diff --git a/setup.cfg b/setup.cfg
index be477f5500741f3e2d6eba8d1593478698f02dc9..ff786503bc7690e7ee5d1d4e7b39afbf66fd7aed 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -48,7 +48,7 @@ packages = find:
install_requires =
pathlib;python_version<'3.10'
six
- numpy
+ numpy>=1.20.0
sympy<=1.6.2 # diffgeom changes in 1.7 see unit branch for first implementation of compatibility
scipy
rna>=0.6.3
diff --git a/tests/test_core.py b/tests/test_core.py
index be2a588d8dfb8747a35aaf526fd4766767f75bb4..b703af11fc043a1dde6d2443acecc043d8002b9f 100644
--- a/tests/test_core.py
+++ b/tests/test_core.py
@@ -1,6 +1,5 @@
# pylint:disable=missing-function-docstring,missing-module-docstring,missing-class-docstring,invalid-name,protected-access
import pickle
-import pathlib
import unittest
import uuid
from tempfile import NamedTemporaryFile
@@ -337,14 +336,15 @@ class TensorMaps_Test(TensorFields_Check, unittest.TestCase):
tfields.TensorMaps([], maps=tfields.Maps([]), dim=3),
]
- def test_legacy(self):
- this_dir = pathlib.Path(__file__).parent
- legacy_file = (
- this_dir
- / "resources/TensorMaps_0.2.1_ce3ea1fb69058dc39815be65f485abebb487a6bd.npz"
- ) # NOQA
- tm = tfields.TensorMaps.load(legacy_file)
- self.assertTrue(self._inst.equal(tm))
+ # Removed legacy AFTER commit 3fe8d037655f17bc7985a11e9fb64dd9c3d54b7e
+ # def test_legacy(self):
+ # this_dir = pathlib.Path(__file__).parent
+ # legacy_file = (
+ # this_dir
+ # / "resources/TensorMaps_0.2.1_ce3ea1fb69058dc39815be65f485abebb487a6bd.npz"
+ # ) # NOQA
+ # tm = tfields.TensorMaps.load(legacy_file)
+ # self.assertTrue(self._inst.equal(tm))
class TensorMaps_Indexing_Test(unittest.TestCase):
@@ -396,7 +396,13 @@ class TensorMaps_NoFields_Test(Tensors_Check, unittest.TestCase):
class Maps_Test(Base_Check, unittest.TestCase):
def demand_equal(self, other):
super().demand_equal(other)
- self._inst.equal(other)
+ self.assertTrue(self._inst.equal(other))
+
+ def test_dict(self):
+ super().test_dict()
+ dict_ = self._inst._as_dict()
+ self.assertIsInstance(dict_['args::0::args::0::args::1::args::0'], np.ndarray)
+ self.assertNotIsInstance(dict_['args::0::args::0::args::1::args::0'], tfields.Tensors)
def setUp(self):
self._inst = tfields.Maps(
diff --git a/tfields/core.py b/tfields/core.py
index 02797192d4e01201033359415d1f1fc619cf2f3f..5ef52bdba9d8bfde8207467fea7fcd4a7178cc1a 100644
--- a/tfields/core.py
+++ b/tfields/core.py
@@ -17,6 +17,8 @@ TODO:
"""
# builtin
import warnings
+import typing
+import builtins
import inspect
from contextlib import contextmanager
from collections import Counter
@@ -55,6 +57,63 @@ def dim(tensor):
return tensor.shape[1]
+_HIERARCHY_SEPARATOR = "::"
+
+
+def _from_dict(content: dict, eval_type=None):
+ # build the nested dict from the chierarchy_flattened dict keys
+ here = {}
+ for string in content:
+ if string == "type":
+ continue
+
+ value = content[string]
+
+ attr, _, end = string.partition(_HIERARCHY_SEPARATOR)
+ key, _, end = end.partition(_HIERARCHY_SEPARATOR)
+ if attr not in here:
+ here[attr] = {}
+ if key not in here[attr]:
+ here[attr][key] = {}
+ here[attr][key][end] = value
+
+ if "type" not in content:
+ return here[attr][key].pop("")
+
+ obj_type = content.get("type")
+ # build type for recursion
+ if isinstance(obj_type, np.ndarray): # happens on np.load
+ obj_type = obj_type.tolist()
+ if isinstance(obj_type, bytes):
+ # astonishingly, this is not necessary under linux.
+ # Found under nt. ???
+ obj_type = obj_type.decode("UTF-8")
+
+ try:
+ cls = getattr(builtins, obj_type)
+ except AttributeError:
+ cls = getattr(tfields, obj_type)
+
+ # Do the recursion
+ # pylint:disable=consider-using-dict-items
+ for attr in here:
+ # pylint:disable=consider-using-dict-items
+ for key in here[attr]:
+ here[attr][key] = _from_dict(here[attr][key])
+
+ # Build the generic way
+ args = here.pop("args", tuple())
+ args = tuple(args[key] for key in sorted(args))
+ kwargs = here.pop("kwargs", {})
+ assert len(here) == 0
+ if cls in (tuple, list):
+ # TODO: remove this in favour of better pacing tuple?
