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improved dashboard, fixed language tags, tests graph plotting

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Florian Förster 2024-06-26 16:13:53 +02:00
parent fb4437a3a2
commit 2656780907
11 changed files with 541 additions and 1714 deletions
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@ -2,10 +2,62 @@
# It is not intended for manual editing. # It is not intended for manual editing.
[metadata] [metadata]
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks", "trials", "trails"]
strategy = ["cross_platform", "inherit_metadata"] strategy = ["cross_platform", "inherit_metadata"]
lock_version = "4.4.1" lock_version = "4.4.2"
content_hash = "sha256:e00f157f833ee7615d96375c352e2caa6b4f6b50e5615ccbefa79446189594c7" content_hash = "sha256:36979d60d30dad28e15e0f93496b4ea25af7fc5a12b91e82c12e1b957325c0af"
[[package]]
name = "alph"
version = "0.4.10"
requires_python = "<4.0,>=3.9"
summary = "alph"
groups = ["trails", "trials"]
dependencies = [
"altair>=5.0.1",
"networkx>=2.6.3",
"pandas>=1.3.5",
"scikit-network>=0.27.1",
]
files = [
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{file = "alph-0.4.10.tar.gz", hash = "sha256:a2cfe932c7a6a973c718f8c5bc1b1dbc7a1d18a122cb5e438db5ea3a61d6b5c3"},
]
[[package]]
name = "alph"
version = "0.4.10"
extras = ["graphviz"]
requires_python = "<4.0,>=3.9"
summary = "alph"
groups = ["trails", "trials"]
dependencies = [
"alph==0.4.10",
"pygraphviz>=1.10",
]
files = [
{file = "alph-0.4.10-py3-none-any.whl", hash = "sha256:47649ef9d12ac7bddaa9cfc7510ab333e7fe1c76d4da4d1b09629bbd174fbe63"},
{file = "alph-0.4.10.tar.gz", hash = "sha256:a2cfe932c7a6a973c718f8c5bc1b1dbc7a1d18a122cb5e438db5ea3a61d6b5c3"},
]
[[package]]
name = "altair"
version = "5.3.0"
requires_python = ">=3.8"
summary = "Vega-Altair: A declarative statistical visualization library for Python."
groups = ["trails", "trials"]
dependencies = [
"jinja2",
"jsonschema>=3.0",
"numpy",
"packaging",
"pandas>=0.25",
"toolz",
]
files = [
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[[package]] [[package]]
name = "annotated-types" name = "annotated-types"
@ -136,7 +188,7 @@ name = "attrs"
version = "23.2.0" version = "23.2.0"
requires_python = ">=3.7" requires_python = ">=3.7"
summary = "Classes Without Boilerplate" summary = "Classes Without Boilerplate"
groups = ["notebooks"] groups = ["notebooks", "trails", "trials"]
files = [ files = [
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@ -187,7 +239,7 @@ name = "blinker"
version = "1.8.2" version = "1.8.2"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Fast, simple object-to-object and broadcast signaling" summary = "Fast, simple object-to-object and broadcast signaling"
groups = ["trials"] groups = ["default"]
files = [ files = [
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@ -231,7 +283,7 @@ name = "certifi"
version = "2024.2.2" version = "2024.2.2"
requires_python = ">=3.6" requires_python = ">=3.6"
summary = "Python package for providing Mozilla's CA Bundle." summary = "Python package for providing Mozilla's CA Bundle."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
files = [ files = [
{file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"}, {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
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@ -276,7 +328,7 @@ name = "charset-normalizer"
version = "3.3.2" version = "3.3.2"
requires_python = ">=3.7.0" requires_python = ">=3.7.0"
summary = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." summary = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
files = [ files = [
{file = "charset-normalizer-3.3.2.tar.gz", hash = "sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5"}, {file = "charset-normalizer-3.3.2.tar.gz", hash = "sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5"},
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@ -317,7 +369,7 @@ name = "click"
version = "8.1.7" version = "8.1.7"
requires_python = ">=3.7" requires_python = ">=3.7"
summary = "Composable command line interface toolkit" summary = "Composable command line interface toolkit"
groups = ["default", "trials"] groups = ["default"]
dependencies = [ dependencies = [
"colorama; platform_system == \"Windows\"", "colorama; platform_system == \"Windows\"",
] ]
@ -342,7 +394,7 @@ name = "colorama"
version = "0.4.6" version = "0.4.6"
requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
summary = "Cross-platform colored terminal text." summary = "Cross-platform colored terminal text."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
marker = "platform_system == \"Windows\" or sys_platform == \"win32\"" marker = "platform_system == \"Windows\" or sys_platform == \"win32\""
files = [ files = [
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@ -402,7 +454,7 @@ name = "dash"
version = "2.17.0" version = "2.17.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "A Python framework for building reactive web-apps. Developed by Plotly." summary = "A Python framework for building reactive web-apps. Developed by Plotly."
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"Flask<3.1,>=1.0.4", "Flask<3.1,>=1.0.4",
"Werkzeug<3.1", "Werkzeug<3.1",
@ -426,7 +478,7 @@ files = [
name = "dash-core-components" name = "dash-core-components"
version = "2.0.0" version = "2.0.0"
summary = "Core component suite for Dash" summary = "Core component suite for Dash"
groups = ["trials"] groups = ["default"]
files = [ files = [
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@ -437,7 +489,7 @@ name = "dash-cytoscape"
version = "1.0.1" version = "1.0.1"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "A Component Library for Dash aimed at facilitating network visualization in Python, wrapped around Cytoscape.js" summary = "A Component Library for Dash aimed at facilitating network visualization in Python, wrapped around Cytoscape.js"
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"dash", "dash",
] ]
@ -449,7 +501,7 @@ files = [
name = "dash-html-components" name = "dash-html-components"
version = "2.0.0" version = "2.0.0"
summary = "Vanilla HTML components for Dash" summary = "Vanilla HTML components for Dash"
groups = ["trials"] groups = ["default"]
files = [ files = [
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@ -459,7 +511,7 @@ files = [
name = "dash-table" name = "dash-table"
version = "5.0.0" version = "5.0.0"
summary = "Dash table" summary = "Dash table"
groups = ["trials"] groups = ["default"]
files = [ files = [
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@ -543,7 +595,7 @@ name = "flask"
version = "3.0.3" version = "3.0.3"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "A simple framework for building complex web applications." summary = "A simple framework for building complex web applications."
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"Jinja2>=3.1.2", "Jinja2>=3.1.2",
"Werkzeug>=3.0.0", "Werkzeug>=3.0.0",
@ -647,7 +699,7 @@ name = "idna"
version = "3.7" version = "3.7"
requires_python = ">=3.5" requires_python = ">=3.5"
summary = "Internationalized Domain Names in Applications (IDNA)" summary = "Internationalized Domain Names in Applications (IDNA)"
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
files = [ files = [
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@ -658,7 +710,7 @@ name = "importlib-metadata"
version = "7.1.0" version = "7.1.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Read metadata from Python packages" summary = "Read metadata from Python packages"
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"zipp>=0.5", "zipp>=0.5",
] ]
@ -767,7 +819,7 @@ name = "itsdangerous"
