Tessero\Np

apply(string $name, mixed ...$args): mixed

Call a function by its SciPy/NumPy name: Np::apply('log_ndtr', $x).

allclose(mixed $a, mixed $b, mixed $rtol = 1.0E-5, mixed $atol = 1.0E-8, mixed $equalNan = false): mixed

True when two arrays are element-wise equal within a tolerance (numpy.allclose).

append(mixed $arr, mixed $values, mixed $axis = null): mixed

Append values to the end of an array (numpy.append).

argpartition(mixed $a, mixed $kth, ?int $axis = -1): Tessero\NDArray|int|float

Indices that partition the array (numpy.argpartition).

argwhere(mixed $a): mixed

Indices of the non-zero elements, one row per element (numpy.argwhere).

around(mixed $a, mixed $decimals = 0): mixed

Round to the given number of decimals, half to even (numpy.around; an alias of round).

arrayEqual(mixed $a1, mixed $a2, mixed $equalNan = false): mixed

True when two arrays have the same shape and elements (numpy.array_equal).

arrayEquiv(mixed $a1, mixed $a2): mixed

True when two arrays are shape-consistent and equal (numpy.array_equiv).

arraySplit(mixed $ary, mixed $indicesOrSections, mixed $axis = 0): mixed

Split into sections of nearly equal size (numpy.array_split).

asarrayChkfinite(mixed $a, mixed $dtype = null, mixed $order = null): mixed

Convert to array, raising if it contains NaN or Inf (numpy.asarray_chkfinite).

ascontiguousarray(mixed $a, mixed $dtype = null): mixed

A C-contiguous array (ndim >= 1) of the given dtype (numpy.ascontiguousarray).

asfortranarray(mixed $a, mixed $dtype = null): mixed

A contiguous array (ndim >= 1); Tessero has no Fortran memory order, so the values, shape and dtype match numpy.asfortranarray but the memory layout is C order.

atleast1d(mixed ...$arys): mixed

Arrays with at least one dimension; several arguments give a list (numpy.atleast_1d).

atleast2d(mixed ...$arys): mixed

Arrays with at least two dimensions; several arguments give a list (numpy.atleast_2d).

atleast3d(mixed ...$arys): mixed

Arrays with at least three dimensions; several arguments give a list (numpy.atleast_3d).

average(mixed $a, mixed $weights = null, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Weighted average along the given axes (numpy.average).

bartlett(mixed $M): mixed

Bartlett (triangular) window (numpy.bartlett).

bincount(mixed $x, mixed $weights = null, mixed $minlength = 0): mixed

Count (or sum weights of) each non-negative integer (numpy.bincount).

bitwiseAnd(mixed $x1, mixed $x2): mixed

Element-wise bitwise AND of two integer arrays (numpy.bitwise_and).

bitwiseCount(mixed $x): mixed

The number of 1-bits in the absolute value of each integer element, as uint8 (numpy.bitwise_count).

bitwiseOr(mixed $x1, mixed $x2): mixed

Element-wise bitwise OR of two integer arrays (numpy.bitwise_or).

bitwiseXor(mixed $x1, mixed $x2): mixed

Element-wise bitwise XOR of two integer arrays (numpy.bitwise_xor).

blackman(mixed $M): mixed

Blackman window (numpy.blackman).

broadcastArrays(mixed ...$args): mixed

Broadcast arrays against each other (numpy.broadcast_arrays).

broadcastShapes(mixed ...$args): mixed

The broadcast shape of the given shapes (numpy.broadcast_shapes).

broadcastTo(mixed $array, mixed $shape): mixed

Broadcast an array to a shape (numpy.broadcast_to).

canCast(mixed $from_, mixed $to, mixed $casting = 'safe'): mixed

Whether a cast between two dtypes is allowed under a casting rule (numpy.can_cast).

choose(mixed $a, mixed $choices, mixed $mode = 'raise'): mixed

Build an array from an index array and a list of choices (numpy.choose).

columnStack(mixed $tup): mixed

Stack 1-D arrays as columns of a 2-D array (numpy.column_stack).

compress(mixed $condition, mixed $a, mixed $axis = null): mixed

Selected slices along an axis (numpy.compress).

concat(mixed $arrays, mixed $axis = 0, mixed $dtype = null, mixed $casting = 'same_kind'): mixed

Join arrays along an existing axis (numpy.concat, the Array API name of concatenate).

