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28 changes: 28 additions & 0 deletions climada/trajectories/__init__.py
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"""
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You need to add this module to the docs

This file is part of CLIMADA.

Copyright (C) 2017 ETH Zurich, CLIMADA contributors listed in AUTHORS.

CLIMADA is free software: you can redistribute it and/or modify it under the
terms of the GNU General Public License as published by the Free
Software Foundation, version 3.

CLIMADA is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along
with CLIMADA. If not, see <https://www.gnu.org/licenses/>.

---

This module implements risk trajectory objects which enable computation and
possibly interpolation of risk metric over multiple dates.

"""

from .snapshot import Snapshot

__all__ = [
"Snapshot",
]
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Excellent 👏 We will need this everywhere, eventually.

232 changes: 232 additions & 0 deletions climada/trajectories/snapshot.py
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"""
This file is part of CLIMADA.

Copyright (C) 2017 ETH Zurich, CLIMADA contributors listed in AUTHORS.

CLIMADA is free software: you can redistribute it and/or modify it under the
terms of the GNU General Public License as published by the Free
Software Foundation, version 3.

CLIMADA is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along
with CLIMADA. If not, see <https://www.gnu.org/licenses/>.

---

This modules implements the Snapshot class.

Snapshot are used to store a snapshot of Exposure, Hazard and Vulnerability
at a specific date.

"""

import copy
import datetime
import logging
import warnings

from climada.entity.exposures import Exposures
from climada.entity.impact_funcs import ImpactFuncSet
from climada.entity.measures.base import Measure
from climada.hazard import Hazard

LOGGER = logging.getLogger(__name__)

__all__ = ["Snapshot"]


class Snapshot:
"""
A snapshot of exposure, hazard, and impact function at a specific date.

Parameters
----------
exposure : Exposures
hazard : Hazard
impfset : ImpactFuncSet
date : int | datetime.date | str
The date of the Snapshot, it can be an integer representing a year,
a datetime object or a string representation of a datetime object
with format "YYYY-MM-DD".
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@peanutfun peanutfun Jan 5, 2026

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Using a date instead of a datetime might be overly restrictive. datetime64 can encode each date and is compatible with pandas datetime index / timestamp

ref_only : bool, default False
Should the `Snapshot` contain deep copies of the Exposures, Hazard and Impfset (False)
or references only (True).

Attributes
----------
date : datetime
Date of the snapshot.
measure: Measure | None
The possible measure applied to the snapshot.
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Classes don't have parameters, their methods do (the init in particular)


Notes
-----

The object creates deep copies of the exposure hazard and impact function set.
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Suggested change
The object creates deep copies of the exposure hazard and impact function set.
If ``ref_only`` is True (default), the object creates deep copies of the
exposure, hazard, and impact function set.


Also note that exposure, hazard and impfset are read-only properties.
Consider snapshot as immutable objects.

To create a snapshot with a measure, create a snapshot `snap` without
the measure and call `snap.apply_measure(measure)`, which returns a new Snapshot object
with the measure applied to its risk dimensions.
"""

def __init__(
self,
*,
exposure: Exposures,
hazard: Hazard,
impfset: ImpactFuncSet,
measure: Measure | None,
date: int | datetime.date | str,
ref_only: bool = False,
_from_factory: bool = False,
) -> None:
if not _from_factory:
warnings.warn(
"Direct instantiation of 'Snapshot' is discouraged. "
"Use 'Snapshot.from_triplet()' instead.",
UserWarning,
stacklevel=2,
)
self._exposure = exposure if ref_only else copy.deepcopy(exposure)
self._hazard = hazard if ref_only else copy.deepcopy(hazard)
self._impfset = impfset if ref_only else copy.deepcopy(impfset)
self._measure = measure if ref_only else copy.deepcopy(measure)
self._date = self._convert_to_date(date)

@classmethod
def from_triplet(
cls,
*,
exposure: Exposures,
hazard: Hazard,
impfset: ImpactFuncSet,
date: int | datetime.date | str,
ref_only: bool = False,
) -> "Snapshot":
"""Create a Snapshot from exposure, hazard and impact functions set

This method is the main point of entry for the creation of Snapshot. It
creates a new Snapshot object for the given date with copies of the
hazard, exposure and impact function set given in argument (or
references if ref_only is True)

Parameters
----------
exposure : Exposures
hazard : Hazard
impfset : ImpactFuncSet
date : int | datetime.date | str
ref_only : bool
If true, uses references to the exposure, hazard and impact
function objects. Note that modifying the original objects after
computations using the Snapshot might lead to inconsistencies in
results.

Returns
-------
Snapshot

Notes
-----

To create a Snapshot with a measure, first create the Snapshot without
the measure using this method, and use `apply_measure(measure)` afterward.

"""
return cls(
exposure=exposure,
hazard=hazard,
impfset=impfset,
measure=None,
date=date,
ref_only=ref_only,
_from_factory=True,
)

@property
def exposure(self) -> Exposures:
"""Exposure data for the snapshot."""
return self._exposure

@property
def hazard(self) -> Hazard:
"""Hazard data for the snapshot."""
return self._hazard

@property
def impfset(self) -> ImpactFuncSet:
"""Impact function set data for the snapshot."""
return self._impfset

@property
def measure(self) -> Measure | None:
"""(Adaptation) Measure data for the snapshot."""
return self._measure

@property
def date(self) -> datetime.date:
"""Date of the snapshot."""
return self._date
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This is a lot of boilerplate code. Maybe just create a custom __setattr__, like outlined in option 4 here: https://www.sqlpey.com/python/top-5-methods-to-create-immutable-objects-in-python/


@property
def impact_calc_data(self) -> dict:
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Make clear that this can be plugged in as kwargs?

Suggested change
def impact_calc_data(self) -> dict:
def impact_calc_kwargs(self) -> dict:

"""Convenience function for ImpactCalc class."""
return {
"exposures": self.exposure,
"hazard": self.hazard,
"impfset": self.impfset,
}

@staticmethod
def _convert_to_date(date_arg) -> datetime.date:
"""Convert date argument of type int or str to a datetime.date object."""
if isinstance(date_arg, int):
# Assume the integer represents a year
return datetime.date(date_arg, 1, 1)
if isinstance(date_arg, str):
# Try to parse the string as a date
try:
return datetime.datetime.strptime(date_arg, "%Y-%m-%d").date()
except ValueError as exc:
raise ValueError("String must be in the format 'YYYY-MM-DD'") from exc
if isinstance(date_arg, datetime.date):
# Already a date object
return date_arg

raise TypeError("date_arg must be an int, str, or datetime.date")

def apply_measure(self, measure: Measure) -> "Snapshot":
"""Create a new snapshot by applying a Measure object.

This method creates a new `Snapshot` object by applying a measure on
the current one.

Parameters
----------
measure : Measure
The measure to be applied to the snapshot.

Returns
-------
The Snapshot with the measure applied.

"""

LOGGER.debug("Applying measure %s on snapshot %s", measure.name, id(self))
exp, impfset, haz = measure.apply(self.exposure, self.impfset, self.hazard)
snap = Snapshot(
exposure=exp,
hazard=haz,
impfset=impfset,
date=self.date,
measure=measure,
ref_only=True, # Avoid unecessary copies of new objects
_from_factory=True,
)
return snap
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