Participer au site avec un Tip
Rechercher
 

Améliorations / Corrections

Vous avez des améliorations (ou des corrections) à proposer pour ce document : je vous remerçie par avance de m'en faire part, cela m'aide à améliorer le site.

Emplacement :

Description des améliorations :

Contenu du module « numpy »

Liste des classes du module numpy

Nom de la classe Description
bool_ Boolean type (True or False), stored as a byte. [extrait de bool_.__doc__]
broadcast Produce an object that mimics broadcasting. [extrait de broadcast.__doc__]
busdaycalendar busdaycalendar(weekmask='1111100', holidays=None) [extrait de busdaycalendar.__doc__]
bytes_ A byte string. [extrait de bytes_.__doc__]
character Abstract base class of all character string scalar types. [extrait de character.__doc__]
chararray
complex128 Complex number type composed of two double-precision floating-point [extrait de complex128.__doc__]
complex256 Complex number type composed of two extended-precision floating-point [extrait de complex256.__doc__]
complex64 Complex number type composed of two single-precision floating-point [extrait de complex64.__doc__]
complexfloating Abstract base class of all complex number scalar types that are made up of [extrait de complexfloating.__doc__]
DataSource
datetime64 A datetime stored as a 64-bit integer, counting from ``1970-01-01T00:00:00``. [extrait de datetime64.__doc__]
dtype
errstate
finfo
flatiter Flat iterator object to iterate over arrays. [extrait de flatiter.__doc__]
flexible Abstract base class of all scalar types without predefined length. [extrait de flexible.__doc__]
float128 Extended-precision floating-point number type, compatible with C [extrait de float128.__doc__]
float16 Half-precision floating-point number type. [extrait de float16.__doc__]
float32 Single-precision floating-point number type, compatible with C ``float``. [extrait de float32.__doc__]
float64 Double-precision floating-point number type, compatible with Python `float` [extrait de float64.__doc__]
floating Abstract base class of all floating-point scalar types. [extrait de floating.__doc__]
format_parser
generic Base class for numpy scalar types. [extrait de generic.__doc__]
iinfo
inexact Abstract base class of all numeric scalar types with a (potentially) [extrait de inexact.__doc__]
int16 Signed integer type, compatible with C ``short``. [extrait de int16.__doc__]
int32 Signed integer type, compatible with C ``int``. [extrait de int32.__doc__]
int64 Signed integer type, compatible with Python `int` and C ``long``. [extrait de int64.__doc__]
int8 Signed integer type, compatible with C ``char``. [extrait de int8.__doc__]
integer Abstract base class of all integer scalar types. [extrait de integer.__doc__]
longlong Signed integer type, compatible with C ``long long``. [extrait de longlong.__doc__]
MachAr
matrix
memmap Create a memory-map to an array stored in a *binary* file on disk. [extrait de memmap.__doc__]
ndarray ndarray(shape, dtype=float, buffer=None, offset=0, [extrait de ndarray.__doc__]
ndenumerate
ndindex
nditer nditer(op, flags=None, op_flags=None, op_dtypes=None, order='K', casting='safe', op_axes=None, itershape=None, buffersize=0) [extrait de nditer.__doc__]
number Abstract base class of all numeric scalar types. [extrait de number.__doc__]
object_ Any Python object. [extrait de object_.__doc__]
poly1d
recarray Construct an ndarray that allows field access using attributes. [extrait de recarray.__doc__]
record A data-type scalar that allows field access as attribute lookup. [extrait de record.__doc__]
signedinteger Abstract base class of all signed integer scalar types. [extrait de signedinteger.__doc__]
str_ A unicode string. [extrait de str_.__doc__]
timedelta64 A timedelta stored as a 64-bit integer. [extrait de timedelta64.__doc__]
ufunc Functions that operate element by element on whole arrays. [extrait de ufunc.__doc__]
uint16 Unsigned integer type, compatible with C ``unsigned short``. [extrait de uint16.__doc__]
uint32 Unsigned integer type, compatible with C ``unsigned int``. [extrait de uint32.__doc__]
uint64 Unsigned integer type, compatible with C ``unsigned long``. [extrait de uint64.__doc__]
uint8 Unsigned integer type, compatible with C ``unsigned char``. [extrait de uint8.__doc__]
ulonglong Signed integer type, compatible with C ``unsigned long long``. [extrait de ulonglong.__doc__]
unsignedinteger Abstract base class of all unsigned integer scalar types. [extrait de unsignedinteger.__doc__]
vectorize
void Either an opaque sequence of bytes, or a structure. [extrait de void.__doc__]

Liste des exceptions du module numpy

Nom de la classe d'exception Description
AxisError Axis supplied was invalid. [extrait de AxisError.__doc__]
ComplexWarning
ModuleDeprecationWarning Module deprecation warning. [extrait de ModuleDeprecationWarning.__doc__]
RankWarning
TooHardError
VisibleDeprecationWarning Visible deprecation warning. [extrait de VisibleDeprecationWarning.__doc__]

