mirror of
https://github.com/meteoinfo/MeteoInfo.git
synced 2026-02-01 17:20:51 +00:00
update interpolate package
This commit is contained in:
wyq
parent
12fc6e66a5
commit
34341dcdd9
@ -1,7 +1,6 @@
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<?xml version="1.0" encoding="UTF-8" standalone="no"?>
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<MeteoInfo File="milconfig.xml" Type="configurefile">
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<Path OpenPath="D:\Working\MIScript\Jython\mis\common_math\random">
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\array"/>
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<Path OpenPath="D:\Working\MIScript\Jython\mis\common_math\interpolate">
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\plot_types\contour"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\io"/>
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@ -14,19 +13,28 @@
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\toolbox\miml"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\io\burf"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\common_math"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\common_math\random"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\common_math"/>
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<RecentFolder Folder="D:\Working\MIScript\Jython\mis\common_math\interpolate"/>
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</Path>
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<File>
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<OpenedFiles>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\deep_learning\mnist_1.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\cluster\specc_1.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\random\random_seed_1.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp1d_1.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp2d_1.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\nearest_3d.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\linint2.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp2d_3.py"/>
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<OpenedFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp2d_2.py"/>
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</OpenedFiles>
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<RecentFiles>
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<RecentFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\deep_learning\mnist_1.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\toolbox\miml\cluster\specc_1.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\random\random_seed_1.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp1d_1.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp2d_1.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\nearest_3d.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\linint2.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp2d_3.py"/>
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<RecentFile File="D:\Working\MIScript\Jython\mis\common_math\interpolate\interp2d_2.py"/>
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</RecentFiles>
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</File>
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<Font>
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Binary file not shown.
@ -43,9 +43,9 @@ __all__ = [
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'broadcast_to','cdiff','ceil','concatenate','corrcoef','cos','cumsum','degrees','delete','delnan','diag',
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'diff','dim_array','datatable','dot','empty','empty_like','exp','eye','floor','fmax','fmin','full',
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'griddata','hcurl','hdivg','hstack','identity','interp2d',
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'interpn','isarray','isfinite','isinf','isnan','linint2','linregress','linspace','log','log10',
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'interpn','isarray','isfinite','isinf','isnan','linspace','log','log10',
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'logical_not','logspace','magnitude','max','maximum','mean','median','meshgrid','min','minimum',
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'monthname','moveaxis','newaxis','nonzero','ones','ones_like','pol2cart','polyval','power','radians','ravel',
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'monthname','moveaxis','newaxis','nonzero','ones','ones_like','pol2cart','power','radians','ravel',
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'reshape','repeat','roll','rolling_mean','rot90','sin','shape','smooth5','smooth9','sort','squeeze','argsort',
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'split','sqrt','square','std','sum','swapaxes','tan','tile','transpose','trapz','vdot','unique',
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'unravel_index','var','vstack','where','zeros','zeros_like'
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@ -2034,44 +2034,7 @@ def corrcoef(x, y):
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b = ArrayMath.getR(y.asarray(), x.asarray())
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r = array([[1, a], [b, 1]])
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return r
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def linregress(x, y):
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'''
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Calculate a linear least-squares regression for two sets of measurements.
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:param x, y: (*array_like*) Two sets of measurements. Both arrays should have the same length.
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:returns: Result slope, intercept, relative coefficient, two-sided p-value for a hypothesis test
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whose null hypothesis is that the slope is zero, standard error of the estimated gradient,
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validate data number (remove NaN values).
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'''
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if isinstance(x, list):
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x = array(x)
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if isinstance(y, list):
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y = array(y)
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r = ArrayMath.lineRegress(x.asarray(), y.asarray())
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return r[0], r[1], r[2], r[3], r[4], r[5]
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def polyval(p, x):
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"""
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Evaluate a polynomial at specific values.
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If p is of length N, this function returns the value:
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p[0]*x**(N-1) + p[1]*x**(N-2) + ... + p[N-2]*x + p[N-1]
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If x is a sequence, then p(x) is returned for each element of x. If x is another polynomial then the
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composite polynomial p(x(t)) is returned.
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:param p: (*array_like*) 1D array of polynomial coefficients (including coefficients equal to zero)
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from highest degree to the constant term.
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:param x: (*array_like*) A number, an array of numbers, or an instance of poly1d, at which to evaluate
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p.
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:returns: Polynomial value
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"""
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return NDArray(ArrayMath.polyVal(p, x.asarray()))
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def transpose(a, axes=None):
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'''
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Transpose 2-D array.
