doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
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numpy.distutils.misc_util.get_ext_source_files(ext)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_ext_source_files |
numpy.distutils.misc_util.get_frame(level=0)[source]
Return frame object from call stack with given level. | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_frame |
numpy.distutils.misc_util.get_info(pkgname, dirs=None)[source]
Return an info dict for a given C library. The info dict contains the necessary options to use the C library. Parameters
pkgnamestr
Name of the package (should match the name of the .ini file, without the extension, e.g. foo for the file foo.ini). ... | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_info |
numpy.distutils.misc_util.get_language(sources)[source]
Determine language value (c,f77,f90) from sources | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_language |
numpy.distutils.misc_util.get_lib_source_files(lib)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_lib_source_files |
numpy.distutils.misc_util.get_mathlibs(path=None)[source]
Return the MATHLIB line from numpyconfig.h | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_mathlibs |
numpy.distutils.misc_util.get_num_build_jobs()[source]
Get number of parallel build jobs set by the –parallel command line argument of setup.py If the command did not receive a setting the environment variable NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of processors on the system, with a maxim... | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_num_build_jobs |
numpy.distutils.misc_util.get_numpy_include_dirs()[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_numpy_include_dirs |
numpy.distutils.misc_util.get_pkg_info(pkgname, dirs=None)[source]
Return library info for the given package. Parameters
pkgnamestr
Name of the package (should match the name of the .ini file, without the extension, e.g. foo for the file foo.ini).
dirssequence, optional
If given, should be a sequence of add... | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_pkg_info |
numpy.distutils.misc_util.get_script_files(scripts)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.get_script_files |
numpy.distutils.misc_util.gpaths(paths, local_path='', include_non_existing=True)[source]
Apply glob to paths and prepend local_path if needed. | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.gpaths |
numpy.distutils.misc_util.green_text(s)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.green_text |
numpy.distutils.misc_util.has_cxx_sources(sources)[source]
Return True if sources contains C++ files | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.has_cxx_sources |
numpy.distutils.misc_util.has_f_sources(sources)[source]
Return True if sources contains Fortran files | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.has_f_sources |
numpy.distutils.misc_util.is_local_src_dir(directory)[source]
Return true if directory is local directory. | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.is_local_src_dir |
numpy.distutils.misc_util.is_sequence(seq)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.is_sequence |
numpy.distutils.misc_util.is_string(s)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.is_string |
numpy.distutils.misc_util.mingw32()[source]
Return true when using mingw32 environment. | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.mingw32 |
numpy.distutils.misc_util.minrelpath(path)[source]
Resolve and ‘.’ from path. | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.minrelpath |
numpy.distutils.misc_util.njoin(*path)[source]
Join two or more pathname components + - convert a /-separated pathname to one using the OS’s path separator. - resolve and from path. Either passing n arguments as in njoin(‘a’,’b’), or a sequence of n names as in njoin([‘a’,’b’]) is handled, or a mixture of such argu... | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.njoin |
numpy.distutils.misc_util.red_text(s)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.red_text |
numpy.distutils.misc_util.sanitize_cxx_flags(cxxflags)[source]
Some flags are valid for C but not C++. Prune them. | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.sanitize_cxx_flags |
numpy.distutils.misc_util.terminal_has_colors()[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.terminal_has_colors |
numpy.distutils.misc_util.yellow_text(s)[source] | numpy.reference.distutils.misc_util#numpy.distutils.misc_util.yellow_text |
numpy.divide numpy.divide(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'true_divide'>
Returns a true division of the inputs, element-wise. Unlike ‘floor division’, true division adjusts the output type to present the best answer, regardles... | numpy.reference.generated.numpy.divide |
numpy.divmod numpy.divmod(x1, x2, [out1, out2, ]/, [out=(None, None), ]*, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'divmod'>
