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# -*- coding: utf-8 -*- |
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"""Helpers to fit scalar values into sequences. |
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SPDX-FileCopyrightText: Uwe Krien <[email protected]> |
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SPDX-FileCopyrightText: Simon Hilpert |
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SPDX-FileCopyrightText: Cord Kaldemeyer |
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SPDX-FileCopyrightText: henhuy |
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SPDX-License-Identifier: MIT |
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""" |
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from collections import abc |
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from itertools import repeat |
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import numpy as np |
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def sequence(iterable_or_scalar): |
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"""Checks if an object is iterable (except string) or scalar and returns |
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the original sequence if object is an iterable and an 'emulated' |
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sequence object of class _Sequence if object is a scalar or string. |
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Parameters |
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---------- |
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iterable_or_scalar : iterable or None or int or float |
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Examples |
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-------- |
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>>> y = sequence([1,2,3,4,5,6,7,8,9,10,11]) |
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>>> y[0] |
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1 |
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>>> y[10] |
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11 |
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>>> import pandas as pd |
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>>> s1 = sequence(pd.Series([1,5,9])) |
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>>> s1[2] |
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9 |
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>>> x = sequence(10) |
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>>> x[0] |
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10 |
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>>> x[10] |
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10 |
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""" |
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if isinstance(iterable_or_scalar, str): |
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return iterable_or_scalar |
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elif isinstance(iterable_or_scalar, abc.Iterable): |
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return np.array(iterable_or_scalar) |
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else: |
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return _FakeSequence(value=iterable_or_scalar) |
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class _FakeSequence: |
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"""Emulates a list whose length is not known in advance. |
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Parameters |
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---------- |
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value : scalar |
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length : integer |
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Examples |
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-------- |
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>>> s = _FakeSequence(value=42, length=5) |
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>>> s |
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[42, 42, 42, 42, 42] |
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>>> s = _FakeSequence(value=42) |
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>>> # undefined lenght, access still works |
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>>> s[1337] |
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42 |
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""" |
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def __init__(self, value, length=None): |
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self._value = value |
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self._length = length |
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@property |
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def size(self): |
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return self._length |
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@size.setter |
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def size(self, value): |
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self._length = value |
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def __getitem__(self, _): |
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return self._value |
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def __repr__(self): |
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if self._length is not None: |
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return str([i for i in self]) |
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else: |
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return f"[{self._value}, {self._value}, ..., {self._value}]" |
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def __len__(self): |
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return self._length |
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def __iter__(self): |
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return repeat(self._value, self._length) |
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def max(self): |
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return self._value |
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def min(self): |
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return self._value |
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def sum(self): |
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if self._length is None: |
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return np.inf |
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else: |
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return self._length * self._value |
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def to_numpy(self, length=None): |
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if length is not None: |
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return np.full(length, self._value) |
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else: |
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return np.full(len(self), self._value) |
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@property |
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def value(self): |
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return self._value |
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oemof /
oemof-solph
