Documentation
¶
Index ¶
- Constants
- Variables
- func Abs[T BaseType](x []T) []T
- func Add[T Number](x []T, y any) []T
- func Align[T BaseType](x []T, a T, dLen int) []T
- func All[T Number | ~bool](x []T) bool
- func And[S ~[]E, E any](v S, x any) []bool
- func Any[T Number | ~bool](x []T) bool
- func AnyToBool(v any) bool
- func AnyToFloat32(v any) float32
- func AnyToFloat64(v any) float64
- func AnyToInt32(v any) int32
- func AnyToInt64(v any) int64
- func AnyToSlice[T BaseType](A any, n int) []T
- func AnyToString(v any) string
- func Arange[T Number](start T, end T, argv ...T) []T
- func ArgMax[T Number](x []T) int
- func ArgMax2[T BaseType](x []T) int
- func ArgMin[T Number](x []T) int
- func ArgMin2[T BaseType](x []T) int
- func BoolToFloat32(b bool) float32
- func BoolToFloat64(b bool) float64
- func BoolToInt(b bool) int8
- func BoolToInt32(b bool) int32
- func BoolToInt64(b bool) int64
- func BoolToString(b bool) string
- func Concat1D[T Number](a, b, c []T) [][]T
- func ConfidenceIntervalToZscore(confidenceInterval float64) (zScore float64)
- func Count[T Number | ~bool](x []T) int
- func CumSum[T Number](x []T) []T
- func DTypeIsNaN(d DType) bool
- func DefaultFormatter(v interface{}) string
- func Diff[T Number](s []T, param any) []T
- func Diff2[T BaseType](s []T, param any) []T
- func Div[T Number](x []T, y any) []T
- func Dot[T Number](a, b [][]T) [][]T
- func Dot1D[T Number](a, b []T) T
- func Dot2D[T Number](a, b [][]T) [][]T
- func Dot2D1[T Number](a [][]T, b []T) []T
- func Dot2D1_v2[T Number](a [][]T, b []T) []T
- func Dot2D_V1[T Number](a, b [][]T) [][]T
- func Dot_v1[T Number](a, b [][]T) [][]T
- func Equal[T BaseType](x, y []T) []bool
- func Fill[T BaseType](v []T, d T, args ...any) (rows []T)
- func FillNa[T BaseType](x []T, v any, args ...any) []T
- func FindPercent(zScore float64) (percent float64)
- func FindZScore(percent float64) (zScore float64)
- func Float32IsNaN(f float32) bool
- func Float64IsNaN(f float64) bool
- func GenericParse[T BaseType](text string) T
- func GetAvx2Enabled() bool
- func Gt[S ~[]E, E any](v S, x any) []bool
- func Gte[S ~[]E, E any](v S, x any) []bool
- func Inverse(a [][]float64) [][]float64
- func IsEmpty(s string) bool
- func LinearRegression(x, y, weights []float64, origin bool) (alpha, beta float64)
- func Lt[S ~[]E, E any](v S, x any) []bool
- func Lte[S ~[]E, E any](v S, x any) []bool
- func Max[T Number](x []T) T
- func Max2[T BaseType](x []T) T
- func Maximum[T Number](f1, f2 []T) []T
- func Mean[T Number](x []T) T
- func Mean2[T BaseType](x []T) T
- func Min[T Number](x []T) T
- func Min2[T BaseType](x []T) T
- func Minimum[T Number](f1, f2 []T) []T
- func Mul[T Number](x []T, y any) []T
- func NaN() float64
- func Not[S ~[]E, E any](v S) []bool
- func NotEqual[T BaseType](x, y []T) []bool
- func Ones[T Number](v []T) []T
- func Or[S ~[]E, E any](v S, x any) []bool
- func PanicTrace(err interface{}) string
- func ParseBool(s string, v any) bool
- func ParseFloat32(s string, v any) float32
- func ParseFloat64(s string, v any) float64
- func ParseInt32(s string, v any) int32
- func ParseInt64(s string, v any) int64
- func Pow[T Number](v []T, n int) []T
- func PrintString(v any) string
- func Range[T Number](n int) []T
- func Repeat[T BaseType](f T, n int) []T
- func RepeatInto[T BaseType](s []T, f T, n int) []T
- func Reverse[S ~[]E, E any](s S) S
- func Rolling[T BaseType](S []T, N any) [][]T
- func SetAvx2Enabled(enabled bool)
- func Shape[T Number](x any) (r, c int)
- func Shift[T BaseType](S []T, N any) []T
- func ShiftN[T BaseType](S []T, periods int) []T
- func SliceToBool(v any) []bool
- func SliceToFloat32(v any) []float32
- func SliceToFloat64(v any) []float64
- func SliceToString(v any) []string
- func Slope(x1 int, y1 float64, x2 int, y2 float64) float64
- func Sqrt[T Number](v []T) []T
- func Std[T BaseType](f []T) T
- func Std_TODO[T Float](f []T) T
- func StringIsFalse(s string) bool