+ obj = cls(args, **kwargs)
+ return obj
+ obj = cls(*args, **kwargs)
+ return obj
+
+
class AbstractObject(rna.polymorphism.Storable):
"""
Abstract base class for all tfields objects implementing polymorphisms
@@ -135,13 +194,14 @@ class AbstractObject(rna.polymorphism.Storable):
"""
return dict()
- _HIERARCHY_SEPARATOR = "::"
-
- def _as_dict(self) -> dict:
+ def _as_dict(self, recurse: typing.Dict[str, typing.Callable] = None) -> dict:
"""
Get an object represenation in a dict format. This is necessary e.g. for saving the full
file uniquely in the npz format
+ Args:
+ recurse: dict of {attribute: callable(iterable) -> dict}
+
Returns:
dict: object packed as nested dictionary
"""
@@ -156,12 +216,19 @@ class AbstractObject(rna.polymorphism.Storable):
("kwargs", self._kwargs().items()),
]:
for attr, value in iterable:
- attr = base_attr + self._HIERARCHY_SEPARATOR + attr
- if hasattr(value, "_as_dict"):
- part_dict = value._as_dict() # pylint: disable=protected-access
+ attr = base_attr + _HIERARCHY_SEPARATOR + attr
+ if (
+ (recurse is not None and attr in recurse)
+ or hasattr(value, "_as_dict")
+ ):
+ if recurse is not None and attr in recurse:
+ part_dict = recurse[attr](value)
+ else:
+ part_dict = value._as_dict() # pylint: disable=protected-access
+
for part_attr, part_value in part_dict.items():
content[
- attr + self._HIERARCHY_SEPARATOR + part_attr
+ attr + _HIERARCHY_SEPARATOR + part_attr
] = part_value
else:
content[attr] = value
@@ -169,110 +236,10 @@ class AbstractObject(rna.polymorphism.Storable):
@classmethod
def _from_dict(cls, content: dict):
- try:
- content.pop("type")
- except KeyError:
- # legacy
- return cls._from_dict_legacy(**content)
-
- here = {}
- for string in content: # TODO no sortelist
- value = content[string]
-
- attr, _, end = string.partition(cls._HIERARCHY_SEPARATOR)
- key, _, end = end.partition(cls._HIERARCHY_SEPARATOR)
- if attr not in here:
- here[attr] = {}
- if key not in here[attr]:
- here[attr][key] = {}
- here[attr][key][end] = value
-
- # Do the recursion
- # pylint:disable=consider-using-dict-items
- for attr in here:
- # pylint:disable=consider-using-dict-items
- for key in here[attr]:
- if "type" in here[attr][key]:
- obj_type = here[attr][key].get("type")
- if isinstance(obj_type, np.ndarray): # happens on np.load
- obj_type = obj_type.tolist()
- if isinstance(obj_type, bytes):
- # astonishingly, this is not necessary under linux.
- # Found under nt. ???
- obj_type = obj_type.decode("UTF-8")
- obj_type = getattr(tfields, obj_type)
- attr_value = (
- obj_type._from_dict( # pylint: disable=protected-access
- here[attr][key]
- )
- )
- else: # if len(here[attr][key]) == 1:
- attr_value = here[attr][key].pop("")
- here[attr][key] = attr_value
-
- # Build the generic way
- args = here.pop("args", tuple())
- args = tuple(args[key] for key in sorted(args))
- kwargs = here.pop("kwargs", {})
- assert len(here) == 0
- obj = cls(*args, **kwargs)
- return obj
-
- @classmethod
- def _from_dict_legacy(cls, **content):
- """
- legacy method of _from_dict - Opposite of old _as_dict method
- which is overridden in this version
- """
- list_dict = {}
- kwargs = {}
- # De-Flatten the first layer of lists
- for key in sorted(list(content)):
- if "::" in key:
- attr, _, end = key.partition("::")
- if attr not in list_dict:
- list_dict[attr] = {}
-
- index, _, end = end.partition("::")
- if not index.isdigit():
- raise ValueError("None digit index given")
- index = int(index)
- if index not in list_dict[attr]:
- list_dict[attr][index] = {}
- list_dict[attr][index][end] = content[key]
- else:
- kwargs[key] = content[key]
-
- # Build the lists (recursively)
- for key in list(list_dict):
- sub_dict = list_dict[key]
- list_dict[key] = []
- for index in sorted(list(sub_dict)):
- bulk_type = sub_dict[index].get("bulk_type")
- bulk_type = bulk_type.tolist()
- if isinstance(bulk_type, bytes):
- # asthonishingly, this is not necessary under linux.
- # Found under nt. ???