Return element-wise quotient and remainder simultaneously. New in version 1.13.0. np.divmod(x, y) is equivalent to (x // y, x % y), ... | numpy.reference.generated.numpy.divmod |
numpy.dot numpy.dot(a, b, out=None)
Dot product of two arrays. Specifically, If both a and b are 1-D arrays, it is inner product of vectors (without complex conjugation). If both a and b are 2-D arrays, it is matrix multiplication, but using matmul or a @ b is preferred. If either a or b is 0-D (scalar), it is equ... | numpy.reference.generated.numpy.dot |
class numpy.double(x=0, /)[source]
Double-precision floating-point number type, compatible with Python float and C double. Character code
'd' Alias
numpy.float_ Alias on this platform (Linux x86_64)
numpy.float64: 64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa. | numpy.reference.arrays.scalars#numpy.double |
numpy.dsplit numpy.dsplit(ary, indices_or_sections)[source]
Split array into multiple sub-arrays along the 3rd axis (depth). Please refer to the split documentation. dsplit is equivalent to split with axis=2, the array is always split along the third axis provided the array dimension is greater than or equal to 3. ... | numpy.reference.generated.numpy.dsplit |
numpy.dstack numpy.dstack(tup)[source]
Stack arrays in sequence depth wise (along third axis). This is equivalent to concatenation along the third axis after 2-D arrays of shape (M,N) have been reshaped to (M,N,1) and 1-D arrays of shape (N,) have been reshaped to (1,N,1). Rebuilds arrays divided by dsplit. This fu... | numpy.reference.generated.numpy.dstack |
numpy.dtype class numpy.dtype(dtype, align=False, copy=False)[source]
Create a data type object. A numpy array is homogeneous, and contains elements described by a dtype object. A dtype object can be constructed from different combinations of fundamental numeric types. Parameters
dtype
Object to be converted to... | numpy.reference.generated.numpy.dtype |
numpy.e
Euler’s constant, base of natural logarithms, Napier’s constant. e = 2.71828182845904523536028747135266249775724709369995... See Also exp : Exponential function log : Natural logarithm References https://en.wikipedia.org/wiki/E_%28mathematical_constant%29 | numpy.reference.constants#numpy.e |
numpy.ediff1d numpy.ediff1d(ary, to_end=None, to_begin=None)[source]
The differences between consecutive elements of an array. Parameters
aryarray_like
If necessary, will be flattened before the differences are taken.
to_endarray_like, optional
Number(s) to append at the end of the returned differences. ... | numpy.reference.generated.numpy.ediff1d |
numpy.einsum numpy.einsum(subscripts, *operands, out=None, dtype=None, order='K', casting='safe', optimize=False)[source]
Evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional, linear algebraic array operations can be represented in a sim... | numpy.reference.generated.numpy.einsum |
numpy.einsum_path numpy.einsum_path(subscripts, *operands, optimize='greedy')[source]
Evaluates the lowest cost contraction order for an einsum expression by considering the creation of intermediate arrays. Parameters
subscriptsstr
Specifies the subscripts for summation.
*operandslist of array_like
These ... | numpy.reference.generated.numpy.einsum_path |
numpy.empty numpy.empty(shape, dtype=float, order='C', *, like=None)
Return a new array of given shape and type, without initializing entries. Parameters
shapeint or tuple of int
Shape of the empty array, e.g., (2, 3) or 2.
dtypedata-type, optional
Desired output data-type for the array, e.g, numpy.int8. ... | numpy.reference.generated.numpy.empty |
numpy.empty_like numpy.empty_like(prototype, dtype=None, order='K', subok=True, shape=None)
Return a new array with the same shape and type as a given array. Parameters
prototypearray_like
The shape and data-type of prototype define these same attributes of the returned array.
dtypedata-type, optional
Ove... | numpy.reference.generated.numpy.empty_like |
numpy.equal numpy.equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'equal'>
Return (x1 == x2) element-wise. Parameters
x1, x2array_like
Input arrays. If x1.shape != x2.shape, they must be broadcastable to a common shape (which beco... | numpy.reference.generated.numpy.equal |
numpy.errstate class numpy.errstate(**kwargs)[source]
Context manager for floating-point error handling. Using an instance of errstate as a context manager allows statements in that context to execute with a known error handling behavior. Upon entering the context the error handling is set with seterr and seterrcal... | numpy.reference.generated.numpy.errstate |
numpy.euler_gamma
γ = 0.5772156649015328606065120900824024310421... References https://en.wikipedia.org/wiki/Euler-Mascheroni_constant | numpy.reference.constants#numpy.euler_gamma |
numpy.exp numpy.exp(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'exp'>
Calculate the exponential of all elements in the input array. Parameters
xarray_like
Input values.