Liste des fonctions du module numpy

Signature de la fonction Description
absolute absolute(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de absolute.__doc__]
add add(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de add.__doc__]
add_docstring add_docstring(obj, docstring) [extrait de add_docstring.__doc__]
add_newdoc(place, obj, doc, warn_on_python=True)
alen(a)
all(a, axis=None, out=None, keepdims=<no value>, *, where=<no value>)
allclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)
alltrue(*args, **kwargs)
amax(a, axis=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
amin(a, axis=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
angle(z, deg=False)
any(a, axis=None, out=None, keepdims=<no value>, *, where=<no value>)
append(arr, values, axis=None)
apply_along_axis(func1d, axis, arr, *args, **kwargs)
apply_over_axes(func, a, axes)
arange arange([start,] stop[, step,], dtype=None, *, like=None) [extrait de arange.__doc__]
arccos arccos(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arccos.__doc__]
arccosh arccosh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arccosh.__doc__]
arcsin arcsin(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arcsin.__doc__]
arcsinh arcsinh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arcsinh.__doc__]
arctan arctan(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arctan.__doc__]
arctan2 arctan2(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arctan2.__doc__]
arctanh arctanh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de arctanh.__doc__]
argmax(a, axis=None, out=None)
argmin(a, axis=None, out=None)
argpartition(a, kth, axis=-1, kind='introselect', order=None)
argsort(a, axis=-1, kind=None, order=None)
argwhere(a)
around(a, decimals=0, out=None)
array array(object, dtype=None, *, copy=True, order='K', subok=False, ndmin=0, [extrait de array.__doc__]
array2string(a, max_line_width=None, precision=None, suppress_small=None, separator=' ', prefix='', style=<no value>, formatter=None, threshold=None, edgeitems=None, sign=None, floatmode=None, suffix='', *, legacy=None)
array_equal(a1, a2, equal_nan=False)
array_equiv(a1, a2)
array_repr(arr, max_line_width=None, precision=None, suppress_small=None)
array_split(ary, indices_or_sections, axis=0)
array_str(a, max_line_width=None, precision=None, suppress_small=None)
asanyarray(a, dtype=None, order=None, *, like=None) Convert the input to an ndarray, but pass ndarray subclasses through. [extrait de asanyarray.__doc__]
asarray(a, dtype=None, order=None, *, like=None) Convert the input to an array. [extrait de asarray.__doc__]
asarray_chkfinite(a, dtype=None, order=None) Convert the input to an array, checking for NaNs or Infs. [extrait de asarray_chkfinite.__doc__]
ascontiguousarray(a, dtype=None, *, like=None)
asfarray(a, dtype=<class 'numpy.float64'>)
asfortranarray(a, dtype=None, *, like=None)
asmatrix(data, dtype=None)
asscalar(a)
atleast_1d(*arys)
atleast_2d(*arys)
atleast_3d(*arys)
average(a, axis=None, weights=None, returned=False)
bartlett(M)
base_repr(number, base=2, padding=0)
binary_repr(num, width=None)
bincount
bitwise_and bitwise_and(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de bitwise_and.__doc__]
bitwise_or bitwise_or(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de bitwise_or.__doc__]
bitwise_xor bitwise_xor(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de bitwise_xor.__doc__]
blackman(M)
block(arrays)
bmat(obj, ldict=None, gdict=None)
broadcast_arrays(*args, subok=False)
broadcast_shapes(*args)
broadcast_to(array, shape, subok=False) Broadcast an array to a new shape. [extrait de broadcast_to.__doc__]
busday_count
busday_offset
byte_bounds(a)
can_cast
cbrt cbrt(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de cbrt.__doc__]
ceil ceil(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de ceil.__doc__]
choose(a, choices, out=None, mode='raise')
clip(a, a_min, a_max, out=None, **kwargs)
column_stack(tup)
common_type(*arrays)
compare_chararrays compare_chararrays(a, b, cmp_op, rstrip) [extrait de compare_chararrays.__doc__]
compress(condition, a, axis=None, out=None)
concatenate
conjugate conjugate(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de conjugate.__doc__]
convolve(a, v, mode='full')
copy(a, order='K', subok=False)
copysign copysign(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de copysign.__doc__]
copyto
corrcoef(x, y=None, rowvar=True, bias=<no value>, ddof=<no value>, *, dtype=None)
correlate(a, v, mode='valid')
cos cos(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de cos.__doc__]
cosh cosh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de cosh.__doc__]
count_nonzero(a, axis=None, *, keepdims=False)
cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, aweights=None, *, dtype=None)
cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None)
cumprod(a, axis=None, dtype=None, out=None)
cumproduct(*args, **kwargs)
cumsum(a, axis=None, dtype=None, out=None)
datetime_as_string
datetime_data datetime_data(dtype, /) [extrait de datetime_data.__doc__]
deg2rad deg2rad(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de deg2rad.__doc__]
degrees degrees(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de degrees.__doc__]
delete(arr, obj, axis=None)
deprecate(*args, **kwargs)
diag(v, k=0)
diag_indices(n, ndim=2)
diag_indices_from(arr)
diagflat(v, k=0)
diagonal(a, offset=0, axis1=0, axis2=1)
diff(a, n=1, axis=-1, prepend=<no value>, append=<no value>)
digitize(x, bins, right=False)
disp(mesg, device=None, linefeed=True)
divmod divmod(x1, x2[, out1, out2], / [, out=(None, None)], *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de divmod.__doc__]
dot
dsplit(ary, indices_or_sections)
dstack(tup)
ediff1d(ary, to_end=None, to_begin=None)
einsum(*operands, out=None, optimize=False, **kwargs)
einsum_path(*operands, optimize='greedy', einsum_call=False)
empty empty(shape, dtype=float, order='C', *, like=None) [extrait de empty.__doc__]
empty_like
equal equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de equal.__doc__]
exp exp(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de exp.__doc__]
exp2 exp2(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de exp2.__doc__]
expand_dims(a, axis)
expm1 expm1(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de expm1.__doc__]
extract(condition, arr)
eye(N, M=None, k=0, dtype=<class 'float'>, order='C', *, like=None)
fabs fabs(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de fabs.__doc__]
fill_diagonal(a, val, wrap=False) Fill the main diagonal of the given array of any dimensionality. [extrait de fill_diagonal.__doc__]
find_common_type(array_types, scalar_types)
fix(x, out=None)
flatnonzero(a)
flip(m, axis=None)
fliplr(m)
flipud(m)
float_power float_power(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de float_power.__doc__]
floor floor(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de floor.__doc__]
