebval2d(x, y, c)[source]
Evaluate a 2-D Chebyshev series at points (x, y). This function returns the values: \[p(x,y) = \sum_{i,j} c_{i,j} * T_i(x) * T_j(y)\] The parameters x and y are converted to arrays only if they are tuples or a lists, otherwise the... | numpy.reference.generated.numpy.polynomial.chebyshev.chebval2d |
numpy.polynomial.chebyshev.chebval3d polynomial.chebyshev.chebval3d(x, y, z, c)[source]
Evaluate a 3-D Chebyshev series at points (x, y, z). This function returns the values: \[p(x,y,z) = \sum_{i,j,k} c_{i,j,k} * T_i(x) * T_j(y) * T_k(z)\] The parameters x, y, and z are converted to arrays only if they are tuples ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebval3d |
numpy.polynomial.chebyshev.chebvander polynomial.chebyshev.chebvander(x, deg)[source]
Pseudo-Vandermonde matrix of given degree. Returns the pseudo-Vandermonde matrix of degree deg and sample points x. The pseudo-Vandermonde matrix is defined by \[V[..., i] = T_i(x),\] where 0 <= i <= deg. The leading indices of V... | numpy.reference.generated.numpy.polynomial.chebyshev.chebvander |
numpy.polynomial.chebyshev.chebvander2d polynomial.chebyshev.chebvander2d(x, y, deg)[source]
Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y). The pseudo-Vandermonde matrix is defined by \[V[..., (deg[1] + 1)*i + j] = T_i(x) * T_j(y),\] where... | numpy.reference.generated.numpy.polynomial.chebyshev.chebvander2d |
numpy.polynomial.chebyshev.chebvander3d polynomial.chebyshev.chebvander3d(x, y, z, deg)[source]
Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y, z). If l, m, n are the given degrees in x, y, z, then The pseudo-Vandermonde matrix is defined by ... | numpy.reference.generated.numpy.polynomial.chebyshev.chebvander3d |
numpy.polynomial.chebyshev.chebweight polynomial.chebyshev.chebweight(x)[source]
The weight function of the Chebyshev polynomials. The weight function is \(1/\sqrt{1 - x^2}\) and the interval of integration is \([-1, 1]\). The Chebyshev polynomials are orthogonal, but not normalized, with respect to this weight fun... | numpy.reference.generated.numpy.polynomial.chebyshev.chebweight |
numpy.polynomial.chebyshev.chebx polynomial.chebyshev.chebx = array([0, 1])
An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is an i... | numpy.reference.generated.numpy.polynomial.chebyshev.chebx |
numpy.polynomial.chebyshev.Chebyshev.__call__ method polynomial.chebyshev.Chebyshev.__call__(arg)[source]
Call self as a function. | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.__call__ |
numpy.polynomial.chebyshev.Chebyshev.basis method classmethod polynomial.chebyshev.Chebyshev.basis(deg, domain=None, window=None)[source]
Series basis polynomial of degree deg. Returns the series representing the basis polynomial of degree deg. New in version 1.7.0. Parameters
degint
Degree of the basis pol... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.basis |
numpy.polynomial.chebyshev.Chebyshev.cast method classmethod polynomial.chebyshev.Chebyshev.cast(series, domain=None, window=None)[source]
Convert series to series of this class. The series is expected to be an instance of some polynomial series of one of the types supported by by the numpy.polynomial module, but c... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.cast |
numpy.polynomial.chebyshev.Chebyshev.convert method polynomial.chebyshev.Chebyshev.convert(domain=None, kind=None, window=None)[source]
Convert series to a different kind and/or domain and/or window. Parameters
domainarray_like, optional
The domain of the converted series. If the value is None, the default do... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.convert |
numpy.polynomial.chebyshev.Chebyshev.copy method polynomial.chebyshev.Chebyshev.copy()[source]
Return a copy. Returns
new_seriesseries
Copy of self. | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.copy |
numpy.polynomial.chebyshev.Chebyshev.cutdeg method polynomial.chebyshev.Chebyshev.cutdeg(deg)[source]
