aleksapand commented on a change in pull request #1191: URL: https://github.com/apache/systemds/pull/1191#discussion_r584361884
########## File path: scripts/builtin/cspline.dml ########## @@ -0,0 +1,63 @@ +#------------------------------------------------------------- +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +# +#------------------------------------------------------------- +# +# THIS SCRIPT SOLVES CUBIC SPLINE INTERPOLATION +# +# INPUT PARAMETERS: +# -------------------------------------------------------------------------------------------- +# NAME TYPE DEFAULT MEANING +# -------------------------------------------------------------------------------------------- +# X Matrix[Double] --- 1-column matrix of x values knots +# Y Matrix[Double] --- 1-column matrix of corresponding y values knots +# inp_x Double --- the given input x, for which the cspline will find predicted y. +# Log String " " Location to store iteration-specific variables for monitoring and debugging purposes +# +# tol Double 0.000001 Tolerance (epsilon); conjugate graduent procedure terminates early if +# L2 norm of the beta-residual is less than tolerance * its initial norm +# maxi Int 0 Maximum number of conjugate gradient iterations, 0 = no maximum +# -------------------------------------------------------------------------------------------- +# OUTPUT: +# pred_Y Matrix[Double] --- Predicted value +# K Matrix[Double] --- Matrix of k parameters Review comment: With X and Y we meant sample points. Sorry for leaving it ambiguous. For the new point we would do the following: https://en.wikipedia.org/wiki/Spline_interpolation#Algorithm_to_find_the_interpolating_cubic_spline So K will be calculated from sample points using cspline builtin function and for each new x, we would need already calculated K, sample points X, Y and new x. It is too late to include it in this PR since it is a submission for the DIA practical, but I could do it in the following weeks in a new PR. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