version = "2.2.0" version = "2.2.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Safely pass data to untrusted environments and back." summary = "Safely pass data to untrusted environments and back."
groups = ["trials"] groups = ["default"]
files = [ files = [
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@ -792,7 +844,7 @@ name = "jinja2"
version = "3.1.4" version = "3.1.4"
requires_python = ">=3.7" requires_python = ">=3.7"
summary = "A very fast and expressive template engine." summary = "A very fast and expressive template engine."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks", "trails", "trials"]
dependencies = [ dependencies = [
"MarkupSafe>=2.0", "MarkupSafe>=2.0",
] ]
@ -839,7 +891,7 @@ name = "jsonschema"
version = "4.22.0" version = "4.22.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "An implementation of JSON Schema validation for Python" summary = "An implementation of JSON Schema validation for Python"
groups = ["notebooks"] groups = ["notebooks", "trails", "trials"]
dependencies = [ dependencies = [
"attrs>=22.2.0", "attrs>=22.2.0",
"jsonschema-specifications>=2023.03.6", "jsonschema-specifications>=2023.03.6",
@ -856,7 +908,7 @@ name = "jsonschema-specifications"
version = "2023.12.1" version = "2023.12.1"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry" summary = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
groups = ["notebooks"] groups = ["notebooks", "trails", "trials"]
dependencies = [ dependencies = [
"referencing>=0.31.0", "referencing>=0.31.0",
] ]
@ -1160,7 +1212,7 @@ name = "markupsafe"
version = "2.1.5" version = "2.1.5"
requires_python = ">=3.7" requires_python = ">=3.7"
summary = "Safely add untrusted strings to HTML/XML markup." summary = "Safely add untrusted strings to HTML/XML markup."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks", "trails", "trials"]
files = [ files = [
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@ -1325,7 +1377,7 @@ name = "nest-asyncio"
version = "1.6.0" version = "1.6.0"
requires_python = ">=3.5" requires_python = ">=3.5"
summary = "Patch asyncio to allow nested event loops" summary = "Patch asyncio to allow nested event loops"
groups = ["notebooks", "trials"] groups = ["default", "notebooks"]
files = [ files = [
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@ -1336,7 +1388,7 @@ name = "networkx"
version = "3.3" version = "3.3"
requires_python = ">=3.10" requires_python = ">=3.10"
summary = "Python package for creating and manipulating graphs and networks" summary = "Python package for creating and manipulating graphs and networks"
groups = ["default"] groups = ["default", "trails", "trials"]
files = [ files = [
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{file = "networkx-3.3.tar.gz", hash = "sha256:0c127d8b2f4865f59ae9cb8aafcd60b5c70f3241ebd66f7defad7c4ab90126c9"}, {file = "networkx-3.3.tar.gz", hash = "sha256:0c127d8b2f4865f59ae9cb8aafcd60b5c70f3241ebd66f7defad7c4ab90126c9"},
@ -1361,7 +1413,7 @@ name = "numpy"
version = "1.26.4" version = "1.26.4"
requires_python = ">=3.9" requires_python = ">=3.9"
summary = "Fundamental package for array computing in Python" summary = "Fundamental package for array computing in Python"
groups = ["default"] groups = ["default", "trails", "trials"]
files = [ files = [
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@ -1555,7 +1607,7 @@ name = "packaging"
version = "24.0" version = "24.0"
requires_python = ">=3.7" requires_python = ">=3.7"
summary = "Core utilities for Python packages" summary = "Core utilities for Python packages"
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks", "trails", "trials"]
files = [ files = [
{file = "packaging-24.0-py3-none-any.whl", hash = "sha256:2ddfb553fdf02fb784c234c7ba6ccc288296ceabec964ad2eae3777778130bc5"}, {file = "packaging-24.0-py3-none-any.whl", hash = "sha256:2ddfb553fdf02fb784c234c7ba6ccc288296ceabec964ad2eae3777778130bc5"},
{file = "packaging-24.0.tar.gz", hash = "sha256:eb82c5e3e56209074766e6885bb04b8c38a0c015d0a30036ebe7ece34c9989e9"}, {file = "packaging-24.0.tar.gz", hash = "sha256:eb82c5e3e56209074766e6885bb04b8c38a0c015d0a30036ebe7ece34c9989e9"},
@ -1566,7 +1618,7 @@ name = "pandas"
version = "2.2.2" version = "2.2.2"
requires_python = ">=3.9" requires_python = ">=3.9"
summary = "Powerful data structures for data analysis, time series, and statistics" summary = "Powerful data structures for data analysis, time series, and statistics"
groups = ["default"] groups = ["default", "trails", "trials"]
dependencies = [ dependencies = [
"numpy>=1.23.2; python_version == \"3.11\"", "numpy>=1.23.2; python_version == \"3.11\"",
"numpy>=1.26.0; python_version >= \"3.12\"", "numpy>=1.26.0; python_version >= \"3.12\"",
@ -1701,7 +1753,7 @@ name = "plotly"
version = "5.22.0" version = "5.22.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "An open-source, interactive data visualization library for Python" summary = "An open-source, interactive data visualization library for Python"
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"packaging", "packaging",
"tenacity>=6.2.0", "tenacity>=6.2.0",
@ -1890,12 +1942,22 @@ files = [
{file = "pygments-2.18.0.tar.gz", hash = "sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199"}, {file = "pygments-2.18.0.tar.gz", hash = "sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199"},
] ]
[[package]]
name = "pygraphviz"
version = "1.13"
requires_python = ">=3.10"
summary = "Python interface to Graphviz"
groups = ["trails", "trials"]
files = [
{file = "pygraphviz-1.13.tar.gz", hash = "sha256:6ad8aa2f26768830a5a1cfc8a14f022d13df170a8f6fdfd68fd1aa1267000964"},
]
[[package]] [[package]]
name = "python-dateutil" name = "python-dateutil"
version = "2.9.0.post0" version = "2.9.0.post0"
requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
summary = "Extensions to the standard Python datetime module" summary = "Extensions to the standard Python datetime module"
groups = ["default", "notebooks"] groups = ["default", "notebooks", "trails", "trials"]
dependencies = [ dependencies = [
"six>=1.5", "six>=1.5",
] ]
@ -1919,7 +1981,7 @@ files = [
name = "pytz" name = "pytz"
version = "2024.1" version = "2024.1"
summary = "World timezone definitions, modern and historical" summary = "World timezone definitions, modern and historical"
groups = ["default"] groups = ["default", "trails", "trials"]
files = [ files = [
{file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"}, {file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"},
{file = "pytz-2024.1.tar.gz", hash = "sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812"}, {file = "pytz-2024.1.tar.gz", hash = "sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812"},
@ -2041,7 +2103,7 @@ name = "referencing"
version = "0.35.1" version = "0.35.1"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "JSON Referencing + Python" summary = "JSON Referencing + Python"
groups = ["notebooks"] groups = ["notebooks", "trails", "trials"]
dependencies = [ dependencies = [
"attrs>=22.2.0", "attrs>=22.2.0",
"rpds-py>=0.7.0", "rpds-py>=0.7.0",
@ -2096,7 +2158,7 @@ name = "requests"
version = "2.31.0" version = "2.31.0"
requires_python = ">=3.7" requires_python = ">=3.7"
summary = "Python HTTP for Humans." summary = "Python HTTP for Humans."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
dependencies = [ dependencies = [
"certifi>=2017.4.17", "certifi>=2017.4.17",
"charset-normalizer<4,>=2", "charset-normalizer<4,>=2",
@ -2112,7 +2174,7 @@ files = [
name = "retrying" name = "retrying"
version = "1.3.4" version = "1.3.4"
summary = "Retrying" summary = "Retrying"
