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1642 lines
47 KiB
1642 lines
47 KiB
import collections
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import warnings
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import cython
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from cpython.object cimport (
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Py_EQ,
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Py_NE,
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PyObject_RichCompare,
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)
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import numpy as np
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cimport numpy as cnp
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from numpy cimport (
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int64_t,
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ndarray,
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)
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cnp.import_array()
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from cpython.datetime cimport (
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PyDateTime_Check,
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PyDateTime_IMPORT,
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PyDelta_Check,
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timedelta,
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)
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PyDateTime_IMPORT
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cimport pandas._libs.tslibs.util as util
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from pandas._libs.tslibs.base cimport ABCTimestamp
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from pandas._libs.tslibs.conversion cimport (
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cast_from_unit,
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precision_from_unit,
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)
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from pandas._libs.tslibs.nattype cimport (
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NPY_NAT,
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c_NaT as NaT,
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c_nat_strings as nat_strings,
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checknull_with_nat,
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)
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from pandas._libs.tslibs.np_datetime cimport (
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NPY_DATETIMEUNIT,
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cmp_scalar,
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get_datetime64_unit,
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get_timedelta64_value,
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pandas_timedeltastruct,
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td64_to_tdstruct,
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)
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from pandas._libs.tslibs.offsets cimport is_tick_object
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from pandas._libs.tslibs.util cimport (
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is_array,
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is_datetime64_object,
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is_float_object,
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is_integer_object,
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is_timedelta64_object,
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)
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from pandas._libs.tslibs.fields import (
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RoundTo,
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round_nsint64,
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)
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# ----------------------------------------------------------------------
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# Constants
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# components named tuple
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Components = collections.namedtuple(
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"Components",
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[
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"days",
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"hours",
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"minutes",
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"seconds",
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"milliseconds",
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"microseconds",
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"nanoseconds",
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],
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)
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cdef dict timedelta_abbrevs = {
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"Y": "Y",
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"y": "Y",
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"M": "M",
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"W": "W",
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"w": "W",
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"D": "D",
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"d": "D",
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"days": "D",
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"day": "D",
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"hours": "h",
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"hour": "h",
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"hr": "h",
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"h": "h",
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"m": "m",
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"minute": "m",
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"min": "m",
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"minutes": "m",
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"t": "m",
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"s": "s",
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"seconds": "s",
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"sec": "s",
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"second": "s",
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"ms": "ms",
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"milliseconds": "ms",
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"millisecond": "ms",
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"milli": "ms",
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"millis": "ms",
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"l": "ms",
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"us": "us",
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"microseconds": "us",
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"microsecond": "us",
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"µs": "us",
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"micro": "us",
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"micros": "us",
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"u": "us",
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"ns": "ns",
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"nanoseconds": "ns",
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"nano": "ns",
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"nanos": "ns",
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"nanosecond": "ns",
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"n": "ns",
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}
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_no_input = object()
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# ----------------------------------------------------------------------
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# API
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@cython.boundscheck(False)
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@cython.wraparound(False)
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def ints_to_pytimedelta(const int64_t[:] arr, box=False):
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"""
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convert an i8 repr to an ndarray of timedelta or Timedelta (if box ==
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True)
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Parameters
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----------
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arr : ndarray[int64_t]
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box : bool, default False
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Returns
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-------
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result : ndarray[object]
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array of Timedelta or timedeltas objects
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"""
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cdef:
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Py_ssize_t i, n = len(arr)
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int64_t value
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object[:] result = np.empty(n, dtype=object)
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for i in range(n):
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value = arr[i]
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if value == NPY_NAT:
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result[i] = <object>NaT
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else:
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if box:
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result[i] = Timedelta(value)
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else:
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result[i] = timedelta(microseconds=int(value) / 1000)
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return result.base # .base to access underlying np.ndarray
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# ----------------------------------------------------------------------
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cpdef int64_t delta_to_nanoseconds(delta) except? -1:
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if is_tick_object(delta):
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return delta.nanos
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if isinstance(delta, _Timedelta):
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delta = delta.value
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if is_timedelta64_object(delta):
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return get_timedelta64_value(ensure_td64ns(delta))
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if is_integer_object(delta):
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return delta
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if PyDelta_Check(delta):
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try:
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return (
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delta.days * 24 * 3600 * 1_000_000
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+ delta.seconds * 1_000_000
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+ delta.microseconds
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) * 1000
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except OverflowError as err:
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from pandas._libs.tslibs.conversion import OutOfBoundsTimedelta
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raise OutOfBoundsTimedelta(*err.args) from err
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raise TypeError(type(delta))
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cdef str npy_unit_to_abbrev(NPY_DATETIMEUNIT unit):
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if unit == NPY_DATETIMEUNIT.NPY_FR_ns or unit == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
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# generic -> default to nanoseconds
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return "ns"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_us:
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return "us"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_ms:
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return "ms"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_s:
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return "s"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_m:
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return "m"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_h:
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return "h"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_D:
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return "D"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_W:
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return "W"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_M:
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return "M"
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elif unit == NPY_DATETIMEUNIT.NPY_FR_Y:
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return "Y"
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else:
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raise NotImplementedError(unit)
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@cython.overflowcheck(True)
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cdef object ensure_td64ns(object ts):
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"""
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Overflow-safe implementation of td64.astype("m8[ns]")
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Parameters
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----------
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ts : np.timedelta64
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Returns
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-------
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np.timedelta64[ns]
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"""
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cdef:
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NPY_DATETIMEUNIT td64_unit
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int64_t td64_value, mult
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str unitstr
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td64_unit = get_datetime64_unit(ts)
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if (
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td64_unit != NPY_DATETIMEUNIT.NPY_FR_ns
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and td64_unit != NPY_DATETIMEUNIT.NPY_FR_GENERIC
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):
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unitstr = npy_unit_to_abbrev(td64_unit)
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td64_value = get_timedelta64_value(ts)
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mult = precision_from_unit(unitstr)[0]
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try:
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# NB: cython#1381 this cannot be *=
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td64_value = td64_value * mult
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except OverflowError as err:
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from pandas._libs.tslibs.conversion import OutOfBoundsTimedelta
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raise OutOfBoundsTimedelta(ts) from err
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return np.timedelta64(td64_value, "ns")
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return ts
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cdef convert_to_timedelta64(object ts, str unit):
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"""
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Convert an incoming object to a timedelta64 if possible.