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@ -2611,38 +2574,6 @@ def asgridarray(data, x=None, y=None, fill_value=-9999.0):
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def asstationdata(data, x, y, fill_value=-9999.0):
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stdata = StationData(data.asarray(), x.asarray(), y.asarray(), fill_value)
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return PyStationData(stdata)
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def linint2(*args, **kwargs):
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"""
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Interpolates from a rectilinear grid to another rectilinear grid using bilinear interpolation.
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:param x: (*array_like*) X coordinate array of the sample data (one dimension).
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:param y: (*array_like*) Y coordinate array of the sample data (one dimension).
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:param z: (*array_like*) Value array of the sample data (muti-dimension, last two dimensions are y and x).
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:param xq: (*array_like*) X coordinate array of the query data (one dimension).
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:param yq: (*array_like*) Y coordinate array of the query data (one dimension).
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:returns: (*array_like*) Interpolated array.
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"""
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if len(args) == 3:
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z = args[0]
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x = z.dimvalue(z.ndim - 1)
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y = z.dimvalue(z.ndim - 2)
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xq = args[1]
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yq = args[2]
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else:
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x = args[0]
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y = args[1]
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z = args[2]
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xq = args[3]
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yq = args[4]
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x = array(x)._array
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y = array(y)._array
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z = array(z)._array
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xq = array(xq)._array
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yq = array(yq)._array
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r = ArrayUtil.linint2(z, x, y, xq, yq)
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return NDArray(r)
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def interp2d(*args, **kwargs):
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"""
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Binary file not shown.
@ -7,13 +7,13 @@
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#-----------------------------------------------------
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from org.meteoinfo.math.interpolate import InterpUtil
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from org.meteoinfo.math import ArrayMath, ArrayUtil
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from org.meteoinfo.ndarray import Array
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from org.meteoinfo.math import ArrayUtil
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from ..core import NDArray, DimArray
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from ..core import NDArray
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from ..core import numeric as np
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__all__ = [
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'interp1d','RectBivariateSpline'
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'interp1d','interp2d','linint2','RectBivariateSpline'
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]
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class interp1d(object):
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@ -27,9 +27,9 @@ class interp1d(object):
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'''
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def __init__(self, x, y, kind='linear'):
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if isinstance(x, list):
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x = NDArray(ArrayUtil.array(x))
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x = np.array(x)
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if isinstance(y, list):
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y = NDArray(ArrayUtil.array(y))
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y = np.array(y)
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self._func = InterpUtil.getInterpFunc(x.asarray(), y.asarray(), kind)
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def __call__(self, x):
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@ -39,8 +39,8 @@ class interp1d(object):
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:param x: (*array_like*) Points to evaluate the interpolant at.
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'''
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if isinstance(x, list):
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x = NDArray(ArrayUtil.array(x))
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if isinstance(x, (NDArray, DimArray)):
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x = np.array(x)
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if isinstance(x, NDArray):
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x = x.asarray()
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r = InterpUtil.evaluate(self._func, x)
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if isinstance(r, float):
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@ -66,12 +66,12 @@ class interp2d(object):
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'''
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def __init__(self, x, y, z, kind='linear'):
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if isinstance(x, list):
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x = NDArray(ArrayUtil.array(x))
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x = np.array(x)
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if isinstance(y, list):
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y = NDArray(ArrayUtil.array(y))
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y = np.array(y)
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if isinstance(z, list):
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z = NDArray(ArrayUtil.array(z))
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self._func = InterpUtil.getBiInterpFunc(x.asarray(), y.asarray(), z.asarray())
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z = np.array(z)
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self._func = InterpUtil.getBiInterpFunc(x.asarray(), y.asarray(), z.T.asarray(), kind)
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def __call__(self, x, y):
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'''
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@ -81,12 +81,12 @@ class interp2d(object):
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:param y: (*array_like*) Y to evaluate the interpolant at.
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'''
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if isinstance(x, list):
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x = NDArray(ArrayUtil.array(x))
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if isinstance(x, (NDArray, DimArray)):
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x = np.array(x)
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if isinstance(x, NDArray):
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x = x.asarray()
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if isinstance(y, list):
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y = NDArray(ArrayUtil.array(y))
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if isinstance(y, (NDArray, DimArray)):
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y = np.array(y)
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if isinstance(y, NDArray):
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y = y.asarray()
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r = InterpUtil.evaluate(self._func, x, y)
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if isinstance(r, float):
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@ -106,12 +106,12 @@ class RectBivariateSpline(object):
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'''
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def __init__(self, x, y, z):
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if isinstance(x, list):
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x = NDArray(ArrayUtil.array(x))
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x = np.array(x)
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if isinstance(y, list):
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y = NDArray(ArrayUtil.array(y))
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y = np.array(y)
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if isinstance(z, list):
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z = NDArray(ArrayUtil.array(z))
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self._func = InterpUtil.getBiInterpFunc(x.asarray(), y.asarray(), z.asarray())
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z = np.array(z)
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self._func = InterpUtil.getBiInterpFunc(x.asarray(), y.asarray(), z.asarray(), 'linear')
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def __call__(self, x, y):
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'''
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@ -121,17 +121,47 @@ class RectBivariateSpline(object):
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:param y: (*array_like*) Y to evaluate the interpolant at.
