import lightgbm as lgb
import numpy as np
class DatasetTest:
  def __init__(self):
    self._matrix1 = lgb.Dataset('data/train.svm.txt')
    self._matrix2 = lgb.Dataset(data=np.arange(0, 12).reshape((4, 3)), 
                                label=[1, 2, 3, 4], weight=[0.5, 0.4, 0.3, 0.2],
                                silent=False, feature_name=['a', 'b', 'c'])
  def print(self,matrix):
    '''
    Matrix 构建尚未完成时的属性
    :param matrix:
    :return:
    '''
    print('data: %s' % matrix.data)
    print('label: %s' % matrix.label)
    print('weight: %s' % matrix.weight)
    print('init_score: %s' % matrix.init_score)
    print('group: %s' % matrix.group)
​
  def run_method(self,matrix):
    '''
    测试一些 方法
    :param matrix:
    :return:
    '''
    print('get_ref_chain():', matrix.get_ref_chain(ref_limit=10))
    # get_ref_chain(): {<lightgbm.basic.Dataset object at 0x7f29cd762f28>}
    print('subset():', matrix.subset(used_indices=[0,1]))
    # subset(): <lightgbm.basic.Dataset object at 0x7f29a4aeb518>
    
  def test(self):
    self.print(self._matrix1)
    # data: data/train.svm.txt
    # label: None
    # weight: None
    # init_score: None
    # group: None
    
    self.print(self._matrix2)
    # data: [[ 0  1  2]
    #  [ 3  4  5]
    #  [ 6  7  8]
    #  [ 9 10 11]]
    # label: [1, 2, 3, 4]
    # weight: [0.5, 0.4, 0.3, 0.2]
    # init_score: No
    
    self.run_method(self._matrix2)