ó šßÈ[c@`sNdZddlmZmZmZmZddlZddlZddl m Z ddl m Z ddl mZy&ddlZdd lmZeZWnek r¯eZnXeoÂe ed ƒZd d d gZidgd 6Zde fd„ƒYZdd„Zeddd ƒZeddd ƒZdZdee_dee_dS(u¤ Tabular models. Tabular models of any dimension can be created using `tabular_model`. For convenience `Tabular1D` and `Tabular2D` are provided. Examples -------- >>> table = np.array([[ 3., 0., 0.], ... [ 0., 2., 0.], ... [ 0., 0., 0.]]) >>> points = ([1, 2, 3], [1, 2, 3]) >>> t2 = Tabular2D(points, lookup_table=table, bounds_error=False, fill_value=None, method='nearest') i(tabsolute_importtunicode_literalstdivisiontprint_functionNi(tModeli(t minversion(trange(tinterpnu0.14u tabular_modelu Tabular1Du Tabular2Duscipyt_TabularcB`sƒeZdZeZeZeZd Zej ƒZ e Z dZ d d de ejd„Zd„Zd„Zed„ƒZd„ZRS( uÜ Returns an interpolated lookup table value. Parameters ---------- points : tuple of ndarray of float, with shapes (m1, ), ..., (mn, ), optional The points defining the regular grid in n dimensions. lookup_table : array-like, shape (m1, ..., mn, ...) The data on a regular grid in n dimensions. method : str, optional The method of interpolation to perform. Supported are "linear" and "nearest", and "splinef2d". "splinef2d" is only supported for 2-dimensional data. Default is "linear". bounds_error : bool, optional If True, when interpolated values are requested outside of the domain of the input data, a ValueError is raised. If False, then ``fill_value`` is used. fill_value : float, optional If provided, the value to use for points outside of the interpolation domain. If None, values outside the domain are extrapolated. Extrapolation is not supported by method "splinef2d". Returns ------- value : ndarray Interpolated values at input coordinates. Raises ------ ImportError Scipy is not installed. Notes ----- Uses `scipy.interpolate.interpn`. uyiulinearcK`si|jddƒ}|dkr-tdƒ‚ntt|ƒj||dk rtj|ƒ}|jj |j kr‘t dj |jj ƒƒ‚n||_n|dkrËt d„|jj Dƒƒ|_n|jj dkrüt|t ƒ rü|f|_n ||_t|jƒ|jj krJt dj |jj t|jƒƒƒ‚n||_||_||_dS(Nun_modelsiuOnly n_models=1 is supported.u3lookup_table should be an array with {0} dimensionscs`s'|]}tj|dtjƒVqdS(tdtypeN(tnptarangetfloat(t.0tx((s7lib/python2.7/site-packages/astropy/modeling/tabular.pys nsu/Expected grid points in {0} directions, got {1}(tgettNotImplementedErrortsuperRt__init__tNoneR tasarrayt lookup_tabletndimt ValueErrortformatttupletshapetpointst isinstancetlent bounds_errortmethodt fill_value(tselfRRRRR tkwargstn_models((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyR_s.      "     cC`s%dj|jj|j|jƒ}|S(Nu#<{0}(points={1}, lookup_table={2})>(Rt __class__t__name__RR(R!tfmt((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyt__repr__~sc C`s¼d|jjfd|jfd|jfd|jfdd|jfd|jfd |jfd |jfd |j fg }g|D]*\}}|dk rd j ||ƒ^q}d j |ƒS(NuModeluNameuInputsuOutputsu Parametersuu pointsu lookup_tableu methodu fill_valueu bounds_erroru{0}: {1}u (u Parametersu( R$R%tnametinputstoutputsRRRR RRRtjoin(R!tdefault_keywordstkeywordtvaluetparts((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyt__str__ƒs       $cC`sdg|jD]}t|ƒt|ƒf^q ddd…}t|ƒdkrZ|d}nt|ƒS(uÖ Tuple defining the default ``bounding_box`` limits, ``(points_low, points_high)``. Examples -------- >>> from astropy.modeling.models import Tabular1D, Tabular2D >>> t1 = Tabular1D(points=[1,2,3], lookup_table=[10, 20, 30]) >>> t1.bounding_box (1, 3) >>> t2 = Tabular2D(points=[[1,2,3],[2,3,4]], lookup_table=[[10,20,30],[20,30,40]]) >>> t2.bounding_box ((2, 4), (1, 3)) Niÿÿÿÿii(RtmintmaxRR(R!tptbbox((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyt bounding_box—s; c G`sÔ|dj}g||j D]}|jƒ^q}tj|ƒj}tsZtdƒ‚nt|j |j |d|j d|j d|j ƒ}|jdkr®|j|ƒ}n"g|D]}|j|ƒ^qµ}|S(u Return the interpolated values at the input coordinates. Parameters ---------- inputs : list of scalars or ndarrays Input coordinates. The number of inputs must be equal to the dimensions of the lookup table. iu"This model requires scipy >= v0.14RRR i(Rtn_inputstflattenR tarraytTt has_scipyt ImportErrorRRRRRR t n_outputstreshape(R!R)Rtinptresulttr((s7lib/python2.7/site-packages/astropy/modeling/tabular.pytevaluate­s & "(uyN(R%t __module__t__doc__tFalsetlineartfittabletstandard_broadcastingR*tabctabstractpropertyRtTruet _is_dynamict_idRR tnanRR'R0tpropertyR5RA(((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyR+s&    cC`s˜tjdg|ƒ}td„t|jƒDƒƒ}i|d6|d6}|dkrtj}tjd7_dj|ƒ}nt t |ƒtf|ƒS(ué Make a ``Tabular`` model where ``n_inputs`` is based on the dimension of the lookup_table. This model has to be further initialized and when evaluated returns the interpolated values. Parameters ---------- dim : int Dimensions of the lookup table. name : str Name for the class. Examples -------- >>> table = np.array([[3., 0., 0.], ... [0., 2., 0.], ... [0., 0., 0.]]) >>> tab = tabular_model(2, name='Tabular2D') >>> print(tab) Name: Tabular2D Inputs: (u'x0', u'x1') Outputs: (u'y',) >>> points = ([1, 2, 3], [1, 2, 3]) Setting fill_value to None, allows extrapolation. >>> m = tab(points, lookup_table=table, name='my_table', bounds_error=False, fill_value=None, method='nearest') >>> xinterp = [0, 1, 1.5, 2.72, 3.14] >>> m(xinterp, xinterp) # doctest: +FLOAT_CMP array([3., 3., 3., 0., 0.]) ics`s|]}dj|ƒVqdS(ux{0}N(R(R tidx((s7lib/python2.7/site-packages/astropy/modeling/tabular.pys ïsu lookup_tableuinputsiu Tabular{0}N( R tzerosRRRRRRLRttypetstr(tdimR(ttableR)tmemberstmodel_id((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyt tabular_modelÉs%  R(uŒ method : str, optional The method of interpolation to perform. Supported are "linear" and "nearest", and "splinef2d". "splinef2d" is only supported for 2-dimensional data. Default is "linear". bounds_error : bool, optional If True, when interpolated values are requested outside of the domain of the input data, a ValueError is raised. If False, then ``fill_value`` is used. fill_value : float, optional If provided, the value to use for points outside of the interpolation domain. If None, values outside the domain are extrapolated. Extrapolation is not supported by method "splinef2d". Returns ------- value : ndarray Interpolated values at input coordinates. Raises ------ ImportError Scipy is not installed. Notes ----- Uses `scipy.interpolate.interpn`. u! Tabular model in 1D. Returns an interpolated lookup table value. Parameters ---------- points : array-like of float of ndim=1. The points defining the regular grid in n dimensions. lookup_table : array-like, of ndim=1. The data in one dimensions. uQ Tabular model in 2D. Returns an interpolated lookup table value. Parameters ---------- points : tuple of ndarray of float, with shapes (m1, m2), optional The points defining the regular grid in n dimensions. lookup_table : array-like, shape (m1, m2) The data on a regular grid in 2 dimensions. (RCt __future__RRRRRHtnumpyR tcoreRtutilsRtextern.six.movesRtscipytscipy.interpolateRRJR:R;RDt__all__t__doctest_requires__RRRWt Tabular1Dt Tabular2Dt _tab_docs(((s7lib/python2.7/site-packages/astropy/modeling/tabular.pyts,"      ž 0