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'''
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if isinstance(x, list):
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x = NDArray(ArrayUtil.array(x))
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if isinstance(x, (NDArray, DimArray)):
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x = np.array(x)
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if isinstance(x, NDArray):
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x = x.asarray()
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if isinstance(y, list):
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y = NDArray(ArrayUtil.array(y))
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if isinstance(y, (NDArray, DimArray)):
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y = np.array(y)
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if isinstance(y, NDArray):
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y = y.asarray()
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r = InterpUtil.evaluate(self._func, x, y)
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if isinstance(r, float):
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return r
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else:
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return NDArray(r)
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############################################################
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def linint2(*args, **kwargs):
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"""
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Interpolates from a rectilinear grid to another rectilinear grid using bilinear interpolation.
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:param x: (*array_like*) X coordinate array of the sample data (one dimension).
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:param y: (*array_like*) Y coordinate array of the sample data (one dimension).
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:param z: (*array_like*) Value array of the sample data (muti-dimension, last two dimensions are y and x).
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:param xq: (*array_like*) X coordinate array of the query data (one dimension).
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:param yq: (*array_like*) Y coordinate array of the query data (one dimension).
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:returns: (*array_like*) Interpolated array.
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"""
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if len(args) == 3:
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z = args[0]
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x = z.dimvalue(z.ndim - 1)
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y = z.dimvalue(z.ndim - 2)
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xq = args[1]
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yq = args[2]
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else:
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x = args[0]
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y = args[1]
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z = args[2]
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xq = args[3]
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yq = args[4]
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x = np.array(x)._array
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y = np.array(y)._array
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z = np.array(z)._array
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xq = np.array(xq)._array
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yq = np.array(yq)._array
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r = ArrayUtil.linint2(z, x, y, xq, yq)
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return NDArray(r)
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@ -9,15 +9,7 @@ import java.util.ArrayList;
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import java.util.List;
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import org.apache.commons.math3.analysis.BivariateFunction;
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import org.apache.commons.math3.analysis.UnivariateFunction;
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import org.apache.commons.math3.analysis.interpolation.AkimaSplineInterpolator;
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import org.apache.commons.math3.analysis.interpolation.BicubicInterpolator;
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import org.apache.commons.math3.analysis.interpolation.BivariateGridInterpolator;
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import org.apache.commons.math3.analysis.interpolation.DividedDifferenceInterpolator;
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import org.apache.commons.math3.analysis.interpolation.LinearInterpolator;
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import org.apache.commons.math3.analysis.interpolation.LoessInterpolator;
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import org.apache.commons.math3.analysis.interpolation.NevilleInterpolator;
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import org.apache.commons.math3.analysis.interpolation.SplineInterpolator;
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import org.apache.commons.math3.analysis.interpolation.UnivariateInterpolator;
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import org.apache.commons.math3.analysis.interpolation.*;
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import org.apache.commons.math3.analysis.polynomials.PolynomialSplineFunction;
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import org.meteoinfo.geoprocess.GeoComputation;
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import org.meteoinfo.global.PointD;
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@ -95,13 +87,22 @@ public class InterpUtil {
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* @param x X data
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* @param y Y data
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* @param z Z data
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* @param kind Specifies the kind of interpolation as a string.
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* @return Interpolation function
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*/
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public static BivariateFunction getBiInterpFunc(Array x, Array y, Array z) {
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public static BivariateFunction getBiInterpFunc(Array x, Array y, Array z, String kind) {
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double[] xd = (double[]) ArrayUtil.copyToNDJavaArray_Double(x);
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double[] yd = (double[]) ArrayUtil.copyToNDJavaArray_Double(y);
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double[][] zd = (double[][]) ArrayUtil.copyToNDJavaArray_Double(z);
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BivariateGridInterpolator li = new BicubicInterpolator();
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BivariateGridInterpolator li;
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switch (kind) {
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case "spline":
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li = new PiecewiseBicubicSplineInterpolator();
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break;
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default:
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li = new BicubicInterpolator();
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break;
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}
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BivariateFunction func = li.interpolate(xd, yd, zd);
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return func;
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