floor_divide floor_divide(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de floor_divide.__doc__]
fmax fmax(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de fmax.__doc__]
fmin fmin(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de fmin.__doc__]
fmod fmod(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de fmod.__doc__]
format_float_positional(x, precision=None, unique=True, fractional=True, trim='k', sign=False, pad_left=None, pad_right=None)
format_float_scientific(x, precision=None, unique=True, trim='k', sign=False, pad_left=None, exp_digits=None)
frexp frexp(x[, out1, out2], / [, out=(None, None)], *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de frexp.__doc__]
frombuffer frombuffer(buffer, dtype=float, count=-1, offset=0, *, like=None) [extrait de frombuffer.__doc__]
fromfile fromfile(file, dtype=float, count=-1, sep='', offset=0, *, like=None) [extrait de fromfile.__doc__]
fromfunction(function, shape, *, dtype=<class 'float'>, like=None, **kwargs)
fromiter fromiter(iterable, dtype, count=-1, *, like=None) [extrait de fromiter.__doc__]
frompyfunc frompyfunc(func, nin, nout, *[, identity]) [extrait de frompyfunc.__doc__]
fromregex(file, regexp, dtype, encoding=None)
fromstring fromstring(string, dtype=float, count=-1, sep='', *, like=None) [extrait de fromstring.__doc__]
full(shape, fill_value, dtype=None, order='C', *, like=None)
full_like(a, fill_value, dtype=None, order='K', subok=True, shape=None)
gcd gcd(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de gcd.__doc__]
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_sensitive=True, defaultfmt='f%i', unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None, encoding='bytes', *, like=None)
geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0)
get_array_wrap(*args) Find the wrapper for the array with the highest priority. [extrait de get_array_wrap.__doc__]
get_include()
get_printoptions()
getbufsize()
geterr()
geterrcall()
geterrobj geterrobj() [extrait de geterrobj.__doc__]
gradient(f, *varargs, axis=None, edge_order=1)
greater greater(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de greater.__doc__]
greater_equal greater_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de greater_equal.__doc__]
hamming(M)
hanning(M)
heaviside heaviside(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de heaviside.__doc__]
histogram(a, bins=10, range=None, normed=None, weights=None, density=None)
histogram2d(x, y, bins=10, range=None, normed=None, weights=None, density=None)
histogram_bin_edges(a, bins=10, range=None, weights=None)
histogramdd(sample, bins=10, range=None, normed=None, weights=None, density=None)
hsplit(ary, indices_or_sections)
hstack(tup)
hypot hypot(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de hypot.__doc__]
i0(x)
identity(n, dtype=None, *, like=None)
imag(val)
in1d(ar1, ar2, assume_unique=False, invert=False)
indices(dimensions, dtype=<class 'int'>, sparse=False)
info(object=None, maxwidth=76, output=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, toplevel='numpy')
inner
insert(arr, obj, values, axis=None)
interp(x, xp, fp, left=None, right=None, period=None)
intersect1d(ar1, ar2, assume_unique=False, return_indices=False)
invert invert(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de invert.__doc__]
is_busday
isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)
iscomplex(x)
iscomplexobj(x)
isfinite isfinite(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de isfinite.__doc__]
isfortran(a)
isin(element, test_elements, assume_unique=False, invert=False)
isinf isinf(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de isinf.__doc__]
isnan isnan(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de isnan.__doc__]
isnat isnat(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de isnat.__doc__]
isneginf(x, out=None)
isposinf(x, out=None)
isreal(x)
isrealobj(x)
isscalar(element)
issctype(rep)
issubclass_(arg1, arg2)
issubdtype(arg1, arg2)
issubsctype(arg1, arg2)
iterable(y)
ix_(*args)
kaiser(M, beta)
kron(a, b)
lcm lcm(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de lcm.__doc__]
ldexp ldexp(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de ldexp.__doc__]
left_shift left_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de left_shift.__doc__]
less less(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de less.__doc__]
less_equal less_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de less_equal.__doc__]
lexsort
linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)
load(file, mmap_mode=None, allow_pickle=False, fix_imports=True, encoding='ASCII')
loads(*args, **kwargs)
loadtxt(fname, dtype=<class 'float'>, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0, encoding='bytes', max_rows=None, *, like=None)
log log(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de log.__doc__]
log10 log10(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de log10.__doc__]
log1p log1p(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de log1p.__doc__]
log2 log2(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de log2.__doc__]
logaddexp logaddexp(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de logaddexp.__doc__]
logaddexp2 logaddexp2(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de logaddexp2.__doc__]
logical_and logical_and(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de logical_and.__doc__]
logical_not logical_not(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de logical_not.__doc__]
logical_or logical_or(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de logical_or.__doc__]
logical_xor logical_xor(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de logical_xor.__doc__]
logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0)
lookfor(what, module=None, import_modules=True, regenerate=False, output=None)
mafromtxt(fname, **kwargs)
mask_indices(n, mask_func, k=0)
matmul matmul(x1, x2, /, out=None, *, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de matmul.__doc__]
maximum maximum(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de maximum.__doc__]
maximum_sctype(t)
may_share_memory
mean(a, axis=None, dtype=None, out=None, keepdims=<no value>, *, where=<no value>)
median(a, axis=None, out=None, overwrite_input=False, keepdims=False)
meshgrid(*xi, copy=True, sparse=False, indexing='xy')
min_scalar_type
minimum minimum(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de minimum.__doc__]
mintypecode(typechars, typeset='GDFgdf', default='d')
modf modf(x[, out1, out2], / [, out=(None, None)], *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de modf.__doc__]
moveaxis(a, source, destination)
msort(a)
multiply multiply(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de multiply.__doc__]
nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None)
nanargmax(a, axis=None)
nanargmin(a, axis=None)
nancumprod(a, axis=None, dtype=None, out=None)
nancumsum(a, axis=None, dtype=None, out=None)