concatenate(mixed $arrays, mixed $axis = 0, mixed $dtype = null, mixed $casting = 'same_kind'): mixed

Join arrays along an existing axis; axis=None flattens them first (numpy.concatenate).

convolve(mixed $a, mixed $v, mixed $mode = 'full'): mixed

Discrete linear convolution of two 1-D sequences (numpy.convolve).

copyto(mixed $dst, mixed $src, mixed $casting = 'same_kind', mixed $where = null): mixed

Copy values into an array, broadcasting, in place (numpy.copyto).

corrcoef(mixed $x, mixed $y = null, mixed $rowvar = true): mixed

Pearson correlation coefficients (numpy.corrcoef).

correlate(mixed $a, mixed $v, mixed $mode = 'valid'): mixed

Cross-correlation of two 1-D sequences (numpy.correlate).

countNonzero(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Number of non-zero values (numpy.count_nonzero).

cov(mixed $m, mixed $y = null, mixed $rowvar = true, mixed $bias = false, mixed $ddof = null, mixed $fweights = null, mixed $aweights = null): mixed

Covariance matrix (numpy.cov).

cross(mixed $a, mixed $b, mixed $axisa = -1, mixed $axisb = -1, mixed $axisc = -1, mixed $axis = null): mixed

Cross product of 3- (or 2-) element vectors (numpy.cross).

cumulativeSimpson(mixed $y, mixed $x = null, mixed $dx = 1.0, mixed $axis = -1, mixed $initial = null): mixed

Running integral by the composite Simpson's rule (scipy.integrate.cumulative_simpson).

cumulativeTrapezoid(mixed $y, mixed $x = null, mixed $dx = 1.0, mixed $axis = -1, mixed $initial = null): mixed

Running integral by the trapezoidal rule (scipy.integrate.cumulative_trapezoid).

cumulativeProd(mixed $x, ?int $axis = null, int|float|bool|null $includeInitial = false): Tessero\NDArray|int|float

Cumulative product, optionally starting with 1 (numpy.cumulative_prod).

cumulativeSum(mixed $x, ?int $axis = null, int|float|bool|null $includeInitial = false): Tessero\NDArray|int|float

Cumulative sum, optionally starting with 0 (numpy.cumulative_sum).

delete(mixed $arr, mixed $obj, mixed $axis = null): mixed

Remove the given indices along an axis (numpy.delete).

diag(mixed $v, mixed $k = 0): mixed

Extract a diagonal, or build a 2-D array with the given diagonal (numpy.diag).

diagIndices(mixed $n, mixed $ndim = 2): mixed

Indices of the main diagonal of an n x ... x n array (numpy.diag_indices).

diagIndicesFrom(mixed $arr): mixed

Indices of the main diagonal of an array (numpy.diag_indices_from).

diagflat(mixed $v, mixed $k = 0): mixed

A 2-D array with the flattened input as a diagonal (numpy.diagflat).

diagonal(mixed $a, mixed $offset = 0, mixed $axis1 = 0, mixed $axis2 = 1): mixed

The given diagonal of an array (numpy.diagonal).

diff(mixed $a, mixed $n = 1, mixed $axis = -1, mixed $prepend = null, mixed $append = null): mixed

n-th discrete difference along an axis (numpy.diff).

digitize(mixed $x, mixed $bins, int|float|bool|null $right = false): Tessero\NDArray|int|float

Indices of the bins to which each value belongs (numpy.digitize).

divmod(mixed $x1, mixed $x2): mixed

The element-wise floor-division quotient and remainder as a pair (numpy.divmod).

dsplit(mixed $ary, mixed $indicesOrSections): mixed

Split along the third axis (numpy.dsplit).

dstack(mixed $tup): mixed

Stack arrays depth-wise, along the third axis (numpy.dstack).

e(): mixed

Euler's number e (numpy.e).

ediff1d(mixed $ary, mixed $toEnd = null, mixed $toBegin = null): mixed

Differences between consecutive elements of the flattened array (numpy.ediff1d).

einsum(mixed ...$operands): mixed

Einstein summation over the operands (numpy.einsum); real float64 operands.

emptyLike(mixed $a, mixed $dtype = null, mixed $shape = null): mixed

An array with the shape and dtype of another; Tessero fills it with zeros (numpy.empty_like).

eulerGamma(): mixed

The Euler-Mascheroni constant (numpy.euler_gamma).