outndarray, None, or tuple of ndarray and None, optional
A loca... | numpy.reference.generated.numpy.exp |
numpy.exp2 numpy.exp2(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'exp2'>
Calculate 2**p for all p in the input array. Parameters
xarray_like
Input values.
outndarray, None, or tuple of ndarray and None, optional
A location into whic... | numpy.reference.generated.numpy.exp2 |
numpy.expand_dims numpy.expand_dims(a, axis)[source]
Expand the shape of an array. Insert a new axis that will appear at the axis position in the expanded array shape. Parameters
aarray_like
Input array.
axisint or tuple of ints
Position in the expanded axes where the new axis (or axes) is placed. Deprec... | numpy.reference.generated.numpy.expand_dims |
numpy.expm1 numpy.expm1(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'expm1'>
Calculate exp(x) - 1 for all elements in the array. Parameters
xarray_like
Input values.
outndarray, None, or tuple of ndarray and None, optional
A location... | numpy.reference.generated.numpy.expm1 |
numpy.extract numpy.extract(condition, arr)[source]
Return the elements of an array that satisfy some condition. This is equivalent to np.compress(ravel(condition), ravel(arr)). If condition is boolean np.extract is equivalent to arr[condition]. Note that place does the exact opposite of extract. Parameters
con... | numpy.reference.generated.numpy.extract |
numpy.eye numpy.eye(N, M=None, k=0, dtype=<class 'float'>, order='C', *, like=None)[source]
Return a 2-D array with ones on the diagonal and zeros elsewhere. Parameters
Nint
Number of rows in the output.
Mint, optional
Number of columns in the output. If None, defaults to N.
kint, optional
Index of th... | numpy.reference.generated.numpy.eye |
numpy.f2py.get_include()[source]
Return the directory that contains the fortranobject.c and .h files. Note This function is not needed when building an extension with numpy.distutils directly from .f and/or .pyf files in one go. Python extension modules built with f2py-generated code need to use fortranobject.c as ... | numpy.f2py.usage#numpy.f2py.get_include |
numpy.f2py.run_main(comline_list)[source]
Equivalent to running: f2py <args>
where <args>=string.join(<list>,' '), but in Python. Unless -h is used, this function returns a dictionary containing information on generated modules and their dependencies on source files. For example, the command f2py -m scalar scalar.f ... | numpy.f2py.usage#numpy.f2py.run_main |
numpy.fabs numpy.fabs(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'fabs'>
Compute the absolute values element-wise. This function returns the absolute values (positive magnitude) of the data in x. Complex values are not handled, use absolute t... | numpy.reference.generated.numpy.fabs |
numpy.fill_diagonal numpy.fill_diagonal(a, val, wrap=False)[source]
Fill the main diagonal of the given array of any dimensionality. For an array a with a.ndim >= 2, the diagonal is the list of locations with indices a[i, ..., i] all identical. This function modifies the input array in-place, it does not return a v... | numpy.reference.generated.numpy.fill_diagonal |
numpy.find_common_type numpy.find_common_type(array_types, scalar_types)[source]
Determine common type following standard coercion rules. Parameters
array_typessequence
A list of dtypes or dtype convertible objects representing arrays.
scalar_typessequence
A list of dtypes or dtype convertible objects rep... | numpy.reference.generated.numpy.find_common_type |
numpy.finfo class numpy.finfo(dtype)[source]
Machine limits for floating point types. Parameters
dtypefloat, dtype, or instance
Kind of floating point data-type about which to get information. See also MachAr
The implementation of the tests that produce this information. iinfo
The equivalent for inte... | numpy.reference.generated.numpy.finfo |
numpy.fix numpy.fix(x, out=None)[source]
Round to nearest integer towards zero. Round an array of floats element-wise to nearest integer towards zero. The rounded values are returned as floats. Parameters
xarray_like
An array of floats to be rounded
outndarray, optional
A location into which the result is... | numpy.reference.generated.numpy.fix |
numpy.flatiter class numpy.flatiter[source]
Flat iterator object to iterate over arrays. A flatiter iterator is returned by x.flat for any array x. It allows iterating over the array as if it were a 1-D array, either in a for-loop or by calling its next method. Iteration is done in row-major, C-style order (the las... | numpy.reference.generated.numpy.flatiter |
numpy.flatnonzero numpy.flatnonzero(a)[source]
Return indices that are non-zero in the flattened version of a. This is equivalent to np.nonzero(np.ravel(a))[0]. Parameters
aarray_like
Input data. Returns
resndarray
Output array, containing the indices of the elements of a.ravel() that are non-zero. ... | numpy.reference.generated.numpy.flatnonzero |
class numpy.flexible[source]
Abstract base class of all scalar types without predefined length. The actual size of these types depends on the specific np.dtype instantiation. | numpy.reference.arrays.scalars#numpy.flexible |
numpy.flip numpy.flip(m, axis=None)[source]
Reverse the order of elements in an array along the given axis. The shape of the array is preserved, but the elements are reordered. New in version 1.12.0. Parameters
marray_like
Input array.
