B q\*@sdZddlZddlZddlmZddlmZddl m Z yddl Z ddl m Z dZWnek rld ZYnXeoze e d Zd d d gZd dgiZGdddeZddd Zedd dZedd dZdZdee_dee_dS)a 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') N)Model)units) minversion)interpnTFz0.14 tabular_model Tabular1D Tabular2DscipycseZdZdZdZdZdZdZee j ddZ dZ dZ ddd dejffd d Zd d ZddZeddZeddZeddZddZZS)_Tabulara\ 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 or `~astropy.units.Quantity`, 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". If Quantity is given, it will be converted to the unit of ``lookup_table``, if applicable. Returns ------- value : ndarray Interpolated values at input coordinates. Raises ------ ImportError Scipy is not installed. Notes ----- Uses `scipy.interpolate.interpn`. F)ycCsdS)N)selfr r 7lib/python3.7/site-packages/astropy/modeling/tabular.py lookup_tableYsz_Tabular.lookup_tableTrNlinearc  sh|dd}|dkrtdtjf||dkr:tdt|tjsPt |}|j j |j krptd |j j |dkrt dd|jD}n~|j dkrt|t s|f}t|}||j krtd |j ||dkr t|d tjr ttd d |Ddkr td t|tjrFt|tjs8td |j||jj}||_||_ ||_||_||_dS)Nn_modelsrzOnly n_models=1 is supported.zMust provide a lookup table.z4lookup_table should be an array with {0} dimensions.css|]}tj|tdVqdS))ZdtypeN)npZarangefloat).0xr r r usz$_Tabular.__init__..z0Expected grid points in {0} directions, got {1}.rcSsg|]}t|ddqS)unitN)getattr)rpr r r sz%_Tabular.__init__..z#points must all have the same unit.z1fill value is in {0} but expected to be unitless.)getNotImplementedErrorsuper__init__ ValueError isinstanceuQuantityrZasarrayrndimformattupleshapelensetrtovaluepoints bounds_errormethod fill_value) rr,rr.r-r/kwargsrZnpts) __class__r rrbsD       z_Tabular.__init__cCsd|jj|j|j}|S)Nz#<{0}(points={1}, lookup_table={2})>)r%r1__name__r,r)rZfmtr r r__repr__sz_Tabular.__repr__c Cshd|jjfd|jfd|jfd|jfdd|jfd|jfd|jfd |jfd |j fg }d d |D}d |S)NrNameZInputsZOutputs)Z Parametersz pointsz lookup_tablez methodz fill_valuez bounds_errorcSs$g|]\}}|dk rd||qS)Nz{0}: {1})r%)rkeywordr+r r rrsz$_Tabular.__str__.. ) r1r2nameinputsoutputsr,rr.r/r-join)rZdefault_keywordspartsr r r__str__s  z_Tabular.__str__cs6|jdttjsdStfdd|jDSdS)Nrcsg|]}|jfqSr )r)rr)ptsr rrsz(_Tabular.input_units..)r,r!r"r#dictr9)rr )r>r input_unitss  z_Tabular.input_unitscCs"t|jtjsdSd|jjiSdS)Nr )r!rr"r#r)rr r r return_unitssz_Tabular.return_unitscCs6dd|jDddd}t|dkr.|d}t|S)a 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)) cSsg|]}t|t|fqSr )minmax)rrr r rrsz)_Tabular.bounding_box..Nrr)r,r(r&)rZbboxr r r bounding_boxs z_Tabular.bounding_boxcst|tjr|j}|djdd|d|jD}t|j}t sLt dt |j |j ||j|j|jd}t|j tjrt|j dtjs||j j}|jdkr|}nfdd|D}|S) a 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. rcSsg|] }|qSr )Zflatten)rZinpr r rrsz%_Tabular.evaluate..Nz"This model requires scipy >= v0.14)r.r-r/rcsg|]}|qSr )reshape)rr)r'r rrs)r!r"r#r+r'Zn_inputsrZarrayT has_scipy ImportErrorrr,rr.r-r/rZ n_outputsrF)rr9resultr )r'revaluates"        z_Tabular.evaluate)r2 __module__ __qualname____doc__rZfittableZstandard_broadcastingr:propertyabcabstractmethodrZ _is_dynamic_idrnanrr3r=r@rArErL __classcell__r r )r1rr *s"',   r cCs|dkrtdtdg|}tddt|jD}||d}|dkrTd|d<nd |d<|d krtj}tjd7_d |}t t |tf|S) a 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.]) rz.Lookup table must have at least one dimension.css|]}d|VqdS)zx{0}N)r%)ridxr r rrsz tabular_model..)rr9TZ _separableFNz Tabular{0}) r rZzerosr&ranger$r rSr%typestr)Zdimr8tabler9membersZmodel_idr r rrs'   )r8rVa 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`. a! 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. aQ 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. )N)rOrQZnumpyrZcorerZastropyrr"Z astropy.utilsrr Zscipy.interpolaterrIrJ__all__Z__doctest_requires__r rrr Z _tab_docsr r r rs,       F ;