nanmax(a, axis=None, out=None, keepdims=<no value>)
nanmean(a, axis=None, dtype=None, out=None, keepdims=<no value>)
nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=<no value>)
nanmin(a, axis=None, out=None, keepdims=<no value>)
nanpercentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=<no value>)
nanprod(a, axis=None, dtype=None, out=None, keepdims=<no value>)
nanquantile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=<no value>)
nanstd(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>)
nansum(a, axis=None, dtype=None, out=None, keepdims=<no value>)
nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>)
ndfromtxt(fname, **kwargs)
ndim(a)
negative negative(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de negative.__doc__]
nested_iters Create nditers for use in nested loops [extrait de nested_iters.__doc__]
nextafter nextafter(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de nextafter.__doc__]
nonzero(a)
not_equal not_equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de not_equal.__doc__]
obj2sctype(rep, default=None)
ones(shape, dtype=None, order='C', *, like=None)
ones_like(a, dtype=None, order='K', subok=True, shape=None)
outer(a, b, out=None)
packbits
pad(array, pad_width, mode='constant', **kwargs)
partition(a, kth, axis=-1, kind='introselect', order=None)
percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False)
piecewise(x, condlist, funclist, *args, **kw)
place(arr, mask, vals)
poly(seq_of_zeros)
polyadd(a1, a2)
polyder(p, m=1)
polydiv(u, v)
polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False)
polyint(p, m=1, k=None)
polymul(a1, a2)
polysub(a1, a2)
polyval(p, x)
positive positive(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de positive.__doc__]
power power(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de power.__doc__]
printoptions(*args, **kwargs) Context manager for setting print options. [extrait de printoptions.__doc__]
prod(a, axis=None, dtype=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
product(*args, **kwargs)
promote_types promote_types(type1, type2) [extrait de promote_types.__doc__]
ptp(a, axis=None, out=None, keepdims=<no value>)
put(a, ind, v, mode='raise')
put_along_axis(arr, indices, values, axis)
putmask
quantile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False)
rad2deg rad2deg(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de rad2deg.__doc__]
radians radians(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de radians.__doc__]
ravel(a, order='C') Return a contiguous flattened array. [extrait de ravel.__doc__]
ravel_multi_index
real(val)
real_if_close(a, tol=100)
recfromcsv(fname, **kwargs)
recfromtxt(fname, **kwargs)
reciprocal reciprocal(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de reciprocal.__doc__]
remainder remainder(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de remainder.__doc__]
repeat(a, repeats, axis=None)
require(a, dtype=None, requirements=None, *, like=None)
reshape(a, newshape, order='C')
resize(a, new_shape)
result_type
right_shift right_shift(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de right_shift.__doc__]
rint rint(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de rint.__doc__]
roll(a, shift, axis=None)
rollaxis(a, axis, start=0)
roots(p)
rot90(m, k=1, axes=(0, 1))
round_(a, decimals=0, out=None)
safe_eval(source)
save(file, arr, allow_pickle=True, fix_imports=True)
savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='\n', header='', footer='', comments='# ', encoding=None)
savez(file, *args, **kwds) Save several arrays into a single file in uncompressed ``.npz`` format. [extrait de savez.__doc__]
savez_compressed(file, *args, **kwds)
sctype2char(sctype)
searchsorted(a, v, side='left', sorter=None)
select(condlist, choicelist, default=0)
set_numeric_ops set_numeric_ops(op1=func1, op2=func2, ...) [extrait de set_numeric_ops.__doc__]
set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, suppress=None, nanstr=None, infstr=None, formatter=None, sign=None, floatmode=None, *, legacy=None)
set_string_function(f, repr=True)
setbufsize(size)
setdiff1d(ar1, ar2, assume_unique=False)
seterr(all=None, divide=None, over=None, under=None, invalid=None)
seterrcall(func)
seterrobj seterrobj(errobj) [extrait de seterrobj.__doc__]
setxor1d(ar1, ar2, assume_unique=False)
shape(a)
shares_memory
sign sign(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de sign.__doc__]
signbit signbit(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de signbit.__doc__]
sin sin(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de sin.__doc__]
sinc(x)
sinh sinh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de sinh.__doc__]
size(a, axis=None)
sometrue(*args, **kwargs)
sort(a, axis=-1, kind=None, order=None)
sort_complex(a)
source(object, output=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>)
spacing spacing(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de spacing.__doc__]
split(ary, indices_or_sections, axis=0)
sqrt sqrt(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de sqrt.__doc__]
square square(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de square.__doc__]
squeeze(a, axis=None)
stack(arrays, axis=0, out=None)
std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>, *, where=<no value>)
subtract subtract(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de subtract.__doc__]
sum(a, axis=None, dtype=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
swapaxes(a, axis1, axis2)
take(a, indices, axis=None, out=None, mode='raise')
take_along_axis(arr, indices, axis)
tan tan(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de tan.__doc__]
tanh tanh(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de tanh.__doc__]
tensordot(a, b, axes=2)
test(label='fast', verbose=1, extra_argv=None, doctests=False, coverage=False, durations=-1, tests=None)
tile(A, reps)
trace(a, offset=0, axis1=0, axis2=1, dtype=None, out=None)
transpose(a, axes=None)
trapz(y, x=None, dx=1.0, axis=-1)
tri(N, M=None, k=0, dtype=<class 'float'>, *, like=None)
tril(m, k=0)
tril_indices(n, k=0, m=None)
tril_indices_from(arr, k=0)
trim_zeros(filt, trim='fb')
triu(m, k=0)
triu_indices(n, k=0, m=None)
triu_indices_from(arr, k=0)
true_divide true_divide(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de true_divide.__doc__]
trunc trunc(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) [extrait de trunc.__doc__]
typename(char)
union1d(ar1, ar2)
unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None)
unpackbits
unravel_index
unwrap(p, discont=3.141592653589793, axis=-1)
vander(x, N=None, increasing=False)
var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=<no value>, *, where=<no value>)
vdot
vsplit(ary, indices_or_sections)
vstack(tup)
where
who(vardict=None)
zeros zeros(shape, dtype=float, order='C', *, like=None) [extrait de zeros.__doc__]
zeros_like(a, dtype=None, order='K', subok=True, shape=None)