- func StringIsNaN(s string) bool
- func StringIsTrue(s string) bool
- func Sub[T Number](x []T, y any) []T
- func Sum[T Number](f []T) T
- func Throw(tv any) *exception.Exception
- func ToBool(s Series) []bool
- func ToFloat32(s Series) []float32
- func ToFloat64(s Series) []float64
- func Transpose2D[T Number](x [][]T) [][]T
- func TriangleBevel(slope float64, x1 int, y1 float64, xn int) float64
- func Where[T StatType](condition []T, x, y []T) []T
- func Zeros[T BaseType](shape int) []T
- func ZscoreToConfidenceInterval(zScore float64) (confidenceInterval float64)
- type AlphaType
- type BaseType
- type BigFloat
- type Complex
- type DType
- type EW
- type ExponentialMovingWindow
- type Float
- type GenericType
- type Int
- type Integer
- type LeafNode
- type MoveTypedeprecated
- type NDArray
- func (self NDArray[T]) Add(x any) Series
- func (self NDArray[T]) And(x any) Series
- func (self NDArray[T]) Append(values ...any) Series
- func (self NDArray[T]) Apply(f func(idx int, v any))
- func (self NDArray[T]) Apply2(f func(idx int, v any) any, args ...bool) Series
- func (self NDArray[T]) ArgMax() int
- func (self NDArray[T]) ArgMin() int
- func (self NDArray[T]) Bools() []bool
- func (self NDArray[T]) Concat(x Series) Series
- func (self NDArray[T]) Copy() Series
- func (self NDArray[T]) DTypes() []DType
- func (self NDArray[T]) Diff(n any) Series
- func (self NDArray[T]) Div(x any) Series
- func (self NDArray[T]) EWM(alpha EW) ExponentialMovingWindow
- func (self NDArray[T]) Empty(tv ...Type) Series
- func (self NDArray[T]) Eq(x any) Series
- func (self NDArray[T]) FillNa(v any, inplace bool) Series
- func (self NDArray[T]) Floats() []float32
- func (self NDArray[T]) Gt(x any) Series
- func (self NDArray[T]) Gte(x any) Series
- func (self NDArray[T]) IndexOf(index int, opt ...any) any
- func (self NDArray[T]) Ints() []Int
- func (arr NDArray[T]) Len() int
- func (arr NDArray[T]) Less(i, j int) bool
- func (self NDArray[T]) Logic(f func(idx int, v any) bool) []bool
- func (self NDArray[T]) Lt(x any) Series
- func (self NDArray[T]) Lte(x any) Series
- func (self NDArray[T]) Max() any
- func (self NDArray[T]) Mean() DType
- func (self NDArray[T]) Min() any
- func (self NDArray[T]) Mul(x any) Series
- func (self NDArray[T]) NaN() any
- func (self NDArray[T]) Name() string
- func (self NDArray[T]) Neq(x any) Series
- func (self NDArray[T]) Not() Series
- func (self NDArray[T]) Or(x any) Series
- func (self NDArray[T]) Records(round ...bool) []string
- func (self NDArray[T]) Ref(n any) Series
- func (self NDArray[T]) Rename(name string)
- func (self NDArray[T]) Repeat(x any, repeats int) Series
- func (self NDArray[T]) Reverse() Series
- func (self NDArray[T]) Rolling(param any) RollingAndExpandingMixin
- func (self NDArray[T]) Select(r api.ScopeLimit) Series
- func (self NDArray[T]) Shift(periods int) Series
- func (self NDArray[T]) Std() DType
- func (self NDArray[T]) StdDev() DType
- func (self NDArray[T]) Strings() []string
- func (self NDArray[T]) Sub(x any) Series
- func (self NDArray[T]) Subset(start, end int, opt ...any) Series
- func (self NDArray[T]) Sum() DType
- func (arr NDArray[T]) Swap(i, j int)
- func (self NDArray[T]) Type() Type
- func (self NDArray[T]) Values() any
- type Node
- type Number
- type Number16deprecated
- type Number32deprecated
- type Number64deprecated
- type Number8deprecated
- type NumberOfCPUBitsRelated
- type Options
- type Ordered
- type RollingAndExpandingMixin
- func (r RollingAndExpandingMixin) Apply(f func(S Series, N DType) DType) (s Series)
- func (r RollingAndExpandingMixin) Count() (s Series)
- func (r RollingAndExpandingMixin) GetBlocks() (blocks []Series)
- func (r RollingAndExpandingMixin) Max() (s Series)
- func (r RollingAndExpandingMixin) Mean() (s Series)
- func (r RollingAndExpandingMixin) Min() (s Series)
- func (r RollingAndExpandingMixin) Std() Series
- func (r RollingAndExpandingMixin) Sum() Series
- type Series
- type Signed
