#!/usr/bin/env python # -*- coding: utf-8 -*- # # Copyright 2019 The FATE Authors. All Rights Reserved. # # Licensed 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. # from pipeline.param.base_param import BaseParam import collections class SampleParam(BaseParam): """ Define the sample method Parameters ---------- mode: str, accepted 'random','stratified', 'exact_by_weight', specify sample to use, default: 'random' method: str, accepted 'downsample','upsample' only in this version. default: 'downsample' fractions: None or float or list, if mode equals to random, it should be a float number greater than 0, otherwise a list of elements of pairs like [label_i, sample_rate_i], e.g. [[0, 0.5], [1, 0.8], [2, 0.3]]. default: None random_state: int, RandomState instance or None, default: None need_run: bool, default True Indicate if this module needed to be run """ def __init__(self, mode="random", method="downsample", fractions=None, random_state=None, task_type="hetero", need_run=True): self.mode = mode self.method = method self.fractions = fractions self.random_state = random_state self.task_type = task_type self.need_run = need_run def check(self): descr = "sample param" self.mode = self.check_and_change_lower(self.mode, ["random", "stratified", "exact_by_weight"], descr) self.method = self.check_and_change_lower(self.method, ["upsample", "downsample"], descr) if self.mode == "stratified" and self.fractions is not None: if not isinstance(self.fractions, list): raise ValueError("fractions of sample param when using stratified should be list") for ele in self.fractions: if not isinstance(ele, collections.Container) or len(ele) != 2: raise ValueError( "element in fractions of sample param using stratified should be a pair like [label_i, rate_i]") return True