├── .coverage
├── .coverage_report.txt
├── .gitignore
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── Dockerfile
├── LICENSE.txt
├── MANIFEST
├── README.md
├── docker-entrypoint.sh
├── docs
    ├── .buildinfo
    ├── .doctrees
    │   ├── environment.pickle
    │   ├── index.doctree
    │   ├── lcc.bin.doctree
    │   ├── lcc.cli.doctree
    │   ├── lcc.data_manager.doctree
    │   ├── lcc.db_tier.connectors.doctree
    │   ├── lcc.db_tier.doctree
    │   ├── lcc.doctree
    │   ├── lcc.entities.doctree
    │   ├── lcc.stars_processing.deciders.doctree
    │   ├── lcc.stars_processing.deciders.unsupervised.doctree
    │   ├── lcc.stars_processing.descriptors.doctree
    │   ├── lcc.stars_processing.doctree
    │   ├── lcc.stars_processing.systematic_search.doctree
    │   ├── lcc.stars_processing.tools.doctree
    │   ├── lcc.stars_processing.utilities.doctree
    │   ├── lcc.utils.doctree
    │   └── modules.doctree
    ├── _sources
    │   ├── index.txt
    │   ├── lcc.bin.txt
    │   ├── lcc.cli.txt
    │   ├── lcc.data_manager.txt
    │   ├── lcc.db_tier.connectors.txt
    │   ├── lcc.db_tier.txt
    │   ├── lcc.entities.txt
    │   ├── lcc.stars_processing.deciders.txt
    │   ├── lcc.stars_processing.deciders.unsupervised.txt
    │   ├── lcc.stars_processing.descriptors.txt
    │   ├── lcc.stars_processing.systematic_search.txt
    │   ├── lcc.stars_processing.tools.txt
    │   ├── lcc.stars_processing.txt
    │   ├── lcc.stars_processing.utilities.txt
    │   ├── lcc.txt
    │   ├── lcc.utils.txt
    │   └── modules.txt
    ├── genindex.html
    ├── index.html
    ├── lcc.bin.html
    ├── lcc.cli.html
    ├── lcc.data_manager.html
    ├── lcc.db_tier.connectors.html
    ├── lcc.db_tier.html
    ├── lcc.entities.html
    ├── lcc.html
    ├── lcc.stars_processing.deciders.html
    ├── lcc.stars_processing.deciders.unsupervised.html
    ├── lcc.stars_processing.descriptors.html
    ├── lcc.stars_processing.html
    ├── lcc.stars_processing.systematic_search.html
    ├── lcc.stars_processing.tools.html
    ├── lcc.stars_processing.utilities.html
    ├── lcc.utils.html
    ├── modules.html
    ├── objects.inv
    ├── py-modindex.html
    ├── search.html
    └── searchindex.js
├── example_notebooks
    ├── compl_procedure.ipynb
    └── create_star_example.ipynb
├── lcc
    ├── __init__.py
    ├── bin
    │   ├── __init__.py
    │   ├── create_project.py
    │   ├── filter_stars.py
    │   ├── make_filter.py
    │   ├── plot_lcs.py
    │   └── prepare_query.py
    ├── cli
    │   ├── __init__.py
    │   ├── input_parse.py
    │   ├── lcc.py
    │   └── stars_handling.py
    ├── data_manager
    │   ├── __init__.py
    │   ├── filter_serializer.py
    │   ├── package_reader.py
    │   ├── prepare_package.py
    │   └── status_resolver.py
    ├── db_tier
    │   ├── TAP_query.py
    │   ├── __init__.py
    │   ├── base_query.py
    │   ├── connectors
    │   │   ├── __init__.py
    │   │   ├── asas.py
    │   │   ├── catalina.py
    │   │   ├── corot.py
    │   │   ├── file_manager.py
    │   │   ├── kepler.py
    │   │   ├── macho.py
    │   │   ├── ogleII.py
    │   │   └── ogleIII.py
    │   ├── stars_provider.py
    │   └── vizier_tap_base.py
    ├── entities
    │   ├── __init__.py
    │   ├── exceptions.py
    │   ├── light_curve.py
    │   └── star.py
    ├── examples
    │   ├── download_from_ogle.sh
    │   ├── examples_data
    │   │   └── light_curves
    │   │   │   ├── cepheids
    │   │   │       ├── LMC_SC1237629.dat
    │   │   │       ├── LMC_SC1242626.dat
    │   │   │       ├── LMC_SC1246999.dat
