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added function up_or_down2 and test to it
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Alina Voilova committed Jun 13, 2024
1 parent f1a5c26 commit a4190d5
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Showing 2 changed files with 287 additions and 93 deletions.
180 changes: 150 additions & 30 deletions portfolyo/tools/freq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,6 +50,11 @@ def get_allowed_classes(frequencies: List[str]) -> List[Tuple[Type, ...]]:
type(TO_OFFSET("AS")),
]

quarter_matrix = [
["QS", "QS-APR", "QS-JUL", "QS-OCT"],
["QS-FEB", "QS-MAY", "QS-AUG", "QS-NOV"],
["QS-MAR", "QS-JUN", "QS-SEP", "QS-DEC"],
]

STANDARD_COMMON_TS = pd.Timestamp("2020-01-01 0:00")
BACKUP_COMMON_TS = pd.Timestamp("2020-02-03 04:05:06")
Expand Down Expand Up @@ -138,28 +143,31 @@ def assert_freq_valid(freq: str) -> None:
raise ValueError(f"The passed frequency '{freq}' is not allowed.")

# Define restricted classes that should have n == 1
restricted_classes = (
pd._libs.tslibs.offsets.MonthBegin,
pd._libs.tslibs.offsets.Day,
pd._libs.tslibs.offsets.Hour,
)

if isinstance(freq_offset, restricted_classes) and freq_offset.n != 1:
raise ValueError(f"The passed frequency '{freq}' is not allowed.")
# Check if the offset is an instance of Minute and if n is not 15 or 30
elif (
isinstance(freq_offset, pd._libs.tslibs.offsets.Minute) and freq_offset.n != 15
):
raise ValueError(f"The passed frequency {freq} is not allowed.")
restricted_classes = {
pd._libs.tslibs.offsets.MonthBegin: 1,
pd._libs.tslibs.offsets.Day: 1,
pd._libs.tslibs.offsets.Hour: 1,
pd._libs.tslibs.offsets.Minute: 15,
}
allowed_n = restricted_classes.get(type(freq_offset))
if allowed_n is not None: # case where freq is not in restricted class
# Check if freq_offset.n is not None and if it doesn't match allowed_n
if freq_offset.n is None or freq_offset.n != allowed_n:
raise ValueError(f"The passed frequency {freq} is not allowed.")


def assert_freq_sufficiently_long(freq, freq_ref, strict: bool = False) -> None:
"""Compares ``freq`` and ``freq_ref``, raising an AssertionError if ``freq`` is not long enough.
If ``strict`` is True, ``freq`` must be strictly longer than ``freq_long``. If False, it may be
equally long."""
# check if passed freuenices are valid
assert_freq_valid(freq)
assert_freq_valid(freq_ref)
"""
Compares ``freq`` and ``freq_ref``, raising an AssertionError if ``freq`` is not long enough.
Parameters
----------
freq_source, freq_ref : frequencies to compare.
strict : bool, optional (default: False)
- If ``strict`` is True, ``freq`` must be strictly longer than ``freq_long``.
- If False, it may be equally long.
"""
# freq should start from the beginning of the year
index_freq = SHORTEST_TO_LONGEST.index(type(TO_OFFSET(freq)))
index_ref = SHORTEST_TO_LONGEST.index(type(TO_OFFSET(freq_ref)))
Expand All @@ -175,8 +183,101 @@ def assert_freq_sufficiently_long(freq, freq_ref, strict: bool = False) -> None:
)