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"six>=1.7.0", "six>=1.7.0",
] ]
@ -2151,7 +2213,7 @@ name = "rpds-py"
version = "0.18.1" version = "0.18.1"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Python bindings to Rust's persistent data structures (rpds)" summary = "Python bindings to Rust's persistent data structures (rpds)"
groups = ["notebooks"] groups = ["notebooks", "trails", "trials"]
files = [ 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_10_12_x86_64.whl", hash = "sha256:6b5ff7e1d63a8281654b5e2896d7f08799378e594f09cf3674e832ecaf396ce8"},
{file = "rpds_py-0.18.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8927638a4d4137a289e41d0fd631551e89fa346d6dbcfc31ad627557d03ceb6d"}, {file = "rpds_py-0.18.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8927638a4d4137a289e41d0fd631551e89fa346d6dbcfc31ad627557d03ceb6d"},
@ -2302,12 +2364,29 @@ files = [
{file = "scikit_learn-1.4.2-cp312-cp312-win_amd64.whl", hash = "sha256:d762070980c17ba3e9a4a1e043ba0518ce4c55152032f1af0ca6f39b376b5928"}, {file = "scikit_learn-1.4.2-cp312-cp312-win_amd64.whl", hash = "sha256:d762070980c17ba3e9a4a1e043ba0518ce4c55152032f1af0ca6f39b376b5928"},
] ]
[[package]]
name = "scikit-network"
version = "0.32.1"
requires_python = ">=3.8"
summary = "Graph algorithms"
groups = ["trails", "trials"]
dependencies = [
"numpy>=1.22.4",
"scipy>=1.7.3",
]
files = [
{file = "scikit_network-0.32.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6228326cc5a813f4a7c031b64f1276d9cc1d5ccff082e62fb176f1e53ae2cc46"},
{file = "scikit_network-0.32.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d634aab1e379702134c877c8c4a6803b7d7ba4efc103198474b7e896ec37e242"},
{file = "scikit_network-0.32.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e32e247728815750b12b950279cae6b12041a0c4bf95d1accdd273b0c1a6ea1"},
{file = "scikit_network-0.32.1-cp311-cp311-win_amd64.whl", hash = "sha256:c7016dce37120aa527fcff4254985360f164306ed060c496a6cf296a6d0fd2c3"},
]
[[package]] [[package]]
name = "scipy" name = "scipy"
version = "1.13.0" version = "1.13.0"
requires_python = ">=3.9" requires_python = ">=3.9"
summary = "Fundamental algorithms for scientific computing in Python" summary = "Fundamental algorithms for scientific computing in Python"
groups = ["default"] groups = ["default", "trails", "trials"]
dependencies = [ dependencies = [
"numpy<2.3,>=1.22.4", "numpy<2.3,>=1.22.4",
] ]
@ -2364,7 +2443,7 @@ name = "setuptools"
version = "69.5.1" version = "69.5.1"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Easily download, build, install, upgrade, and uninstall Python packages" summary = "Easily download, build, install, upgrade, and uninstall Python packages"
groups = ["default", "trials"] groups = ["default"]
files = [ files = [
{file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"}, {file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"},
{file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"}, {file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"},
@ -2375,7 +2454,7 @@ name = "six"
version = "1.16.0" version = "1.16.0"
requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*" requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
summary = "Python 2 and 3 compatibility utilities" summary = "Python 2 and 3 compatibility utilities"
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks", "trails", "trials"]
files = [ files = [
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"}, {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"}, {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
@ -2635,7 +2714,7 @@ name = "tenacity"
version = "8.3.0" version = "8.3.0"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Retry code until it succeeds" summary = "Retry code until it succeeds"
groups = ["trials"] groups = ["default"]
files = [ files = [
{file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"}, {file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"},
{file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"}, {file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"},
@ -2790,6 +2869,17 @@ files = [
{file = "tokenizers-0.15.2.tar.gz", hash = "sha256:e6e9c6e019dd5484be5beafc775ae6c925f4c69a3487040ed09b45e13df2cb91"}, {file = "tokenizers-0.15.2.tar.gz", hash = "sha256:e6e9c6e019dd5484be5beafc775ae6c925f4c69a3487040ed09b45e13df2cb91"},
] ]
[[package]]
name = "toolz"
version = "0.12.1"
requires_python = ">=3.7"
summary = "List processing tools and functional utilities"
groups = ["trails", "trials"]
files = [
{file = "toolz-0.12.1-py3-none-any.whl", hash = "sha256:d22731364c07d72eea0a0ad45bafb2c2937ab6fd38a3507bf55eae8744aa7d85"},
{file = "toolz-0.12.1.tar.gz", hash = "sha256:ecca342664893f177a13dac0e6b41cbd8ac25a358e5f215316d43e2100224f4d"},
]
[[package]] [[package]]
name = "torch" name = "torch"
version = "2.3.0" version = "2.3.0"
@ -2941,7 +3031,7 @@ name = "typing-extensions"
version = "4.12.2" version = "4.12.2"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Backported and Experimental Type Hints for Python 3.8+" summary = "Backported and Experimental Type Hints for Python 3.8+"
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
files = [ files = [
{file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"}, {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"}, {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
@ -2952,7 +3042,7 @@ name = "tzdata"
version = "2024.1" version = "2024.1"
requires_python = ">=2" requires_python = ">=2"
summary = "Provider of IANA time zone data" summary = "Provider of IANA time zone data"
groups = ["default"] groups = ["default", "trails", "trials"]
files = [ files = [
{file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"}, {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
{file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"}, {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
@ -2974,7 +3064,7 @@ name = "urllib3"
version = "2.2.1" version = "2.2.1"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "HTTP library with thread-safe connection pooling, file post, and more." summary = "HTTP library with thread-safe connection pooling, file post, and more."
groups = ["default", "notebooks", "trials"] groups = ["default", "notebooks"]
files = [ files = [
{file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"}, {file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"},
{file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"}, {file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"},
@ -3063,7 +3153,7 @@ name = "werkzeug"
version = "3.0.3" version = "3.0.3"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "The comprehensive WSGI web application library." summary = "The comprehensive WSGI web application library."
groups = ["trials"] groups = ["default"]
dependencies = [ dependencies = [
"MarkupSafe>=2.1.1", "MarkupSafe>=2.1.1",
] ]
@ -3088,7 +3178,7 @@ name = "zipp"
version = "3.18.2" version = "3.18.2"
requires_python = ">=3.8" requires_python = ">=3.8"
summary = "Backport of pathlib-compatible object wrapper for zip files" summary = "Backport of pathlib-compatible object wrapper for zip files"
groups = ["trials"] groups = ["default"]
files = [ files = [
{file = "zipp-3.18.2-py3-none-any.whl", hash = "sha256:dce197b859eb796242b0622af1b8beb0a722d52aa2f57133ead08edd5bf5374e"}, {file = "zipp-3.18.2-py3-none-any.whl", hash = "sha256:dce197b859eb796242b0622af1b8beb0a722d52aa2f57133ead08edd5bf5374e"},
{file = "zipp-3.18.2.tar.gz", hash = "sha256:6278d9ddbcfb1f1089a88fde84481528b07b0e10474e09dcfe53dad4069fa059"}, {file = "zipp-3.18.2.tar.gz", hash = "sha256:6278d9ddbcfb1f1089a88fde84481528b07b0e10474e09dcfe53dad4069fa059"},