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Before calling, unit must be standardized to avoid repeated unit conversion
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Handle these types of objects:
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- timedelta/Timedelta
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- timedelta64
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- an offset
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- np.int64 (with unit providing a possible modifier)
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- None/NaT
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Return an ns based int64
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"""
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if checknull_with_nat(ts):
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return np.timedelta64(NPY_NAT, "ns")
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elif isinstance(ts, _Timedelta):
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# already in the proper format
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ts = np.timedelta64(ts.value, "ns")
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elif is_timedelta64_object(ts):
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ts = ensure_td64ns(ts)
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elif is_integer_object(ts):
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if ts == NPY_NAT:
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return np.timedelta64(NPY_NAT, "ns")
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else:
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if unit in ["Y", "M", "W"]:
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ts = np.timedelta64(ts, unit)
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else:
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ts = cast_from_unit(ts, unit)
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ts = np.timedelta64(ts, "ns")
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elif is_float_object(ts):
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if unit in ["Y", "M", "W"]:
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ts = np.timedelta64(int(ts), unit)
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else:
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ts = cast_from_unit(ts, unit)
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ts = np.timedelta64(ts, "ns")
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elif isinstance(ts, str):
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if (len(ts) > 0 and ts[0] == "P") or (len(ts) > 1 and ts[:2] == "-P"):
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ts = parse_iso_format_string(ts)
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else:
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ts = parse_timedelta_string(ts)
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ts = np.timedelta64(ts, "ns")
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elif is_tick_object(ts):
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ts = np.timedelta64(ts.nanos, "ns")
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if PyDelta_Check(ts):
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ts = np.timedelta64(delta_to_nanoseconds(ts), "ns")
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elif not is_timedelta64_object(ts):
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raise ValueError(f"Invalid type for timedelta scalar: {type(ts)}")
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return ts.astype("timedelta64[ns]")
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@cython.boundscheck(False)
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@cython.wraparound(False)
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def array_to_timedelta64(
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ndarray[object] values, str unit=None, str errors="raise"
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) -> ndarray:
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"""
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Convert an ndarray to an array of timedeltas. If errors == 'coerce',
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coerce non-convertible objects to NaT. Otherwise, raise.
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Returns
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-------
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np.ndarray[timedelta64ns]
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"""
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cdef:
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Py_ssize_t i, n
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int64_t[:] iresult
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if errors not in {'ignore', 'raise', 'coerce'}:
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raise ValueError("errors must be one of {'ignore', 'raise', or 'coerce'}")
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n = values.shape[0]
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result = np.empty(n, dtype='m8[ns]')
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iresult = result.view('i8')
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if unit is not None:
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for i in range(n):
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if isinstance(values[i], str) and errors != "coerce":
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raise ValueError(
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"unit must not be specified if the input contains a str"
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)
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# Usually, we have all strings. If so, we hit the fast path.
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# If this path fails, we try conversion a different way, and
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# this is where all of the error handling will take place.
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try:
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for i in range(n):
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if values[i] is NaT:
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# we allow this check in the fast-path because NaT is a C-object
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# so this is an inexpensive check
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iresult[i] = NPY_NAT
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else:
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result[i] = parse_timedelta_string(values[i])
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except (TypeError, ValueError):
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parsed_unit = parse_timedelta_unit(unit or 'ns')
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for i in range(n):
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try:
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result[i] = convert_to_timedelta64(values[i], parsed_unit)
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except ValueError as err:
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if errors == 'coerce':
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result[i] = NPY_NAT
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elif "unit abbreviation w/o a number" in str(err):
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# re-raise with more pertinent message
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msg = f"Could not convert '{values[i]}' to NumPy timedelta"
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raise ValueError(msg) from err
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else:
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raise
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return iresult.base # .base to access underlying np.ndarray
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|
|
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cdef inline int64_t parse_timedelta_string(str ts) except? -1:
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"""
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Parse a regular format timedelta string. Return an int64_t (in ns)
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or raise a ValueError on an invalid parse.
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"""
|
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cdef:
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unicode c
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bint neg = 0, have_dot = 0, have_value = 0, have_hhmmss = 0
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object current_unit = None
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int64_t result = 0, m = 0, r
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list number = [], frac = [], unit = []
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# neg : tracks if we have a leading negative for the value
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# have_dot : tracks if we are processing a dot (either post hhmmss or
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# inside an expression)
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# have_value : track if we have at least 1 leading unit
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# have_hhmmss : tracks if we have a regular format hh:mm:ss
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if len(ts) == 0 or ts in nat_strings:
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return NPY_NAT
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|
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for c in ts:
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|
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# skip whitespace / commas
|
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if c == ' ' or c == ',':
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pass
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|
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# positive signs are ignored
|
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elif c == '+':
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pass
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|
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# neg
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elif c == '-':
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|
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if neg or have_value or have_hhmmss:
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raise ValueError("only leading negative signs are allowed")
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neg = 1
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|
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# number (ascii codes)
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elif ord(c) >= 48 and ord(c) <= 57:
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|
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if have_dot:
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# we found a dot, but now its just a fraction
|
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if len(unit):
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number.append(c)
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have_dot = 0
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else:
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frac.append(c)
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|
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elif not len(unit):
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number.append(c)
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|
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else:
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r = timedelta_from_spec(number, frac, unit)
|
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unit, number, frac = [], [c], []
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result += timedelta_as_neg(r, neg)
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|
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# hh:mm:ss.
|
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elif c == ':':
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|
|
# we flip this off if we have a leading value
|
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if have_value:
|
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neg = 0
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|
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# we are in the pattern hh:mm:ss pattern
|
|
if len(number):
|
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if current_unit is None:
|
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current_unit = 'h'
|
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m = 1000000000 * 3600
|
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elif current_unit == 'h':
|
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current_unit = 'm'
|
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m = 1000000000 * 60
|
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elif current_unit == 'm':
|
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current_unit = 's'
|
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m = 1000000000
|
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r = <int64_t>int(''.join(number)) * m
|
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result += timedelta_as_neg(r, neg)
|
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have_hhmmss = 1
|
|
else:
|
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raise ValueError(f"expecting hh:mm:ss format, received: {ts}")
|
|
|
|
unit, number = [], []
|
|
|
|
# after the decimal point
|
|
elif c == '.':
|
|
|
|
if len(number) and current_unit is not None:
|
|
|
|
# by definition we had something like
|
|
# so we need to evaluate the final field from a
|
|
# hh:mm:ss (so current_unit is 'm')
|
|
if current_unit != 'm':
|
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raise ValueError("expected hh:mm:ss format before .")