def up_or_down2(freq_source: str, freq_target: str) -> int:
"""
Compare source frequency with target frequency to see if it needs up- or downsampling.
Upsampling means that the number of values increases - one value in the source
corresponds to multiple values in the target.
Parameters
----------
freq_source, freq_target : frequencies to compare.
Returns
-------
* 1 if source frequency must be upsampled to obtain (i.e, is longer than) target frequency.
* 0 if source frequency is same as target frequency.
* -1 if source frequency must be downsampled to obtain (i.e, is shorter than) target frequency.
Notes
-----
If the freq can't be down- or upsampled, throws ValueError.
Examples
--------
>>> freq.up_or_down('D', 'MS')
-1
>>> freq.up_or_down('MS', 'D')
1
>>> freq.up_or_down('MS', 'MS')
0
>>> freq.up_or_down('QS', 'QS-APR')
ValueError
"""
# check if passed freuenices are valid
assert_freq_valid(freq_source)
assert_freq_valid(freq_target)
# Compare if the freq are the same
if freq_source == freq_target:
return 0
restricted_classes = [
pd._libs.tslibs.offsets.QuarterBegin,
pd._libs.tslibs.offsets.YearBegin,
]
freq_source_as_offset = pd.tseries.frequencies.to_offset(freq_source)
freq_target_as_offset = pd.tseries.frequencies.to_offset(freq_target)
# One of the freq can be in restircted class, but not both
if not (
type(freq_source_as_offset) in restricted_classes
and type(freq_target_as_offset) in restricted_classes
):
try:
assert_freq_sufficiently_long(freq_source, freq_target, strict=True)
return 1
except AssertionError:
return -1
# If both in restricted class
else:
source_index = restricted_classes.index(type(freq_source_as_offset))
target_index = restricted_classes.index(type(freq_target_as_offset))
group_by_month_beginn = (
freq_source_as_offset.startingMonth
if source_index == 0
else freq_source_as_offset.month
) % 3 == (
freq_target_as_offset.startingMonth
if target_index == 0
else freq_target_as_offset.month
) % 3

if group_by_month_beginn:
if source_index > target_index:
# we are in case AS and QS
return 1
elif source_index < target_index:
# we are in the case QS and AS
return -1
elif source_index == 0:
# we are in the case QS and QS
return 0

raise ValueError


def assert_freq_sufficiently_short(freq, freq_ref, strict: bool = False) -> None:
"""Same but different."""
"""
Compares ``freq`` and ``freq_ref``, raising an AssertionError if ``freq`` is not short enough.
Parameters
----------
freq_source, freq_ref : frequencies to compare.
strict : bool, optional (default: False)
- If ``strict`` is True, ``freq`` must be strictly shorter than ``freq_long``.
- If False, it may be equally long, or rather, short.
"""
assert_freq_sufficiently_long(freq_ref, freq, strict)


Expand Down Expand Up @@ -251,8 +352,16 @@ def to_offset(freq: str) -> pd.Timedelta | pd.DateOffset:
return pd.Timedelta(hours=0.25)
elif freq == "H":
return pd.Timedelta(hours=1)
elif freq in FREQUENCIES:
return pd.tseries.frequencies.to_offset(freq)
# elif freq in FREQUENCIES:
# return pd.tseries.frequencies.to_offset(freq)
elif freq == "D":
return pd.DateOffset(days=1)
elif freq == "MS":
return pd.DateOffset(months=1)
elif freq == "QS":
return pd.DateOffset(months=3)
elif freq == "AS":
return pd.DateOffset(years=1)
else:
for freq2 in ["MS", "QS"]: # Edge case: month-/quarterly but starting != Jan.
try:
Expand Down Expand Up @@ -316,12 +425,23 @@ def guess_to_frame(fr: Series_or_DataFrame) -> Series_or_DataFrame:
)
i = fr.index.copy(deep=True)
if i.freq:
pass
if not i.freq:
try:
i.freq = pd.infer_freq(i)
except ValueError:
pass # Couldn't find a frequency, e.g., because there are not enough values
return fr

# Freq not set.
try:

inferred_freq = pd.infer_freq(i)
for row_index in range(len(quarter_matrix)): # Loop through the rows
if (
inferred_freq in quarter_matrix[row_index]
): # check if inferred_freq is somewhere in this row
inferred_freq = quarter_matrix[row_index][
0
] # set inferred_freq to the first value in the row
i.freq = inferred_freq

except ValueError:
pass # Couldn't find a frequency, e.g., because there are not enough values
return fr.set_axis(i, axis=0)


Expand All @@ -332,7 +452,7 @@ def set_to_frame(fr: Series_or_DataFrame, wanted: str) -> Series_or_DataFrame:
----------
fr : pd.Series or pd.DataFrame
wanted : str
Frequency to set. If none provided, try to infer.
Frequency to set.
Returns
-------
Expand All @@ -345,7 +465,7 @@ def set_to_frame(fr: Series_or_DataFrame, wanted: str) -> Series_or_DataFrame:
"The data does not have a datetime index and can therefore not have a frequency."
)

# Find frequency.
# Set frequency.
i = fr.index.copy(deep=True)
i.freq = wanted

Expand Down
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