14
pyproject.toml
View File

@ -13,6 +13,9 @@ dependencies = [
"numpy>=1.26.4", "numpy>=1.26.4",
"pip>=24.0", "pip>=24.0",
"typing-extensions>=4.12.2", "typing-extensions>=4.12.2",
"plotly>=5.22.0",
"dash>=2.17.0",
"dash-cytoscape>=1.0.1",
] ]
requires-python = ">=3.11" requires-python = ">=3.11"
readme = "README.md" readme = "README.md"
@ -31,10 +34,13 @@ notebooks = [
"jupyterlab>=4.2.0", "jupyterlab>=4.2.0",
"ipywidgets>=8.1.2", "ipywidgets>=8.1.2",
] ]
trials = [ # Alph relies on Pygraphviz which again relies on Graphviz, to sucessfully build
"plotly>=5.22.0", # Pygraphviz the MSVC toolchain should be installed on the target system if it is Windows
"dash>=2.17.0", # (Linux not tested yet). The compiler needs additional information about the location of Graphviz
"dash-cytoscape>=1.0.1", # 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 = [
"alph[graphviz]>=0.4.10",
] ]
[tool.ruff] [tool.ruff]

6
scripts/analyse_dataset.py
View File

@ -30,11 +30,11 @@ from lang_main.types import (
) )
# ** build pipelines # ** build pipelines
pipe_merge = build_merge_duplicates_pipe()
pipe_target_feat = build_base_target_feature_pipe() pipe_target_feat = build_base_target_feature_pipe()
pipe_timeline = build_timeline_pipe() pipe_merge = build_merge_duplicates_pipe()
pipe_token_analysis = build_tk_graph_pipe() pipe_token_analysis = build_tk_graph_pipe()
pipe_graph_postprocessing = build_tk_graph_post_pipe() pipe_graph_postprocessing = build_tk_graph_post_pipe()
pipe_timeline = build_timeline_pipe()
# ** preprocessing pipeline # ** preprocessing pipeline
@ -76,8 +76,6 @@ def run_graph_postprocessing() -> None:
# filter graph by edge weight and remove single nodes (no connection) # filter graph by edge weight and remove single nodes (no connection)
ret = cast(tuple[TokenGraph], pipe_graph_postprocessing.run(starting_values=(tk_graph,))) ret = cast(tuple[TokenGraph], pipe_graph_postprocessing.run(starting_values=(tk_graph,)))
tk_graph_filtered = ret[0] tk_graph_filtered = ret[0]
# tk_graph_filtered = tk_graph.filter_by_edge_weight(THRESHOLD_EDGE_WEIGHT, None)
# tk_graph_filtered = tk_graph_filtered.filter_by_node_degree(1, None)
tk_graph_filtered.to_GraphML( tk_graph_filtered.to_GraphML(
SAVE_PATH_FOLDER, filename='TokenGraph-filtered', directed=False SAVE_PATH_FOLDER, filename='TokenGraph-filtered', directed=False
) )

16
scripts/dashboard/cyto.py
View File

@ -16,8 +16,8 @@ target = '../results/test_20240529/Pipe-Token_Analysis_Step-1_build_token_graph.
p = Path(target).resolve() p = Path(target).resolve()
ret = lang_main.io.load_pickle(p) ret = lang_main.io.load_pickle(p)
tk_graph = cast(graphs.TokenGraph, ret[0]) tk_graph = cast(graphs.TokenGraph, ret[0])
tk_graph_filtered = tk_graph.filter_by_edge_weight(150, None) tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, 150, None)
tk_graph_filtered = tk_graph_filtered.filter_by_node_degree(1, None) tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None)
cyto_data_base, weight_data = graphs.convert_graph_to_cytoscape(tk_graph_filtered) cyto_data_base, weight_data = graphs.convert_graph_to_cytoscape(tk_graph_filtered)
MIN_WEIGHT = weight_data['min'] MIN_WEIGHT = weight_data['min']
@ -235,8 +235,16 @@ def update_edge_weight(weight_min, weight_max):
weight_min = MIN_WEIGHT weight_min = MIN_WEIGHT
if weight_max is None: if weight_max is None:
weight_max = MAX_WEIGHT weight_max = MAX_WEIGHT
tk_graph_filtered = tk_graph.filter_by_edge_weight(weight_min, weight_max) tk_graph_filtered = graphs.filter_graph_by_edge_weight(
tk_graph_filtered = tk_graph_filtered.filter_by_node_degree(1, None) tk_graph,
weight_min,
weight_max,
)
tk_graph_filtered = graphs.filter_graph_by_node_degree(
tk_graph_filtered,
1,
None,
)
cyto_data, _ = graphs.convert_graph_to_cytoscape(tk_graph_filtered) cyto_data, _ = graphs.convert_graph_to_cytoscape(tk_graph_filtered)
return cyto_data return cyto_data