expandDims(mixed $a, mixed $axis): mixed

Insert length-1 axes (numpy.expand_dims).

extract(mixed $condition, mixed $arr): mixed

Elements where the condition holds, flattened (numpy.extract).

fabs(mixed $x): mixed

Element-wise absolute value as float64 (numpy.fabs).

fillDiagonal(mixed $a, mixed $val, mixed $wrap = false): mixed

Fill the main diagonal, in place (numpy.fill_diagonal).

finfo(mixed $dtype): mixed

The machine limits of a floating-point dtype as a dict of the common fields (numpy.finfo).

flatnonzero(mixed $a): mixed

Indices of the non-zero elements of the flattened array (numpy.flatnonzero).

flip(mixed $m, mixed $axis = null): mixed

Reverse the order of elements along the given axes (numpy.flip).

fliplr(mixed $m): mixed

Reverse the order along axis 1 (numpy.fliplr).

flipud(mixed $m): mixed

Reverse the order along axis 0 (numpy.flipud).

frexp(mixed $x): mixed

The normalised mantissa and integer exponent of each element as a (mantissa, exponent) pair (numpy.frexp).

fromfile(mixed $fname, mixed $dtype = null, mixed $count = -1, mixed $sep = null, mixed $offset = 0): mixed

Read a binary or text file into a 1-D array of the given dtype (numpy.fromfile).

fromiter(mixed $iterable, mixed $dtype, mixed $count = -1): mixed

A 1-D array built from the first count elements of an iterable, cast to dtype (numpy.fromiter).

fullLike(mixed $a, mixed $fillValue, mixed $dtype = null, mixed $shape = null): mixed

An array of fill_value with the shape and dtype of another (numpy.full_like).

genfromtxt(mixed $fname, mixed $delimiter = null, mixed $skipHeader = 0, mixed $skipFooter = 0, mixed $comments = null, mixed $usecols = null): mixed

Load a text file of numbers into a float64 array, missing fields as NaN (numpy.genfromtxt).

geomspace(mixed $start, mixed $stop, mixed $num = 50, mixed $endpoint = true, mixed $dtype = null, mixed $axis = 0): mixed

Numbers spaced evenly on a log scale, a geometric progression (numpy.geomspace).

gradient(mixed ...$varargs): mixed

Gradient by central differences, one-sided at the edges (numpy.gradient); several axes give a list.

hamming(mixed $M): mixed

Hamming window (numpy.hamming).

hanning(mixed $M): mixed

Hanning window (numpy.hanning).

histogram(mixed $a, mixed $bins = 10, mixed $range = null, mixed $density = false, mixed $weights = null): mixed

Histogram of the data: counts (or density) and bin edges (numpy.histogram).

histogram2d(mixed $x, mixed $y, mixed $bins = 10, mixed $range = null, mixed $density = false, mixed $weights = null): mixed

The 2-D histogram of a set of points: counts (or density) and the bin edges (numpy.histogram2d).

histogramBinEdges(mixed $a, mixed $bins = 10, mixed $range = null, mixed $weights = null): mixed

Bin edges numpy.histogram would use (numpy.histogram_bin_edges).

histogramdd(mixed $sample, mixed $bins = 10, mixed $range = null, mixed $density = false, mixed $weights = null): mixed

The D-dimensional histogram of a set of points: counts (or density) and the per-axis bin edges (numpy.histogramdd).

hsplit(mixed $ary, mixed $indicesOrSections): mixed

Split horizontally, column-wise (numpy.hsplit).

hstack(mixed $tup, mixed $dtype = null, mixed $casting = 'same_kind'): mixed

Stack arrays horizontally, column-wise (numpy.hstack).

i0(mixed $x): mixed

Modified Bessel function of the first kind, order 0 (numpy.i0).

identity(mixed $n, mixed $dtype = null): mixed

The identity matrix (numpy.identity).

iinfo(mixed $dtype): mixed

The limits of an integer dtype as a dict (min, max, bits) (numpy.iinfo).

indices(mixed $dimensions, mixed $dtype = 'int64', mixed $sparse = false): mixed

An array of grid indices (numpy.indices); sparse=True gives a list of arrays.

inf(): mixed

IEEE 754 positive infinity (numpy.inf).

inner(mixed $a, mixed $b): mixed

Inner product over the last axes (numpy.inner).

insert(mixed $arr, mixed $obj, mixed $values, mixed $axis = null): mixed

Insert values before the given indices (numpy.insert).

