Esempio n. 1
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    def sid_day_index(self, sid, day):
        """
        all data for all assets is stored sequentially. to get the right values we must find the index
        for this sid and this day. so we calculate the offset in this long array.
        Parameters
        ----------
        sid : int
            The asset identifier.
        day : datetime64-like
            Midnight of the day for which data is requested.

        Returns
        -------
        int
            Index into the data tape for the given sid and day.
            Raises a NoDataOnDate exception if the given day and sid is before
            or after the date range of the equity.
        """
        try:
            day_loc = self.sessions.get_loc(day)
        except Exception:
            raise NoDataOnDate("day={0} is outside of calendar={1}".format(
                day, self.sessions))
        offset = day_loc - self._calendar_offsets[sid]
        if offset < 0:
            raise NoDataBeforeDate(
                "No data on or before day={0} for sid={1}".format(
                    day, sid))
        ix = self._first_rows[sid] + offset
        if ix > self._last_rows[sid]:
            raise NoDataAfterDate(
                "No data on or after day={0} for sid={1}".format(
                    day, sid))

        return ix
Esempio n. 2
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    def sid_day_index(self, sid, day):
        """
        Parameters
        ----------
        sid : int
            The asset identifier.
        day : datetime64-like
            Midnight of the day for which data is requested.

        Returns
        -------
        int
            Index into the data tape for the given sid and day.
            Raises a NoDataOnDate exception if the given day and sid is before
            or after the date range of the equity.
        """
        try:
            day_loc = self.sessions.get_loc(day)
        except:
            raise NoDataOnDate("day={0} is outside of calendar={1}".format(
                day, self.sessions))
        if sid not in self._calendar_offsets:
            raise NoDataOnDate("day={0} is outside of calendar={1}".format(
                day, self.sessions))
        offset = day_loc - self._calendar_offsets[sid]
        if offset < 0:
            raise NoDataBeforeDate(
                "No data on or before day={0} for sid={1}".format(day, sid))
        ix = self._first_rows[sid] + offset
        if ix > self._last_rows[sid]:
            raise NoDataAfterDate(
                "No data on or after day={0} for sid={1}".format(day, sid))
        return ix
Esempio n. 3
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 def get_value(self, sid, dt, field):
     day = self._fmt_date(dt)
     sql = "SELECT %s FROM prices WHERE sid = %d and date = '%s'" % (field, sid, day)
     res = self._query(sql)
     if len(res) == 0:
         if self._exist_sid(sid):
             raise NoDataBeforeDate("No data on or before day={0} for sid={1}".format(dt, sid))
         else:
             raise KeyError(sid)
     return res[0][0]
Esempio n. 4
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    def get_value(self, sid, dt, field):
        """
        Retrieve the value at the given coordinates.

        Parameters
        ----------
        sid : int
            The asset identifier.
        dt : pd.Timestamp
            The timestamp for the desired data point.
        field : string
            The OHLVC name for the desired data point.

        Returns
        -------
        value : float|int
            The value at the given coordinates, ``float`` for OHLC, ``int``
            for 'volume'.

        Raises
        ------
        NoDataOnDate
            If the given dt is not a valid market minute (in minute mode) or
            session (in daily mode) according to this reader's tradingcalendar.
        """
        self._validate_assets([sid])
        self._validate_timestamp(dt)

        sid_ix = self.sids.searchsorted(sid)
        dt_ix = self.dates.searchsorted(dt.asm8)

        value = self._postprocessors[field](
            self._country_group[DATA][field][sid_ix, dt_ix]
        )

        # When the value is nan, this dt may be outside the asset's lifetime.
        # If that's the case, the proper NoDataOnDate exception is raised.
        # Otherwise (when there's just a hole in the middle of the data), the
        # nan is returned.
        if np.isnan(value):
            if dt.asm8 < self.asset_start_dates[sid_ix]:
                raise NoDataBeforeDate()

            if dt.asm8 > self.asset_end_dates[sid_ix]:
                raise NoDataAfterDate()

        return value