|
|
m = 1000000000
|
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r = <int64_t>int(''.join(number)) * m
|
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result += timedelta_as_neg(r, neg)
|
|
have_value = 1
|
|
unit, number, frac = [], [], []
|
|
|
|
have_dot = 1
|
|
|
|
# unit
|
|
else:
|
|
unit.append(c)
|
|
have_value = 1
|
|
have_dot = 0
|
|
|
|
# we had a dot, but we have a fractional
|
|
# value since we have an unit
|
|
if have_dot and len(unit):
|
|
r = timedelta_from_spec(number, frac, unit)
|
|
result += timedelta_as_neg(r, neg)
|
|
|
|
# we have a dot as part of a regular format
|
|
# e.g. hh:mm:ss.fffffff
|
|
elif have_dot:
|
|
|
|
if ((len(number) or len(frac)) and not len(unit)
|
|
and current_unit is None):
|
|
raise ValueError("no units specified")
|
|
|
|
if len(frac) > 0 and len(frac) <= 3:
|
|
m = 10**(3 -len(frac)) * 1000 * 1000
|
|
elif len(frac) > 3 and len(frac) <= 6:
|
|
m = 10**(6 -len(frac)) * 1000
|
|
elif len(frac) > 6 and len(frac) <= 9:
|
|
m = 10**(9 -len(frac))
|
|
else:
|
|
m = 1
|
|
frac = frac[:9]
|
|
r = <int64_t>int(''.join(frac)) * m
|
|
result += timedelta_as_neg(r, neg)
|
|
|
|
# we have a regular format
|
|
# we must have seconds at this point (hence the unit is still 'm')
|
|
elif current_unit is not None:
|
|
if current_unit != 'm':
|
|
raise ValueError("expected hh:mm:ss format")
|
|
m = 1000000000
|
|
r = <int64_t>int(''.join(number)) * m
|
|
result += timedelta_as_neg(r, neg)
|
|
|
|
# we have a last abbreviation
|
|
elif len(unit):
|
|
if len(number):
|
|
r = timedelta_from_spec(number, frac, unit)
|
|
result += timedelta_as_neg(r, neg)
|
|
else:
|
|
raise ValueError("unit abbreviation w/o a number")
|
|
|
|
# we only have symbols and no numbers
|
|
elif len(number) == 0:
|
|
raise ValueError("symbols w/o a number")
|
|
|
|
# treat as nanoseconds
|
|
# but only if we don't have anything else
|
|
else:
|
|
if have_value:
|
|
raise ValueError("have leftover units")
|
|
if len(number):
|
|
r = timedelta_from_spec(number, frac, 'ns')
|
|
result += timedelta_as_neg(r, neg)
|
|
|
|
return result
|
|
|
|
|
|
cdef inline int64_t timedelta_as_neg(int64_t value, bint neg):
|
|
"""
|
|
|
|
Parameters
|
|
----------
|
|
value : int64_t of the timedelta value
|
|
neg : bool if the a negative value
|
|
"""
|
|
if neg:
|
|
return -value
|
|
return value
|
|
|
|
|
|
cdef inline timedelta_from_spec(object number, object frac, object unit):
|
|
"""
|
|
|
|
Parameters
|
|
----------
|
|
number : a list of number digits
|
|
frac : a list of frac digits
|
|
unit : a list of unit characters
|
|
"""
|
|
cdef:
|
|
str n
|
|
|
|
try:
|
|
unit = ''.join(unit)
|
|
|
|
if unit in ["M", "Y", "y"]:
|
|
warnings.warn(
|
|
"Units 'M', 'Y' and 'y' do not represent unambiguous "
|
|
"timedelta values and will be removed in a future version.",
|
|
FutureWarning,
|
|
stacklevel=2,
|
|
)
|
|
|
|
if unit == 'M':
|
|
# To parse ISO 8601 string, 'M' should be treated as minute,
|
|
# not month
|
|
unit = 'm'
|
|
unit = parse_timedelta_unit(unit)
|
|
except KeyError:
|
|
raise ValueError(f"invalid abbreviation: {unit}")
|
|
|
|
n = ''.join(number) + '.' + ''.join(frac)
|
|
return cast_from_unit(float(n), unit)
|
|
|
|
|
|
cpdef inline str parse_timedelta_unit(str unit):
|
|
"""
|
|
Parameters
|
|
----------
|
|
unit : str or None
|
|
|
|
Returns
|
|
-------
|
|
str
|
|
Canonical unit string.
|
|
|
|
Raises
|
|
------
|
|
ValueError : on non-parseable input
|
|
"""
|
|
if unit is None:
|
|
return "ns"
|
|
elif unit == "M":
|
|
return unit
|
|
try:
|
|
return timedelta_abbrevs[unit.lower()]
|
|
except (KeyError, AttributeError):
|
|
raise ValueError(f"invalid unit abbreviation: {unit}")
|
|
|
|
# ----------------------------------------------------------------------
|
|
# Timedelta ops utilities
|
|
|
|
cdef bint _validate_ops_compat(other):
|
|
# return True if we are compat with operating
|
|
if checknull_with_nat(other):
|
|
return True
|
|
elif is_any_td_scalar(other):
|
|
return True
|
|
elif isinstance(other, str):
|
|
return True
|
|
return False
|
|
|
|
|
|
def _op_unary_method(func, name):
|
|
def f(self):
|
|
return Timedelta(func(self.value), unit='ns')
|
|
f.__name__ = name
|
|
return f
|
|
|
|
|
|
def _binary_op_method_timedeltalike(op, name):
|
|
# define a binary operation that only works if the other argument is
|
|
# timedelta like or an array of timedeltalike
|
|
def f(self, other):
|
|
if other is NaT:
|
|
return NaT
|
|
|
|
elif is_datetime64_object(other) or (
|
|
PyDateTime_Check(other) and not isinstance(other, ABCTimestamp)
|
|
):
|
|
# this case is for a datetime object that is specifically
|
|
# *not* a Timestamp, as the Timestamp case will be
|
|
# handled after `_validate_ops_compat` returns False below
|
|
from pandas._libs.tslibs.timestamps import Timestamp
|
|
return op(self, Timestamp(other))