- type StatType
- type StringFormatter
- type Type
- type Unsigned
- type ZTable
Constants ¶
View Source
const ( SERIES_TYPE_INVAILD = reflect.Invalid // 无效类型 SERIES_TYPE_BOOL = reflect.Bool // 布尔类型 SERIES_TYPE_INT32 = reflect.Int32 // int64 SERIES_TYPE_INT64 = reflect.Int64 // int64 SERIES_TYPE_FLOAT32 = reflect.Float32 // float32 SERIES_TYPE_FLOAT64 = reflect.Float64 // float64 SERIES_TYPE_DTYPE = SERIES_TYPE_FLOAT64 SERIES_TYPE_STRING = reflect.String // string )
Supported Series Types
View Source
const ( Nil2Bool = false // 空指针转bool BoolNaN = false // bool 无效值 True2Bool = true // true转bool False2Bool = false // false 转bool True2Float32 float32 = float32(1) // true转float32 False2Float32 float32 = float32(0) // false转float32 StringBad2Bool = false // 字符串解析bool异常 StringTrue2Bool = true // 字符串true转bool StringFalse2Bool = false // 字符串false转bool )
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const ( MaxFloat32 = float32(math.MaxFloat32) // float32最大值 MinFloat32 = float32(math.SmallestNonzeroFloat32) // float32最小值 StringTrue2Float32 float32 = float32(1) // 字符串true转float32 StringFalse2Float32 float32 = float32(0) // 字符串false转float32 )
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const ( MaxFloat64 float64 = float64(math.MaxFloat64) // float64最大值 MinFloat64 float64 = float64(math.SmallestNonzeroFloat64) // float64最小值 True2Float64 float64 = float64(1) // true转float64 False2Float64 float64 = float64(0) // false转float64 StringNil2Float float64 = float64(0) // deprecated: 字符串空指针转float64 StringBad2Float float64 = float64(0) // deprecated: 字符串解析float64异常 StringTrue2Float64 float64 = float64(1) // 字符串true转float64 StringFalse2Float64 float64 = float64(0) // 字符串false转float64 )
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const ( MaxInt32 = int32(math.MaxInt32) MinInt32 = int32(math.MinInt32) Nil2Int32 = int32(0) // 空指针转int32 Int32NaN = int32(0) // int32 无效值 True2Int32 = int32(1) // true转int32 False2Int32 = int32(0) // false 转int32 StringBad2Int32 = int32(0) // 字符串解析int32异常 StringTrue2Int32 = int32(1) // 字符串true转int32 StringFalse2Int32 = int32(0) // 字符串false转int32 )
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const ( MaxInt64 = int64(math.MaxInt64) MinInt64 = int64(math.MinInt64) Nil2Int64 = int64(0) // 空指针转int64 Int64NaN = int64(0) // int64 无效值 True2Int64 = int64(1) // true转int64 False2Int64 = int64(0) // false 转int64 StringBad2Int64 = int64(0) // 字符串解析int64异常 StringTrue2Int64 = int64(1) // 字符串true转int64 StringFalse2Int64 = int64(0) // 字符串false转int64 )
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const ( StringNaN = "NaN" // 字符串NaN Nil2String = "NaN" // nil指针转string True2String = "true" // true转string False2String = "false" // false转string )
Variables ¶
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var ( // Nil2Float64 nil指针转换float64 Nil2Float64 = float64(0) // Nil2Float32 nil指针转换float32 Nil2Float32 = float32(0) DTypeNaN = DType(0) )
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var ( // IgnoreParseExceptions 忽略解析异常 IgnoreParseExceptions bool = true Avx2Enabled = false // AVX2加速开关 )
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var ( // ErrUnsupportedType 不支持的类型 ErrUnsupportedType = exception.New(errorTypeBase+0, "Unsupported type") ErrRange = exception.New(errorTypeBase+1, "range error") )
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var ( TypeBool = reflect.TypeOf([]bool{}) TypeInt64 = reflect.TypeOf([]int64{}) TypeFloat32 = reflect.TypeOf([]float32{}) TypeFloat64 = reflect.TypeOf([]float64{}) TypeString = reflect.TypeOf([]string{}) )
初始化全局的私有变量
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var ( // PossibleNaOfString 有可能出现的NaN字符串的全部选项 PossibleNaOfString = []string{"NA", "NaN", "nan", "<nil>"} )
Functions ¶
func AnyToFloat32 ¶ added in v0.6.4
func AnyToFloat64 ¶ added in v0.6.4
func Arange ¶ added in v0.7.0
func Arange[T Number](start T, end T, argv ...T) []T
Arange Return evenly spaced values within a given interval.
