Python testing.str_to_seconds函数代码示例

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本文整理汇总了Python中zipline.testing.str_to_seconds函数的典型用法代码示例。如果您正苦于以下问题：Python str_to_seconds函数的具体用法？Python str_to_seconds怎么用？Python str_to_seconds使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。

在下文中一共展示了str_to_seconds函数的10个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: make_mergers_data

 def make_mergers_data(cls):
     return pd.DataFrame.from_records([
         {
             'effective_date': str_to_seconds('2016-01-06'),
             'ratio': 0.5,
             'sid': cls.MERGER_ASSET_SID,
         },
         {
             'effective_date': str_to_seconds('2016-01-07'),
             'ratio': 0.6,
             'sid': cls.ILLIQUID_MERGER_ASSET_SID,
         }
     ])

开发者ID:280185386，项目名称:zipline，代码行数:13，代码来源:test_bar_data.py

示例2: make_splits_data

 def make_splits_data(cls):
     return pd.DataFrame.from_records([
         {
             'effective_date': str_to_seconds("2016-01-06"),
             'ratio': 0.5,
             'sid': cls.SPLIT_ASSET_SID,
         },
         {
             'effective_date': str_to_seconds("2016-01-07"),
             'ratio': 0.5,
             'sid': cls.ILLIQUID_SPLIT_ASSET_SID,
         },
     ])

开发者ID:280185386，项目名称:zipline，代码行数:13，代码来源:test_bar_data.py

示例3: create_adjustment_reader

 def create_adjustment_reader(cls, tempdir):
     dbpath = tempdir.getpath('adjustments.sqlite')
     writer = SQLiteAdjustmentWriter(dbpath, cls.env.trading_days,
                                     MockDailyBarSpotReader())
     splits = DataFrame.from_records([
         {
             'effective_date': str_to_seconds('2014-06-09'),
             'ratio': (1 / 7.0),
             'sid': cls.AAPL,
         }
     ])
     mergers = DataFrame(
         {
             # Hackery to make the dtypes correct on an empty frame.
             'effective_date': array([], dtype=int),
             'ratio': array([], dtype=float),
             'sid': array([], dtype=int),
         },
         index=DatetimeIndex([]),
         columns=['effective_date', 'ratio', 'sid'],
     )
     dividends = DataFrame({
         'sid': array([], dtype=uint32),
         'amount': array([], dtype=float64),
         'record_date': array([], dtype='datetime64[ns]'),
         'ex_date': array([], dtype='datetime64[ns]'),
         'declared_date': array([], dtype='datetime64[ns]'),
         'pay_date': array([], dtype='datetime64[ns]'),
     })
     writer.write(splits, mergers, dividends)
     return SQLiteAdjustmentReader(dbpath)

开发者ID:Mapgax，项目名称:zipline，代码行数:31，代码来源:test_pipeline_algo.py

示例4: create_adjustments_reader

    def create_adjustments_reader(cls):
        path = cls.tempdir.getpath("test_adjustments.db")

        adj_writer = SQLiteAdjustmentWriter(
            path,
            cls.env.trading_days,
            MockDailyBarReader()
        )

        splits = pd.DataFrame([
            {
                'effective_date': str_to_seconds("2016-01-06"),
                'ratio': 0.5,
                'sid': cls.asset3.sid
            }
        ])

        # Mergers and Dividends are not tested, but we need to have these
        # anyway
        mergers = pd.DataFrame({}, columns=['effective_date', 'ratio', 'sid'])
        mergers.effective_date = mergers.effective_date.astype(np.int64)
        mergers.ratio = mergers.ratio.astype(np.float64)
        mergers.sid = mergers.sid.astype(np.int64)

        dividends = pd.DataFrame({}, columns=['ex_date', 'record_date',
                                              'declared_date', 'pay_date',
                                              'amount', 'sid'])
        dividends.amount = dividends.amount.astype(np.float64)
        dividends.sid = dividends.sid.astype(np.int64)

        adj_writer.write(splits, mergers, dividends)

        return SQLiteAdjustmentReader(path)

开发者ID:AdaoSmith，项目名称:zipline，代码行数:33，代码来源:test_api_shim.py

示例5: make_splits_data

 def make_splits_data(cls):
     return pd.DataFrame([
         {
             'effective_date': str_to_seconds('2016-01-06'),
             'ratio': 0.5,
             'sid': 3,
         }
     ])