200
scripts/dashboard/timeline.py → scripts/dashboard/dash_timeline.py
View File

@ -2,10 +2,9 @@ import time
import webbrowser import webbrowser
from pathlib import Path from pathlib import Path
from threading import Thread from threading import Thread
from typing import cast from typing import Any, Final, cast
import dash_cytoscape as cyto import dash_cytoscape as cyto
import pandas as pd
import plotly.express as px import plotly.express as px
from dash import ( from dash import (
Dash, Dash,
@ -19,45 +18,33 @@ from dash import (
) )
from pandas import DataFrame from pandas import DataFrame
from lang_main.analysis import graphs import lang_main.io
from lang_main.io import load_pickle from lang_main.analysis import graphs, tokens
from lang_main.types import ObjectID, TimelineCandidates
from lang_main.analysis import tokens
from lang_main.constants import SPCY_MODEL from lang_main.constants import SPCY_MODEL
from lang_main.types import ObjectID, TimelineCandidates
# df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder_unfiltered.csv')
# ** data # ** data
# p_df = Path(r'../Pipe-TargetFeature_Step-3_remove_NA.pkl').resolve()
p_df = Path(r'../results/test_20240619/TIMELINE.pkl').resolve() p_df = Path(r'../results/test_20240619/TIMELINE.pkl').resolve()
# p_tl = Path(r'/Pipe-Timeline_Analysis_Step-4_get_timeline_candidates.pkl').resolve() (data,) = cast(tuple[DataFrame], lang_main.io.load_pickle(p_df))
p_tl = Path(r'../results/test_20240619/TIMELINE_POSTPROCESSING.pkl').resolve() p_tl = Path(r'../results/test_20240619/TIMELINE_POSTPROCESSING.pkl').resolve()
ret = cast(tuple[DataFrame], load_pickle(p_df)) cands, texts = cast(
data = ret[0] tuple[TimelineCandidates, dict[ObjectID, str]], lang_main.io.load_pickle(p_tl)
ret = cast(tuple[TimelineCandidates, dict[ObjectID, str]], load_pickle(p_tl)) )
cands = ret[0]
texts = ret[1]
# p_df = Path(r'.\test-notebooks\dashboard\data.pkl')
# p_cands = Path(r'.\test-notebooks\dashboard\map_candidates.pkl')
# p_map = Path(r'.\test-notebooks\dashboard\map_texts.pkl')
# data = cast(DataFrame, load_pickle(p_df))
# cands = cast(TimelineCandidates, load_pickle(p_cands))
# texts = cast(dict[ObjectID, str], load_pickle(p_map))
table_feats = [ TABLE_FEATS: Final[list[str]] = [
'ErstellungsDatum', 'ErstellungsDatum',
'ErledigungsDatum', 'ErledigungsDatum',
'VorgangsTypName', 'VorgangsTypName',
'VorgangsBeschreibung', 'VorgangsBeschreibung',
] ]
table_feats_dates = [ TABLE_FEATS_DATES: Final[list[str]] = [
'ErstellungsDatum', 'ErstellungsDatum',
'ErledigungsDatum', 'ErledigungsDatum',
] ]
# ** figure config # ** figure config
markers = { MARKERS: Final[dict[str, Any]] = {
'size': 12, 'size': 12,
'color': 'yellow', 'color': 'yellow',
'line': { 'line': {
@ -65,15 +52,15 @@ markers = {
'color': 'red', 'color': 'red',
}, },
} }
hover_data = { HOVER_DATA: Final[dict[str, Any]] = {
'ErstellungsDatum': '|%d.%m.%Y', 'ErstellungsDatum': '|%d.%m.%Y',
'VorgangsBeschreibung': True, 'VorgangsBeschreibung': True,
} }
# ** graphs # ** graph
target = '../results/test_20240529/Pipe-Token_Analysis_Step-1_build_token_graph.pkl' target = '../results/test_20240529/Pipe-Token_Analysis_Step-1_build_token_graph.pkl'
p = Path(target).resolve() p = Path(target).resolve()
ret = load_pickle(p) ret = lang_main.io.load_pickle(p)
tk_graph = cast(graphs.TokenGraph, ret[0]) tk_graph = cast(graphs.TokenGraph, ret[0])
tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, 150, None) tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, 150, None)
tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None) tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None)
@ -142,14 +129,12 @@ my_stylesheet = [
# {'selector': '.triangle', 'style': {'shape': 'triangle'}}, # {'selector': '.triangle', 'style': {'shape': 'triangle'}},
] ]
# ** app
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = Dash(__name__, external_stylesheets=external_stylesheets)
graph_layout = html.Div( graph_layout = html.Div(
[ [
html.Button('Trigger JS Weight', id='test_js_weight'), html.Button('Trigger JS Weight', id='test_js_weight'),
html.Button('Trigger Candidate Graph', id='cand_graph'), html.Button('Trigger Candidate Graph', id='graph-build-btn'),
dcc.Store(id='graph-store', storage_type='memory'),
dcc.Store(id='graph-store-cyto-curr_cands', storage_type='memory'),
html.Div(id='output'), html.Div(id='output'),
html.Div( html.Div(
[ [
@ -184,7 +169,7 @@ graph_layout = html.Div(
[ [
html.H3('Graph Filter'), html.H3('Graph Filter'),
dcc.Input( dcc.Input(
id='weight_min', id='graph-weight_min',
type='number', type='number',
min=MIN_WEIGHT, min=MIN_WEIGHT,
max=MAX_WEIGHT, max=MAX_WEIGHT,
@ -194,7 +179,7 @@ graph_layout = html.Div(
style={'width': '40%'}, style={'width': '40%'},
), ),
dcc.Input( dcc.Input(
id='weight_max', id='graph-weight_max',
type='number', type='number',
min=MIN_WEIGHT, min=MIN_WEIGHT,
max=MAX_WEIGHT, max=MAX_WEIGHT,
@ -204,7 +189,7 @@ graph_layout = html.Div(
style={'width': '40%'}, style={'width': '40%'},
), ),
html.H3('Graph'), html.H3('Graph'),
html.Button('Re-Layout', id='trigger_relayout'), html.Button('Re-Layout', id='graph-trigger_relayout'),
html.Div( html.Div(
[ [
cyto.Cytoscape( cyto.Cytoscape(
@ -230,6 +215,12 @@ graph_layout = html.Div(
], ],
) )
# ** app
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div( app.layout = html.Div(
[ [
html.H1(children='Demo Zeitreihenanalyse', style={'textAlign': 'center'}), html.H1(children='Demo Zeitreihenanalyse', style={'textAlign': 'center'}),
@ -238,16 +229,16 @@ app.layout = html.Div(
html.H2('Wählen Sie ein Objekt aus (ObjektID):'), html.H2('Wählen Sie ein Objekt aus (ObjektID):'),
dcc.Dropdown( dcc.Dropdown(
list(cands.keys()), list(cands.keys()),
id='dropdown-selection', id='selector-obj_id',
placeholder='ObjektID auswählen...', placeholder='ObjektID auswählen...',
), ),
] ]
), ),
html.Div( html.Div(
children=[ children=[
html.H3(id='object_text'), html.H3(id='object-text'),
dcc.Dropdown(id='choice-candidates'), dcc.Dropdown(id='selector-candidates'),
dcc.Graph(id='graph-output'), dcc.Graph(id='graph-candidates'),
] ]
), ),
html.Div( html.Div(
@ -260,8 +251,8 @@ app.layout = html.Div(
@callback( @callback(
Output('object_text', 'children'), Output('object-text', 'children'),
Input('dropdown-selection', 'value'), Input('selector-obj_id', 'value'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def update_obj_text(obj_id): def update_obj_text(obj_id):
@ -272,21 +263,24 @@ def update_obj_text(obj_id):
@callback( @callback(
Output('choice-candidates', 'options'), [Output('selector-candidates', 'options'), Output('selector-candidates', 'value')],
Input('dropdown-selection', 'value'), Input('selector-obj_id', 'value'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def update_choice_candidates(obj_id): def update_choice_candidates(obj_id):
obj_id = int(obj_id) obj_id = int(obj_id)
cands_obj_id = cands[obj_id] cands_obj_id = cands[obj_id]
choices = list(range(1, len(cands_obj_id) + 1)) choices = list(range(1, len(cands_obj_id) + 1))
return choices return choices, choices[0]
# TODO check possible storage of pre-filtered result
# TODO change input of ``update_table_candidates`` and ``display_candidates_as_graph``
# TODO to storage component
@callback( @callback(
Output('graph-output', 'figure'), Output('graph-candidates', 'figure'),
Input('choice-candidates', 'value'), Input('selector-candidates', 'value'),
State('dropdown-selection', 'value'), State('selector-obj_id', 'value'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def update_timeline(index, obj_id): def update_timeline(index, obj_id):
@ -295,19 +289,20 @@ def update_timeline(index, obj_id):
obj_text = texts[obj_id] obj_text = texts[obj_id]
title = f'HObjektText: {obj_text}' title = f'HObjektText: {obj_text}'
# cands # cands
cands_obj_id = cands[obj_id] # cands_per_obj_id = cands[obj_id]
cands_choice = cands_obj_id[int(index) - 1] # cands_similar = cands_per_obj_id[int(index) - 1]
# data # data
df = data.loc[list(cands_choice)].sort_index() # type: ignore # df = data.loc[list(cands_similar)].sort_index() # type: ignore
df = pre_filter_data(data, idx=index, obj_id=obj_id)
# figure # figure
fig = px.line( fig = px.line(
data_frame=df, data_frame=df,