Liste des variables globales du module numpy

Nom de la variable globale Valeur
ALLOW_THREADS 1
BUFSIZE 8192
c_ <numpy.lib.index_tricks.CClass object at 0x7f5076a93790>
cast {<class 'numpy.complex256'>: <function <lambda> at 0x7f5077266e50>, <class 'numpy.float128'>: <function <lambda> at 0x7f5077266f70>, <class 'numpy.uint64'>: <function <lambda> at 0x7f5077269040>, <class 'numpy.int64'>: <function <lambda> at 0x7f50772690d0>, <class 'numpy.str_'>: <function <lambda> at 0x7f5077269160>, <class 'numpy.complex128'>: <function <lambda> at 0x7f50772691f0>, <class 'numpy.float64'>: <function <lambda> at 0x7f5077269280>, <class 'numpy.uint32'>: <function <lambda> at 0x7f5077269310>, <class 'numpy.int32'>: <function <lambda> at 0x7f50772693a0>, <class 'numpy.bytes_'>: <function <lambda> at 0x7f5077269430>, <class 'numpy.complex64'>: <function <lambda> at 0x7f50772694c0>, <class 'numpy.float32'>: <function <lambda> at 0x7f5077269550>, <class 'numpy.uint16'>: <function <lambda> at 0x7f50772695e0>, <class 'numpy.int16'>: <function <lambda> at 0x7f5077269670>, <class 'numpy.bool_'>: <function <lambda> at 0x7f5077269700>, <class 'numpy.timedelta64'>: <function <lambda> at 0x7f5077269790>, <class 'numpy.float16'>: <function <lambda> at 0x7f5077269820>, <class 'numpy.uint8'>: <function <lambda> at 0x7f50772698b0>, <class 'numpy.int8'>: <function <lambda> at 0x7f5077269940>, <class 'numpy.object_'>: <function <lambda> at 0x7f50772699d0>, <class 'numpy.datetime64'>: <function <lambda> at 0x7f5077269a60>, <class 'numpy.ulonglong'>: <function <lambda> at 0x7f5077269af0>, <class 'numpy.longlong'>: <function <lambda> at 0x7f5077269b80>, <class 'numpy.void'>: <function <lambda> at 0x7f5077269c10>}
CLIP 0
e 2.718281828459045
ERR_CALL 3
ERR_DEFAULT 521
ERR_IGNORE 0
ERR_LOG 5
ERR_PRINT 4
ERR_RAISE 2
ERR_WARN 1
euler_gamma 0.5772156649015329
False_ False
FLOATING_POINT_SUPPORT 1
FPE_DIVIDEBYZERO 1
FPE_INVALID 8
FPE_OVERFLOW 2
FPE_UNDERFLOW 4
index_exp <numpy.lib.index_tricks.IndexExpression object at 0x7f5076a93250>
Inf inf
inf inf
Infinity inf
infty inf
kernel_version (5, 12)
little_endian True
MAXDIMS 32
MAY_SHARE_BOUNDS 0
MAY_SHARE_EXACT -1
mgrid <numpy.lib.index_tricks.MGridClass object at 0x7f5076a93070>
NAN nan
NaN nan
nan nan
nbytes {<class 'numpy.bool_'>: 1, <class 'numpy.int8'>: 1, <class 'numpy.uint8'>: 1, <class 'numpy.int16'>: 2, <class 'numpy.uint16'>: 2, <class 'numpy.int32'>: 4, <class 'numpy.uint32'>: 4, <class 'numpy.int64'>: 8, <class 'numpy.uint64'>: 8, <class 'numpy.longlong'>: 8, <class 'numpy.ulonglong'>: 8, <class 'numpy.float16'>: 2, <class 'numpy.float32'>: 4, <class 'numpy.float64'>: 8, <class 'numpy.float128'>: 16, <class 'numpy.complex64'>: 8, <class 'numpy.complex128'>: 16, <class 'numpy.complex256'>: 32, <class 'numpy.object_'>: 8, <class 'numpy.bytes_'>: 0, <class 'numpy.str_'>: 0, <class 'numpy.void'>: 0, <class 'numpy.datetime64'>: 8, <class 'numpy.timedelta64'>: 8}
newaxis None
NINF -inf
numarray removed
NZERO -0.0
ogrid <numpy.lib.index_tricks.OGridClass object at 0x7f5076a931c0>
oldnumeric removed
pi 3.141592653589793
PINF inf
PZERO 0.0
r_ <numpy.lib.index_tricks.RClass object at 0x7f5076a93b80>
RAISE 2
s_ <numpy.lib.index_tricks.IndexExpression object at 0x7f5076a93850>
ScalarType (<class 'int'>, <class 'float'>, <class 'complex'>, <class 'int'>, <class 'bool'>, <class 'bytes'>, <class 'str'>, <class 'memoryview'>, <class 'numpy.complex256'>, <class 'numpy.float128'>, <class 'numpy.uint64'>, <class 'numpy.int64'>, <class 'numpy.str_'>, <class 'numpy.complex128'>, <class 'numpy.float64'>, <class 'numpy.uint32'>, <class 'numpy.int32'>, <class 'numpy.bytes_'>, <class 'numpy.complex64'>, <class 'numpy.float32'>, <class 'numpy.uint16'>, <class 'numpy.int16'>, <class 'numpy.bool_'>, <class 'numpy.timedelta64'>, <class 'numpy.float16'>, <class 'numpy.uint8'>, <class 'numpy.int8'>, <class 'numpy.object_'>, <class 'numpy.datetime64'>, <class 'numpy.ulonglong'>, <class 'numpy.longlong'>, <class 'numpy.void'>)
