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adjustment of skewed edge weights

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Florian Förster 2024-07-03 18:01:33 +02:00
parent 2656780907
commit 55a9ef7f69
5 changed files with 853 additions and 134 deletions
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@ -2,17 +2,17 @@
# It is not intended for manual editing.
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files = [
{file = "numpy-1.26.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4c66707fabe114439db9068ee468c26bbdf909cac0fb58686a42a24de1760c71"},
{file = "numpy-1.26.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:edd8b5fe47dab091176d21bb6de568acdd906d1887a4584a15a9a96a1dca06ef"},
@ -1607,7 +1720,7 @@ name = "packaging"
version = "24.0"
requires_python = ">=3.7"
summary = "Core utilities for Python packages"
groups = ["default", "notebooks", "trails", "trials"]
groups = ["default", "notebooks", "trials"]
files = [
{file = "packaging-24.0-py3-none-any.whl", hash = "sha256:2ddfb553fdf02fb784c234c7ba6ccc288296ceabec964ad2eae3777778130bc5"},
{file = "packaging-24.0.tar.gz", hash = "sha256:eb82c5e3e56209074766e6885bb04b8c38a0c015d0a30036ebe7ece34c9989e9"},
@ -1618,7 +1731,7 @@ name = "pandas"
version = "2.2.2"
requires_python = ">=3.9"
summary = "Powerful data structures for data analysis, time series, and statistics"
groups = ["default", "trails", "trials"]
groups = ["default", "trials"]
dependencies = [
"numpy>=1.23.2; python_version == \"3.11\"",
"numpy>=1.26.0; python_version >= \"3.12\"",
@ -1849,6 +1962,28 @@ files = [
{file = "pure_eval-0.2.2.tar.gz", hash = "sha256:2b45320af6dfaa1750f543d714b6d1c520a1688dec6fd24d339063ce0aaa9ac3"},
]
[[package]]
name = "py4cytoscape"
version = "1.9.0"
requires_python = ">=3.8"
summary = "Cytoscape Automation API"
groups = ["trials"]
dependencies = [
"backoff",
"chardet",
"colorbrewer",
"colour",
"decorator",
"igraph",
"networkx",
"pandas",
"requests",
]
files = [
{file = "py4cytoscape-1.9.0-py3-none-any.whl", hash = "sha256:7e9088832d49489406d1933596225256652c9d58f1d1ee097fea50762bd70dca"},
{file = "py4cytoscape-1.9.0.tar.gz", hash = "sha256:ebf214c5888497ecb9db0c166f6e66123e49402522f7058fe1169b87307e8512"},
]
[[package]]
name = "pycparser"
version = "2.22"
@ -1947,7 +2082,7 @@ name = "pygraphviz"
version = "1.13"
requires_python = ">=3.10"
summary = "Python interface to Graphviz"
groups = ["trails", "trials"]
groups = ["trials"]
files = [
{file = "pygraphviz-1.13.tar.gz", hash = "sha256:6ad8aa2f26768830a5a1cfc8a14f022d13df170a8f6fdfd68fd1aa1267000964"},
]
@ -1957,7 +2092,7 @@ name = "python-dateutil"
version = "2.9.0.post0"
requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
summary = "Extensions to the standard Python datetime module"
groups = ["default", "notebooks", "trails", "trials"]
groups = ["default", "notebooks", "trials"]
dependencies = [
"six>=1.5",
]
@ -1981,7 +2116,7 @@ files = [
name = "pytz"
version = "2024.1"
summary = "World timezone definitions, modern and historical"
groups = ["default", "trails", "trials"]
groups = ["default", "trials"]
files = [
{file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"},
{file = "pytz-2024.1.tar.gz", hash = "sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812"},
@ -2103,7 +2238,7 @@ name = "referencing"
version = "0.35.1"
requires_python = ">=3.8"
summary = "JSON Referencing + Python"