开发者ID:280185386，项目名称:zipline，代码行数:8，代码来源:test_api_shim.py

示例6: make_splits_data

 def make_splits_data(cls):
     return DataFrame.from_records([
         {
             'effective_date': str_to_seconds('2014-06-09'),
             'ratio': (1 / 7.0),
             'sid': cls.AAPL,
         }
     ])

开发者ID:AtwooTM，项目名称:zipline，代码行数:8，代码来源:test_pipeline_algo.py

示例7: DataFrame

# ADJUSTMENTS use the following scheme to indicate information about the value
# upon inspection.
#
# 1s place is the equity
#
# 0.1s place is the action type, with:
#
# splits, 1
# mergers, 2
# dividends, 3
#
# 0.001s is the date
SPLITS = DataFrame(
    [
        # Before query range, should be excluded.
        {'effective_date': str_to_seconds('2015-06-03'),
         'ratio': 1.103,
         'sid': 1},
        # First day of query range, should be excluded.
        {'effective_date': str_to_seconds('2015-06-10'),
         'ratio': 3.110,
         'sid': 3},
        # Third day of query range, should have last_row of 2
        {'effective_date': str_to_seconds('2015-06-12'),
         'ratio': 3.112,
         'sid': 3},
        # After query range, should be excluded.
        {'effective_date': str_to_seconds('2015-06-21'),
         'ratio': 6.121,
         'sid': 6},
        # Another action in query range, should have last_row of 1

开发者ID:AdaoSmith，项目名称:zipline，代码行数:31，代码来源:test_us_equity_pricing_loader.py

示例8: make_splits_data

 def make_splits_data(cls):
     return DataFrame.from_records(
         [{"effective_date": str_to_seconds("2014-06-09"), "ratio": (1 / 7.0), "sid": cls.AAPL}]
     )

开发者ID:RoyHsiao，项目名称:zipline，代码行数:4，代码来源:test_pipeline_algo.py

示例9: test_ingest

    def test_ingest(self):
        start = pd.Timestamp('2014-01-06', tz='utc')
        end = pd.Timestamp('2014-01-10', tz='utc')
        calendar = get_calendar('NYSE')

        sessions = calendar.sessions_in_range(start, end)
        minutes = calendar.minutes_for_sessions_in_range(start, end)

        sids = tuple(range(3))
        equities = make_simple_equity_info(
            sids,
            start,
            end,
        )

        daily_bar_data = make_bar_data(equities, sessions)
        minute_bar_data = make_bar_data(equities, minutes)
        first_split_ratio = 0.5
        second_split_ratio = 0.1
        splits = pd.DataFrame.from_records([
            {
                'effective_date': str_to_seconds('2014-01-08'),
                'ratio': first_split_ratio,
                'sid': 0,
            },
            {
                'effective_date': str_to_seconds('2014-01-09'),
                'ratio': second_split_ratio,
                'sid': 1,
            },
        ])

        @self.register(
            'bundle',
            calendar=calendar,
            start_session=start,
            end_session=end,
        )
        def bundle_ingest(environ,
                          asset_db_writer,
                          minute_bar_writer,
                          daily_bar_writer,
                          adjustment_writer,
                          calendar,
                          start_session,
                          end_session,
                          cache,
                          show_progress,
                          output_dir):
            assert_is(environ, self.environ)

            asset_db_writer.write(equities=equities)
            minute_bar_writer.write(minute_bar_data)
            daily_bar_writer.write(daily_bar_data)
            adjustment_writer.write(splits=splits)

            assert_is_instance(calendar, TradingCalendar)
            assert_is_instance(cache, dataframe_cache)
            assert_is_instance(show_progress, bool)

        self.ingest('bundle', environ=self.environ)
        bundle = self.load('bundle', environ=self.environ)

        assert_equal(set(bundle.asset_finder.sids), set(sids))

        columns = 'open', 'high', 'low', 'close', 'volume'

        actual = bundle.equity_minute_bar_reader.load_raw_arrays(
            columns,
            minutes[0],
            minutes[-1],
            sids,
        )

        for actual_column, colname in zip(actual, columns):
            assert_equal(
                actual_column,
                expected_bar_values_2d(minutes, equities, colname),
                msg=colname,
            )

        actual = bundle.equity_daily_bar_reader.load_raw_arrays(
            columns,
            start,
            end,
            sids,
        )
        for actual_column, colname in zip(actual, columns):
            assert_equal(
                actual_column,
                expected_bar_values_2d(sessions, equities, colname),
                msg=colname,
            )
        adjustments_for_cols = bundle.adjustment_reader.load_adjustments(
            columns,
            sessions,
            pd.Index(sids),
        )
        for column, adjustments in zip(columns, adjustments_for_cols[:-1]):
            # iterate over all the adjustments but `volume`
#.........这里部分代码省略.........

