1672b5a9a47b081aa3e61c9f2ca76fae26ed8730,cheml/wrappers/cheml_cml/cheml_wrapper.py,DistanceMatrix,fit,#DistanceMatrix#,221

Before Change

    def fit(self):
        from cheml.chem import DistanceMatrix
        // check inputs
        if isinstance(self.legal_inputs["df"], type(None)):
            msg = "@Task //%i(%s): input data frame is required"%(self.iblock,self.SuperFunction)
            raise IOError(msg)
        try:
            model = DistanceMatrix(**self.parameters)
        except Exception as err:
            msg = "@Task //%i(%s): " % (self.iblock + 1, self.SuperFunction) + type(err).__name__ + ": " + err.message
            raise TypeError(msg)
        order = [edge[1] for edge in self.Base.graph if edge[0] == self.iblock]
        for token in set(order):
            if token == "df":
                val = pd.DataFrame(model.transform(self.legal_inputs["df"][0].values))
                self.Base.send[(self.iblock, token)] = [val, order.count(token)]
            else:
                msg = "@Task //%i(%s): asked to send a non valid output token "%s"" % (
                    self.iblock + 1, self.SuperFunction, token)

After Change

            if token not in self.outputs:
                msg = "@Task //%i(%s): not a valid output token "%s"" % (self.iblock + 1, self.Task, token)
                raise NameError(msg)
            elif token == "df":
                ar = self.inputs["df"].value
                df = pd.DataFrame(model.transform(ar))
                self.set_value(token, df)
                self.outputs[token].count = order.count(token)
                self.Base.send[(self.iblock, token)] = self.outputs[token]
        del self.inputs

Instances