sctypeDict {'?': <class 'numpy.bool_'>, 0: <class 'numpy.bool_'>, 'byte': <class 'numpy.int8'>, 'b': <class 'numpy.int8'>, 1: <class 'numpy.int8'>, 'ubyte': <class 'numpy.uint8'>, 'B': <class 'numpy.uint8'>, 2: <class 'numpy.uint8'>, 'short': <class 'numpy.int16'>, 'h': <class 'numpy.int16'>, 3: <class 'numpy.int16'>, 'ushort': <class 'numpy.uint16'>, 'H': <class 'numpy.uint16'>, 4: <class 'numpy.uint16'>, 'i': <class 'numpy.int32'>, 5: <class 'numpy.int32'>, 'uint': <class 'numpy.uint64'>, 'I': <class 'numpy.uint32'>, 6: <class 'numpy.uint32'>, 'intp': <class 'numpy.int64'>, 'p': <class 'numpy.int64'>, 7: <class 'numpy.int64'>, 'uintp': <class 'numpy.uint64'>, 'P': <class 'numpy.uint64'>, 8: <class 'numpy.uint64'>, 'long': <class 'numpy.int64'>, 'l': <class 'numpy.int64'>, 'L': <class 'numpy.uint64'>, 'longlong': <class 'numpy.longlong'>, 'q': <class 'numpy.longlong'>, 9: <class 'numpy.longlong'>, 'ulonglong': <class 'numpy.ulonglong'>, 'Q': <class 'numpy.ulonglong'>, 10: <class 'numpy.ulonglong'>, 'half': <class 'numpy.float16'>, 'e': <class 'numpy.float16'>, 23: <class 'numpy.float16'>, 'f': <class 'numpy.float32'>, 11: <class 'numpy.float32'>, 'double': <class 'numpy.float64'>, 'd': <class 'numpy.float64'>, 12: <class 'numpy.float64'>, 'longdouble': <class 'numpy.float128'>, 'g': <class 'numpy.float128'>, 13: <class 'numpy.float128'>, 'cfloat': <class 'numpy.complex128'>, 'F': <class 'numpy.complex64'>, 14: <class 'numpy.complex64'>, 'cdouble': <class 'numpy.complex128'>, 'D': <class 'numpy.complex128'>, 15: <class 'numpy.complex128'>, 'clongdouble': <class 'numpy.complex256'>, 'G': <class 'numpy.complex256'>, 16: <class 'numpy.complex256'>, 'O': <class 'numpy.object_'>, 17: <class 'numpy.object_'>, 'S': <class 'numpy.bytes_'>, 18: <class 'numpy.bytes_'>, 'unicode': <class 'numpy.str_'>, 'U': <class 'numpy.str_'>, 19: <class 'numpy.str_'>, 'void': <class 'numpy.void'>, 'V': <class 'numpy.void'>, 20: <class 'numpy.void'>, 'M': <class 'numpy.datetime64'>, 21: <class 'numpy.datetime64'>, 'm': <class 'numpy.timedelta64'>, 22: <class 'numpy.timedelta64'>, 'bool8': <class 'numpy.bool_'>, 'b1': <class 'numpy.bool_'>, 'int64': <class 'numpy.int64'>, 'i8': <class 'numpy.int64'>, 'uint64': <class 'numpy.uint64'>, 'u8': <class 'numpy.uint64'>, 'float16': <class 'numpy.float16'>, 'f2': <class 'numpy.float16'>, 'float32': <class 'numpy.float32'>, 'f4': <class 'numpy.float32'>, 'float64': <class 'numpy.float64'>, 'f8': <class 'numpy.float64'>, 'float128': <class 'numpy.float128'>, 'f16': <class 'numpy.float128'>, 'complex64': <class 'numpy.complex64'>, 'c8': <class 'numpy.complex64'>, 'complex128': <class 'numpy.complex128'>, 'c16': <class 'numpy.complex128'>, 'complex256': <class 'numpy.complex256'>, 'c32': <class 'numpy.complex256'>, 'object0': <class 'numpy.object_'>, 'bytes0': <class 'numpy.bytes_'>, 'str0': <class 'numpy.str_'>, 'void0': <class 'numpy.void'>, 'datetime64': <class 'numpy.datetime64'>, 'M8': <class 'numpy.datetime64'>, 'timedelta64': <class 'numpy.timedelta64'>, 'm8': <class 'numpy.timedelta64'>, 'Bytes0': <class 'numpy.bytes_'>, 'Datetime64': <class 'numpy.datetime64'>, 'Str0': <class 'numpy.str_'>, 'Uint64': <class 'numpy.uint64'>, 'int32': <class 'numpy.int32'>, 'i4': <class 'numpy.int32'>, 'uint32': <class 'numpy.uint32'>, 'u4': <class 'numpy.uint32'>, 'int16': <class 'numpy.int16'>, 'i2': <class 'numpy.int16'>, 'uint16': <class 'numpy.uint16'>, 'u2': <class 