    │   │   │       ├── LMC_SC1247109.dat
    │   │   │       ├── LMC_SC127813.dat
    │   │   │       ├── LMC_SC1312.dat
    │   │   │       ├── LMC_SC1335127.dat
    │   │   │       ├── LMC_SC1340244.dat
    │   │   │       ├── LMC_SC1340265.dat
    │   │   │       ├── LMC_SC143442.dat
    │   │   │       ├── LMC_SC147198.dat
    │   │   │       └── LMC_SC1510.dat
    │   │   │   ├── quasars
    │   │   │       ├── LMC_SC109749.dat
    │   │   │       ├── LMC_SC1178697.dat
    │   │   │       ├── LMC_SC1184977.dat
    │   │   │       ├── LMC_SC1202485.dat
    │   │   │       ├── LMC_SC1215149.dat
    │   │   │       ├── LMC_SC123554.dat
    │   │   │       ├── LMC_SC1327328.dat
    │   │   │       ├── LMC_SC144736.dat
    │   │   │       ├── LMC_SC15399.dat
    │   │   │       ├── LMC_SC320480.dat
    │   │   │       ├── LMC_SC586317.dat
    │   │   │       └── LMC_SC91184.dat
    │   │   │   └── some_stars
    │   │   │       ├── LMC_SC224102.dat
    │   │   │       ├── LMC_SC225216.dat
    │   │   │       ├── LMC_SC225241.dat
    │   │   │       ├── LMC_SC227079.dat
    │   │   │       ├── LMC_SC227090.dat
    │   │   │       ├── LMC_SC227101.dat
    │   │   │       ├── LMC_SC230096.dat
    │   │   │       ├── LMC_SC230116.dat
    │   │   │       ├── LMC_SC230149.dat
    │   │   │       ├── LMC_SC231361.dat
    │   │   │       ├── LMC_SC231388.dat
    │   │   │       └── LMC_SC231401.dat
    │   ├── filter_folders_by_abbefilter.sh
    │   ├── filter_ogle_by_histvario.sh
    │   ├── prepare_query_folders.sh
    │   ├── prepare_query_ogle.sh
    │   ├── prepare_tuning_abbe_filter.sh
    │   ├── prepare_tuning_color_filter.sh
    │   ├── prepare_tuning_color_filter2.sh
    │   ├── prepare_tuning_histvario_filter.sh
    │   ├── tune_abbe_filter_from_folders.sh
    │   ├── tune_from_local_db.sh
    │   ├── tune_histvario_filter_from_folders.sh
    │   └── tune_histvario_filter_from_ogle.sh
    ├── stars_processing
    │   ├── __init__.py
    │   ├── deciders
    │   │   ├── __init__.py
    │   │   ├── custom_decider.py
    │   │   ├── neuron_decider.py
    │   │   ├── supervised_deciders.py
    │   │   └── unsupervised
    │   │   │   ├── __init__.py
    │   │   │   └── k_means_decider.py
    │   ├── descriptors
    │   │   ├── __init__.py
    │   │   ├── abbe_value_descr.py
    │   │   ├── color_index_descr.py
    │   │   ├── curve_density_descr.py
    │   │   ├── curve_descr.py
    │   │   ├── curves_shape_descr.py
    │   │   ├── hist_shape_descr.py
    │   │   ├── kurtosis_desc.py
    │   │   ├── position_descriptor.py
    │   │   ├── property_desc.py
    │   │   ├── skewness_desc.py
    │   │   ├── variogram_shape_descr.py
    │   │   └── variogram_slope_descr.py
    │   ├── stars_filter.py
    │   ├── stars_filter.pyc
    │   ├── systematic_search
    │   │   ├── __init__.py
    │   │   ├── stars_searcher.py
    │   │   └── worker.py
    │   ├── tools
    │   │   ├── __init__.py
    │   │   ├── params_estim.py
    │   │   ├── stats_manager.py
    │   │   └── visualization.py
    │   └── utilities
    │   │   ├── __init__.py
    │   │   ├── base_decider.py
    │   │   ├── base_descriptor.py
    │   │   ├── compare.py
    │   │   ├── sax.py
    │   │   ├── superv_base_decider.py
    │   │   ├── symbolic_representation.py
    │   │   └── unsupervised_base.py
    └── utils
    │   ├── __init__.py
    │   ├── commons.py
    │   ├── data_analysis.py
    │   ├── data_analysis.pyc
    │   ├── helpers.py
    │   ├── output_process_modules.py
    │   └── stars.py
├── lcc_web
    ├── logs
    │   └── django.log
    ├── sample_data
    │   ├── .DS_Store