返回给定间隔内的等间距值
func ArgMax ¶ added in v0.6.4
ArgMax Returns the indices of the maximum values along an axis.
返回轴上最大值的索引
func ArgMin ¶ added in v0.6.4
ArgMin Returns the indices of the minimum values along an axis.
返回轴上最小值的索引
func BoolToInt32 ¶ added in v0.6.6
func BoolToInt64 ¶ added in v0.6.6
func Concat1D ¶ added in v0.7.0
func Concat1D[T Number](a, b, c []T) [][]T
Concat1D
Translates slice objects to concatenation along the second axis. 沿第二个轴将切片对象转换为串联
func ConfidenceIntervalToZscore ¶ added in v0.7.7
ConfidenceIntervalToZscore 通过置信区间百分比查找Z分值
func DefaultFormatter ¶ added in v0.6.5
func DefaultFormatter(v interface{}) string
DefaultFormatter will return a string representation of the data in a particular row.
func Diff ¶ added in v0.6.5
Diff 元素的第一个离散差
First discrete difference of element.
Calculates the difference of a {klass} element compared with another
element in the {klass} (default is element in previous row).
func Dot2D ¶ added in v0.7.0
func Dot2D[T Number](a, b [][]T) [][]T
Dot2D 二维矩阵点积
点积(dot)运算及简单应用 https://www.jianshu.com/p/482abac8798c
func Fill ¶ added in v0.6.4
Fill 填充
Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series, or DataFrame
Value to use to fill holes (e.g. 0), alternately a
dict/Series/DataFrame of values specifying which value to use for
each index (for a Series) or column (for a DataFrame). Values not
in the dict/Series/DataFrame will not be filled. This value cannot
be a list.
method : {{'backfill', 'bfill', 'pad', 'ffill', None}}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use next valid observation to fill gap.
axis : {axes_single_arg}
Axis along which to fill missing values. For `Series`
this parameter is unused and defaults to 0.
inplace : bool, default False [√]
If True, fill in-place. Note: this will modify any
other views on this object (e.g., a no-copy slice for a column in a
DataFrame).
limit : int, default None
If method is specified, this is the maximum number of consecutive
NaN values to forward/backward fill. In other words, if there is
a gap with more than this number of consecutive NaNs, it will only
be partially filled. If method is not specified, this is the
maximum number of entries along the entire axis where NaNs will be
filled. Must be greater than 0 if not None.
downcast : dict, default is None
A dict of item->dtype of what to downcast if possible,
or the string 'infer' which will try to downcast to an appropriate
equal type (e.g. float64 to int64 if possible).
Returns
-------
[]T or None
func FindPercent ¶ added in v0.7.7
func FindZScore ¶ added in v0.7.7
func Inverse ¶ added in v0.7.0
Inverse 计算矩阵的（乘法）逆
Compute the (multiplicative) inverse of a matrix. Given a square matrix `a`, return the matrix `ainv` satisfying ``dot(a, ainv) = dot(ainv, a) = eye(a.shape[0])``.
func LinearRegression ¶
LinearRegression 线性回归
func Maximum ¶ added in v0.6.4
func Maximum[T Number](f1, f2 []T) []T
Maximum AVX2版本, 两个序列横向比较最大值
TODO:print(np.maximum(1.4, np.nan)) 输出nan
func ParseFloat32 ¶ added in v0.6.4
ParseFloat32 字符串转float32
func ParseFloat64 ¶ added in v0.6.4
ParseFloat64 字符串转float64 任意组合的nan字符串都会被解析成NaN
func ParseInt32 ¶ added in v0.6.6
ParseInt32 解析int字符串, 尝试解析10进制和16进制
func ParseInt64 ¶ added in v0.6.4
ParseInt64 解析int字符串, 尝试解析10进制和16进制
func PrintString ¶ added in v0.9.20
func RepeatInto ¶ added in v0.6.6
RepeatInto 替换n长度的f的泛型切片
func Rolling ¶ added in v0.6.5
Rolling returns an array with elements that roll beyond the last position are re-introduced at the first. 滑动窗口, 数据不足是用空数组占位
func SliceToFloat32 ¶ added in v0.6.4
SliceToFloat32 any输入只能是一维slice或者数组
func SliceToFloat64 ¶ added in v0.6.4
SliceToFloat64 any输入只能是一维slice或者数组
func SliceToString ¶ added in v0.6.22
SliceToString any输入只能是一维slice或者数组
func Std_TODO ¶ added in v0.6.4
func Std_TODO[T Float](f []T) T
Std_TODO StdDev 这个版本有bug, gonum计算的std不对 TODO: 于总来解决
func StringIsFalse ¶ added in v0.6.6
func StringIsTrue ¶ added in v0.6.6
func TriangleBevel ¶ added in v0.9.23
TriangleBevel 三角形斜边
func Where ¶
func Where[T StatType](condition []T, x, y []T) []T
Where 返回根据“条件”从“x”或“y”中选择的元素 这里先实现一个简单的, 留给于总重构 params只支持两个默认值x和y, 如果condition为true返回x, 否则返回y condition和param都可能是基础数据类型,也可能是一个slice, 并且长度可能不一致 直接写成序列版本, 可能更简单
func Zeros ¶ added in v0.6.4
Zeros Return a new array of given shape and type, filled with zeros.