Truncate series to the given degree. Reduce the degree of the series to deg by discarding the high order terms. If deg is greater than the current degree a copy of the current series is returned. This can be useful... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.cutdeg |
numpy.polynomial.chebyshev.Chebyshev.degree method polynomial.chebyshev.Chebyshev.degree()[source]
The degree of the series. New in version 1.5.0. Returns
degreeint
Degree of the series, one less than the number of coefficients. | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.degree |
numpy.polynomial.chebyshev.Chebyshev.deriv method polynomial.chebyshev.Chebyshev.deriv(m=1)[source]
Differentiate. Return a series instance of that is the derivative of the current series. Parameters
mnon-negative int
Find the derivative of order m. Returns
new_seriesseries
A new series representing t... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.deriv |
numpy.polynomial.chebyshev.Chebyshev.domain attribute polynomial.chebyshev.Chebyshev.domain = array([-1, 1]) | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.domain |
numpy.polynomial.chebyshev.Chebyshev.fit method classmethod polynomial.chebyshev.Chebyshev.fit(x, y, deg, domain=None, rcond=None, full=False, w=None, window=None)[source]
Least squares fit to data. Return a series instance that is the least squares fit to the data y sampled at x. The domain of the returned instanc... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.fit |
numpy.polynomial.chebyshev.Chebyshev.fromroots method classmethod polynomial.chebyshev.Chebyshev.fromroots(roots, domain=[], window=None)[source]
Return series instance that has the specified roots. Returns a series representing the product (x - r[0])*(x - r[1])*...*(x - r[n-1]), where r is a list of roots. Parame... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.fromroots |
numpy.polynomial.chebyshev.Chebyshev.has_samecoef method polynomial.chebyshev.Chebyshev.has_samecoef(other)[source]
Check if coefficients match. New in version 1.6.0. Parameters
otherclass instance
The other class must have the coef attribute. Returns
boolboolean
True if the coefficients are the sam... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.has_samecoef |
numpy.polynomial.chebyshev.Chebyshev.has_samedomain method polynomial.chebyshev.Chebyshev.has_samedomain(other)[source]
Check if domains match. New in version 1.6.0. Parameters
otherclass instance
The other class must have the domain attribute. Returns
boolboolean
True if the domains are the same, F... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.has_samedomain |
numpy.polynomial.chebyshev.Chebyshev.has_sametype method polynomial.chebyshev.Chebyshev.has_sametype(other)[source]
Check if types match. New in version 1.7.0. Parameters
otherobject
Class instance. Returns
boolboolean
True if other is same class as self | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.has_sametype |
numpy.polynomial.chebyshev.Chebyshev.has_samewindow method polynomial.chebyshev.Chebyshev.has_samewindow(other)[source]
Check if windows match. New in version 1.6.0. Parameters
otherclass instance
The other class must have the window attribute. Returns
boolboolean
True if the windows are the same, F... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.has_samewindow |
numpy.polynomial.chebyshev.Chebyshev.identity method classmethod polynomial.chebyshev.Chebyshev.identity(domain=None, window=None)[source]
Identity function. If p is the returned series, then p(x) == x for all values of x. Parameters
domain{None, array_like}, optional
If given, the array must be of the form [... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.identity |
numpy.polynomial.chebyshev.Chebyshev.integ method polynomial.chebyshev.Chebyshev.integ(m=1, k=[], lbnd=None)[source]
Integrate. Return a series instance that is the definite integral of the current series. Parameters
mnon-negative int
The number of integrations to perform.