    │   ├── sample1
    │   │   ├── LMC_SC1_1.fits
    │   │   ├── LMC_SC1_10.fits
    │   │   ├── LMC_SC1_11.fits
    │   │   ├── LMC_SC1_12.fits
    │   │   ├── LMC_SC1_13.fits
    │   │   ├── LMC_SC1_14.fits
    │   │   ├── LMC_SC1_15.fits
    │   │   ├── LMC_SC1_16.fits
    │   │   ├── LMC_SC1_17.fits
    │   │   ├── LMC_SC1_18.fits
    │   │   ├── LMC_SC1_19.fits
    │   │   ├── LMC_SC1_2.fits
    │   │   ├── LMC_SC1_20.fits
    │   │   ├── LMC_SC1_21.fits
    │   │   ├── LMC_SC1_22.fits
    │   │   ├── LMC_SC1_23.fits
    │   │   ├── LMC_SC1_24.fits
    │   │   ├── LMC_SC1_25.fits
    │   │   ├── LMC_SC1_26.fits
    │   │   ├── LMC_SC1_27.fits
    │   │   ├── LMC_SC1_28.fits
    │   │   ├── LMC_SC1_29.fits
    │   │   ├── LMC_SC1_3.fits
    │   │   ├── LMC_SC1_4.fits
    │   │   ├── LMC_SC1_5.fits
    │   │   ├── LMC_SC1_6.fits
    │   │   ├── LMC_SC1_7.fits
    │   │   ├── LMC_SC1_8.fits
    │   │   └── LMC_SC1_9.fits
    │   └── sample2
    │   │   ├── LMC_SC2_10.fits
    │   │   ├── LMC_SC2_11.fits
    │   │   ├── LMC_SC2_12.fits
    │   │   ├── LMC_SC2_13.fits
    │   │   ├── LMC_SC2_14.fits
    │   │   ├── LMC_SC2_15.fits
    │   │   ├── LMC_SC2_16.fits
    │   │   ├── LMC_SC2_17.fits
    │   │   ├── LMC_SC2_18.fits
    │   │   ├── LMC_SC2_19.fits
    │   │   ├── LMC_SC2_2.fits
    │   │   ├── LMC_SC2_21.fits
    │   │   ├── LMC_SC2_22.fits
    │   │   ├── LMC_SC2_23.fits
    │   │   ├── LMC_SC2_24.fits
    │   │   ├── LMC_SC2_25.fits
    │   │   ├── LMC_SC2_26.fits
    │   │   ├── LMC_SC2_27.fits
    │   │   ├── LMC_SC2_28.fits
    │   │   ├── LMC_SC2_29.fits
    │   │   ├── LMC_SC2_3.fits
    │   │   ├── LMC_SC2_5.fits
    │   │   ├── LMC_SC2_6.fits
    │   │   ├── LMC_SC2_7.fits
    │   │   ├── LMC_SC2_8.fits
    │   │   └── LMC_SC2_9.fits
    └── web
    │   ├── LCCwebApp
    │       ├── .gitignore
    │       ├── __init__.py
    │       ├── settings.py
    │       ├── urls.py
    │       └── wsgi.py
    │   ├── interface
    │       ├── .gitignore
    │       ├── __init__.py
    │       ├── admin.py
    │       ├── apps.py
    │       ├── forms.py
    │       ├── helpers.py
    │       ├── lcc_views
    │       │   ├── __init__.py
    │       │   ├── filtering.py
    │       │   ├── jobs.py
    │       │   ├── searching.py
    │       │   └── visualization.py
    │       ├── migrations
    │       │   ├── .gitignore
    │       │   ├── 0001_initial.py
    │       │   ├── 0002_auto_20170313_1922.py
    │       │   ├── 0003_auto_20170313_1933.py
    │       │   ├── 0004_auto_20170313_1952.py
    │       │   ├── 0005_dbquery_queries.py
    │       │   ├── 0006_auto_20170315_1023.py
    │       │   ├── 0007_auto_20170315_1029.py
    │       │   ├── 0008_auto_20180405_2036.py
    │       │   └── __init__.py
    │       ├── models.py
    │       ├── static
    │       │   ├── __init__.py
    │       │   ├── css
    │       │   │   ├── __init__.py
    │       │   │   ├── bootstrap.min.css
    │       │   │   ├── popup.css
    │       │   │   ├── reset.css
    │       │   │   ├── styles.css
    │       │   │   └── styles2.css
    │       │   ├── fonts
    │       │   │   ├── glyphicons-halflings-regular.eot
    │       │   │   ├── glyphicons-halflings-regular.svg
    │       │   │   ├── glyphicons-halflings-regular.ttf
    │       │   │   └── glyphicons-halflings-regular.woff
    │       │   ├── img
    │       │   │   ├── Thumbs.db
    │       │   │   ├── backg_img.jpg
    │       │   │   ├── comp_hist_bestar.png
    │       │   │   ├── comp_hist_qso.png
    │       │   │   ├── comp_lc_bestar.png
    │       │   │   ├── comp_lc_qso.png
