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.gitignore
vendored
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244
.gitignore
vendored
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# Created by https://www.gitignore.io/api/python,pycharm,pycharm+all,pycharm+iml
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### PyCharm ###
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# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and Webstorm
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# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
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# User-specific stuff:
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.idea/**/workspace.xml
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.idea/**/tasks.xml
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.idea/dictionaries
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# Sensitive or high-churn files:
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.idea/**/dataSources/
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.idea/**/dataSources.ids
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.idea/**/dataSources.xml
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.idea/**/dataSources.local.xml
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.idea/**/sqlDataSources.xml
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.idea/**/dynamic.xml
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.idea/**/uiDesigner.xml
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# Gradle:
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.idea/**/gradle.xml
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.idea/**/libraries
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# CMake
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cmake-build-debug/
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# Mongo Explorer plugin:
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.idea/**/mongoSettings.xml
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## File-based project format:
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*.iws
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## Plugin-specific files:
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# IntelliJ
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/out/
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# mpeltonen/sbt-idea plugin
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.idea_modules/
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# JIRA plugin
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atlassian-ide-plugin.xml
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# Cursive Clojure plugin
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.idea/replstate.xml
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# Ruby plugin and RubyMine
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/.rakeTasks
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# Crashlytics plugin (for Android Studio and IntelliJ)
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com_crashlytics_export_strings.xml
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crashlytics.properties
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crashlytics-build.properties
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fabric.properties
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### PyCharm Patch ###
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# Comment Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-215987721
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# *.iml
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# modules.xml
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# .idea/misc.xml
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# *.ipr
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# Sonarlint plugin
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.idea/sonarlint
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### PyCharm+all ###
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# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and Webstorm
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# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
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# User-specific stuff:
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# Sensitive or high-churn files:
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# Gradle:
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# CMake
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# Mongo Explorer plugin:
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## File-based project format:
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## Plugin-specific files:
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# IntelliJ
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# mpeltonen/sbt-idea plugin
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# JIRA plugin
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# Cursive Clojure plugin
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# Ruby plugin and RubyMine
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# Crashlytics plugin (for Android Studio and IntelliJ)
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### PyCharm+all Patch ###
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# Ignores the whole idea folder
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# See https://github.com/joeblau/gitignore.io/issues/186 and https://github.com/joeblau/gitignore.io/issues/360
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.idea/
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### PyCharm+iml ###
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# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and Webstorm
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# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
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# User-specific stuff:
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# Sensitive or high-churn files:
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# Gradle:
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# CMake
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# Mongo Explorer plugin:
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## File-based project format:
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## Plugin-specific files:
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# IntelliJ
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# mpeltonen/sbt-idea plugin
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# JIRA plugin
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# Cursive Clojure plugin
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# Ruby plugin and RubyMine
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# Crashlytics plugin (for Android Studio and IntelliJ)
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### PyCharm+iml Patch ###
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# Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-249601023
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*.iml
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modules.xml
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.idea/misc.xml
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*.ipr
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### Python ###
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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.pytest_cache/
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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# Translations
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*.mo
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*.pot
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule.*
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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# End of https://www.gitignore.io/api/python,pycharm,pycharm+all,pycharm+iml
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@ -375,5 +375,4 @@ size: 536870912, step: 8388608 and time Elapsed: 70 milliseconds
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size: 536870912, step: 16777216 and time Elapsed: 48 milliseconds
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size: 536870912, step: 33554432 and time Elapsed: 93 milliseconds
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size: 536870912, step: 67108864 and time Elapsed: 71 milliseconds
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size: 536870912, step: 134217728 and time Elapsed: 78 milliseconds
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size: 536870912, step: 134217728 and time Elapsed: 78 milliseconds
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BIN
heatmap.png
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BIN
heatmap.png
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After Width: | Height: | Size: 37 KiB |
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plotter.py
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plotter.py
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import subprocess
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import tempfile
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import re
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import matplotlib.pyplot as plt
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from collections import defaultdict
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import argparse
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from math import log2
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import pandas as pd
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parser = argparse.ArgumentParser(description='Read data from a data file and plot this.')
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parser.add_argument('--data_file', action='store', dest='data_file', default='plot_data.txt',
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help='The desired data to be plotted.')
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parser.add_argument('--static_n', action='store_true',
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help="Is the n variable static in the data file?")
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parser.add_argument('--static_step', action='store_true',
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help="Is the step variable static in the data file?")
