added gitignore
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.gitignore
vendored
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160
.gitignore
vendored
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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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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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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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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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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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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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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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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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@ -21,10 +21,17 @@ def eval_data(file):
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ax2.plot(percentage, o)
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ax2.plot([0, 1], [o[0], o[-1]], "k:")
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ax.set_title(lab)
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title = ""
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if "ising" in file:
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fig.suptitle("Ising")
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title += "Ising "
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else:
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fig.suptitle("Random")
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title += "Random "
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if "rect" in file:
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title += "rect "
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if "voro" in file:
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title += "voro "
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fig.suptitle(title)
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fig.savefig(f"{file}.png")
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@ -47,31 +54,36 @@ def parse_lists(out):
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def eval_data_print(file):
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data = np.load(file, allow_pickle=True)
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percentage = data["percentage"]
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out = parse_lists(data["out"])
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out = np.array(out)
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print(out.shape)
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out = out[[0, 2], :, :]
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print(out.shape)
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fig, all_axs = plt.subplots(2, out.shape[0])
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#out = parse_lists(data["out"])
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out = []
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for o in ["out_1","out_2","out_3","out_4"]:
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out.append(np.array(data[o]))
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fig, all_axs = plt.subplots(2, len(out))
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axs = all_axs[0, :]
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axs2 = all_axs[1, :]
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for o, ax, ax2, lab in zip(out, axs, axs2, ["rutile", "monoclinic", "mono"]):
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for o, ax, ax2, lab in zip(out, axs, axs2, ["rutile", "monoclinic", "mono", "rest"]):
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# ax.plot(percentage, o/np.max(o, axis=0))
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ax.plot(percentage, o/o[0])
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# ax.plot(percentage, o)
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o = np.mean(o, axis=1)
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o = o/o[0]
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#o = o/o[0]
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ax2.plot(percentage, o)
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ax2.plot([0, 1], [o[0], o[-1]], "k:")
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ax.set_title(lab)
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if "ising" in file:
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fig.suptitle("Ising")
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else:
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fig.suptitle("Random")
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for ax in all_axs.flatten():
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ax.set_xlabel("Rutile Phase")
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ax.set_ylabel("Normalized Intensity")
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title = ""
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if "ising" in file:
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title += "Ising "
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else:
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title += "Random "
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if "rect" in file:
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title += "rect "
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if "voro" in file:
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title += "voro "
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fig.suptitle(title)
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plt.tight_layout()
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