def _default(self, model, fit=False):
if fit:
self._modelfile = tempfile().name
model = model or self._modelfile
assert model is not None
argv = map(str, self._argv)
argv += ["--dimensionality", self._dim]
argv += [("--test_file", "--training_file")[fit], self._data]
argv += [("--model_in", "--model_out")[fit], model]
if not fit:
outfile = tempfile().name
argv += ["--cluster_mapping_out", outfile]
call(argv, verbose=self.verbose)
X, y = read_svmlight(outfile)
return X.todense()
else:
call(argv, verbose=self.verbose)
self._modelfile = model
def _default(self, argv, X, Y=None):
infile, descfile = WiseRFRegressor._make_wiserf_csvs(X, Y)
argv += ["--in-file", infile]
argv += ["--desc-file", descfile]
call(argv, verbose=self.verbose)
def _default(self, argv):
argv += ["--dimensionality", str(self._dim)]
call(argv, verbose=self.verbose)