def _make_mock_data_array(self, tickers, fields):
    all_dates_market_open = pd.date_range(start=(self.data_start_date + MarketOpenEvent.trigger_time()), end=(self.data_end_date + MarketOpenEvent.trigger_time()), freq='B')
    all_dates_market_close = pd.date_range(start=((self.data_start_date + MarketCloseEvent.trigger_time()) - Frequency.MIN_1.time_delta()), end=((self.data_end_date + MarketCloseEvent.trigger_time()) - Frequency.MIN_1.time_delta()), freq='B')
    num_of_dates = len(all_dates_market_open)
    num_of_tickers = len(tickers)
    num_of_fields = len(fields)
    start_value = 100.0
    values = np.arange(start_value, (((num_of_dates * num_of_tickers) * num_of_fields) + start_value))
    reshaped_values = np.reshape(values, (num_of_dates, num_of_tickers, num_of_fields))
    mocked_result_market_open = QFDataArray.create(all_dates_market_open, tickers, fields, data=reshaped_values)
    mocked_result_market_close = QFDataArray.create(all_dates_market_close, tickers, fields, data=reshaped_values)
    mocked_result_market_close.loc[:, :, PriceField.Low] -= 5.0
    mocked_result_market_close.loc[:, :, PriceField.High] += 5.0
    all_dates = all_dates_market_open.union(all_dates_market_close)
    mocked_result = QFDataArray.create(all_dates, tickers, fields)
    mocked_result.loc[all_dates_market_open, :, :] = mocked_result_market_open.loc[:, :, :]
    mocked_result.loc[all_dates_market_close, :, :] = mocked_result_market_close.loc[:, :, :]
    self._add_test_cases(mocked_result, tickers)
    return mocked_result
def _make_mock_data_array(self, tickers, fields):
    all_dates_market_open = pd.date_range(start=(self.data_start_date + MarketOpenEvent.trigger_time()), end=(self.data_end_date + MarketOpenEvent.trigger_time()), freq='B')
    all_dates_market_close = pd.date_range(start=((self.data_start_date + MarketCloseEvent.trigger_time()) - Frequency.MIN_1.time_delta()), end=((self.data_end_date + MarketCloseEvent.trigger_time()) - Frequency.MIN_1.time_delta()), freq='B')
    num_of_dates = len(all_dates_market_open)
    num_of_tickers = len(tickers)
    num_of_fields = len(fields)
    start_value = 100.0
    values = np.arange(start_value, (((num_of_dates * num_of_tickers) * num_of_fields) + start_value))
    reshaped_values = np.reshape(values, (num_of_dates, num_of_tickers, num_of_fields))
    mocked_result_market_open = QFDataArray.create(all_dates_market_open, tickers, fields, data=reshaped_values)
    mocked_result_market_close = QFDataArray.create(all_dates_market_close, tickers, fields, data=reshaped_values)
    mocked_result_market_close.loc[:, :, PriceField.Low] -= 5.0
    mocked_result_market_close.loc[:, :, PriceField.High] += 5.0
    all_dates = all_dates_market_open.union(all_dates_market_close)
    mocked_result = QFDataArray.create(all_dates, tickers, fields)
    mocked_result.loc[all_dates_market_open, :, :] = mocked_result_market_open.loc[:, :, :]
    mocked_result.loc[all_dates_market_close, :, :] = mocked_result_market_close.loc[:, :, :]
    self._add_test_cases(mocked_result, tickers)
    return mocked_result