args[0] dtype 基础数据类型
func ZscoreToConfidenceInterval ¶ added in v0.7.7
ZscoreToConfidenceInterval 通过分值查找置信区间
Types ¶
type AlphaType ¶ added in v0.6.6
type AlphaType int
const ( // AlphaAlpha Specify smoothing factor α directly, 0<α≤1. AlphaAlpha AlphaType = iota // AlphaCom Specify decay in terms of center of mass, α=1/(1+com), for com ≥ 0. AlphaCom // AlphaSpan Specify decay in terms of span, α=2/(span+1), for span ≥ 1. AlphaSpan // AlphaHalfLife Specify decay in terms of half-life, α=1−exp(−ln(2)/halflife), for halflife > 0. AlphaHalfLife )
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.ewm.html
type Complex ¶ added in v0.6.5
type Complex interface {
~complex64 | ~complex128
}
Complex is a constraint that permits any complex numeric type. If future releases of Go add new predeclared complex numeric types, this constraint will be modified to include them.
type DType ¶ added in v0.6.4
type DType = float64
func Median ¶ added in v0.6.4
Median returns median value of series. Linear interpolation is used for odd length. TODO:未加验证, 未加速
func PolyFit ¶ added in v0.6.4
PolyFit
Least squares polynomial fit.
.. note::
This forms part of the old polynomial API. Since version 1.4, the
new polynomial API defined in `numpy.polynomial` is preferred.
A summary of the differences can be found in the
:doc:`transition guide </reference/routines.polynomials>`.
Fit a polynomial ``p(x) = p[0] * x**deg + ... + p[deg]`` of degree `deg`
to points `(x, y)`. Returns a vector of coefficients `p` that minimises
the squared error in the order `deg`, `deg-1`, ... `0`.
The `Polynomial.fit <numpy.polynomial.polynomial.Polynomial.fit>` class
method is recommended for new code as it is more stable numerically. See
the documentation of the method for more information.
Parameters
----------
x : array_like, shape (M,)
x-coordinates of the M sample points ``(x[i], y[i])``.
y : array_like, shape (M,) or (M, K)
y-coordinates of the sample points. Several data sets of sample
points sharing the same x-coordinates can be fitted at once by
passing in a 2D-array that contains one dataset per column.
deg : int
Degree of the fitting polynomial
Returns
-------
p : ndarray, shape (deg + 1,) or (deg + 1, K)
Polynomial coefficients, highest power first. If `y` was 2-D, the
coefficients for `k`-th data set are in ``p[:,k]``.
residuals, rank, singular_values, rcond
These values are only returned if ``full == True``
- residuals -- sum of squared residuals of the least squares fit
- rank -- the effective rank of the scaled Vandermonde
coefficient matrix
- singular_values -- singular values of the scaled Vandermonde
coefficient matrix
- rcond -- value of `rcond`.
For more details, see `numpy.linalg.lstsq`.
Warns
-----
RankWarning
The rank of the coefficient matrix in the least-squares fit is
deficient. The warning is only raised if ``full == False``.
The warnings can be turned off by
>>> import warnings
>>> warnings.simplefilter('ignore', np.RankWarning)
See Also
--------
polyval : Compute polynomial values.
linalg.lstsq : Computes a least-squares fit.
scipy.interpolate.UnivariateSpline : Computes spline fits.
Notes
-----
The solution minimizes the squared error
.. math::
E = \\sum_{j=0}^k |p(x_j) - y_j|^2
in the equations::
x[0]**n * p[0] + ... + x[0] * p[n-1] + p[n] = y[0]
x[1]**n * p[0] + ... + x[1] * p[n-1] + p[n] = y[1]
...
x[k]**n * p[0] + ... + x[k] * p[n-1] + p[n] = y[k]
The coefficient matrix of the coefficients `p` is a Vandermonde matrix.