karray_like
Integration constant... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.integ |
numpy.polynomial.chebyshev.Chebyshev.interpolate method classmethod polynomial.chebyshev.Chebyshev.interpolate(func, deg, domain=None, args=())[source]
Interpolate a function at the Chebyshev points of the first kind. Returns the series that interpolates func at the Chebyshev points of the first kind scaled and shi... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.interpolate |
numpy.polynomial.chebyshev.Chebyshev.linspace method polynomial.chebyshev.Chebyshev.linspace(n=100, domain=None)[source]
Return x, y values at equally spaced points in domain. Returns the x, y values at n linearly spaced points across the domain. Here y is the value of the polynomial at the points x. By default the... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.linspace |
numpy.polynomial.chebyshev.Chebyshev.mapparms method polynomial.chebyshev.Chebyshev.mapparms()[source]
Return the mapping parameters. The returned values define a linear map off + scl*x that is applied to the input arguments before the series is evaluated. The map depends on the domain and window; if the current do... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.mapparms |
numpy.polynomial.chebyshev.Chebyshev.roots method polynomial.chebyshev.Chebyshev.roots()[source]
Return the roots of the series polynomial. Compute the roots for the series. Note that the accuracy of the roots decrease the further outside the domain they lie. Returns
rootsndarray
Array containing the roots of... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.roots |
numpy.polynomial.chebyshev.Chebyshev.trim method polynomial.chebyshev.Chebyshev.trim(tol=0)[source]
Remove trailing coefficients Remove trailing coefficients until a coefficient is reached whose absolute value greater than tol or the beginning of the series is reached. If all the coefficients would be removed the s... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.trim |
numpy.polynomial.chebyshev.Chebyshev.truncate method polynomial.chebyshev.Chebyshev.truncate(size)[source]
Truncate series to length size. Reduce the series to length size by discarding the high degree terms. The value of size must be a positive integer. This can be useful in least squares where the coefficients of... | numpy.reference.generated.numpy.polynomial.chebyshev.chebyshev.truncate |
numpy.polynomial.chebyshev.chebzero polynomial.chebyshev.chebzero = array([0])
An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is a... | numpy.reference.generated.numpy.polynomial.chebyshev.chebzero |
numpy.polynomial.chebyshev.poly2cheb polynomial.chebyshev.poly2cheb(pol)[source]
Convert a polynomial to a Chebyshev series. Convert an array representing the coefficients of a polynomial (relative to the “standard” basis) ordered from lowest degree to highest, to an array of the coefficients of the equivalent Cheb... | numpy.reference.generated.numpy.polynomial.chebyshev.poly2cheb |
numpy.polynomial.hermite.herm2poly polynomial.hermite.herm2poly(c)[source]
Convert a Hermite series to a polynomial. Convert an array representing the coefficients of a Hermite series, ordered from lowest degree to highest, to an array of the coefficients of the equivalent polynomial (relative to the “standard” bas... | numpy.reference.generated.numpy.polynomial.hermite.herm2poly |
numpy.polynomial.hermite.hermadd polynomial.hermite.hermadd(c1, c2)[source]
Add one Hermite series to another. Returns the sum of two Hermite series c1 + c2. The arguments are sequences of coefficients ordered from lowest order term to highest, i.e., [1,2,3] represents the series P_0 + 2*P_1 + 3*P_2. Parameters
... | numpy.reference.generated.numpy.polynomial.hermite.hermadd |
numpy.polynomial.hermite.hermcompanion polynomial.hermite.hermcompanion(c)[source]
Return the scaled companion matrix of c. The basis polynomials are scaled so that the companion matrix is symmetric when c is an Hermite basis polynomial. This provides better eigenvalue estimates than the unscaled case and for basis... | numpy.reference.generated.numpy.polynomial.hermite.hermcompanion |
numpy.polynomial.hermite.hermder polynomial.hermite.hermder(c, m=1, scl=1, axis=0)[source]
Differentiate a Hermite series. Returns the Hermite series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl (the scaling factor is for use in a linear change of variable). Th... | numpy.reference.generated.numpy.polynomial.hermite.hermder |
numpy.polynomial.hermite.hermdiv polynomial.hermite.hermdiv(c1, c2)[source]
Divide one Hermite series by another. Returns the quotient-with-remainder of two Hermite series c1 / c2. The arguments are sequences of coefficients from lowest order “term” to highest, e.g., [1,2,3] represents the series P_0 + 2*P_1 + 3*P_... | numpy.reference.generated.numpy.polynomial.hermite.hermdiv |
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