axisNone or int or tuple of ints, optional
Axis or axes along which ... | numpy.reference.generated.numpy.flip |
numpy.fliplr numpy.fliplr(m)[source]
Reverse the order of elements along axis 1 (left/right). For a 2-D array, this flips the entries in each row in the left/right direction. Columns are preserved, but appear in a different order than before. Parameters
marray_like
Input array, must be at least 2-D. Return... | numpy.reference.generated.numpy.fliplr |
numpy.flipud numpy.flipud(m)[source]
Reverse the order of elements along axis 0 (up/down). For a 2-D array, this flips the entries in each column in the up/down direction. Rows are preserved, but appear in a different order than before. Parameters
marray_like
Input array. Returns
outarray_like
A view ... | numpy.reference.generated.numpy.flipud |
numpy.float96
numpy.float128[source]
Alias for numpy.longdouble, named after its size in bits. The existence of these aliases depends on the platform. | numpy.reference.arrays.scalars#numpy.float128 |
numpy.float16[source]
alias of numpy.half | numpy.reference.arrays.scalars#numpy.float16 |
numpy.float32[source]
alias of numpy.single | numpy.reference.arrays.scalars#numpy.float32 |
numpy.float64[source]
alias of numpy.double | numpy.reference.arrays.scalars#numpy.float64 |
numpy.float96
numpy.float128[source]
Alias for numpy.longdouble, named after its size in bits. The existence of these aliases depends on the platform. | numpy.reference.arrays.scalars#numpy.float96 |
numpy.float_power numpy.float_power(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'float_power'>
First array elements raised to powers from second array, element-wise. Raise each base in x1 to the positionally-corresponding power in x2. x1 ... | numpy.reference.generated.numpy.float_power |
numpy.floor numpy.floor(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'floor'>
Return the floor of the input, element-wise. The floor of the scalar x is the largest integer i, such that i <= x. It is often denoted as \(\lfloor x \rfloor\). Para... | numpy.reference.generated.numpy.floor |
numpy.floor_divide numpy.floor_divide(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'floor_divide'>
Return the largest integer smaller or equal to the division of the inputs. It is equivalent to the Python // operator and pairs with the Pyt... | numpy.reference.generated.numpy.floor_divide |
numpy.fmax numpy.fmax(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'fmax'>
Element-wise maximum of array elements. Compare two arrays and returns a new array containing the element-wise maxima. If one of the elements being compared is a Na... | numpy.reference.generated.numpy.fmax |
numpy.fmin numpy.fmin(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'fmin'>
Element-wise minimum of array elements. Compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a Na... | numpy.reference.generated.numpy.fmin |
numpy.fmod numpy.fmod(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'fmod'>
Returns the element-wise remainder of division. This is the NumPy implementation of the C library function fmod, the remainder has the same sign as the dividend x1.... | numpy.reference.generated.numpy.fmod |
numpy.format_float_positional numpy.format_float_positional(x, precision=None, unique=True, fractional=True, trim='k', sign=False, pad_left=None, pad_right=None, min_digits=None)[source]
Format a floating-point scalar as a decimal string in positional notation. Provides control over rounding, trimming and padding. ... | numpy.reference.generated.numpy.format_float_positional |
numpy.format_float_scientific numpy.format_float_scientific(x, precision=None, unique=True, trim='k', sign=False, pad_left=None, exp_digits=None, min_digits=None)[source]
Format a floating-point scalar as a decimal string in scientific notation. Provides control over rounding, trimming and padding. Uses and assumes... | numpy.reference.generated.numpy.format_float_scientific |
numpy.format_parser class numpy.format_parser(formats, names, titles, aligned=False, byteorder=None)[source]
Class to convert formats, names, titles description to a dtype. After constructing the format_parser object, the dtype attribute is the converted data-type: dtype = format_parser(formats, names, titles).dtyp... | numpy.reference.generated.numpy.format_parser |
numpy.frexp numpy.frexp(x, [out1, out2, ]/, [out=(None, None), ]*, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'frexp'>
Decompose the elements of x into mantissa and twos exponent. Returns (mantissa, exponent), where x = mantissa * 2**exponent`. The mantissa lie... | numpy.reference.generated.numpy.frexp |
numpy.frombuffer numpy.frombuffer(buffer, dtype=float, count=- 1, offset=0, *, like=None)
Interpret a buffer as a 1-dimensional array. Parameters
bufferbuffer_like
An object that exposes the buffer interface.