interp(mixed $x, mixed $xp, mixed $fp, mixed $left = null, mixed $right = null, mixed $period = null): mixed

One-dimensional piecewise linear interpolation (numpy.interp).

intersect1d(mixed $ar1, mixed $ar2, mixed $assumeUnique = false, mixed $returnIndices = false): mixed

Sorted unique values in both arrays (numpy.intersect1d).

isclose(mixed $a, mixed $b, mixed $rtol = 1.0E-5, mixed $atol = 1.0E-8, mixed $equalNan = false): mixed

Element-wise test for approximate equality within a tolerance (numpy.isclose).

iscomplex(mixed $x): mixed

Element-wise test for a non-zero imaginary part (numpy.iscomplex).

iscomplexobj(mixed $x): mixed

True for a complex dtype (numpy.iscomplexobj).

isin(mixed $element, mixed $testElements, int|float|bool|null $invert = false): Tessero\NDArray|int|float|bool

Whether each element is in test_elements (numpy.isin).

isneginf(mixed $x): mixed

Element-wise test for negative infinity (numpy.isneginf).

isposinf(mixed $x): mixed

Element-wise test for positive infinity (numpy.isposinf).

isreal(mixed $x): mixed

Element-wise test for a zero imaginary part (numpy.isreal).

isrealobj(mixed $x): mixed

True for a non-complex dtype (numpy.isrealobj).

ix_(mixed ...$args): mixed

An open mesh from several sequences (numpy.ix_).

kaiser(mixed $M, mixed $beta): mixed

Kaiser window (numpy.kaiser).

kron(mixed $a, mixed $b): mixed

Kronecker product (numpy.kron).

ldexp(mixed $x1, mixed $x2): mixed

x1 * 2**x2 element-wise, with an integer exponent (numpy.ldexp).

leftShift(mixed $x1, mixed $x2): mixed

Shift the bits of each integer left by the per-element count (numpy.left_shift).

lexsort(mixed $keys): mixed

Indirect stable sort on several keys, the last key primary (numpy.lexsort).

loadtxt(mixed $fname, mixed $delimiter = null, mixed $skiprows = 0, mixed $comments = null, mixed $usecols = null): mixed

Load a text file of numbers into a float64 array (numpy.loadtxt).

logspace(mixed $start, mixed $stop, mixed $num = 50, mixed $endpoint = true, mixed $base = 10.0, mixed $dtype = null, mixed $axis = 0): mixed

Numbers spaced evenly on a log scale (numpy.logspace).

matrixTranspose(mixed $x): mixed

Transpose the last two axes (numpy.matrix_transpose).

matvec(mixed $x1, mixed $x2): mixed

Matrix-vector product over the last two axes of x1 and the last axis of x2 (numpy.matvec).

median(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Median along the given axes (numpy.median).

meshgrid(mixed ...$xi): mixed

Coordinate matrices from coordinate vectors (numpy.meshgrid).

modf(mixed $x): mixed

The fractional and integral parts of each element as a (frac, intpart) pair, both carrying the sign of x (numpy.modf).

moveaxis(mixed $a, mixed $source, mixed $destination): mixed

Move axes to new positions (numpy.moveaxis).

nan(): mixed

IEEE 754 not-a-number (numpy.nan).

nanToNum(mixed $x, mixed $copy = true, mixed $nan = 0.0, mixed $posinf = null, mixed $neginf = null): mixed

Replace NaN and infinities by finite numbers (numpy.nan_to_num).

nanargmax(mixed $a, ?int $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Index of the maximum ignoring NaN (numpy.nanargmax).

nanargmin(mixed $a, ?int $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Index of the minimum ignoring NaN (numpy.nanargmin).

nancumprod(mixed $a, ?int $axis = null): Tessero\NDArray|int|float

Cumulative product treating NaN as one (numpy.nancumprod).

nancumsum(mixed $a, ?int $axis = null): Tessero\NDArray|int|float

Cumulative sum treating NaN as zero (numpy.nancumsum).

nanmax(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Maximum ignoring NaN; NaN for an all-NaN slice (numpy.nanmax).

nanmean(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Mean ignoring NaN (numpy.nanmean).

nanmedian(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Median ignoring NaNs (numpy.nanmedian).

nanmin(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Minimum ignoring NaN; NaN for an all-NaN slice (numpy.nanmin).