|
|
# We are implicitly requiring the canonical behavior to be
|
|
# defined by Timestamp methods.
|
|
|
|
elif is_array(other):
|
|
# nd-array like
|
|
if other.dtype.kind in ['m', 'M']:
|
|
return op(self.to_timedelta64(), other)
|
|
elif other.dtype.kind == 'O':
|
|
return np.array([op(self, x) for x in other])
|
|
else:
|
|
return NotImplemented
|
|
|
|
elif not _validate_ops_compat(other):
|
|
# Includes any of our non-cython classes
|
|
return NotImplemented
|
|
|
|
try:
|
|
other = Timedelta(other)
|
|
except ValueError:
|
|
# failed to parse as timedelta
|
|
return NotImplemented
|
|
|
|
if other is NaT:
|
|
# e.g. if original other was timedelta64('NaT')
|
|
return NaT
|
|
return Timedelta(op(self.value, other.value), unit='ns')
|
|
|
|
f.__name__ = name
|
|
return f
|
|
|
|
|
|
# ----------------------------------------------------------------------
|
|
# Timedelta Construction
|
|
|
|
cdef inline int64_t parse_iso_format_string(str ts) except? -1:
|
|
"""
|
|
Extracts and cleanses the appropriate values from a match object with
|
|
groups for each component of an ISO 8601 duration
|
|
|
|
Parameters
|
|
----------
|
|
ts: str
|
|
ISO 8601 Duration formatted string
|
|
|
|
Returns
|
|
-------
|
|
ns: int64_t
|
|
Precision in nanoseconds of matched ISO 8601 duration
|
|
|
|
Raises
|
|
------
|
|
ValueError
|
|
If ``ts`` cannot be parsed
|
|
"""
|
|
|
|
cdef:
|
|
unicode c
|
|
int64_t result = 0, r
|
|
int p = 0, sign = 1
|
|
object dec_unit = 'ms', err_msg
|
|
bint have_dot = 0, have_value = 0, neg = 0
|
|
list number = [], unit = []
|
|
|
|
err_msg = f"Invalid ISO 8601 Duration format - {ts}"
|
|
|
|
if ts[0] == "-":
|
|
sign = -1
|
|
ts = ts[1:]
|
|
|
|
for c in ts:
|
|
# number (ascii codes)
|
|
if 48 <= ord(c) <= 57:
|
|
|
|
have_value = 1
|
|
if have_dot:
|
|
if p == 3 and dec_unit != 'ns':
|
|
unit.append(dec_unit)
|
|
if dec_unit == 'ms':
|
|
dec_unit = 'us'
|
|
elif dec_unit == 'us':
|
|
dec_unit = 'ns'
|
|
p = 0
|
|
p += 1
|
|
|
|
if not len(unit):
|
|
number.append(c)
|
|
else:
|
|
r = timedelta_from_spec(number, '0', unit)
|
|
result += timedelta_as_neg(r, neg)
|
|
|
|
neg = 0
|
|
unit, number = [], [c]
|
|
else:
|
|
if c == 'P' or c == 'T':
|
|
pass # ignore marking characters P and T
|
|
elif c == '-':
|
|
if neg or have_value:
|
|
raise ValueError(err_msg)
|
|
else:
|
|
neg = 1
|
|
elif c == "+":
|
|
pass
|
|
elif c in ['W', 'D', 'H', 'M']:
|
|
if c in ['H', 'M'] and len(number) > 2:
|
|
raise ValueError(err_msg)
|
|
if c == 'M':
|
|
c = 'min'
|
|
unit.append(c)
|
|
r = timedelta_from_spec(number, '0', unit)
|
|
result += timedelta_as_neg(r, neg)
|
|
|
|
neg = 0
|
|
unit, number = [], []
|
|
elif c == '.':
|
|
# append any seconds
|
|
if len(number):
|
|
r = timedelta_from_spec(number, '0', 'S')
|
|
result += timedelta_as_neg(r, neg)
|
|
unit, number = [], []
|
|
have_dot = 1
|
|
elif c == 'S':
|
|
if have_dot: # ms, us, or ns
|
|
if not len(number) or p > 3:
|
|
raise ValueError(err_msg)
|
|
# pad to 3 digits as required
|
|
pad = 3 - p
|
|
while pad > 0:
|
|
number.append('0')
|
|
pad -= 1
|
|
|
|
r = timedelta_from_spec(number, '0', dec_unit)
|
|
result += timedelta_as_neg(r, neg)
|
|
else: # seconds
|
|
r = timedelta_from_spec(number, '0', 'S')
|
|
result += timedelta_as_neg(r, neg)
|
|
else:
|
|
raise ValueError(err_msg)
|
|
|
|
if not have_value:
|
|
# Received string only - never parsed any values
|
|
raise ValueError(err_msg)
|
|
|
|
return sign*result
|
|
|
|
|
|
cdef _to_py_int_float(v):
|
|
# Note: This used to be defined inside Timedelta.__new__
|
|
# but cython will not allow `cdef` functions to be defined dynamically.
|
|
if is_integer_object(v):
|
|
return int(v)
|
|
elif is_float_object(v):
|
|
return float(v)
|
|
raise TypeError(f"Invalid type {type(v)}. Must be int or float.")
|
|
|
|
|
|
# Similar to Timestamp/datetime, this is a construction requirement for
|
|
# timedeltas that we need to do object instantiation in python. This will
|
|
# serve as a C extension type that shadows the Python class, where we do any
|
|
# heavy lifting.
|
|
cdef class _Timedelta(timedelta):
|
|
# cdef readonly:
|
|
# int64_t value # nanoseconds
|
|
# object freq # frequency reference
|
|
# bint is_populated # are my components populated
|
|
# int64_t _d, _h, _m, _s, _ms, _us, _ns
|
|
|
|
# higher than np.ndarray and np.matrix
|
|
__array_priority__ = 100
|
|
|
|
def __hash__(_Timedelta self):
|
|
if self._has_ns():
|
|
return hash(self.value)
|
|
else:
|
|
return timedelta.__hash__(self)
|
|
|
|
def __richcmp__(_Timedelta self, object other, int op):
|
|
cdef:
|
|
_Timedelta ots
|
|
int ndim
|
|
|
|
if isinstance(other, _Timedelta):
|
|
ots = other
|
|
elif is_any_td_scalar(other):
|
|
ots = Timedelta(other)
|
|
# TODO: watch out for overflows
|
|
|
|
elif other is NaT:
|
|
return op == Py_NE
|
|
|
|
elif util.is_array(other):
|
|
# TODO: watch out for zero-dim
|
|
if other.dtype.kind == "m":
|
|
return PyObject_RichCompare(self.asm8, other, op)
|
|
elif other.dtype.kind == "O":
|
|
# operate element-wise
|
|
return np.array(
|
|
[PyObject_RichCompare(self, x, op) for x in other],
|
|
dtype=bool,
|
|
)
|
|
if op == Py_EQ:
|
|
return np.zeros(other.shape, dtype=bool)
|
|
elif op == Py_NE:
|
|
return np.ones(other.shape, dtype=bool)
|
|
return NotImplemented # let other raise TypeError
|
|
|
|
else:
|
|
return NotImplemented
|
|
|
|
return cmp_scalar(self.value, ots.value, op)
|
|
|
|
cpdef bint _has_ns(self):
|
|
return self.value % 1000 != 0
|
|
|
|
def _ensure_components(_Timedelta self):
|
|
"""
|
|
compute the components
|
|
"""
|
|
if self.is_populated:
|
|
return
|
|
|
|
cdef:
|
|
pandas_timedeltastruct tds
|
|
|
|
td64_to_tdstruct(self.value, &tds)
|
|
self._d = tds.days
|
|
self._h = tds.hrs
|
|
self._m = tds.min
|
|
self._s = tds.sec
|
|
self._ms = tds.ms
|
|
self._us = tds.us
|
|
self._ns = tds.ns
|
|
self._seconds = tds.seconds
|
|
self._microseconds = tds.microseconds
|
|
|
|
self.is_populated = 1
|
|
|
|
cpdef timedelta to_pytimedelta(_Timedelta self):
|
|
"""
|
|
Convert a pandas Timedelta object into a python ``datetime.timedelta`` object.
