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How to use test_load_one method in tavern

Best Python code snippet using tavern

DataAnalysis.py

Source:DataAnalysis.py

...50        a = DataCollector(os.getcwd() + "test/", data_name_list=["d1", "d2", "d3"], data_length_when_save=200)51        for i in range(2000):52            a.add_data([[1, 2], [1, 2, 3], [1, 2, 3, 4]])53    @staticmethod54    def test_load_one():55        a = np.load(os.getcwd() + "test/d3_1800.npy")56        print(a)57        print(a.shape)58class DataAnalysis():59    @staticmethod60    def plot_hist_on_different_ylabel(x, y, kwargs_for_ax=None, xlim=None):61        '''62        ç»å¶ä¸åy labelä¸çxçåå¸,ä¼åæ ¹æ®yè¿æ»¤x,è¿æ»¤çæ¯ç»xä½ç´æ¹å¾63        :param x: æµ®ç¹æ°åé64        :param y: æ´æ°åé,ä»£è¡¨label65        :return:66        '''67        assert isinstance(x, np.ndarray)68        assert isinstance(y, np.ndarray)69        y = y.astype(np.int8)70        assert x.shape[0] == y.shape[0]71        labels = list(set(y))72        label_to_x_dict = {}73        for label in labels:74            # éåºlabelåæ¯ä¸ªlabelç¸åçx,ä¹å°±æ¯group by label75            index = np.argwhere(label == y)76            filted_x = x[index]77            label_to_x_dict[label] = filted_x78        n_ax = len(labels)79        # å¦ælabelå¤§äº9,å°±3å,å°äº9å°±ä¸¤å80        if n_ax >= 9:81            n_cols = 382        else:83            n_cols = 284        n_rows = 085        while n_rows * n_cols < n_ax:86            n_rows += 187        fig, ax_list = plt.subplots(nrows=n_rows, ncols=n_cols)88        ax_list = ax_list.flatten()89        for i in range(n_ax):90            x = label_to_x_dict[labels[i]]91            mean = np.mean(x)92            std = np.std(x)93            if kwargs_for_ax is None:94                ax_list[i].hist(x, )95            else:96                ax_list[i].hist(x, **kwargs_for_ax)97            mean = "%.4f" % mean98            std = "%.4f" % std99            ax_list[i].set_title(str(labels[i]) + " mean: %s, std: %s" % (mean, std))100            if xlim is not None:101                ax_list[i].set_xlim(*xlim)102        fig.tight_layout()103        return plt104    @staticmethod105    def test_plot_hist_on_different_ylabel():106        DataAnalysis.plot_hist_on_different_ylabel(107            x=np.array([1, 2, 3, 4, 5, 6, 7, 8]),108            y=np.array([1, 2, 3, 1, 2, 3, 1, 1])109        ).show()110if __name__ == '__main__':111    # DataCollector.test_save()112    # DataCollector.test_load_one()...

test_database.py

Source:test_database.py

...23    def test_load_all(self):24        database = Database(':memory:')25        result = database.load_all('SELECT * FROM habits', [])26        self.assertEqual(5, len(result))27    def test_load_one(self):28        database = Database(':memory:')29        result = database.load_one('SELECT rowid FROM habits WHERE rowid=?', [1])...

test_yahoo_events.py

Source:test_yahoo_events.py

...5from pxtrade.events.yahoo import (6    load_yahoo_prices,7    YahooAssetLoader,8)9def test_load_one():10    with pytest.raises(NotImplementedError):11        load_yahoo_prices(None)  # not a supported type12def test_loader():13    reset()14    with pytest.raises(TypeError):15        # requires a backtest object16        YahooAssetLoader(None, None)17    class MyStrategy(Strategy):18        def generate_trades(self):19            return None20    stock = Stock("AAPL")21    stock.yahoo_ticker = 12322    backtest = Backtest(MyStrategy())23    # yahoo_ticker for stock must be None or string...

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