nanpercentile(mixed $a, mixed $q, array|int|null $axis = null, string $method = 'linear', bool $keepdims = false): Tessero\NDArray|int|float|bool

Percentiles ignoring NaNs (numpy.nanpercentile).

nanprod(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Product treating NaN as one (numpy.nanprod).

nanquantile(mixed $a, mixed $q, array|int|null $axis = null, string $method = 'linear', bool $keepdims = false): Tessero\NDArray|int|float|bool

Quantiles ignoring NaNs (numpy.nanquantile).

nanstd(mixed $a, array|int|null $axis = null, int|float|bool|null $ddof = 0, bool $keepdims = false): Tessero\NDArray|int|float

Standard deviation ignoring NaN (numpy.nanstd).

nansum(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Sum treating NaN as zero (numpy.nansum).

nanvar(mixed $a, array|int|null $axis = null, int|float|bool|null $ddof = 0, bool $keepdims = false): Tessero\NDArray|int|float

Variance ignoring NaN (numpy.nanvar).

ndim(mixed $a): mixed

Number of dimensions (numpy.ndim).

newtonCotes(mixed $rn, mixed $equal = 0): mixed

Equally-spaced Newton-Cotes quadrature weights for rn intervals (scipy.integrate.newton_cotes).

nonzero(mixed $a): mixed

Indices of the non-zero elements, one array per axis (numpy.nonzero).

onesLike(mixed $a, mixed $dtype = null, mixed $shape = null): mixed

Ones with the shape and dtype of an array (numpy.ones_like).

outer(mixed $a, mixed $b): mixed

Outer product of two vectors (numpy.outer).

packbits(mixed $a, mixed $axis = null, mixed $bitorder = 'big'): mixed

Pack binary-valued array elements into uint8, MSB-first (numpy.packbits).

pad(mixed $array, mixed $padWidth, mixed $mode = 'constant', mixed $constantValues = null, mixed $endValues = null, mixed $statLength = null, mixed $reflectType = null): mixed

Pad an array (numpy.pad): constant, edge, linear_ramp, maximum, mean, median, minimum, reflect, symmetric, wrap, empty.

partition(mixed $a, mixed $kth, ?int $axis = -1): Tessero\NDArray|int|float

Partially sorted copy: the kth element in its sorted place (numpy.partition).

percentile(mixed $a, mixed $q, array|int|null $axis = null, string $method = 'linear', bool $keepdims = false): Tessero\NDArray|int|float|bool

q-th percentiles along the given axes, q in [0, 100] (numpy.percentile).

pi(): mixed

The constant pi (numpy.pi).

place(mixed $arr, mixed $mask, mixed $vals): mixed

Write successive values where the mask holds, in place (numpy.place).

poly(mixed $seq): mixed

Coefficients of the polynomial with the given roots (numpy.poly).

polyadd(mixed $a1, mixed $a2): mixed

Sum of two polynomials (numpy.polyadd).

polyder(mixed $p, mixed $m = 1): mixed

Derivative of a polynomial (numpy.polyder).

polydiv(mixed $u, mixed $v): mixed

Quotient and remainder of polynomial division (numpy.polydiv).

polyfit(mixed $x, mixed $y, mixed $deg): mixed

Least-squares polynomial fit, highest-degree coefficient first (numpy.polyfit).

polyint(mixed $p, mixed $m = 1, mixed $k = null): mixed

Antiderivative of a polynomial (numpy.polyint).

polymul(mixed $a1, mixed $a2): mixed

Product of two polynomials (numpy.polymul).

polysub(mixed $a1, mixed $a2): mixed

Difference of two polynomials (numpy.polysub).

polyval(mixed $p, mixed $x): mixed

Evaluate a polynomial at x (numpy.polyval).

positive(mixed $x): mixed

Unary plus; a copy of the input (numpy.positive).

promoteTypes(mixed $type1, mixed $type2): mixed

The smallest dtype both arguments can be safely cast to (numpy.promote_types).

ptp(mixed $a, array|int|null $axis = null, bool $keepdims = false): Tessero\NDArray|int|float

Range of values, maximum - minimum (numpy.ptp).

put(mixed $a, mixed $ind, mixed $v, mixed $mode = 'raise'): mixed

Write values at flat indices, in place (numpy.put).

putAlongAxis(mixed $arr, mixed $indices, mixed $values, mixed $axis): mixed

Write values at matching 1-D index slices, in place (numpy.put_along_axis).