`polyfit` issues a `RankWarning` when the least-squares fit is badly
conditioned. This implies that the best fit is not well-defined due
to numerical error. The results may be improved by lowering the polynomial
degree or by replacing `x` by `x` - `x`.mean(). The `rcond` parameter
can also be set to a value smaller than its default, but the resulting
fit may be spurious: including contributions from the small singular
values can add numerical noise to the result.
Note that fitting polynomial coefficients is inherently badly conditioned
when the degree of the polynomial is large or the interval of sample points
is badly centered. The quality of the fit should always be checked in these
cases. When polynomial fits are not satisfactory, splines may be a good
alternative.
References
----------
.. [1] Wikipedia, "Curve fitting",
https://en.wikipedia.org/wiki/Curve_fitting
.. [2] Wikipedia, "Polynomial interpolation",
https://en.wikipedia.org/wiki/Polynomial_interpolation
.. [3] numpy.polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False)
https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html
Examples
--------
>>> import warnings
>>> x = np.array([0.0, 1.0, 2.0, 3.0, 4.0, 5.0])
>>> y = np.array([0.0, 0.8, 0.9, 0.1, -0.8, -1.0])
>>> z = np.polyfit(x, y, 3)
>>> z
array([ 0.08703704, -0.81349206, 1.69312169, -0.03968254]) # may vary
func PolyVal ¶ added in v0.6.4
PolyVal
Evaluate a polynomial at specific values. .. note:: This forms part of the old polynomial API. Since version 1.4, the new polynomial API defined in `numpy.polynomial` is preferred. A summary of the differences can be found in the :doc:`transition guide </reference/routines.polynomials>`. If `p` is of length N, this function returns the value: ``p[0]*x**(N-1) + p[1]*x**(N-2) + ... + p[N-2]*x + p[N-1]`` If `x` is a sequence, then ``p(x)`` is returned for each element of ``x``. If `x` is another polynomial then the composite polynomial ``p(x(t))`` is returned. Parameters
----------
p : array_like or poly1d object 1D array of polynomial coefficients (including coefficients equal to zero) from highest degree to the constant term, or an instance of poly1d. x : array_like or poly1d object A number, an array of numbers, or an instance of poly1d, at which to evaluate `p`. Returns
-------
values : ndarray or poly1d If `x` is a poly1d instance, the result is the composition of the two polynomials, i.e., `x` is "substituted" in `p` and the simplified result is returned. In addition, the type of `x` - array_like or poly1d - governs the type of the output: `x` array_like => `values` array_like, `x` a poly1d object => `values` is also. See Also -------- poly1d: A polynomial class. Notes ----- Horner's scheme [1]_ is used to evaluate the polynomial. Even so, for polynomials of high degree the values may be inaccurate due to rounding errors. Use carefully. If `x` is a subtype of `ndarray` the return value will be of the same type. References ---------- .. [1] I. N. Bronshtein, K. A. Semendyayev, and K. A. Hirsch (Eng. trans. Ed.), *Handbook of Mathematics*, New York, Van Nostrand Reinhold Co., 1985, pg. 720. Examples -------- >>> np.polyval([3,0,1], 5) # 3 * 5**2 + 0 * 5**1 + 1 76 >>> np.polyval([3,0,1], np.poly1d(5)) poly1d([76]) >>> np.polyval(np.poly1d([3,0,1]), 5) 76 >>> np.polyval(np.poly1d([3,0,1]), np.poly1d(5)) poly1d([76])
type EW ¶ added in v0.6.6
type EW struct {
Com DType // 根据质心指定衰减
Span DType // 根据跨度指定衰减
HalfLife DType // 根据半衰期指定衰减
Alpha DType // 直接指定的平滑因子α
Adjust bool // 除以期初的衰减调整系数以核算 相对权重的不平衡（将 EWMA 视为移动平均线）
IgnoreNA bool // 计算权重时忽略缺失值
Callback func(idx int) DType
}
EW (Factor) 指数加权(EW)计算Alpha 结构属性非0即为有效启动同名算法
type ExponentialMovingWindow ¶ added in v0.6.6
type ExponentialMovingWindow struct {
Data Series // 序列
AType AlphaType // 计算方式: com/span/halflefe/alpha
Param DType // 参数类型为浮点
Adjust bool // 默认为真, 是否调整, 默认真时, 计算序列的EW移动平均线, 为假时, 计算指数加权递归
IgnoreNA bool // 默认为假, 计算权重时是否忽略缺失值NaN
Cb func(idx int) DType
// contains filtered or unexported fields
}
ExponentialMovingWindow 加权移动窗口
func (ExponentialMovingWindow) Mean ¶ added in v0.6.6
func (w ExponentialMovingWindow) Mean() Series
type Float ¶ added in v0.6.3
Float is a constraint that permits any floating-point type. If future releases of Go add new predeclared floating-point types, this constraint will be modified to include them.