|
|
|
|
Timedelta objects are internally saved as numpy datetime64[ns] dtype.
|
|
Use to_pytimedelta() to convert to object dtype.
|
|
|
|
Returns
|
|
-------
|
|
datetime.timedelta or numpy.array of datetime.timedelta
|
|
|
|
See Also
|
|
--------
|
|
to_timedelta : Convert argument to Timedelta type.
|
|
|
|
Notes
|
|
-----
|
|
Any nanosecond resolution will be lost.
|
|
"""
|
|
return timedelta(microseconds=int(self.value) / 1000)
|
|
|
|
def to_timedelta64(self) -> np.timedelta64:
|
|
"""
|
|
Return a numpy.timedelta64 object with 'ns' precision.
|
|
"""
|
|
return np.timedelta64(self.value, 'ns')
|
|
|
|
def to_numpy(self, dtype=None, copy=False) -> np.timedelta64:
|
|
"""
|
|
Convert the Timedelta to a NumPy timedelta64.
|
|
|
|
.. versionadded:: 0.25.0
|
|
|
|
This is an alias method for `Timedelta.to_timedelta64()`. The dtype and
|
|
copy parameters are available here only for compatibility. Their values
|
|
will not affect the return value.
|
|
|
|
Returns
|
|
-------
|
|
numpy.timedelta64
|
|
|
|
See Also
|
|
--------
|
|
Series.to_numpy : Similar method for Series.
|
|
"""
|
|
if dtype is not None or copy is not False:
|
|
raise ValueError(
|
|
"Timedelta.to_numpy dtype and copy arguments are ignored"
|
|
)
|
|
return self.to_timedelta64()
|
|
|
|
def view(self, dtype):
|
|
"""
|
|
Array view compatibility.
|
|
"""
|
|
return np.timedelta64(self.value).view(dtype)
|
|
|
|
@property
|
|
def components(self):
|
|
"""
|
|
Return a components namedtuple-like.
|
|
"""
|
|
self._ensure_components()
|
|
# return the named tuple
|
|
return Components(self._d, self._h, self._m, self._s,
|
|
self._ms, self._us, self._ns)
|
|
|
|
@property
|
|
def delta(self):
|
|
"""
|
|
Return the timedelta in nanoseconds (ns), for internal compatibility.
|
|
|
|
Returns
|
|
-------
|
|
int
|
|
Timedelta in nanoseconds.
|
|
|
|
Examples
|
|
--------
|
|
>>> td = pd.Timedelta('1 days 42 ns')
|
|
>>> td.delta
|
|
86400000000042
|
|
|
|
>>> td = pd.Timedelta('3 s')
|
|
>>> td.delta
|
|
3000000000
|
|
|
|
>>> td = pd.Timedelta('3 ms 5 us')
|
|
>>> td.delta
|
|
3005000
|
|
|
|
>>> td = pd.Timedelta(42, unit='ns')
|
|
>>> td.delta
|
|
42
|
|
"""
|
|
return self.value
|
|
|
|
@property
|
|
def asm8(self) -> np.timedelta64:
|
|
"""
|
|
Return a numpy timedelta64 array scalar view.
|
|
|
|
Provides access to the array scalar view (i.e. a combination of the
|
|
value and the units) associated with the numpy.timedelta64().view(),
|
|
including a 64-bit integer representation of the timedelta in
|
|
nanoseconds (Python int compatible).
|
|
|
|
Returns
|
|
-------
|
|
numpy timedelta64 array scalar view
|
|
Array scalar view of the timedelta in nanoseconds.
|
|
|
|
Examples
|
|
--------
|
|
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
|
|
>>> td.asm8
|
|
numpy.timedelta64(86520000003042,'ns')
|
|
|
|
>>> td = pd.Timedelta('2 min 3 s')
|
|
>>> td.asm8
|
|
numpy.timedelta64(123000000000,'ns')
|
|
|
|
>>> td = pd.Timedelta('3 ms 5 us')
|
|
>>> td.asm8
|
|
numpy.timedelta64(3005000,'ns')
|
|
|
|
>>> td = pd.Timedelta(42, unit='ns')
|
|
>>> td.asm8
|
|
numpy.timedelta64(42,'ns')
|
|
"""
|
|
return np.int64(self.value).view('m8[ns]')
|
|
|
|
@property
|
|
def resolution_string(self) -> str:
|
|
"""
|
|
Return a string representing the lowest timedelta resolution.
|
|
|
|
Each timedelta has a defined resolution that represents the lowest OR
|
|
most granular level of precision. Each level of resolution is
|
|
represented by a short string as defined below:
|
|
|
|
Resolution: Return value
|
|
|
|
* Days: 'D'
|
|
* Hours: 'H'
|
|
* Minutes: 'T'
|
|
* Seconds: 'S'
|
|
* Milliseconds: 'L'
|
|
* Microseconds: 'U'
|
|
* Nanoseconds: 'N'
|
|
|
|
Returns
|
|
-------
|
|
str
|
|
Timedelta resolution.
|
|
|
|
Examples
|
|
--------
|
|
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
|
|
>>> td.resolution_string
|
|
'N'
|
|
|
|
>>> td = pd.Timedelta('1 days 2 min 3 us')
|
|
>>> td.resolution_string
|
|
'U'
|
|
|
|
>>> td = pd.Timedelta('2 min 3 s')
|
|
>>> td.resolution_string
|
|
'S'
|
|
|
|
>>> td = pd.Timedelta(36, unit='us')
|
|
>>> td.resolution_string
|
|
'U'
|
|
"""
|
|
self._ensure_components()
|
|
if self._ns:
|
|
return "N"
|
|
elif self._us:
|
|
return "U"
|
|
elif self._ms:
|
|
return "L"
|
|
elif self._s:
|
|
return "S"
|
|
elif self._m:
|
|
return "T"
|
|
elif self._h:
|
|
return "H"
|
|
else:
|
|
return "D"
|
|
|
|
@property
|
|
def nanoseconds(self):
|
|
"""
|
|
Return the number of nanoseconds (n), where 0 <= n < 1 microsecond.
|
|
|
|
Returns
|
|
-------
|
|
int
|
|
Number of nanoseconds.
|
|
|
|
See Also
|
|
--------
|
|
Timedelta.components : Return all attributes with assigned values
|
|
(i.e. days, hours, minutes, seconds, milliseconds, microseconds,
|
|
nanoseconds).