开发者ID:nathanwolfe，项目名称:zipline-minute-bars，代码行数:101，代码来源:test_core.py

示例10: test_ingest

    def test_ingest(self):
        calendar = get_calendar("NYSE")
        sessions = calendar.sessions_in_range(self.START_DATE, self.END_DATE)
        minutes = calendar.minutes_for_sessions_in_range(self.START_DATE, self.END_DATE)

        sids = tuple(range(3))
        equities = make_simple_equity_info(sids, self.START_DATE, self.END_DATE)

        daily_bar_data = make_bar_data(equities, sessions)
        minute_bar_data = make_bar_data(equities, minutes)
        first_split_ratio = 0.5
        second_split_ratio = 0.1
        splits = pd.DataFrame.from_records(
            [
                {"effective_date": str_to_seconds("2014-01-08"), "ratio": first_split_ratio, "sid": 0},
                {"effective_date": str_to_seconds("2014-01-09"), "ratio": second_split_ratio, "sid": 1},
            ]
        )

        @self.register("bundle", calendar_name="NYSE", start_session=self.START_DATE, end_session=self.END_DATE)
        def bundle_ingest(
            environ,
            asset_db_writer,
            minute_bar_writer,
            daily_bar_writer,
            adjustment_writer,
            calendar,
            start_session,
            end_session,
            cache,
            show_progress,
            output_dir,
        ):
            assert_is(environ, self.environ)

            asset_db_writer.write(equities=equities)
            minute_bar_writer.write(minute_bar_data)
            daily_bar_writer.write(daily_bar_data)
            adjustment_writer.write(splits=splits)

            assert_is_instance(calendar, TradingCalendar)
            assert_is_instance(cache, dataframe_cache)
            assert_is_instance(show_progress, bool)

        self.ingest("bundle", environ=self.environ)
        bundle = self.load("bundle", environ=self.environ)

        assert_equal(set(bundle.asset_finder.sids), set(sids))

        columns = "open", "high", "low", "close", "volume"

        actual = bundle.equity_minute_bar_reader.load_raw_arrays(columns, minutes[0], minutes[-1], sids)

        for actual_column, colname in zip(actual, columns):
            assert_equal(actual_column, expected_bar_values_2d(minutes, equities, colname), msg=colname)

        actual = bundle.equity_daily_bar_reader.load_raw_arrays(columns, self.START_DATE, self.END_DATE, sids)
        for actual_column, colname in zip(actual, columns):
            assert_equal(actual_column, expected_bar_values_2d(sessions, equities, colname), msg=colname)
        adjustments_for_cols = bundle.adjustment_reader.load_adjustments(columns, sessions, pd.Index(sids))
        for column, adjustments in zip(columns, adjustments_for_cols[:-1]):
            # iterate over all the adjustments but `volume`
            assert_equal(
                adjustments,
                {
                    2: [Float64Multiply(first_row=0, last_row=2, first_col=0, last_col=0, value=first_split_ratio)],
                    3: [Float64Multiply(first_row=0, last_row=3, first_col=1, last_col=1, value=second_split_ratio)],
                },
                msg=column,
            )

        # check the volume, the value should be 1/ratio
        assert_equal(
            adjustments_for_cols[-1],
            {
                2: [Float64Multiply(first_row=0, last_row=2, first_col=0, last_col=0, value=1 / first_split_ratio)],
                3: [Float64Multiply(first_row=0, last_row=3, first_col=1, last_col=1, value=1 / second_split_ratio)],
            },
            msg="volume",
        )

开发者ID:AtwooTM，项目名称:zipline，代码行数:80，代码来源:test_core.py

注：本文中的zipline.testing.str_to_seconds函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。

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Python testing.str_to_seconds函数代码示例

示例1: make_mergers_data

示例2: make_splits_data

示例3: create_adjustment_reader

示例4: create_adjustments_reader

示例5: make_splits_data

示例6: make_splits_data

示例7: DataFrame

示例8: make_splits_data

示例9: test_ingest

示例10: test_ingest

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