type GenericType ¶ added in v0.6.4
GenericType Series支持的所有类型 Deprecated: 不推荐使用
type Integer ¶ added in v0.6.4
Integer is a constraint that permits any integer type. If future releases of Go add new predeclared integer types, this constraint will be modified to include them.
type LeafNode ¶ added in v0.7.7
type LeafNode struct {
// contains filtered or unexported fields
}
LeafNode struct
type NDArray ¶ added in v0.6.4
type NDArray[T BaseType] []T
func (NDArray[T]) EWM ¶ added in v0.6.6
func (self NDArray[T]) EWM(alpha EW) ExponentialMovingWindow
func (NDArray[T]) Rolling ¶ added in v0.6.6
func (self NDArray[T]) Rolling(param any) RollingAndExpandingMixin
type Node ¶ added in v0.7.7
type Node struct {
// contains filtered or unexported fields
}
Node struct
type NumberOfCPUBitsRelated ¶ added in v0.6.6
NumberOfCPUBitsRelated The number of CPU bits is related Deprecated: 不推荐使用
type Options ¶ added in v0.7.7
type Options struct {
BucketSize int // number of table values to group together in tree leaf-node
}
Options is a config for the NewZTable function which allows bucket size customization. Default bucket size is 30
type Ordered ¶ added in v0.6.5
Ordered is a constraint that permits any ordered type: any type that supports the operators < <= >= >. If future releases of Go add new ordered types, this constraint will be modified to include them.
type RollingAndExpandingMixin ¶ added in v0.6.6
RollingAndExpandingMixin 滚动和扩展静态横切
func (RollingAndExpandingMixin) Apply ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Apply(f func(S Series, N DType) DType) (s Series)
Apply 接受一个回调
func (RollingAndExpandingMixin) Count ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Count() (s Series)
func (RollingAndExpandingMixin) GetBlocks ¶ added in v0.6.6
func (r RollingAndExpandingMixin) GetBlocks() (blocks []Series)
func (RollingAndExpandingMixin) Max ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Max() (s Series)
func (RollingAndExpandingMixin) Mean ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Mean() (s Series)
Mean returns the rolling mean.
func (RollingAndExpandingMixin) Min ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Min() (s Series)
func (RollingAndExpandingMixin) Std ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Std() Series
func (RollingAndExpandingMixin) Sum ¶ added in v0.6.6
func (r RollingAndExpandingMixin) Sum() Series
type Series ¶ added in v0.6.5
type Series interface {
// Name 取得series名称
Name() string
// Rename renames the series.
Rename(name string)
// Type returns the type of Data the series holds.
// 返回series的数据类型
Type() Type
// Values 获得全部数据集
Values() any
// NaN 输出默认的NaN
NaN() any
// Floats 强制转成[]float32
Floats() []float32
// DTypes 强制转[]stat.DType
DTypes() []DType
// Ints 强制转换成整型
Ints() []Int
// Strings 强制转换string切片
Strings() []string
// Bools 强制转换成bool切片
Bools() []bool
// Len 获得行数, 实现sort.Interface接口的获取元素数量方法
Len() int
// Less 实现sort.Interface接口的比较元素方法
Less(i, j int) bool
// Swap 实现sort.Interface接口的交换元素方法
Swap(i, j int)
// Empty returns an empty Series of the same type
Empty(t ...Type) Series
// Copy 复制
Copy() Series
// Reverse 序列反转
Reverse() Series
// Select 选取一段记录
Select(r api.ScopeLimit) Series
// Append 增加一批记录
Append(values ...any) Series
// Concat concatenates two series together. It will return a new Series with the
// combined elements of both Series.
Concat(x Series) Series
// Records returns the elements of a Series as a []string
Records(round ...bool) []string
// IndexOf 取一条记录, index<0时, 从后往前取值
IndexOf(index int, opt ...any) any
// Subset 获取子集
Subset(start, end int, opt ...any) Series
// Repeat elements of an array.
Repeat(x any, repeats int) Series
// FillNa Fill NA/NaN values using the specified method.
FillNa(v any, inplace bool) Series
// Ref 引用其它周期的数据
Ref(periods any) (s Series)
// Shift index by desired number of periods with an optional time freq.
// 使用可选的时间频率按所需的周期数移动索引.