groups = ["notebooks", "trails", "trials"]
groups = ["notebooks", "trials"]
dependencies = [
"attrs>=22.2.0",
"rpds-py>=0.7.0",
@ -2158,7 +2293,7 @@ name = "requests"
version = "2.31.0"
requires_python = ">=3.7"
summary = "Python HTTP for Humans."
groups = ["default", "notebooks"]
groups = ["default", "notebooks", "trials"]
dependencies = [
"certifi>=2017.4.17",
"charset-normalizer<4,>=2",
@ -2213,7 +2348,7 @@ name = "rpds-py"
version = "0.18.1"
requires_python = ">=3.8"
summary = "Python bindings to Rust's persistent data structures (rpds)"
groups = ["notebooks", "trails", "trials"]
groups = ["notebooks", "trials"]
files = [
{file = "rpds_py-0.18.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:6b5ff7e1d63a8281654b5e2896d7f08799378e594f09cf3674e832ecaf396ce8"},
{file = "rpds_py-0.18.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8927638a4d4137a289e41d0fd631551e89fa346d6dbcfc31ad627557d03ceb6d"},
@ -2369,7 +2504,7 @@ name = "scikit-network"
version = "0.32.1"
requires_python = ">=3.8"
summary = "Graph algorithms"
groups = ["trails", "trials"]
groups = ["trials"]
dependencies = [
"numpy>=1.22.4",
"scipy>=1.7.3",
@ -2386,7 +2521,7 @@ name = "scipy"
version = "1.13.0"
requires_python = ">=3.9"
summary = "Fundamental algorithms for scientific computing in Python"
groups = ["default", "trails", "trials"]
groups = ["default", "trials"]
dependencies = [
"numpy<2.3,>=1.22.4",
]
@ -2454,7 +2589,7 @@ name = "six"
version = "1.16.0"
requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
summary = "Python 2 and 3 compatibility utilities"
groups = ["default", "notebooks", "trails", "trials"]
groups = ["default", "notebooks", "trials"]
files = [
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
@ -2736,6 +2871,16 @@ files = [
{file = "terminado-0.18.1.tar.gz", hash = "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e"},
]
[[package]]
name = "texttable"
version = "1.7.0"
summary = "module to create simple ASCII tables"
groups = ["trials"]
files = [
{file = "texttable-1.7.0-py2.py3-none-any.whl", hash = "sha256:72227d592c82b3d7f672731ae73e4d1f88cd8e2ef5b075a7a7f01a23a3743917"},
{file = "texttable-1.7.0.tar.gz", hash = "sha256:2d2068fb55115807d3ac77a4ca68fa48803e84ebb0ee2340f858107a36522638"},
]
[[package]]
name = "thinc"
version = "8.2.3"
@ -2874,7 +3019,7 @@ name = "toolz"
version = "0.12.1"
requires_python = ">=3.7"
summary = "List processing tools and functional utilities"
groups = ["trails", "trials"]
groups = ["trials"]
files = [
{file = "toolz-0.12.1-py3-none-any.whl", hash = "sha256:d22731364c07d72eea0a0ad45bafb2c2937ab6fd38a3507bf55eae8744aa7d85"},
{file = "toolz-0.12.1.tar.gz", hash = "sha256:ecca342664893f177a13dac0e6b41cbd8ac25a358e5f215316d43e2100224f4d"},
@ -3042,7 +3187,7 @@ name = "tzdata"
version = "2024.1"
requires_python = ">=2"
summary = "Provider of IANA time zone data"
groups = ["default", "trails", "trials"]
groups = ["default", "trials"]
files = [
{file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
{file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
@ -3064,7 +3209,7 @@ name = "urllib3"
version = "2.2.1"
requires_python = ">=3.8"
summary = "HTTP library with thread-safe connection pooling, file post, and more."
groups = ["default", "notebooks"]
groups = ["default", "notebooks", "trials"]
files = [
{file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"},
{file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"},