putmask(mixed $a, mixed $mask, mixed $values): mixed

Write values where the mask holds, in place (numpy.putmask).

quantile(mixed $a, mixed $q, array|int|null $axis = null, string $method = 'linear', bool $keepdims = false): Tessero\NDArray|int|float|bool

q-th quantiles along the given axes, q in [0, 1] (numpy.quantile).

ravelMultiIndex(mixed $multiIndex, mixed $dims, mixed $mode = 'raise', mixed $order = 'C'): mixed

Convert coordinate arrays into flat indices (numpy.ravel_multi_index).

realIfClose(mixed $a, mixed $tol = 100): mixed

The real part when every imaginary part is close to zero (numpy.real_if_close).

repeat(mixed $a, mixed $repeats, mixed $axis = null): mixed

Repeat each element (numpy.repeat).

resize(mixed $a, mixed $newShape): mixed

A new array of the given shape, repeating the data cyclically (numpy.resize).

resultType(mixed ...$arraysAndDtypes): mixed

The dtype resulting from NumPy's type-promotion rules (numpy.result_type).

rightShift(mixed $x1, mixed $x2): mixed

Shift the bits of each integer right by the per-element count (numpy.right_shift).

roll(mixed $a, mixed $shift, mixed $axis = null): mixed

Roll elements along the given axes; without axis on the flattened array (numpy.roll).

rollaxis(mixed $a, mixed $axis, mixed $start = 0): mixed

Roll an axis backwards to a position (numpy.rollaxis).

romb(mixed $y, mixed $dx = 1.0): mixed

Romberg integration of 2**k+1 equally-spaced samples (scipy.integrate.romb).

roots(mixed $p): mixed

Roots of a polynomial, complex128 sorted by (re, im) (numpy.roots).

rot90(mixed $m, mixed $k = 1, mixed $axes = null): mixed

Rotate by 90 degrees in the plane of two axes, default (0, 1) (numpy.rot90).

round(mixed $a, mixed $decimals = 0): mixed

Round to the given number of decimals, half to even (numpy.round).

savetxt(mixed $fname, mixed $X, mixed $fmt = null, mixed $delimiter = null, mixed $newline = null, mixed $header = null, mixed $footer = null, mixed $comments = null): mixed

Save an array to a text file (numpy.savetxt).

searchsorted(mixed $a, mixed $v, string $side = 'left'): Tessero\NDArray|int|float

Indices where v would be inserted into the sorted array a (numpy.searchsorted).

select(mixed $condlist, mixed $choicelist, mixed $default = 0): mixed

Elements from the choices where the conditions hold (numpy.select).

setdiff1d(mixed $ar1, mixed $ar2, mixed $assumeUnique = false): mixed

Unique values of ar1 that are not in ar2 (numpy.setdiff1d).

setxor1d(mixed $ar1, mixed $ar2, mixed $assumeUnique = false): mixed

Sorted values in exactly one of the arrays (numpy.setxor1d).

shape(mixed $a): mixed

The shape of an array (numpy.shape).

simpson(mixed $y, mixed $x = null, mixed $dx = 1.0, mixed $axis = -1): mixed

Integral by the composite Simpson's rule (scipy.integrate.simpson).

sinc(mixed $x): mixed

Normalised sinc, sin(pi x) / (pi x) (numpy.sinc).

size(mixed $a, mixed $axis = null): mixed

Number of elements, in total or along axes (numpy.size).

sortComplex(mixed $a): mixed

A complex copy of a sorted by real then imaginary part (numpy.sort_complex).

spacing(mixed $x): mixed

The signed distance from each element to the adjacent representable float (numpy.spacing).

split(mixed $ary, mixed $indicesOrSections, mixed $axis = 0): mixed

Split into equal sections or at the given indices (numpy.split).

squeeze(mixed $a, mixed $axis = null): mixed

Remove length-1 axes (numpy.squeeze).

stack(mixed $arrays, mixed $axis = 0, mixed $dtype = null, mixed $casting = 'same_kind'): mixed

Join arrays along a new axis (numpy.stack).

swapaxes(mixed $a, mixed $axis1, mixed $axis2): mixed

Interchange two axes (numpy.swapaxes).

take(mixed $a, mixed $indices, mixed $axis = null, mixed $mode = 'raise'): mixed

Elements at the given indices along an axis (numpy.take).