    │       │   │   ├── comp_vario_bestar.png
    │       │   │   ├── comp_vario_qso.png
    │       │   │   ├── diagram.png
    │       │   │   ├── fits_header.png
    │       │   │   ├── header_img.jpg
    │       │   │   ├── loader.gif
    │       │   │   ├── logo.png
    │       │   │   ├── select_make_filter.png
    │       │   │   └── show_sc.png
    │       │   └── js
    │       │   │   ├── __init__.py
    │       │   │   ├── bootstrap-filestyle.js
    │       │   │   ├── bootstrap-filestyle.min.js
    │       │   │   ├── bootstrap.min.js
    │       │   │   ├── custom.js
    │       │   │   ├── form_select_stars_copy.js
    │       │   │   ├── jquery.js
    │       │   │   ├── show_filt_by_id.js
    │       │   │   ├── slider.js
    │       │   │   └── superfish.js
    │       ├── templates
    │       │   ├── __init__.py
    │       │   ├── batteries
    │       │   │   ├── __init__.py
    │       │   │   └── change_filt_popup.html
    │       │   ├── interface
    │       │   │   ├── 404.html
    │       │   │   ├── 500.html
    │       │   │   ├── __init__.py
    │       │   │   ├── base_template.html
    │       │   │   ├── base_template2.html
    │       │   │   ├── browse.html
    │       │   │   ├── contact.html
    │       │   │   ├── create_user.html
    │       │   │   ├── error_page.html
    │       │   │   ├── guide_page.html
    │       │   │   ├── header_scr.html
    │       │   │   ├── index.html
    │       │   │   ├── jobs.html
    │       │   │   ├── login.html
    │       │   │   ├── make_filter.html
    │       │   │   ├── manage_modules.html
    │       │   │   ├── results.html
    │       │   │   ├── search.html
    │       │   │   ├── show_stars_filter.html
    │       │   │   ├── show_unsup.html
    │       │   │   ├── to_inter.html
    │       │   │   └── unsupervised.html
    │       │   └── visual
    │       │   │   ├── __init__.py
    │       │   │   ├── plot2D.js
    │       │   │   ├── plot3D.js
    │       │   │   ├── plot3D_scatter.js
    │       │   │   ├── plot3D_scatter_superv.js
    │       │   │   ├── plot3D_surface.js
    │       │   │   ├── plotLC.js
    │       │   │   ├── plotLC_selected.js
    │       │   │   ├── plotROC.js
    │       │   │   ├── plotUnsup2D.js
    │       │   │   └── plotUnsupSpace.js
    │       ├── tests.py
    │       ├── urls.py
    │       └── views.py
    │   ├── manage.py
    │   ├── requirements.in
    │   ├── requirements.txt
    │   ├── run_localy.sh
    │   └── run_localy_dbg.sh
├── nginx.conf
├── requirements.txt
├── sample
    ├── be_stars
    │   ├── LMC_SC1_124845.fits
    │   ├── LMC_SC1_229472.fits
    │   ├── LMC_SC1_235810.fits
    │   ├── LMC_SC1_248039.fits
    │   ├── LMC_SC1_59479.fits
    │   ├── LMC_SC1_60022.fits
    │   ├── LMC_SC1_791.fits
    │   ├── LMC_SC1_79476.fits
    │   ├── LMC_SC2_109026.fits
    │   ├── LMC_SC2_158712.fits
    │   ├── LMC_SC2_158836.fits
    │   ├── LMC_SC2_166301.fits
    │   ├── LMC_SC2_213964.fits
    │   ├── LMC_SC2_214344.fits
    │   ├── LMC_SC2_219136.fits
    │   ├── LMC_SC2_240975.fits
    │   ├── LMC_SC2_289705.fits
    │   └── LMC_SC2_71015.fits
    └── qso
    │   ├── 1.4418.1930.fits
    │   ├── 1.4537.1642.fits
    │   ├── 11.8988.1350.fits
    │   ├── 13.5717.178.fits
    │   ├── 13.5962.237.fits
    │   ├── 13.6805.324.fits
    │   ├── 14.8249.74.fits
    │   ├── 17.2227.488.fits
    │   ├── 17.3197.1182.fits
    │   ├── 2.5873.82.fits
    │   ├── 20.4678.600.fits
    │   ├── 22.4990.462.fits
    │   ├── 22.5595.1333.fits
    │   ├── 5.4643.149.fits
    │   ├── 5.4892.1971.fits