|
|
|
|
Examples
|
|
--------
|
|
**Using string input**
|
|
|
|
>>> td = pd.Timedelta('1 days 2 min 3 us 42 ns')
|
|
|
|
>>> td.nanoseconds
|
|
42
|
|
|
|
**Using integer input**
|
|
|
|
>>> td = pd.Timedelta(42, unit='ns')
|
|
>>> td.nanoseconds
|
|
42
|
|
"""
|
|
self._ensure_components()
|
|
return self._ns
|
|
|
|
def _repr_base(self, format=None) -> str:
|
|
"""
|
|
|
|
Parameters
|
|
----------
|
|
format : None|all|sub_day|long
|
|
|
|
Returns
|
|
-------
|
|
converted : string of a Timedelta
|
|
|
|
"""
|
|
cdef object sign, seconds_pretty, subs, fmt, comp_dict
|
|
|
|
self._ensure_components()
|
|
|
|
if self._d < 0:
|
|
sign = " +"
|
|
else:
|
|
sign = " "
|
|
|
|
if format == 'all':
|
|
fmt = ("{days} days{sign}{hours:02}:{minutes:02}:{seconds:02}."
|
|
"{milliseconds:03}{microseconds:03}{nanoseconds:03}")
|
|
else:
|
|
# if we have a partial day
|
|
subs = (self._h or self._m or self._s or
|
|
self._ms or self._us or self._ns)
|
|
|
|
if self._ms or self._us or self._ns:
|
|
seconds_fmt = "{seconds:02}.{milliseconds:03}{microseconds:03}"
|
|
if self._ns:
|
|
# GH#9309
|
|
seconds_fmt += "{nanoseconds:03}"
|
|
else:
|
|
seconds_fmt = "{seconds:02}"
|
|
|
|
if format == 'sub_day' and not self._d:
|
|
fmt = "{hours:02}:{minutes:02}:" + seconds_fmt
|
|
elif subs or format == 'long':
|
|
fmt = "{days} days{sign}{hours:02}:{minutes:02}:" + seconds_fmt
|
|
else:
|
|
fmt = "{days} days"
|
|
|
|
comp_dict = self.components._asdict()
|
|
comp_dict['sign'] = sign
|
|
|
|
return fmt.format(**comp_dict)
|
|
|
|
def __repr__(self) -> str:
|
|
repr_based = self._repr_base(format='long')
|
|
return f"Timedelta('{repr_based}')"
|
|
|
|
def __str__(self) -> str:
|
|
return self._repr_base(format='long')
|
|
|
|
def __bool__(self) -> bool:
|
|
return self.value != 0
|
|
|
|
def isoformat(self) -> str:
|
|
"""
|
|
Format Timedelta as ISO 8601 Duration like
|
|
``P[n]Y[n]M[n]DT[n]H[n]M[n]S``, where the ``[n]`` s are replaced by the
|
|
values. See https://en.wikipedia.org/wiki/ISO_8601#Durations.
|
|
|
|
Returns
|
|
-------
|
|
str
|
|
|
|
See Also
|
|
--------
|
|
Timestamp.isoformat : Function is used to convert the given
|
|
Timestamp object into the ISO format.
|
|
|
|
Notes
|
|
-----
|
|
The longest component is days, whose value may be larger than
|
|
365.
|
|
Every component is always included, even if its value is 0.
|
|
Pandas uses nanosecond precision, so up to 9 decimal places may
|
|
be included in the seconds component.
|
|
Trailing 0's are removed from the seconds component after the decimal.
|
|
We do not 0 pad components, so it's `...T5H...`, not `...T05H...`
|
|
|
|
Examples
|
|
--------
|
|
>>> td = pd.Timedelta(days=6, minutes=50, seconds=3,
|
|
... milliseconds=10, microseconds=10, nanoseconds=12)
|
|
|
|
>>> td.isoformat()
|
|
'P6DT0H50M3.010010012S'
|
|
>>> pd.Timedelta(hours=1, seconds=10).isoformat()
|
|
'P0DT1H0M10S'
|
|
>>> pd.Timedelta(days=500.5).isoformat()
|
|
'P500DT12H0M0S'
|
|
"""
|
|
components = self.components
|
|
seconds = (f'{components.seconds}.'
|
|
f'{components.milliseconds:0>3}'
|
|
f'{components.microseconds:0>3}'
|
|
f'{components.nanoseconds:0>3}')
|
|
# Trim unnecessary 0s, 1.000000000 -> 1
|
|
seconds = seconds.rstrip('0').rstrip('.')
|
|
tpl = (f'P{components.days}DT{components.hours}'
|
|
f'H{components.minutes}M{seconds}S')
|
|
return tpl
|
|
|
|
|
|
# Python front end to C extension type _Timedelta
|
|
# This serves as the box for timedelta64
|
|
|
|
class Timedelta(_Timedelta):
|
|
"""
|
|
Represents a duration, the difference between two dates or times.
|
|
|
|
Timedelta is the pandas equivalent of python's ``datetime.timedelta``
|
|
and is interchangeable with it in most cases.
|
|
|
|
Parameters
|
|
----------
|
|
value : Timedelta, timedelta, np.timedelta64, str, or int
|
|
unit : str, default 'ns'
|
|
Denote the unit of the input, if input is an integer.
|
|
|
|
Possible values:
|
|
|
|
* 'W', 'D', 'T', 'S', 'L', 'U', or 'N'
|
|
* 'days' or 'day'
|
|
* 'hours', 'hour', 'hr', or 'h'
|
|
* 'minutes', 'minute', 'min', or 'm'
|
|
* 'seconds', 'second', or 'sec'
|
|
* 'milliseconds', 'millisecond', 'millis', or 'milli'
|
|
* 'microseconds', 'microsecond', 'micros', or 'micro'
|
|
* 'nanoseconds', 'nanosecond', 'nanos', 'nano', or 'ns'.
|
|
|
|
**kwargs
|
|
Available kwargs: {days, seconds, microseconds,
|
|
milliseconds, minutes, hours, weeks}.
|
|
Values for construction in compat with datetime.timedelta.
|
|
Numpy ints and floats will be coerced to python ints and floats.
|
|
|
|
Notes
|
|
-----
|
|
The constructor may take in either both values of value and unit or
|
|
kwargs as above. Either one of them must be used during initialization
|
|
|
|
The ``.value`` attribute is always in ns.
|
|
|
|
If the precision is higher than nanoseconds, the precision of the duration is
|
|
truncated to nanoseconds.
|
|
|
|
Examples
|
|
--------
|
|
Here we initialize Timedelta object with both value and unit
|
|
|
|
>>> td = pd.Timedelta(1, "d")
|
|
>>> td
|
|
Timedelta('1 days 00:00:00')
|
|
|
|
Here we initialize the Timedelta object with kwargs
|
|
|
|
>>> td2 = pd.Timedelta(days=1)
|
|
>>> td2
|
|
Timedelta('1 days 00:00:00')
|
|
|
|
We see that either way we get the same result
|
|
"""
|
|
|
|
_req_any_kwargs_new = {"weeks", "days", "hours", "minutes", "seconds",
|
|
"milliseconds", "microseconds", "nanoseconds"}
|
|
|
|
def __new__(cls, object value=_no_input, unit=None, **kwargs):
|
|
cdef _Timedelta td_base
|
|
|
|
if value is _no_input:
|
|
if not len(kwargs):
|
|
raise ValueError("cannot construct a Timedelta without a "
|
|
"value/unit or descriptive keywords "
|
|
"(days,seconds....)")