Shift(periods int) Series
// Rolling 序列化版本
Rolling(param any) RollingAndExpandingMixin
// Apply 接受一个回调函数
Apply(f func(idx int, v any))
// Apply2 增加替换功能, 默认不替换
Apply2(f func(idx int, v any) any, args ...bool) Series
// Logic 逻辑处理
Logic(f func(idx int, v any) bool) []bool
// EWM Provide exponentially weighted (EW) calculations.
//
// Exactly one of “com“, “span“, “halflife“, or “alpha“ must be
// provided if “times“ is not provided. If “times“ is provided,
// “halflife“ and one of “com“, “span“ or “alpha“ may be provided.
EWM(alpha EW) ExponentialMovingWindow
// Mean calculates the average value of a series
Mean() DType
// StdDev calculates the standard deviation of a series
StdDev() DType
// Max 找出最大值
Max() any
// ArgMax Returns the indices of the maximum values along an axis
ArgMax() int
// Min 找出最小值
Min() any
// ArgMin Returns the indices of the minimum values along an axis
ArgMin() int
// Diff 元素的第一个离散差
Diff(param any) (s Series)
// Std 计算标准差
Std() DType
// Sum 计算累和
Sum() DType
// Add 加
Add(x any) Series
// Sub 减
Sub(x any) Series
// Mul 乘
Mul(x any) Series
// Div 除
Div(x any) Series
// Eq 等于
Eq(x any) Series
// Neq 不等于
Neq(x any) Series
// Gt 大于
Gt(x any) Series
// Gte 大于等于
Gte(x any) Series
// Lt 小于
Lt(x any) Series
// Lte 小于等于
Lte(x any) Series
// And 与
And(x any) Series
// Or 或
Or(x any) Series
// Not 非
Not() Series
}
Series
Data structure for 1-dimensional cross-sectional and time series data 一维横截面和时间序列数据的数据结构
func Align2Series ¶ added in v0.9.10
Align2Series any转换成series
type Signed ¶ added in v0.6.5
Signed is a constraint that permits any signed integer type. If future releases of Go add new predeclared signed integer types, this constraint will be modified to include them.
type StringFormatter ¶ added in v0.6.5
type StringFormatter func(val interface{}) string
StringFormatter is used to convert a value into a string. Val can be nil or the concrete type stored by the series.
type Type ¶ added in v0.6.5
Type is a convenience alias that can be used for a more type safe way of reason and use Series types.
func DetectTypeBySlice ¶ added in v0.6.6
DetectTypeBySlice 检测类型
type Unsigned ¶ added in v0.6.5
Unsigned is a constraint that permits any unsigned integer type. If future releases of Go add new predeclared unsigned integer types, this constraint will be modified to include them.
type ZTable ¶ added in v0.7.7
type ZTable struct {
// contains filtered or unexported fields
}
ZTable is the core z-score table component
func NewZTable ¶ added in v0.7.7
NewZTable creates and returns a new ZTable object. 'options' allows you to set the bucket size of the leaf nodes. Tuning bucket size will allow you to trade off memory for speed and vice-versa in the z-score lookup,
func (*ZTable) FindPercentage ¶ added in v0.7.7
FindPercentage returns the percentage of a given z-score from the table
Source Files
¶
- abs.go
- align.go
- argmax.go
- argmin.go
- arithmetics.go
- arithmetics_add.go
- arithmetics_div.go
- arithmetics_mul.go
- arithmetics_sub.go
- builtin.go
- count.go
- cumsum.go
- diff.go
- dot.go
- errors.go
- ewm.go
- fillna.go
- gonum.go
- logic.go
- logic_all.go
- logic_any.go
- logic_equal.go
- matrix.go
- max.go
- maximum.go
- mean.go
- median.go
- min.go
- minimum.go
- ndarray.go
- ndarray_append.go
- ndarray_basic.go
- ndarray_fromnumeric.go
- ndarray_logic.go
- ndarray_range.go
- ndarray_sort.go
- ndarray_type.go
- ones.go
- params.go
- polynomial.go
- pow.go
- range.go
- repeat.go
- reverse.go
- rolling.go
- rolling_count.go
- rolling_max.go
- rolling_mean.go
- rolling_min.go
- rolling_std.go
- rolling_sum.go
- series.go
- series_convert.go
- shape.go
- shift.go
- slope.go
- sqrt.go
- stddev.go
- strings.go
- sum.go
- trace.go
- type.go
- type_bool.go
- type_dtype.go
- type_float32.go
- type_float64.go
- type_int32.go
- type_int64.go
- type_integer.go
- type_xstring.go
- util.go
- where.go
- window_rolling.go
- zeros.go
- ztable.go
- ztable_data.go
- ztable_fast.go
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