From cfb1262ae394edeb6d4ea3aefcc00b452e3d5ac7 Mon Sep 17 00:00:00 2001
From: dboe <dboe@ipp.mpg.de>
Date: Mon, 26 Oct 2020 13:08:43 +0100
Subject: [PATCH] added some todos to core
---
tfields/__init__.py | 4 +++-
tfields/core.py | 31 +++++++++++++++++++++----------
tfields/lib/decorators.py | 25 +++++++++++++++++--------
tfields/mask.py | 28 +++++++++++++++-------------
4 files changed, 56 insertions(+), 32 deletions(-)
diff --git a/tfields/__init__.py b/tfields/__init__.py
index 3917788..7f921e3 100644
--- a/tfields/__init__.py
+++ b/tfields/__init__.py
@@ -1,5 +1,7 @@
# flake8: noqa: F401
-"""Top-level package of tfields."""
+"""Top-level package of tfields.
+TODO: proper documentation, also in dough.
+"""
__author__ = """Daniel Böckenhoff"""
__email__ = "dboe@ipp.mpg.de"
diff --git a/tfields/core.py b/tfields/core.py
index f3fadf7..e31ea79 100644
--- a/tfields/core.py
+++ b/tfields/core.py
@@ -2,15 +2,18 @@
# encoding: utf-8
"""
Author: Daniel Boeckenhoff
-Mail: daniel.boeckenhoff@ipp.mpg.de
+Mail: dboe@ipp.mpg.de
core of tfields library
contains numpy ndarray derived bases of the tfields package
Notes:
- * It could be worthwhile concidering `np.li.mixins.NDArrayOperatorsMixin ...
- <https://docs.scipy.org/doc/numpy-1.15.1/reference/generated/...
- ... numpy.lib.mixins.NDArrayOperatorsMixin.html>`
+ * It could be worthwhile concidering [np.li.mixins.NDArrayOperatorsMixin]<https://
+docs.scipy.org/doc/numpy-1.15.1/reference/generated/numpy.lib.mixins.NDArrayOperatorsMixin.html>
+
+TODO:
+ * lint the docstrings!!!
+ * maybe switch to numpy style for documentation since this is numpy derived. Not yet decided
"""
# builtin
import warnings
@@ -28,6 +31,7 @@ import scipy
import sortedcontainers
import rna
+# 'local'
import tfields.bases
np.seterr(all="warn", over="raise")
@@ -54,6 +58,10 @@ def dim(tensor):
class AbstractObject(object): # pylint: disable=useless-object-inheritance
"""
Abstract base class for all tfields objects implementing polymorphisms
+
+ TODO:
+ * Use abstract base class to define the polymorphism contract:
+ see https://stackoverflow.com/questions/3570796/why-use-abstract-base-classes-in-python
"""
def save(self, path, *args, **kwargs):
@@ -583,7 +591,9 @@ class Tensors(AbstractNdarray): # pylint: disable=too-many-public-methods
Set of tensors with the same basis.
TODO:
- all slot args should be protected -> _base
+ * implement units, one unit for each dimension
+ * implement automatic jacobian for metric calculation
+ * implement multidimensional cross product
Args:
tensors: np.ndarray or AbstractNdarray subclass
@@ -611,10 +621,9 @@ class Tensors(AbstractNdarray): # pylint: disable=too-many-public-methods
Initialize the Levi-Zivita Tensor
- >>> matrices = tfields.Tensors(
- ... [[[0, 0, 0], [0, 0, 1], [0, -1, 0]],
- ... [[0, 0, -1], [0, 0, 0], [1, 0, 0]],
- ... [[0, 1, 0], [-1, 0, 0], [0, 0, 0]]])
+ >>> matrices = tfields.Tensors([[[0, 0, 0], [0, 0, 1], [0, -1, 0]],
+ ... [[0, 0, -1], [0, 0, 0], [1, 0, 0]],
+ ... [[0, 1, 0], [-1, 0, 0], [0, 0, 0]]])
>>> matrices.shape == (3, 3, 3)
True
>>> matrices.rank == 2
@@ -2103,9 +2112,11 @@ class Maps(sortedcontainers.SortedDict, AbstractObject):
| List(Tuple(int, TensorFields)):
| TensorFields:
| Tuple(Tensors, *Fields)):
- TODO: there is more
+ TODO: document
)
+ **kwargs: forwarded to SortedDict
+ TODO: further documentation
"""
def __init__(self, *args, **kwargs):
diff --git a/tfields/lib/decorators.py b/tfields/lib/decorators.py
index 1ff9ed1..ff39988 100644
--- a/tfields/lib/decorators.py
+++ b/tfields/lib/decorators.py
@@ -5,8 +5,8 @@ import time
import functools
-class cached_property(object):
- '''Decorator for read-only properties evaluated only once within TTL period.