'numpy.uint16'>, 'int8': <class 'numpy.int8'>, 'i1': <class 'numpy.int8'>, 'uint8': <class 'numpy.uint8'>, 'u1': <class 'numpy.uint8'>, 'complex_': <class 'numpy.complex128'>, 'int0': <class 'numpy.int64'>, 'uint0': <class 'numpy.uint64'>, 'single': <class 'numpy.float32'>, 'csingle': <class 'numpy.complex64'>, 'singlecomplex': <class 'numpy.complex64'>, 'float_': <class 'numpy.float64'>, 'intc': <class 'numpy.int32'>, 'uintc': <class 'numpy.uint32'>, 'int_': <class 'numpy.int64'>, 'longfloat': <class 'numpy.float128'>, 'clongfloat': <class 'numpy.complex256'>, 'longcomplex': <class 'numpy.complex256'>, 'bool_': <class 'numpy.bool_'>, 'bytes_': <class 'numpy.bytes_'>, 'string_': <class 'numpy.bytes_'>, 'str_': <class 'numpy.str_'>, 'unicode_': <class 'numpy.str_'>, 'object_': <class 'numpy.object_'>, 'int': <class 'numpy.int64'>, 'float': <class 'numpy.float64'>, 'complex': <class 'numpy.complex128'>, 'bool': <class 'numpy.bool_'>, 'object': <class 'numpy.object_'>, 'str': <class 'numpy.str_'>, 'bytes': <class 'numpy.bytes_'>, 'a': <class 'numpy.bytes_'>}
sctypes {'int': [<class 'numpy.int8'>, <class 'numpy.int16'>, <class 'numpy.int32'>, <class 'numpy.int64'>], 'uint': [<class 'numpy.uint8'>, <class 'numpy.uint16'>, <class 'numpy.uint32'>, <class 'numpy.uint64'>], 'float': [<class 'numpy.float16'>, <class 'numpy.float32'>, <class 'numpy.float64'>, <class 'numpy.float128'>], 'complex': [<class 'numpy.complex64'>, <class 'numpy.complex128'>, <class 'numpy.complex256'>], 'others': [<class 'bool'>, <class 'object'>, <class 'bytes'>, <class 'str'>, <class 'numpy.void'>]}
SHIFT_DIVIDEBYZERO 0
SHIFT_INVALID 9
SHIFT_OVERFLOW 3
SHIFT_UNDERFLOW 6
tracemalloc_domain 389047
True_ True
typecodes {'Character': 'c', 'Integer': 'bhilqp', 'UnsignedInteger': 'BHILQP', 'Float': 'efdg', 'Complex': 'FDG', 'AllInteger': 'bBhHiIlLqQpP', 'AllFloat': 'efdgFDG', 'Datetime': 'Mm', 'All': '?bhilqpBHILQPefdgFDGSUVOMm'}
typeDict {'?': <class 'numpy.bool_'>, 0: <class 'numpy.bool_'>, 'byte': <class 'numpy.int8'>, 'b': <class 'numpy.int8'>, 1: <class 'numpy.int8'>, 'ubyte': <class 'numpy.uint8'>, 'B': <class 'numpy.uint8'>, 2: <class 'numpy.uint8'>, 'short': <class 'numpy.int16'>, 'h': <class 'numpy.int16'>, 3: <class 'numpy.int16'>, 'ushort': <class 'numpy.uint16'>, 'H': <class 'numpy.uint16'>, 4: <class 'numpy.uint16'>, 'i': <class 'numpy.int32'>, 5: <class 'numpy.int32'>, 'uint': <class 'numpy.uint64'>, 'I': <class 'numpy.uint32'>, 6: <class 'numpy.uint32'>, 'intp': <class 'numpy.int64'>, 'p': <class 'numpy.int64'>, 7: <class 'numpy.int64'>, 'uintp': <class 'numpy.uint64'>, 'P': <class 'numpy.uint64'>, 8: <class 'numpy.uint64'>, 'long': <class 'numpy.int64'>, 'l': <class 'numpy.int64'>, 'L': <class 'numpy.uint64'>, 'longlong': <class 'numpy.longlong'>, 'q': <class 'numpy.longlong'>, 9: <class 'numpy.longlong'>, 'ulonglong': <class 'numpy.ulonglong'>, 'Q': <class 'numpy.ulonglong'>, 10: <class 'numpy.ulonglong'>, 'half': <class 'numpy.float16'>, 'e': <class 'numpy.float16'>, 23: <class 'numpy.float16'>, 'f': <class 'numpy.float32'>, 11: <class 'numpy.float32'>, 'double': <class 'numpy.float64'>, 'd': <class 'numpy.float64'>, 12: <class 'numpy.float64'>, 'longdouble': <class 'numpy.float128'>, 'g': <class 'numpy.float128'>, 13: <class 'numpy.float128'>, 'cfloat': <class 'numpy.complex128'>, 'F': <class 'numpy.complex64'>, 14: <class 'numpy.complex64'>, 'cdouble': <class 'numpy.complex128'>, 'D': <class 'numpy.complex128'>, 15: <class 'numpy.complex128'>, 'clongdouble': <class 'numpy.complex256'>, 'G': <class 'numpy.complex256'>, 16: <class 'numpy.complex256'>, 'O': <class 'numpy.object_'>, 17: <class 'numpy.object_'>, 'S': <class 'numpy.bytes_'>, 18: <class 'numpy.bytes_'>, 