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args = parser.parse_args()
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data = open(args.data_file).read()
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# d = {'static variable' : {step : time, step : time}}
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def prep_data(static_var, data):
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non_static_var = (static_var + 1) % 2 # if 0 then 1, if 1 then 0
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#non_static_var = 1 - static_var #rip :(
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lines = data.split('\n')
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static_vars = set()
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data = defaultdict(dict)
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for line in lines[0:-1]:
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all_vars = re.findall(r"\d+", line)
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static = int(all_vars[static_var])
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non_static = int(all_vars[non_static_var])
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time = int(all_vars[2])
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static_vars.add(static)
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data[static][non_static] = time
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return data
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static_var = 0 if args.static_n else 1
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plot_data = prep_data(static_var, data)
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df = pd.DataFrame(data=plot_data)
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print(df)
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plt.imshow(df, cmap='hot')
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plt.show()
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#first = plot_data[list(plot_data.keys())[2]]
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#plt.plot(first[0], first[1])
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#for static, plotting_data in plot_data.items():
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# x_axis = [log2(x) for x in plotting_data[0]]
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# plt.plot(x_axis, plotting_data[1], marker="o", label = static)
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#plt.xticks([2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26], ["$log2(2^2)$", "log2(2^4)", "log2(2^6)", "log2(2^8)", "log2(2^10)", "log2(2^12)", "log2(2^14)", "log2(2^16)", "log2(2^18)", "log2(2^20)", "log2(2^22)", "log2(2^24)", "log2(2^26)"])
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#plt.legend(loc=1, borderaxespad=0.)
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#plt.ylabel('time/ms')
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#plt.xlabel('log(step)')
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#plt.show()
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import math
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import subprocess
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import tempfile
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import re
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import matplotlib.pyplot as plt
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from collections import defaultdict
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import argparse
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from math import log2
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import pandas as pd
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import seaborn as sns
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parser = argparse.ArgumentParser(description='Read data from a data file and plot this.')
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parser.add_argument('--data_file', action='store', dest='data_file', default='plot_data.txt',
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help='The desired data to be plotted.')
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parser.add_argument('--static_n', action='store_true',
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help="Is the n variable static in the data file?")
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parser.add_argument('--static_step', action='store_true',
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help="Is the step variable static in the data file?")
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args = parser.parse_args()
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data = open(args.data_file).read()
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# d = {'static variable' : {step : time, step : time}}
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def prep_data(static_var, data):
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non_static_var = (static_var + 1) % 2 # if 0 then 1, if 1 then 0
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#non_static_var = 1 - static_var #rip :(
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lines = data.split('\n')
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static_vars = set()
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data = defaultdict(dict)
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for line in lines[0:-1]:
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all_vars = re.findall(r"\d+", line)
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static = int(all_vars[static_var])
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non_static = int(all_vars[non_static_var])
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time = int(all_vars[2])
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static_vars.add(static)
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data[static][non_static] = time
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return data
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static_var = 0 if args.static_n else 1
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plot_data = prep_data(static_var, data)
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df = pd.DataFrame(data=plot_data)
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print(df)
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hm = sns.heatmap(df, annot=False, square=False, cmap=sns.cm.rocket_r)
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hm.invert_yaxis()
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# fix xtics
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locs, labels = plt.xticks()
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plt.xticks(locs, [f"$2^{{{int(math.log2(int(i.get_text())))}}}$" for i in labels])
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locs, labels = plt.yticks()
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plt.yticks(locs, [f"$2^{{{int(math.log2(int(i.get_text())))}}}$" for i in labels])
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plt.show()
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#first = plot_data[list(plot_data.keys())[2]]
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#plt.plot(first[0], first[1])
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#for static, plotting_data in plot_data.items():
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# x_axis = [log2(x) for x in plotting_data[0]]
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# plt.plot(x_axis, plotting_data[1], marker="o", label = static)
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#plt.xticks([2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26], ["$log2(2^2)$", "log2(2^4)", "log2(2^6)", "log2(2^8)", "log2(2^10)", "log2(2^12)", "log2(2^14)", "log2(2^16)", "log2(2^18)", "log2(2^20)", "log2(2^22)", "log2(2^24)", "log2(2^26)"])
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#plt.legend(loc=1, borderaxespad=0.)
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#plt.ylabel('time/ms')
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#plt.xlabel('log(step)')
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#plt.show()
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