    │   ├── 9.4641.568.fits
    │   ├── 9.4882.332.fits
    │   └── 9.5239.505.fits
├── setup.cfg
├── setup.py
└── test
    ├── __init__.py
    ├── cli
        ├── __init__.py
        └── test_cli.py
    ├── db_tier
        ├── __init__.py
        ├── test_connectors.py
        └── test_stars_searcher.py
    ├── intergation
        ├── __init__.py
        └── test_searcher.py
    ├── resources
        ├── CurveShapeFilter.filter
        ├── project_settings.py
        ├── query_file.txt
        ├── query_local.txt
        ├── query_ogle.txt
        ├── test_filter.pickle
        └── tune_lc_shape.txt
    ├── stars_processing
        ├── __init__.py
        ├── test_comp_descriptors.py
        ├── test_deciders.py
        ├── test_descriptors.py
        ├── test_params_estim.py
        ├── test_stars_filter.py
        └── test_stars_searcher.py
    └── utils
        ├── __init__.py
        └── test_data_analysis.py


/.gitignore:
--------------------------------------------------------------------------------
 1 | *pyc
 2 | .idea
 3 | .cache
 4 | __
 5 | lcc.egg-info
 6 | dist
 7 | *bak
 8 | data
 9 | .coverage.*
10 | migrations
11 | .DS_Store
12 | .ipynb_checkpoints
13 | build
14 | .pytest*
15 | _build
16 | _static
17 | _templates
18 | docs_source
19 | 


--------------------------------------------------------------------------------
/CODE_OF_CONDUCT.md:
--------------------------------------------------------------------------------
 1 | # Contributor Covenant Code of Conduct
 2 | 
 3 | ## Our Pledge
 4 | 
 5 | In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
 6 | 
 7 | ## Our Standards
 8 | 
 9 | Examples of behavior that contributes to creating a positive environment include:
10 | 
11 | * Using welcoming and inclusive language
12 | * Being respectful of differing viewpoints and experiences
13 | * Gracefully accepting constructive criticism
14 | * Focusing on what is best for the community
15 | * Showing empathy towards other community members
16 | 
17 | Examples of unacceptable behavior by participants include:
18 | 
19 | * The use of sexualized language or imagery and unwelcome sexual attention or advances
20 | * Trolling, insulting/derogatory comments, and personal or political attacks
21 | * Public or private harassment
22 | * Publishing others' private information, such as a physical or electronic address, without explicit permission
23 | * Other conduct which could reasonably be considered inappropriate in a professional setting
24 | 
25 | ## Our Responsibilities
26 | 
27 | Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.
28 | 
29 | Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.
30 | 
31 | ## Scope
32 | 
33 | This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.
34 | 
35 | ## Enforcement
36 | 
37 | Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at mavrix@seznam.cz. The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.
38 | 
39 | Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership.
40 | 
41 | ## Attribution
42 | 
43 | This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [http://contributor-covenant.org/version/1/4][version]
44 | 
45 | [homepage]: http://contributor-covenant.org
46 | [version]: http://contributor-covenant.org/version/1/4/
47 | 


--------------------------------------------------------------------------------
/CONTRIBUTING.md:
--------------------------------------------------------------------------------
 1 | # Contributing
 2 | 
 3 | First of all thank you for considering to contribute! The project is quite big for one person a I would really appreciate any help.