takeAlongAxis(mixed $arr, mixed $indices, mixed $axis = -1): mixed

Pick values by matching 1-D index slices (numpy.take_along_axis).

tensordot(mixed $a, mixed $b, mixed $axes = 2): mixed

Tensor dot product over the given axes (numpy.tensordot).

tile(mixed $A, mixed $reps): mixed

Repeat an array the given number of times per axis (numpy.tile).

trace(mixed $a, mixed $offset = 0, mixed $axis1 = 0, mixed $axis2 = 1, mixed $dtype = null): mixed

Sum along a diagonal (numpy.trace).

trapezoid(mixed $y, mixed $x = null, mixed $dx = 1.0, mixed $axis = -1): mixed

Integral by the composite trapezoidal rule (numpy.trapezoid).

tri(mixed $N, mixed $M = null, mixed $k = 0, mixed $dtype = 'float64'): mixed

Ones at and below the k-th diagonal, zeros elsewhere (numpy.tri).

tril(mixed $m, mixed $k = 0): mixed

Lower triangle of an array (numpy.tril).

trilIndices(mixed $n, mixed $k = 0, mixed $m = null): mixed

Indices of the lower triangle of an (n, m) array (numpy.tril_indices).

trilIndicesFrom(mixed $arr, mixed $k = 0): mixed

Indices of the lower triangle of a 2-D array (numpy.tril_indices_from).

trimZeros(mixed $filt, mixed $trim = 'fb', mixed $axis = null): mixed

Trim leading and/or trailing zeros (numpy.trim_zeros).

triu(mixed $m, mixed $k = 0): mixed

Upper triangle of an array (numpy.triu).

triuIndices(mixed $n, mixed $k = 0, mixed $m = null): mixed

Indices of the upper triangle of an (n, m) array (numpy.triu_indices).

triuIndicesFrom(mixed $arr, mixed $k = 0): mixed

Indices of the upper triangle of a 2-D array (numpy.triu_indices_from).

union1d(mixed $ar1, mixed $ar2): mixed

Sorted unique values in either array (numpy.union1d).

unique(mixed $ar, mixed $returnIndex = false, mixed $returnInverse = false, mixed $returnCounts = false, mixed $equalNan = true): mixed

Sorted unique elements, optionally with indices, inverse and counts (numpy.unique).

uniqueAll(mixed $x): mixed

Unique values, first indices, inverse indices and counts (numpy.unique_all).

uniqueCounts(mixed $x): mixed

Unique values and their counts (numpy.unique_counts).

uniqueInverse(mixed $x): mixed

Unique values and the inverse indices (numpy.unique_inverse).

uniqueValues(mixed $x): mixed

Unique values; NaNs are not merged (numpy.unique_values).

unpackbits(mixed $a, mixed $axis = null, mixed $count = null, mixed $bitorder = 'big'): mixed

Unpack uint8 array elements into bits, MSB-first (numpy.unpackbits).

unravelIndex(mixed $indices, mixed $shape, mixed $order = 'C'): mixed

Convert flat indices into a tuple of coordinate arrays (numpy.unravel_index).

unstack(mixed $x, mixed $axis = 0): mixed

Split an array into the arrays along an axis (numpy.unstack).

unwrap(mixed $p, mixed $discont = null, mixed $axis = -1, mixed $period = 6.283185307179586): mixed

Unwrap by taking the complement of large jumps with respect to the period (numpy.unwrap).

vander(mixed $x, mixed $N = null, mixed $increasing = false): mixed

Vandermonde matrix (numpy.vander).

vdot(mixed $a, mixed $b): mixed

Dot product of the flattened arrays (numpy.vdot).

vecdot(mixed $x1, mixed $x2, mixed $axis = -1): mixed

Vector dot product over the last axis (numpy.vecdot).

vecmat(mixed $x1, mixed $x2): mixed

Vector-matrix product; x1 is (..., N), x2 is (..., N, M) (numpy.vecmat).

vsplit(mixed $ary, mixed $indicesOrSections): mixed

Split vertically, row-wise (numpy.vsplit).

vstack(mixed $tup, mixed $dtype = null, mixed $casting = 'same_kind'): mixed

Stack arrays vertically, row-wise (numpy.vstack).

zerosLike(mixed $a, mixed $dtype = null, mixed $shape = null): mixed

Zeros with the shape and dtype of an array (numpy.zeros_like).