|
|
|
|
kwargs = {key: _to_py_int_float(kwargs[key]) for key in kwargs}
|
|
|
|
unsupported_kwargs = set(kwargs)
|
|
unsupported_kwargs.difference_update(cls._req_any_kwargs_new)
|
|
if unsupported_kwargs or not cls._req_any_kwargs_new.intersection(kwargs):
|
|
raise ValueError(
|
|
"cannot construct a Timedelta from the passed arguments, "
|
|
"allowed keywords are "
|
|
"[weeks, days, hours, minutes, seconds, "
|
|
"milliseconds, microseconds, nanoseconds]"
|
|
)
|
|
|
|
# GH43764, convert any input to nanoseconds first and then
|
|
# create the timestamp. This ensures that any potential
|
|
# nanosecond contributions from kwargs parsed as floats
|
|
# are taken into consideration.
|
|
seconds = int((
|
|
(
|
|
(kwargs.get('days', 0) + kwargs.get('weeks', 0) * 7) * 24
|
|
+ kwargs.get('hours', 0)
|
|
) * 3600
|
|
+ kwargs.get('minutes', 0) * 60
|
|
+ kwargs.get('seconds', 0)
|
|
) * 1_000_000_000
|
|
)
|
|
|
|
value = np.timedelta64(
|
|
int(kwargs.get('nanoseconds', 0))
|
|
+ int(kwargs.get('microseconds', 0) * 1_000)
|
|
+ int(kwargs.get('milliseconds', 0) * 1_000_000)
|
|
+ seconds
|
|
)
|
|
|
|
if unit in {'Y', 'y', 'M'}:
|
|
raise ValueError(
|
|
"Units 'M', 'Y', and 'y' are no longer supported, as they do not "
|
|
"represent unambiguous timedelta values durations."
|
|
)
|
|
|
|
# GH 30543 if pd.Timedelta already passed, return it
|
|
# check that only value is passed
|
|
if isinstance(value, _Timedelta) and unit is None and len(kwargs) == 0:
|
|
return value
|
|
elif isinstance(value, _Timedelta):
|
|
value = value.value
|
|
elif isinstance(value, str):
|
|
if unit is not None:
|
|
raise ValueError("unit must not be specified if the value is a str")
|
|
if (len(value) > 0 and value[0] == 'P') or (
|
|
len(value) > 1 and value[:2] == '-P'
|
|
):
|
|
value = parse_iso_format_string(value)
|
|
else:
|
|
value = parse_timedelta_string(value)
|
|
value = np.timedelta64(value)
|
|
elif PyDelta_Check(value):
|
|
value = convert_to_timedelta64(value, 'ns')
|
|
elif is_timedelta64_object(value):
|
|
if unit is not None:
|
|
value = value.astype(f'timedelta64[{unit}]')
|
|
value = ensure_td64ns(value)
|
|
elif is_tick_object(value):
|
|
value = np.timedelta64(value.nanos, 'ns')
|
|
elif is_integer_object(value) or is_float_object(value):
|
|
# unit=None is de-facto 'ns'
|
|
unit = parse_timedelta_unit(unit)
|
|
value = convert_to_timedelta64(value, unit)
|
|
elif checknull_with_nat(value):
|
|
return NaT
|
|
else:
|
|
raise ValueError(
|
|
"Value must be Timedelta, string, integer, "
|
|
f"float, timedelta or convertible, not {type(value).__name__}"
|
|
)
|
|
|
|
if is_timedelta64_object(value):
|
|
value = value.view('i8')
|
|
|
|
# nat
|
|
if value == NPY_NAT:
|
|
return NaT
|
|
|
|
# make timedelta happy
|
|
td_base = _Timedelta.__new__(cls, microseconds=int(value) // 1000)
|
|
td_base.value = value
|
|
td_base.is_populated = 0
|
|
return td_base
|
|
|
|
def __setstate__(self, state):
|
|
(value) = state
|
|
self.value = value
|
|
|
|
def __reduce__(self):
|
|
object_state = self.value,
|
|
return (Timedelta, object_state)
|
|
|
|
@cython.cdivision(True)
|
|
def _round(self, freq, mode):
|
|
cdef:
|
|
int64_t result, unit, remainder
|
|
ndarray[int64_t] arr
|
|
|
|
from pandas._libs.tslibs.offsets import to_offset
|
|
unit = to_offset(freq).nanos
|
|
|
|
arr = np.array([self.value], dtype="i8")
|
|
result = round_nsint64(arr, mode, unit)[0]
|
|
return Timedelta(result, unit="ns")
|
|
|
|
def round(self, freq):
|
|
"""
|
|
Round the Timedelta to the specified resolution.
|
|
|
|
Parameters
|
|
----------
|
|
freq : str
|
|
Frequency string indicating the rounding resolution.
|
|
|
|
Returns
|
|
-------
|
|
a new Timedelta rounded to the given resolution of `freq`
|
|
|
|
Raises
|
|
------
|
|
ValueError if the freq cannot be converted
|
|
"""
|
|
return self._round(freq, RoundTo.NEAREST_HALF_EVEN)
|
|
|
|
def floor(self, freq):
|
|
"""
|
|
Return a new Timedelta floored to this resolution.
|
|
|
|
Parameters
|
|
----------
|
|
freq : str
|
|
Frequency string indicating the flooring resolution.
|
|
"""
|
|
return self._round(freq, RoundTo.MINUS_INFTY)
|
|
|
|
def ceil(self, freq):
|
|
"""
|
|
Return a new Timedelta ceiled to this resolution.
|
|
|
|
Parameters
|
|
----------
|
|
freq : str
|
|
Frequency string indicating the ceiling resolution.
