diff options
| -rw-r--r-- | spline.py | 29 |
1 files changed, 24 insertions, 5 deletions
@@ -2,9 +2,11 @@ # # Aaron LI # Created: 2016-07-10 -# Updated: 2016-07-13 +# Updated: 2016-07-14 # # Change logs: +# 2016-07-14: +# * Workaround the spline fitting error when give constant input y data # 2016-07-13: # * Improve the `np.array` usage a bit # @@ -16,9 +18,12 @@ and/or extrapolate a group of discrete data. * smoothing spline: R's mgcv::gam() """ +import sys + import numpy as np import rpy2.robjects as ro from rpy2.robjects.packages import importr +from rpy2.rinterface import RRuntimeError class Spline: @@ -81,10 +86,24 @@ class SmoothSpline(Spline): else: y = ro.FloatVector(self.y) weights = ro.FloatVector(self.weights) - self.spline = self.mgcv.gam( - ro.Formula("y ~ s(x, bs='ps')"), - data=ro.DataFrame({"x": x, "y": y}), - weights=weights, method="REML") + try: + self.spline = self.mgcv.gam( + ro.Formula("y ~ s(x, bs='ps')"), + data=ro.DataFrame({"x": x, "y": y}), + weights=weights, method="REML") + except RRuntimeError: + # NOTE: + # If the input y data is constant (e.g., the temperature profile + # has only ONE data point), then above smoothing spline fitting + # using method "REML" will failed with error: + # Error in gam.reparam(UrS, sp, grderiv) : + # NA/NaN/Inf in foreign function call (arg 3) + print("WARNING: 'mgcv.gam()' using method 'REML' failed!", + file=sys.stderr) + self.spline = self.mgcv.gam( + ro.Formula("y ~ s(x, bs='ps', sp=0.6)"), + data=ro.DataFrame({"x": x, "y": y}), + weights=weights) def eval(self, x): x = np.array(x, ndmin=1) |