x='ErstellungsDatum', x='ErstellungsDatum',
y='ObjektID', y='ObjektID',
title=title, title=title,
hover_data=hover_data, hover_data=HOVER_DATA,
) )
fig.update_traces(mode='markers+lines', marker=markers, marker_symbol='diamond') fig.update_traces(mode='markers+lines', marker=MARKERS, marker_symbol='diamond')
fig.update_xaxes( fig.update_xaxes(
tickformat='%B\n%Y', tickformat='%B\n%Y',
rangeslider_visible=True, rangeslider_visible=True,
@ -319,24 +314,18 @@ def update_timeline(index, obj_id):
@callback( @callback(
[Output('table-candidates', 'data'), Output('table-candidates', 'columns')], [Output('table-candidates', 'data'), Output('table-candidates', 'columns')],
Input('choice-candidates', 'value'), Input('selector-candidates', 'value'),
State('dropdown-selection', 'value'), State('selector-obj_id', 'value'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def update_table_candidates(index, obj_id): def update_table_candidates(index, obj_id):
# obj_id = int(obj_id)
# # cands
# cands_obj_id = cands[obj_id]
# cands_choice = cands_obj_id[int(index) - 1]
# # data
# df = data.loc[list(cands_choice)].sort_index() # type: ignore
df = pre_filter_data(data, idx=index, obj_id=obj_id) df = pre_filter_data(data, idx=index, obj_id=obj_id)
df = df.filter(items=table_feats, axis=1).sort_values( df = df.filter(items=TABLE_FEATS, axis=1).sort_values(
by='ErstellungsDatum', ascending=True by='ErstellungsDatum', ascending=True
) )
cols = [{'name': i, 'id': i} for i in df.columns] cols = [{'name': i, 'id': i} for i in df.columns]
# convert dates to strings # convert dates to strings
for col in table_feats_dates: for col in TABLE_FEATS_DATES:
df[col] = df[col].dt.strftime(r'%Y-%m-%d') df[col] = df[col].dt.strftime(r'%Y-%m-%d')
table_data = df.to_dict('records') table_data = df.to_dict('records')
@ -348,6 +337,7 @@ def pre_filter_data(
idx: int, idx: int,
obj_id: ObjectID, obj_id: ObjectID,
) -> DataFrame: ) -> DataFrame:
idx = int(idx)
obj_id = int(obj_id) obj_id = int(obj_id)
data = data.copy() data = data.copy()
# cands # cands
@ -359,33 +349,53 @@ def pre_filter_data(
return data return data
# ** graph # ** graph callbacks
# TODO store pre-calculated graph
@app.callback( @app.callback(
Output('cytoscape-graph', 'elements', allow_duplicate=True), Output('cytoscape-graph', 'elements', allow_duplicate=True),
Output('weight_min', 'min', allow_duplicate=True), Output('graph-weight_min', 'min', allow_duplicate=True),
Output('weight_min', 'max', allow_duplicate=True), Output('graph-weight_min', 'max', allow_duplicate=True),
Output('weight_min', 'placeholder', allow_duplicate=True), Output('graph-weight_min', 'placeholder', allow_duplicate=True),
Output('weight_max', 'min', allow_duplicate=True), Output('graph-weight_max', 'min', allow_duplicate=True),
Output('weight_max', 'max', allow_duplicate=True), Output('graph-weight_max', 'max', allow_duplicate=True),
Output('weight_max', 'placeholder', allow_duplicate=True), Output('graph-weight_max', 'placeholder', allow_duplicate=True),
Input('cand_graph', 'n_clicks'), Output('graph-store', 'data'),
State('choice-candidates', 'value'), Output('graph-store-cyto-curr_cands', 'data'),
State('dropdown-selection', 'value'), # Input('graph-build-btn', 'n_clicks'),
Input('selector-candidates', 'value'),
State('selector-obj_id', 'value'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def update_graph_candidates(_, index, obj_id): def display_candidates_as_graph(index, obj_id):
t1 = time.perf_counter()
df = pre_filter_data(data, idx=index, obj_id=obj_id) df = pre_filter_data(data, idx=index, obj_id=obj_id)
t2 = time.perf_counter()
print(f'Time for filtering: {t2 - t1} s')
t1 = time.perf_counter()
tk_graph_cands, _ = tokens.build_token_graph( tk_graph_cands, _ = tokens.build_token_graph(
data=df, data=df,
model=SPCY_MODEL, model=SPCY_MODEL,
target_feature='VorgangsBeschreibung', target_feature='VorgangsBeschreibung',
build_map=False, build_map=False,
logging_graph=False,
) )
t2 = time.perf_counter()
print(f'Time for graph building: {t2 - t1} s')
t1 = time.perf_counter()
cyto_data, weight_info = graphs.convert_graph_to_cytoscape(tk_graph_cands) cyto_data, weight_info = graphs.convert_graph_to_cytoscape(tk_graph_cands)
weight_min = weight_info['min'] weight_min = weight_info['min']
weight_max = weight_info['max'] weight_max = weight_info['max']
placeholder_min = f'Minimum edge weight: {weight_min} - {weight_max}' placeholder_min = f'Minimum edge weight: {weight_min} - {weight_max}'
placeholder_max = f'Minimum edge weight: {weight_min} - {weight_max}' placeholder_max = f'Maximum edge weight: {weight_min} - {weight_max}'
t2 = time.perf_counter()
print(f'Time for graph metadata and conversion: {t2 - t1} s')
t1 = time.perf_counter()
graph_to_store = lang_main.io.encode_to_base64_str(tk_graph_cands)
t2 = time.perf_counter()
print(f'Time for encoding: {t2 - t1} s')
return ( return (
cyto_data, cyto_data,
weight_min, weight_min,
@ -394,6 +404,8 @@ def update_graph_candidates(_, index, obj_id):
weight_min, weight_min,
weight_max, weight_max,
placeholder_max, placeholder_max,
graph_to_store,
cyto_data,
) )
@ -412,30 +424,44 @@ def update_layout_internal(layout_choice):
@app.callback( @app.callback(
Output('cytoscape-graph', 'zoom'), Output('cytoscape-graph', 'zoom'),
Output('cytoscape-graph', 'elements', allow_duplicate=True), Output('cytoscape-graph', 'elements', allow_duplicate=True),
Output('weight_min', 'value'), Output('graph-weight_min', 'value'),
Output('weight_max', 'value'), Output('graph-weight_max', 'value'),
Input('bt-reset', 'n_clicks'), Input('bt-reset', 'n_clicks'),
State('graph-store-cyto-curr_cands', 'data'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def reset_layout(n_clicks): def reset_layout(_, current_cands_cyto_elements):
return (1, cyto_data_base, None, None) return (1, current_cands_cyto_elements, None, None)
# update edge weight # update edge weight
@app.callback( @app.callback(
Output('cytoscape-graph', 'elements', allow_duplicate=True), Output('cytoscape-graph', 'elements', allow_duplicate=True),
Input('weight_min', 'value'), Input('graph-weight_min', 'value'),
Input('weight_max', 'value'), Input('graph-weight_max', 'value'),
State('graph-store', 'data'),
State('graph-store-cyto-curr_cands', 'data'),
State('graph-weight_min', 'min'),
State('graph-weight_min', 'max'),
prevent_initial_call=True, prevent_initial_call=True,
) )
def update_edge_weight(weight_min, weight_max): def update_edge_weight(
if not any([weight_min, weight_max]): weight_min,
return cyto_data_base weight_max,
current_graph,
current_cands_cyto_elements,
current_min,
current_max,
):
if not any((weight_min, weight_max)):
return current_cands_cyto_elements
if weight_min is None: if weight_min is None:
weight_min = MIN_WEIGHT weight_min = current_min
if weight_max is None: if weight_max is None:
weight_max = MAX_WEIGHT weight_max = current_max
tk_graph = cast(graphs.TokenGraph, lang_main.io.decode_from_base64_str(current_graph))
tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, weight_min, weight_max) tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, weight_min, weight_max)
# tk_graph_filtered = tk_graph.filter_by_edge_weight(weight_min, weight_max) # tk_graph_filtered = tk_graph.filter_by_edge_weight(weight_min, weight_max)
tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None) tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None)
@ -444,6 +470,7 @@ def update_edge_weight(weight_min, weight_max):
return cyto_data return cyto_data
# ** graph: layout with edge weight
app.clientside_callback( app.clientside_callback(
""" """
function(n_clicks, layout) { function(n_clicks, layout) {
@ -458,11 +485,12 @@ app.clientside_callback(
} }
""", """,
Output('cytoscape-graph', 'layout', allow_duplicate=True), Output('cytoscape-graph', 'layout', allow_duplicate=True),
Input('trigger_relayout', 'n_clicks'), Input('graph-trigger_relayout', 'n_clicks'),
State('cytoscape-graph', 'layout'), State('cytoscape-graph', 'layout'),
prevent_initial_call=True, prevent_initial_call=True,
) )
# ** graph: display edge weight (line thickness)
app.clientside_callback( app.clientside_callback(
""" """
function(n_clicks, stylesheet) { function(n_clicks, stylesheet) {