- bulk_type = bulk_type.decode("UTF-8")
- bulk_type = getattr(tfields, bulk_type)
- list_dict[key].append(
- bulk_type._from_dict_legacy( # noqa: E501 pylint: disable=protected-access
- **sub_dict[index]
- )
- )
+ type_ = content.get("type")
+ assert type_ == cls.__name__
- with cls._bypass_setters( # pylint: disable=protected-access,no-member
- "fields", demand_existence=False
- ):
- # Build the normal way
- bulk = kwargs.pop("bulk")
- bulk_type = kwargs.pop("bulk_type")
- obj = cls.__new__(cls, bulk, **kwargs)
-
- # Set list attributes
- for attr, list_value in list_dict.items():
- setattr(obj, attr, list_value)
- return obj
+ return _from_dict(content)
class AbstractNdarray(np.ndarray, AbstractObject):
@@ -1952,7 +1919,7 @@ class TensorFields(Tensors):
def _kwargs(self) -> dict:
content = super()._kwargs()
- content.pop("fields")
+ content.pop("fields") # instantiated via _args
return content
def __getitem__(self, index):
@@ -2411,6 +2378,31 @@ class Maps(sortedcontainers.SortedDict, AbstractObject):
def _args(self):
return super()._args() + (list(self.items()),)
+ def _as_dict(self, recurse: typing.Dict[str, typing.Callable] = None) -> dict:
+ if recurse is None:
+ recurse = {}
+
+ def recurse_args_0(iterable: typing.List[typing.Tuple[int, typing.Any]]) -> dict:
+ # iterable is list of tuple
+ part_dict = {"type": "list"}
+ for i, (dim, tensor) in enumerate(iterable):
+ content = tensor._as_dict()
+ tuple_key = _HIERARCHY_SEPARATOR.join(["args", str(i), ""])
+ part_dict[tuple_key + "type"] = "tuple"
+ args_key = tuple_key + _HIERARCHY_SEPARATOR.join(["args", ""])
+
+ part_dict[args_key + _HIERARCHY_SEPARATOR.join(["0", "args", "0"])] = dim
+ part_dict[args_key + _HIERARCHY_SEPARATOR.join(["0", "type"])] = 'int'
+
+ for key, value in content.items():
+ part_dict[args_key + _HIERARCHY_SEPARATOR.join(["1", key])] = value
+
+ return part_dict
+
+ attr = 'args' + _HIERARCHY_SEPARATOR + str(0)
+ recurse[attr] = recurse_args_0
+ return super()._as_dict(recurse=recurse)
+
def equal(self, other, **kwargs):
"""
Test equality with other object.
diff --git a/tfields/lib/util.py b/tfields/lib/util.py
index c71978fe64fd86f54367226875532557f139cc73..cf365652f3efe699b24abb4c923a7bb4dc3723c2 100644
--- a/tfields/lib/util.py
+++ b/tfields/lib/util.py
@@ -2,6 +2,7 @@
Various utility functions
"""
import itertools
+import typing
from six import string_types
import numpy as np
@@ -20,15 +21,18 @@ def pairwise(iterable):
return zip(a, b)
-def flatten(seq, container=None, keep_types=None):
+def flatten(seq, container=None, keep_types=None, key: typing.Callable = None):
"""
Approach to flatten a nested sequence.
+
Args:
seq (iterable): iterable to be flattened
containter (iterable): iterable defining an append method. Values will
be appended there
keep_types (list of type): types that should not be flattened but kept
in nested form
+ key (callable): callable with the signature key(iterable) -> iterable
+
Examples:
>>> from tfields.lib.util import flatten
>>> import numpy as np
@@ -43,21 +47,36 @@ def flatten(seq, container=None, keep_types=None):
>>> flatten([[0, 0, 0, 'A'], [1, 2, 3]])
[0, 0, 0, 'A', 1, 2, 3]
+ Dictionaries will return flattened keys
+ >>> flatten({"a": 1, "b": 2})
+ ['a', 'b']
+
+ You can use the key keyword to specify a transformation on the iterable:
+ >>> flatten({"a": {"a1": 1, "a2": 4}, "b": 2}, key=dict.values)
+ [1, 4, 2]
+
+ >>> def dict_flat_key(item):
+ ... if isinstance(item, dict):
+ ... return item.values()
+ ... return item
+ >>> flatten({"a": {"a1": 1, "a2": [3, 4]}, "b": 2}, key=dict_flat_key)
+ [1, 3, 4, 2]
"""
if keep_types is None:
keep_types = []
if container is None:
container = []
- # pylint:disable=invalid-name
- for s in seq:
+ if key is not None:
+ seq = key(seq)
+ for item in seq:
if (
- hasattr(s, "__iter__")
- and not isinstance(s, string_types)
- and not any((isinstance(s, t) for t in keep_types))
+ hasattr(item, "__iter__")
+ and not isinstance(item, string_types)
+ and not any((isinstance(item, t) for t in keep_types))
):
- flatten(s, container, keep_types)
+ flatten(item, container, keep_types, key=key)
else:
- container.append(s)
+ container.append(item)
return container