dtypedata-type, optional
Data-type of the returned array; default: float.
countint, optional
... | numpy.reference.generated.numpy.frombuffer |
numpy.fromfile numpy.fromfile(file, dtype=float, count=- 1, sep='', offset=0, *, like=None)
Construct an array from data in a text or binary file. A highly efficient way of reading binary data with a known data-type, as well as parsing simply formatted text files. Data written using the tofile method can be read us... | numpy.reference.generated.numpy.fromfile |
numpy.fromfunction numpy.fromfunction(function, shape, *, dtype=<class 'float'>, like=None, **kwargs)[source]
Construct an array by executing a function over each coordinate. The resulting array therefore has a value fn(x, y, z) at coordinate (x, y, z). Parameters
functioncallable
The function is called with ... | numpy.reference.generated.numpy.fromfunction |
numpy.fromiter numpy.fromiter(iter, dtype, count=- 1, *, like=None)
Create a new 1-dimensional array from an iterable object. Parameters
iteriterable object
An iterable object providing data for the array.
dtypedata-type
The data-type of the returned array.
countint, optional
The number of items to re... | numpy.reference.generated.numpy.fromiter |
numpy.frompyfunc numpy.frompyfunc(func, /, nin, nout, *[, identity])
Takes an arbitrary Python function and returns a NumPy ufunc. Can be used, for example, to add broadcasting to a built-in Python function (see Examples section). Parameters
funcPython function object
An arbitrary Python function.
ninint
... | numpy.reference.generated.numpy.frompyfunc |
numpy.fromregex numpy.fromregex(file, regexp, dtype, encoding=None)[source]
Construct an array from a text file, using regular expression parsing. The returned array is always a structured array, and is constructed from all matches of the regular expression in the file. Groups in the regular expression are converte... | numpy.reference.generated.numpy.fromregex |
numpy.fromstring numpy.fromstring(string, dtype=float, count=- 1, *, sep, like=None)
A new 1-D array initialized from text data in a string. Parameters
stringstr
A string containing the data.
dtypedata-type, optional
The data type of the array; default: float. For binary input data, the data must be in ex... | numpy.reference.generated.numpy.fromstring |
numpy.full numpy.full(shape, fill_value, dtype=None, order='C', *, like=None)[source]
Return a new array of given shape and type, filled with fill_value. Parameters
shapeint or sequence of ints
Shape of the new array, e.g., (2, 3) or 2.
fill_valuescalar or array_like
Fill value.
dtypedata-type, optional... | numpy.reference.generated.numpy.full |
numpy.full_like numpy.full_like(a, fill_value, dtype=None, order='K', subok=True, shape=None)[source]
Return a full array 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.
fill_valuescalar
Fill value.
dt... | numpy.reference.generated.numpy.full_like |
numpy.gcd numpy.gcd(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'gcd'>
Returns the greatest common divisor of |x1| and |x2| Parameters
x1, x2array_like, int
Arrays of values. If x1.shape != x2.shape, they must be broadcastable to a ... | numpy.reference.generated.numpy.gcd |
numpy.genfromtxt numpy.genfromtxt(fname, dtype=<class 'float'>, comments='#', delimiter=None, skip_header=0, skip_footer=0, converters=None, missing_values=None, filling_values=None, usecols=None, names=None, excludelist=None, deletechars=" !#$%&'()*+, -./:;<=>?@[\\]^{|}~", replace_space='_', autostrip=False, case_se... | numpy.reference.generated.numpy.genfromtxt |
numpy.geomspace numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0)[source]
Return numbers spaced evenly on a log scale (a geometric progression). This is similar to logspace, but with endpoints specified directly. Each output sample is a constant multiple of the previous. Changed in version 1.... | numpy.reference.generated.numpy.geomspace |
numpy.get_include numpy.get_include()[source]
Return the directory that contains the NumPy *.h header files. Extension modules that need to compile against NumPy should use this function to locate the appropriate include directory. Notes When using distutils, for example in setup.py. import numpy as np
...