7
src/lang_main/__init__.py
View File

@ -1,4 +1,5 @@
import logging import logging
import os
import shutil import shutil
import sys import sys
from pathlib import Path from pathlib import Path
@ -41,3 +42,9 @@ else:
loaded_cfg = load_toml_config(path_to_toml=cfg_path_external) loaded_cfg = load_toml_config(path_to_toml=cfg_path_external)
CONFIG: Final[dict[str, Any]] = loaded_cfg.copy() CONFIG: Final[dict[str, Any]] = loaded_cfg.copy()
# append Graphviz binary folder to system path if not already contained
if sys.platform == 'win32':
path = Path(r'C:\Program Files\Graphviz\bin')
if path.is_dir() and str(path).lower() not in os.environ['PATH'].lower():
os.environ['PATH'] += f';{path}'

15
src/lang_main/analysis/graphs.py
View File

@ -164,6 +164,9 @@ def convert_graph_to_cytoscape(
} }
cyto_data.append(edge_data) cyto_data.append(edge_data)
min_weight: int = 0
max_weight: int = 0
if weights:
min_weight = min(weights) min_weight = min(weights)
max_weight = max(weights) max_weight = max(weights)
weight_metadata: WeightData = {'min': min_weight, 'max': max_weight} weight_metadata: WeightData = {'min': min_weight, 'max': max_weight}
@ -284,6 +287,9 @@ class TokenGraph(DiGraph):
f'{len(self.edges)})' f'{len(self.edges)})'
) )
def disable_logging(self) -> None:
self.logging = False
# !! only used to verify that saving was done correctly # !! only used to verify that saving was done correctly
""" """
def __key(self) -> tuple[Hashable, ...]: def __key(self) -> tuple[Hashable, ...]:
@ -337,16 +343,9 @@ class TokenGraph(DiGraph):
logging: bool | None = ..., logging: bool | None = ...,
) -> Graph: ... ) -> Graph: ...
@overload
def to_undirected( def to_undirected(
self, self,
inplace: bool = ..., inplace: bool = True,
logging: bool | None = ...,
) -> Graph | None: ...
def to_undirected(
self,
inplace=True,
logging: bool | None = None, logging: bool | None = None,
) -> Graph | None: ) -> Graph | None:
if logging is None: if logging is None:

22
src/lang_main/analysis/tokens.py
View File

@ -21,7 +21,8 @@ from lang_main.types import PandasIndex
# POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN', 'ADJ', 'VERB', 'AUX']) # POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN', 'ADJ', 'VERB', 'AUX'])
# POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'ADJ', 'VERB', 'AUX']) # POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'ADJ', 'VERB', 'AUX'])
# POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN']) # POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN'])
POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN', 'VERB', 'AUX']) # POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN', 'VERB', 'AUX'])
POS_OF_INTEREST: frozenset[str] = frozenset(['NOUN', 'PROPN', 'VERB', 'AUX', 'ADV'])
# POS_INDIRECT: frozenset[str] = frozenset(['AUX', 'VERB']) # POS_INDIRECT: frozenset[str] = frozenset(['AUX', 'VERB'])
POS_INDIRECT: frozenset[str] = frozenset(['AUX']) POS_INDIRECT: frozenset[str] = frozenset(['AUX'])
@ -153,6 +154,7 @@ def build_token_graph(
batch_idx_feature: str = ..., batch_idx_feature: str = ...,
build_map: Literal[False], build_map: Literal[False],
batch_size_model: int = ..., batch_size_model: int = ...,
logging_graph: bool = ...,
) -> tuple[TokenGraph, None]: ... ) -> tuple[TokenGraph, None]: ...
@ -166,6 +168,7 @@ def build_token_graph(
batch_idx_feature: str = ..., batch_idx_feature: str = ...,
build_map: Literal[True] = ..., build_map: Literal[True] = ...,
batch_size_model: int = ..., batch_size_model: int = ...,
logging_graph: bool = ...,
) -> tuple[TokenGraph, dict[PandasIndex, SpacyDoc]]: ... ) -> tuple[TokenGraph, dict[PandasIndex, SpacyDoc]]: ...
@ -175,11 +178,12 @@ def build_token_graph(
*, *,
target_feature: str = 'entry', target_feature: str = 'entry',
weights_feature: str | None = None, weights_feature: str | None = None,
batch_idx_feature: str = 'batched_idxs', batch_idx_feature: str | None = 'batched_idxs',
build_map: bool = True, build_map: bool = True,
batch_size_model: int = 50, batch_size_model: int = 50,
logging_graph: bool = True,
) -> tuple[TokenGraph, dict[PandasIndex, SpacyDoc] | None]: ) -> tuple[TokenGraph, dict[PandasIndex, SpacyDoc] | None]:
graph = TokenGraph() graph = TokenGraph(enable_logging=logging_graph)
model_input = cast(tuple[str], tuple(data[target_feature].to_list())) model_input = cast(tuple[str], tuple(data[target_feature].to_list()))
if weights_feature is not None: if weights_feature is not None:
weights = cast(tuple[int], tuple(data[weights_feature].to_list())) weights = cast(tuple[int], tuple(data[weights_feature].to_list()))
@ -187,7 +191,9 @@ def build_token_graph(
weights = None weights = None
docs_mapping: dict[PandasIndex, SpacyDoc] | None docs_mapping: dict[PandasIndex, SpacyDoc] | None
if build_map: if build_map and batch_idx_feature is None:
raise ValueError('Can not build mapping if batched indices are unknown.')
elif build_map:
indices = cast(tuple[list[PandasIndex]], tuple(data[batch_idx_feature].to_list())) indices = cast(tuple[list[PandasIndex]], tuple(data[batch_idx_feature].to_list()))
docs_mapping = {} docs_mapping = {}
else: else:
@ -199,10 +205,10 @@ def build_token_graph(
for doc in tqdm( for doc in tqdm(
model.pipe(model_input, batch_size=batch_size_model), total=len(model_input) model.pipe(model_input, batch_size=batch_size_model), total=len(model_input)
): ):
weight: int | None = None
if weights is not None: if weights is not None:
weight = weights[index] weight = weights[index]
else:
weight = None
add_doc_info_to_graph( add_doc_info_to_graph(
graph=graph, graph=graph,
doc=doc, doc=doc,
@ -219,7 +225,7 @@ def build_token_graph(
# metadata # metadata
graph.update_metadata() graph.update_metadata()
# convert to undirected # convert to undirected
graph.to_undirected() graph.to_undirected(logging=False)
return graph, docs_mapping return graph, docs_mapping
@ -250,7 +256,7 @@ def build_token_graph_simple(
# metadata # metadata
graph.update_metadata() graph.update_metadata()
# convert to undirected # convert to undirected
graph.to_undirected() graph.to_undirected(logging=False)
return graph, docs_mapping return graph, docs_mapping

19
src/lang_main/io.py
View File

@ -1,4 +1,5 @@
import pickle import pickle
import base64
import shutil import shutil
import tomllib import tomllib
from pathlib import Path from pathlib import Path
@ -61,6 +62,24 @@ def load_pickle(
return obj return obj
def encode_to_base64_str(
obj: Any,
encoding: str = 'utf-8',
) -> str:
serialised = pickle.dumps(obj, protocol=pickle.HIGHEST_PROTOCOL)
b64_bytes = base64.b64encode(serialised)
return b64_bytes.decode(encoding=encoding)
def decode_from_base64_str(
b64_str: str,
encoding: str = 'utf-8',
) -> Any:
b64_bytes = b64_str.encode(encoding=encoding)
decoded = base64.b64decode(b64_bytes)
return pickle.loads(decoded)
def get_entry_point( def get_entry_point(
saving_path: Path, saving_path: Path,
filename: str, filename: str,

15
src/lang_main/pipelines/base.py
View File

@ -97,6 +97,18 @@ class BasePipeline(ABC):
class PipelineContainer(BasePipeline): class PipelineContainer(BasePipeline):
"""Container class for basic actions.
Basic actions are usually functions, which do not take any parameters
and return nothing. Indeed, if an action returns any values after its
procedure is finished, an error is raised. Therefore, PipelineContainers
can be seen as a concatenation of many (independent) simple procedures
which are executed in the order in which they were added to the pipe.
With a simple call of the ``run`` method the actions are performed.
Additionally, there is an option to skip actions which can be set in
the ``add`` method. This allows for easily configurable pipelines,
e.g., via a user configuration.
"""
def __init__( def __init__(
self, self,
name: str, name: str,
@ -169,9 +181,6 @@ class Pipeline(BasePipeline):
f'working dir: {self.working_dir}, contents: {self.action_names})' f'working dir: {self.working_dir}, contents: {self.action_names})'
) )
# @property
# def intermediate_result(self) -> tuple[Any, ...] | None:
# return self._intermediate_result
@override @override
def add( def add(
self, self,

1761
test-notebooks/misc.ipynb
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