+class cached_property(object): # pylint: disable=invalid-name
+ """Decorator for read-only properties evaluated only once within TTL period.
It can be used to create a cached property like this::
@@ -35,7 +35,8 @@ class cached_property(object):
del instance._cache[<property name>]
- '''
+ """
+
def __init__(self, ttl=0):
self.ttl = ttl
@@ -69,10 +70,13 @@ def parametrized(dec):
"""
possibility to parametrize a decorator
"""
+
def layer(*args, **kwargs):
- def repl(f):
- return dec(f, *args, **kwargs)
+ def repl(fun):
+ return dec(fun, *args, **kwargs)
+
return repl
+
return layer
@@ -107,17 +111,22 @@ def once(method, arg=False):
already
"""
+
@functools.wraps(method)
def decorator(self, *args, **kwargs):
if getattr(self, arg):
- raise RuntimeError("Argument {arg} indicates the method has been "
- "run already".format(**locals()))
+ raise RuntimeError(
+ "Argument {arg} indicates the method has been "
+ "run already".format(**locals())
+ )
value = method(self, *args, **kwargs)
setattr(self, arg, True)
return value
+
return decorator
-if __name__ == '__main__':
+if __name__ == "__main__":
import doctest
+
doctest.testmod()
diff --git a/tfields/mask.py b/tfields/mask.py
index 4d9b602..9054780 100644
--- a/tfields/mask.py
+++ b/tfields/mask.py
@@ -11,16 +11,16 @@ import numpy as np
import sympy
-def evalf(array, cutExpression=None, coords=None):
+def evalf(array, cut_expression=None, coords=None):
"""
- Linking sympy and numpy by retrieving a mask according to the cutExpression
+ Linking sympy and numpy by retrieving a mask according to the cut_expression
Args:
array (numpy ndarray)
- cutExpression (sympy logical expression)
+ cut_expression (sympy logical expression)
coord_sys (str): coord_sys to evalfuate the expression in.
Returns:
- np.array: mask which is True, where cutExpression evalfuates True.
+ np.array: mask which is True, where cut_expression evalfuates True.
Examples:
>>> import sympy
>>> import numpy as np
@@ -58,28 +58,30 @@ def evalf(array, cutExpression=None, coords=None):
"""
if isinstance(array, list):
array = np.array(array)
- if cutExpression is None:
+ if cut_expression is None:
return np.full((array.shape[0]), False, dtype=bool)
if len(array.shape) != 2:
raise NotImplementedError("Array shape other than 2")
if coords is None:
if array.shape[1] == 3:
- coords = sympy.symbols('x y z')
+ coords = sympy.symbols("x y z")
else:
raise ValueError("coords are None and shape is not (?, 3)")
elif len(coords) != array.shape[1]:
- raise ValueError("Length of coords is not {0} but {1}"
- .format(array.shape[1], len(coords)))
+ raise ValueError(
+ "Length of coords is not {0} but {1}".format(array.shape[1], len(coords))
+ )
- preMask = sympy.utilities.lambdify(
- coords, cutExpression,
- modules={'&': np.logical_and, '|': np.logical_or})
+ pre_mask = sympy.utilities.lambdify(
+ coords, cut_expression, modules={"&": np.logical_and, "|": np.logical_or}
+ )
- mask = np.array([preMask(*vals) for vals in array], dtype=bool)
+ mask = np.array([pre_mask(*vals) for vals in array], dtype=bool)
return mask
-if __name__ == '__main__': # pragma: no cover
+if __name__ == "__main__": # pragma: no cover
import doctest
+
doctest.testmod()
--
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