Extensio... | numpy.reference.generated.numpy.get_include |
numpy.get_printoptions numpy.get_printoptions()[source]
Return the current print options. Returns
print_optsdict
Dictionary of current print options with keys precision : int threshold : int edgeitems : int linewidth : int suppress : bool nanstr : str infstr : str formatter : dict of callables sign : str Fo... | numpy.reference.generated.numpy.get_printoptions |
numpy.getbufsize numpy.getbufsize()[source]
Return the size of the buffer used in ufuncs. Returns
getbufsizeint
Size of ufunc buffer in bytes. | numpy.reference.generated.numpy.getbufsize |
numpy.geterr numpy.geterr()[source]
Get the current way of handling floating-point errors. Returns
resdict
A dictionary with keys “divide”, “over”, “under”, and “invalid”, whose values are from the strings “ignore”, “print”, “log”, “warn”, “raise”, and “call”. The keys represent possible floating-point except... | numpy.reference.generated.numpy.geterr |
numpy.geterrcall numpy.geterrcall()[source]
Return the current callback function used on floating-point errors. When the error handling for a floating-point error (one of “divide”, “over”, “under”, or “invalid”) is set to ‘call’ or ‘log’, the function that is called or the log instance that is written to is returne... | numpy.reference.generated.numpy.geterrcall |
numpy.geterrobj numpy.geterrobj()
Return the current object that defines floating-point error handling. The error object contains all information that defines the error handling behavior in NumPy. geterrobj is used internally by the other functions that get and set error handling behavior (geterr, seterr, geterrcal... | numpy.reference.generated.numpy.geterrobj |
numpy.gradient numpy.gradient(f, *varargs, axis=None, edge_order=1)[source]
Return the gradient of an N-dimensional array. The gradient is computed using second order accurate central differences in the interior points and either first or second order accurate one-sides (forward or backwards) differences at the bou... | numpy.reference.generated.numpy.gradient |
numpy.greater numpy.greater(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'greater'>
Return the truth value of (x1 > x2) element-wise. Parameters
x1, x2array_like
Input arrays. If x1.shape != x2.shape, they must be broadcastable to a ... | numpy.reference.generated.numpy.greater |
numpy.greater_equal numpy.greater_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'greater_equal'>
Return the truth value of (x1 >= x2) element-wise. Parameters
x1, x2array_like
Input arrays. If x1.shape != x2.shape, they must be ... | numpy.reference.generated.numpy.greater_equal |
class numpy.half[source]
Half-precision floating-point number type. Character code
'e' Alias on this platform (Linux x86_64)
numpy.float16: 16-bit-precision floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa. | numpy.reference.arrays.scalars#numpy.half |
numpy.hamming numpy.hamming(M)[source]
Return the Hamming window. The Hamming window is a taper formed by using a weighted cosine. Parameters
Mint
Number of points in the output window. If zero or less, an empty array is returned. Returns
outndarray
The window, with the maximum value normalized to one... | numpy.reference.generated.numpy.hamming |
numpy.hanning numpy.hanning(M)[source]
Return the Hanning window. The Hanning window is a taper formed by using a weighted cosine. Parameters
Mint
Number of points in the output window. If zero or less, an empty array is returned. Returns
outndarray, shape(M,)
The window, with the maximum value normal... | numpy.reference.generated.numpy.hanning |
numpy.heaviside numpy.heaviside(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'heaviside'>
Compute the Heaviside step function. The Heaviside step function is defined as: 0 if x1 < 0
heaviside(x1, x2) = x2 if x1 =... | numpy.reference.generated.numpy.heaviside |
numpy.histogram numpy.histogram(a, bins=10, range=None, normed=None, weights=None, density=None)[source]
Compute the histogram of a dataset. Parameters
aarray_like
Input data. The histogram is computed over the flattened array.
binsint or sequence of scalars or str, optional
If bins is an int, it defines ... | numpy.reference.generated.numpy.histogram |
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