 4 | 
 5 | ## Code style
 6 |  - Just follow PEP8
 7 |  - Well because of legacy code package actually use camelCase for class methods (PEP8 alert)
 8 |  - Function comments are welcomed and should follow [numpy style](http://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_numpy.html)
 9 | 
10 | ## Testing
11 |   - `pytest` is preferred way to do it (run `pytest test`)
12 |   - Current tests coverage can be definitely improved
13 |   - For coverage check use `py.test --cov=lcc test`
14 |   
15 | ## Where to contribute
16 | 
17 | The repo can be divided into 3 areas where it can be contributed:
18 |   1) `lcc` package
19 |   2) `lcc` CLI
20 |   3) Web Interface
21 |   
22 | There are a lots of "ugly" parts of the code which should be refactored...
23 | 


--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------
 1 | FROM python:3.6
 2 | 
 3 | MAINTAINER Martin Vo
 4 | 
 5 | ENV TINI_VERSION v0.14.0
 6 | ADD https://github.com/krallin/tini/releases/download/${TINI_VERSION}/tini /tini
 7 | RUN chmod +x /tini
 8 | ENTRYPOINT ["/tini", "--"]
 9 | 
10 | # apt-get install -y python python-pip python-dev python-tk \
11 | RUN echo "deb http://packages.dotdeb.org jessie all" >> /etc/apt/sources.list && \
12 |     echo "deb-src http://packages.dotdeb.org jessie all" >> /etc/apt/sources.list && \
13 |     wget https://www.dotdeb.org/dotdeb.gpg && apt-key add dotdeb.gpg
14 | RUN apt-get update && apt-get -y install redis-server
15 | RUN apt-get -y install libfreetype6-dev libpng12-dev libxft-dev libblas-dev liblapack-dev libatlas-base-dev gfortran \
16 |     nginx dialog net-tools libxml2-dev libxslt1-dev python-lxml
17 | 
18 | ENV DOCKYARD_SRVHOME=/srv
19 | ENV DOCKYARD_SRVPROJ=$DOCKYARD_SRVHOME/web \
20 |     DOCKYARD_SRVDATA=$DOCKYARD_SRVHOME/data \
21 |     DOCKYARD_SRVSAMPLE=$DOCKYARD_SRVHOME/sample_data \
22 |     DOCKYARD_SRVLOGS=$DOCKYARD_SRVHOME/logs \
23 |     DOCKYARD_SRVSTATIC=$DOCKYARD_SRVHOME/static/ \
24 |     DOCKYARD_WORKERS=5 \
25 |     DOCKYARD_PORT=8000 \
26 |     DOCKYARD_APP_CONTEXT=lcc \
27 |     MPLBACKEND="agg"
28 |     #DOCKYARD_SECRET - should be set during deployment
29 | 
30 | ADD lcc_web/web/requirements.txt tmp/requirements.txt
31 | RUN mkdir -p $DOCKYARD_SRVSTATIC $DOCKYARD_SRVLOGS \
32 | && pip install -r tmp/requirements.txt
33 | 
34 | # prepare web application
35 | ADD . $DOCKYARD_SRVHOME
36 | 
37 | RUN python $DOCKYARD_SRVHOME/setup.py install
38 | RUN mv $DOCKYARD_SRVHOME/lcc_web/* $DOCKYARD_SRVHOME
39 | 
40 | # prepare nginx configuration
41 | ADD nginx.conf /etc/nginx/sites-enabled/default
42 | 
43 | # Port to expose
44 | EXPOSE 80
45 | # 'data' folder for user outputs (better to store data on external ftp
46 | VOLUME ["$DOCKYARD_SRVDATA", "$DOCKYARD_SRVLOGS"]
47 | 
48 | # WORKDIR $DOCKYARD_SRVPROJ
49 | WORKDIR /srv/web
50 | ENV PYTHONPATH /srv
51 | 
52 | # TODO: Fix me
53 | ENV DOCKYARD_SRVSAMPLE $DOCKYARD_SRVHOME/sample_data
54 | RUN pip install lxml
55 | COPY ./docker-entrypoint.sh /
56 | RUN chmod +x /docker-entrypoint.sh
57 | CMD "/docker-entrypoint.sh"
58 | 


--------------------------------------------------------------------------------
/LICENSE.txt:
--------------------------------------------------------------------------------
1 | Copyright <YEAR> <COPYRIGHT HOLDER>
2 | 
3 | Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
4 | 
5 | The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
6 | 
7 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
8 | 


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/docker-entrypoint.sh:
--------------------------------------------------------------------------------
 1 | #!/bin/bash
 2 | python manage.py migrate                  # Apply database migrations
 3 | python manage.py collectstatic --noinput  # Collect static files
 4 | 
 5 | echo "from django.contrib.auth.models import User; User.objects.filter(email='admin@example.com').delete(); User.objects.create_superuser('admin', 'admin@example.com', 'nimda')" | python manage.py shell
 6 | 