'unicode': <class 'numpy.str_'>, 'U': <class 'numpy.str_'>, 19: <class 'numpy.str_'>, 'void': <class 'numpy.void'>, 'V': <class 'numpy.void'>, 20: <class 'numpy.void'>, 'M': <class 'numpy.datetime64'>, 21: <class 'numpy.datetime64'>, 'm': <class 'numpy.timedelta64'>, 22: <class 'numpy.timedelta64'>, 'bool8': <class 'numpy.bool_'>, 'b1': <class 'numpy.bool_'>, 'int64': <class 'numpy.int64'>, 'i8': <class 'numpy.int64'>, 'uint64': <class 'numpy.uint64'>, 'u8': <class 'numpy.uint64'>, 'float16': <class 'numpy.float16'>, 'f2': <class 'numpy.float16'>, 'float32': <class 'numpy.float32'>, 'f4': <class 'numpy.float32'>, 'float64': <class 'numpy.float64'>, 'f8': <class 'numpy.float64'>, 'float128': <class 'numpy.float128'>, 'f16': <class 'numpy.float128'>, 'complex64': <class 'numpy.complex64'>, 'c8': <class 'numpy.complex64'>, 'complex128': <class 'numpy.complex128'>, 'c16': <class 'numpy.complex128'>, 'complex256': <class 'numpy.complex256'>, 'c32': <class 'numpy.complex256'>, 'object0': <class 'numpy.object_'>, 'bytes0': <class 'numpy.bytes_'>, 'str0': <class 'numpy.str_'>, 'void0': <class 'numpy.void'>, 'datetime64': <class 'numpy.datetime64'>, 'M8': <class 'numpy.datetime64'>, 'timedelta64': <class 'numpy.timedelta64'>, 'm8': <class 'numpy.timedelta64'>, 'Bytes0': <class 'numpy.bytes_'>, 'Datetime64': <class 'numpy.datetime64'>, 'Str0': <class 'numpy.str_'>, 'Uint64': <class 'numpy.uint64'>, 'int32': <class 'numpy.int32'>, 'i4': <class 'numpy.int32'>, 'uint32': <class 'numpy.uint32'>, 'u4': <class 'numpy.uint32'>, 'int16': <class 'numpy.int16'>, 'i2': <class 'numpy.int16'>, 'uint16': <class 'numpy.uint16'>, 'u2': <class 'numpy.uint16'>, 'int8': <class 'numpy.int8'>, 'i1': <class 'numpy.int8'>, 'uint8': <class 'numpy.uint8'>, 'u1': <class 'numpy.uint8'>, 'complex_': <class 'numpy.complex128'>, 'int0': <class 'numpy.int64'>, 'uint0': <class 'numpy.uint64'>, 'single': <class 'numpy.float32'>, 'csingle': <class 'numpy.complex64'>, 'singlecomplex': <class 'numpy.complex64'>, 'float_': <class 'numpy.float64'>, 'intc': <class 'numpy.int32'>, 'uintc': <class 'numpy.uint32'>, 'int_': <class 'numpy.int64'>, 'longfloat': <class 'numpy.float128'>, 'clongfloat': <class 'numpy.complex256'>, 'longcomplex': <class 'numpy.complex256'>, 'bool_': <class 'numpy.bool_'>, 'bytes_': <class 'numpy.bytes_'>, 'string_': <class 'numpy.bytes_'>, 'str_': <class 'numpy.str_'>, 'unicode_': <class 'numpy.str_'>, 'object_': <class 'numpy.object_'>, 'int': <class 'numpy.int64'>, 'float': <class 'numpy.float64'>, 'complex': <class 'numpy.complex128'>, 'bool': <class 'numpy.bool_'>, 'object': <class 'numpy.object_'>, 'str': <class 'numpy.str_'>, 'bytes': <class 'numpy.bytes_'>, 'a': <class 'numpy.bytes_'>}
UFUNC_BUFSIZE_DEFAULT 8192
UFUNC_PYVALS_NAME UFUNC_PYVALS
use_hugepage 1
WRAP 1

Liste des alias du module numpy

Nom de l'alias Définition ciblée
Bytes0 bytes_
Datetime64 datetime64
Str0 str_
Tester NoseTester
Uint64 uint64
abs absolute
add_newdoc_ufunc _add_newdoc_ufunc
bitwise_not invert
bool8 bool_
byte int8
bytes0 bytes_
cdouble complex128
cfloat complex128
clongdouble complex256
clongfloat complex256
complex_ complex128
conj conjugate
csingle complex64
deprecate_with_doc <lambda>
divide true_divide
double float64
fastCopyAndTranspose _fastCopyAndTranspose
float_ float64
half float16
int0 int64
int_ int64
intc int32
intp int64
longcomplex complex256
longdouble float128
longfloat float128
mat asmatrix
max amax
min amin
mod remainder
object0 object_
round round_
row_stack vstack
short int16
show_config show
single float32
singlecomplex complex64
str0 str_
string_ bytes_
ubyte uint8
uint uint64
uint0 uint64
uintc uint32
uintp uint64
unicode_ str_
ushort uint16
void0 void