6
pyproject.toml
View File

@ -39,8 +39,12 @@ notebooks = [
# (Linux not tested yet). The compiler needs additional information about the location of Graphviz
# files. This information is provided by extra options.
# --config-setting="--global-option=build_ext" --config-setting="--global-option=-IC:\Program Files\Graphviz\include" --config-setting="--global-option=-LC:\Program Files\Graphviz\lib"
trails = [
trials = [
"alph[graphviz]>=0.4.10",
"py4cytoscape>=1.9.0",
]
dev = [
"cython>=3.0.10",
]
[tool.ruff]

103
src/lang_main/analysis/graphs.py
View File

@ -13,6 +13,7 @@ import numpy.typing as npt
from networkx import DiGraph, Graph
from pandas import DataFrame
from lang_main.constants import EDGE_WEIGHT_DECIMALS
from lang_main.io import load_pickle, save_pickle
from lang_main.loggers import logger_graphs as logger
from lang_main.types import (
@ -105,15 +106,26 @@ def update_graph(
def convert_graph_to_undirected(
graph: DiGraph,
logging: bool = LOGGING_DEFAULT,
cast_int: bool = False,
) -> Graph:
dtype = np.float32
if cast_int:
dtype = np.uint32
# get adjacency matrix
adj_mat = typing.cast(DataFrame, nx.to_pandas_adjacency(G=graph, dtype=np.uint32))
arr = typing.cast(npt.NDArray[np.uint32], adj_mat.to_numpy())
adj_mat = typing.cast(DataFrame, nx.to_pandas_adjacency(G=graph, dtype=dtype))
arr = typing.cast(npt.NDArray[np.float32 | np.uint32], adj_mat.to_numpy())
if not cast_int:
arr = arr * (10**EDGE_WEIGHT_DECIMALS)
arr = np.round(arr, decimals=0)
arr = arr.astype(np.uint32)
# build undirected array: adding edges of lower triangular matrix to upper one
arr_upper = np.triu(arr)
arr_lower = np.tril(arr)
arr_lower = np.rot90(np.fliplr(arr_lower))
arr_new = arr_upper + arr_lower
if not cast_int:
arr_new = (arr_new / 10**EDGE_WEIGHT_DECIMALS).astype(np.float32)
arr_new = np.round(arr_new, decimals=EDGE_WEIGHT_DECIMALS)
# assign new data and create graph
adj_mat.loc[:] = arr_new # type: ignore
graph_undir = typing.cast(Graph, nx.from_pandas_adjacency(df=adj_mat))
@ -164,6 +176,7 @@ def convert_graph_to_cytoscape(
}
cyto_data.append(edge_data)
# TODO: add internal behaviour (if edge added check for new min/max)
min_weight: int = 0
max_weight: int = 0
if weights:
@ -257,6 +270,78 @@ def filter_graph_by_node_degree(
return filtered_graph
def normalise_array_linear(
array: npt.NDArray[np.float_],
) -> npt.NDArray[np.float32]:
"""apply standard linear normalisation
Parameters
----------
array : npt.NDArray[np.float_]
array which shall be normalised
Returns
-------
npt.NDArray[np.float32]
min/max normalised array
"""
arr_norm = (array - array.min()) / (array.max() - array.min())
return arr_norm.astype(np.float32)
def weight_scaling(
weights: npt.NDArray[np.float32],
a: float = 1.1,
b: float = 0.05,
) -> npt.NDArray[np.float32]:
"""non-linear scaling of already normalised edge weights [0;1]: bigger weights
have smaller weight delta than smaller weights. Bigger values für parameter
`b` reinforce this effect.
Based on:
https://math.stackexchange.com/questions/4297805/exponential-function-that-passes-through-0-0-and-1-1-with-variable-slope
With default values the range of edge weights lies approximately between [0.1; 1]
Parameters
----------
weights : npt.NDArray[np.float32]
pre-normalised edge weights as 1D array
a : float, optional
factor to determine the value for edge weights with value 0
with default approx. 0.1, by default 1.1
b : float, optional
adjust the curvature, smaller values increase it, by default 0.05
Returns
-------
npt.NDArray[np.float32]
non-linear adjusted edge weights as 1D array
"""
adjusted_weights = (b**weights - a) / (b - a)
return np.round(adjusted_weights, decimals=EDGE_WEIGHT_DECIMALS)
def rescale_edge_weights(
graph: TokenGraph,
) -> TokenGraph:
graph = graph.copy()
weights = cast(list[int], [data['weight'] for data in graph.edges.values()])
w_log = cast(npt.NDArray[np.float32], np.log(weights, dtype=np.float32))
weights_norm = normalise_array_linear(w_log)
weights_adjusted = weight_scaling(weights_norm)
# assign new weight values
for idx, (node_1, node_2) in enumerate(list(graph.edges)):
graph[node_1][node_2]['weight'] = weights_adjusted[idx]
graph.rescaled_weights = True
graph.update_metadata(logging=False)
return graph
# ** ---------------------------------------
class TokenGraph(DiGraph):
def __init__(
@ -276,6 +361,8 @@ class TokenGraph(DiGraph):
self._metadata_directed: dict[str, int] = {}
self._undirected: Graph | None = None
self._metadata_undirected: dict[str, int] = {}
# indicate rescaled weights
self.rescaled_weights: bool = False
def __repr__(self) -> str:
return self.__str__()
@ -350,11 +437,17 @@ class TokenGraph(DiGraph):
) -> Graph | None:
if logging is None:
logging = self.logging
# cast to integer edge weights only if edges were not rescaled previously
cast_int: bool = True
if self.rescaled_weights:
cast_int = False
self._undirected = convert_graph_to_undirected(graph=self, logging=logging)
self._metadata_undirected = get_graph_metadata(
graph=self._undirected, logging=logging
self._undirected = convert_graph_to_undirected(
graph=self,
logging=logging,
cast_int=cast_int,
)
self._metadata_undirected = get_graph_metadata(graph=self._undirected, logging=False)
if not inplace:
return self._undirected

1
src/lang_main/constants.py
View File

@ -56,6 +56,7 @@ THRESHOLD_SIMILARITY: Final[float] = CONFIG['preprocess']['threshold_similarity'
# ** token analysis
# ** graph postprocessing
EDGE_WEIGHT_DECIMALS: Final[int] = 4
THRESHOLD_EDGE_WEIGHT: Final[int] = CONFIG['graph_postprocessing']['threshold_edge_weight']
# ** time analysis.uniqueness
THRESHOLD_UNIQUE_TEXTS: Final[int] = CONFIG['time_analysis']['uniqueness'][

672
test-notebooks/misc.ipynb
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