|
|
"""
|
|
return self._round(freq, RoundTo.PLUS_INFTY)
|
|
|
|
# ----------------------------------------------------------------
|
|
# Arithmetic Methods
|
|
# TODO: Can some of these be defined in the cython class?
|
|
|
|
__neg__ = _op_unary_method(lambda x: -x, '__neg__')
|
|
__pos__ = _op_unary_method(lambda x: x, '__pos__')
|
|
__abs__ = _op_unary_method(lambda x: abs(x), '__abs__')
|
|
|
|
__add__ = _binary_op_method_timedeltalike(lambda x, y: x + y, '__add__')
|
|
__radd__ = _binary_op_method_timedeltalike(lambda x, y: x + y, '__radd__')
|
|
__sub__ = _binary_op_method_timedeltalike(lambda x, y: x - y, '__sub__')
|
|
__rsub__ = _binary_op_method_timedeltalike(lambda x, y: y - x, '__rsub__')
|
|
|
|
def __mul__(self, other):
|
|
if is_integer_object(other) or is_float_object(other):
|
|
return Timedelta(other * self.value, unit='ns')
|
|
|
|
elif is_array(other):
|
|
# ndarray-like
|
|
return other * self.to_timedelta64()
|
|
|
|
return NotImplemented
|
|
|
|
__rmul__ = __mul__
|
|
|
|
def __truediv__(self, other):
|
|
if _should_cast_to_timedelta(other):
|
|
# We interpret NaT as timedelta64("NaT")
|
|
other = Timedelta(other)
|
|
if other is NaT:
|
|
return np.nan
|
|
return self.value / float(other.value)
|
|
|
|
elif is_integer_object(other) or is_float_object(other):
|
|
# integers or floats
|
|
return Timedelta(self.value / other, unit='ns')
|
|
|
|
elif is_array(other):
|
|
return self.to_timedelta64() / other
|
|
|
|
return NotImplemented
|
|
|
|
def __rtruediv__(self, other):
|
|
if _should_cast_to_timedelta(other):
|
|
# We interpret NaT as timedelta64("NaT")
|
|
other = Timedelta(other)
|
|
if other is NaT:
|
|
return np.nan
|
|
return float(other.value) / self.value
|
|
|
|
elif is_array(other):
|
|
if other.dtype.kind == "O":
|
|
# GH#31869
|
|
return np.array([x / self for x in other])
|
|
return other / self.to_timedelta64()
|
|
|
|
return NotImplemented
|
|
|
|
def __floordiv__(self, other):
|
|
# numpy does not implement floordiv for timedelta64 dtype, so we cannot
|
|
# just defer
|
|
if _should_cast_to_timedelta(other):
|
|
# We interpret NaT as timedelta64("NaT")
|
|
other = Timedelta(other)
|
|
if other is NaT:
|
|
return np.nan
|
|
return self.value // other.value
|
|
|
|
elif is_integer_object(other) or is_float_object(other):
|
|
return Timedelta(self.value // other, unit='ns')
|
|
|
|
elif is_array(other):
|
|
if other.dtype.kind == 'm':
|
|
# also timedelta-like
|
|
return _broadcast_floordiv_td64(self.value, other, _floordiv)
|
|
elif other.dtype.kind in ['i', 'u', 'f']:
|
|
if other.ndim == 0:
|
|
return Timedelta(self.value // other)
|
|
else:
|
|
return self.to_timedelta64() // other
|
|
|
|
raise TypeError(f'Invalid dtype {other.dtype} for __floordiv__')
|
|
|
|
return NotImplemented
|
|
|
|
def __rfloordiv__(self, other):
|
|
# numpy does not implement floordiv for timedelta64 dtype, so we cannot
|
|
# just defer
|
|
if _should_cast_to_timedelta(other):
|
|
# We interpret NaT as timedelta64("NaT")
|
|
other = Timedelta(other)
|
|
if other is NaT:
|
|
return np.nan
|
|
return other.value // self.value
|
|
|
|
elif is_array(other):
|
|
if other.dtype.kind == 'm':
|
|
# also timedelta-like
|
|
return _broadcast_floordiv_td64(self.value, other, _rfloordiv)
|
|
|
|
# Includes integer array // Timedelta, disallowed in GH#19761
|
|
raise TypeError(f'Invalid dtype {other.dtype} for __floordiv__')
|
|
|
|
return NotImplemented
|
|
|
|
def __mod__(self, other):
|
|
# Naive implementation, room for optimization
|
|
return self.__divmod__(other)[1]
|
|
|
|
def __rmod__(self, other):
|
|
# Naive implementation, room for optimization
|
|
return self.__rdivmod__(other)[1]
|
|
|
|
def __divmod__(self, other):
|
|
# Naive implementation, room for optimization
|
|
div = self // other
|
|
return div, self - div * other
|
|
|
|
def __rdivmod__(self, other):
|
|
# Naive implementation, room for optimization
|
|
div = other // self
|
|
return div, other - div * self
|
|
|
|
|
|
cdef bint is_any_td_scalar(object obj):
|
|
"""
|
|
Cython equivalent for `isinstance(obj, (timedelta, np.timedelta64, Tick))`
|
|
|
|
Parameters
|
|
----------
|
|
obj : object
|
|
|
|
Returns
|
|
-------
|
|
bool
|
|
"""
|
|
return (
|
|
PyDelta_Check(obj) or is_timedelta64_object(obj) or is_tick_object(obj)
|
|
)
|
|
|
|
|
|
cdef bint _should_cast_to_timedelta(object obj):
|
|
"""
|
|
Should we treat this object as a Timedelta for the purpose of a binary op
|
|
"""
|
|
return (
|
|
is_any_td_scalar(obj) or obj is None or obj is NaT or isinstance(obj, str)
|
|
)
|
|
|
|
|
|
cdef _floordiv(int64_t value, right):
|
|
return value // right
|
|
|
|
|
|
cdef _rfloordiv(int64_t value, right):
|
|
# analogous to referencing operator.div, but there is no operator.rfloordiv
|
|
return right // value
|
|
|
|
|
|
cdef _broadcast_floordiv_td64(
|
|
int64_t value,
|
|
ndarray other,
|
|
object (*operation)(int64_t value, object right)
|
|
):
|
|
"""
|
|
Boilerplate code shared by Timedelta.__floordiv__ and
|
|
Timedelta.__rfloordiv__ because np.timedelta64 does not implement these.
|
|
|
|
Parameters
|
|
----------
|
|
value : int64_t; `self.value` from a Timedelta object
|
|
other : object
|
|
operation : function, either _floordiv or _rfloordiv
|
|
|
|
Returns
|
|
-------
|
|
result : varies based on `other`
|
|
"""
|
|
# assumes other.dtype.kind == 'm', i.e. other is timedelta-like
|
|
|
|
# We need to watch out for np.timedelta64('NaT').
|
|
mask = other.view('i8') == NPY_NAT
|
|
|
|
if other.ndim == 0:
|
|
if mask:
|
|
return np.nan
|
|
|
|
return operation(value, other.astype('m8[ns]').astype('i8'))
|
|
|
|
else:
|
|
res = operation(value, other.astype('m8[ns]').astype('i8'))
|
|
|
|
if mask.any():
|
|
res = res.astype('f8')
|
|
res[mask] = np.nan
|
|
return res
|
|
|
|
|
|
# resolution in ns
|
|
Timedelta.min = Timedelta(np.iinfo(np.int64).min + 1)
|
|
Timedelta.max = Timedelta(np.iinfo(np.int64).max)
|
|
Timedelta.resolution = Timedelta(nanoseconds=1)
|
|
|