 7 | # Prepare log files and start outputting logs to stdout
 8 | touch $DOCKYARD_SRVLOGS/gunicorn.log
 9 | touch $DOCKYARD_SRVLOGS/access.log
10 | tail -n 0 -f $DOCKYARD_SRVLOGS/*.log &
11 | 
12 | echo Starting Nginx
13 | service nginx start
14 | 
15 | echo Starting redis
16 | redis-server --daemonize yes
17 | 
18 | echo Starting rq workers
19 | exec python $DOCKYARD_SRVHOME/lcc/stars_processing/systematic_search/worker.py &
20 | # Start Gunicorn processes
21 | echo Starting Gunicorn.
22 | exec gunicorn LCCwebApp.wsgi:application \
23 |     --name LCCwebApp \
24 |     --bind 127.0.0.1:$DOCKYARD_PORT \
25 |     --workers $DOCKYARD_WORKERS \
26 |     --timeout 300 \
27 |     --log-level=info \
28 |     --log-file=$DOCKYARD_SRVLOGS/gunicorn.log \
29 |     --access-logfile=$DOCKYARD_SRVLOGS/access.log
30 | 


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/docs/.buildinfo:
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1 | # Sphinx build info version 1
2 | # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
3 | config: 512d4ed287cd391edd99f776d55de8b9
4 | tags: 645f666f9bcd5a90fca523b33c5a78b7
5 | 


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/docs/_sources/index.txt:
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 1 | .. Light Curves Classifier documentation master file, created by
 2 |    sphinx-quickstart on Fri Apr 27 08:34:37 2018.
 3 |    You can adapt this file completely to your liking, but it should at least
 4 |    contain the root `toctree` directive.
 5 | 
 6 | Welcome to Light Curves Classifier's documentation!
 7 | ===================================================
 8 | 
 9 | Contents:
10 | 
11 | .. toctree::
12 |    :maxdepth: 2
13 | 
14 | 
15 | 
16 | Indices and tables
17 | ==================
18 | 
19 | * :ref:`genindex`
20 | * :ref:`modindex`
21 | * :ref:`search`
22 | 
23 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.bin.txt:
--------------------------------------------------------------------------------
 1 | lcc.bin package
 2 | ===============
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.bin.create_project module
 8 | -----------------------------
 9 | 
10 | .. automodule:: lcc.bin.create_project
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.bin.filter_stars module
16 | ---------------------------
17 | 
18 | .. automodule:: lcc.bin.filter_stars
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.bin.make_filter module
24 | --------------------------
25 | 
26 | .. automodule:: lcc.bin.make_filter
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | lcc.bin.plot_lcs module
32 | -----------------------
33 | 
34 | .. automodule:: lcc.bin.plot_lcs
35 |     :members:
36 |     :undoc-members:
37 |     :show-inheritance:
38 | 
39 | lcc.bin.prepare_query module
40 | ----------------------------
41 | 
42 | .. automodule:: lcc.bin.prepare_query
43 |     :members:
44 |     :undoc-members:
45 |     :show-inheritance:
46 | 
47 | 
48 | Module contents
49 | ---------------
50 | 
51 | .. automodule:: lcc.bin
52 |     :members:
53 |     :undoc-members:
54 |     :show-inheritance:
55 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.cli.txt:
--------------------------------------------------------------------------------
 1 | lcc.cli package
 2 | ===============
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.cli.input_parse module
 8 | --------------------------
 9 | 
10 | .. automodule:: lcc.cli.input_parse
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.cli.lcc module
16 | ------------------
17 | 
18 | .. automodule:: lcc.cli.lcc
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.cli.stars_handling module
24 | -----------------------------
25 | 
26 | .. automodule:: lcc.cli.stars_handling
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | 
32 | Module contents
33 | ---------------
34 | 
35 | .. automodule:: lcc.cli
36 |     :members:
37 |     :undoc-members:
38 |     :show-inheritance:
39 | 


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/docs/_sources/lcc.data_manager.txt:
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 1 | lcc.data_manager package
 2 | ========================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.data_manager.filter_serializer module
 8 | -----------------------------------------
 9 | 
10 | .. automodule:: lcc.data_manager.filter_serializer
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.data_manager.package_reader module
16 | --------------------------------------
17 | 
18 | .. automodule:: lcc.data_manager.package_reader
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.data_manager.prepare_package module
24 | ---------------------------------------
25 | 
26 | .. automodule:: lcc.data_manager.prepare_package
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | lcc.data_manager.status_resolver module
32 | ---------------------------------------
33 | 
34 | .. automodule:: lcc.data_manager.status_resolver
35 |     :members:
36 |     :undoc-members:
37 |     :show-inheritance:
38 | 
39 | 
40 | Module contents
41 | ---------------
42 | 
43 | .. automodule:: lcc.data_manager
44 |     :members:
45 |     :undoc-members:
46 |     :show-inheritance:
47 | 


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/docs/_sources/lcc.db_tier.connectors.txt:
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 1 | lcc.db_tier.connectors package
 2 | ==============================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.db_tier.connectors.asas module
 8 | ----------------------------------
 9 | 
10 | .. automodule:: lcc.db_tier.connectors.asas
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.db_tier.connectors.catalina module
16 | --------------------------------------
17 | 
18 | .. automodule:: lcc.db_tier.connectors.catalina
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.db_tier.connectors.corot module
24 | -----------------------------------
25 | 
26 | .. automodule:: lcc.db_tier.connectors.corot
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | lcc.db_tier.connectors.file_manager module
32 | ------------------------------------------
33 | 
34 | .. automodule:: lcc.db_tier.connectors.file_manager
35 |     :members:
36 |     :undoc-members:
37 |     :show-inheritance:
38 | 
39 | lcc.db_tier.connectors.kepler module
40 | ------------------------------------
41 | 
42 | .. automodule:: lcc.db_tier.connectors.kepler
43 |     :members:
44 |     :undoc-members:
45 |     :show-inheritance:
46 | 
47 | lcc.db_tier.connectors.macho module
48 | -----------------------------------
49 | 
50 | .. automodule:: lcc.db_tier.connectors.macho
51 |     :members:
52 |     :undoc-members:
53 |     :show-inheritance:
54 | 
55 | lcc.db_tier.connectors.ogleII module
56 | ------------------------------------
57 | 
58 | .. automodule:: lcc.db_tier.connectors.ogleII
59 |     :members:
60 |     :undoc-members:
61 |     :show-inheritance:
62 | 
63 | lcc.db_tier.connectors.ogleIII module
64 | -------------------------------------
65 | 
66 | .. automodule:: lcc.db_tier.connectors.ogleIII
67 |     :members:
68 |     :undoc-members:
69 |     :show-inheritance:
70 | 
71 | 
72 | Module contents
73 | ---------------
74 | 
75 | .. automodule:: lcc.db_tier.connectors
76 |     :members:
77 |     :undoc-members:
78 |     :show-inheritance:
79 | 


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/docs/_sources/lcc.db_tier.txt:
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 1 | lcc.db_tier package
 2 | ===================
 3 | 
 4 | Subpackages
 5 | -----------
 6 | 
 7 | .. toctree::
 8 | 
 9 |     lcc.db_tier.connectors
10 | 
11 | Submodules
12 | ----------
13 | 
14 | lcc.db_tier.TAP_query module
15 | ----------------------------
16 | 
17 | .. automodule:: lcc.db_tier.TAP_query
18 |     :members:
19 |     :undoc-members:
20 |     :show-inheritance:
21 | 
22 | lcc.db_tier.base_query module
23 | -----------------------------
24 | 
25 | .. automodule:: lcc.db_tier.base_query
26 |     :members:
27 |     :undoc-members:
28 |     :show-inheritance:
29 | 
30 | lcc.db_tier.stars_provider module
31 | ---------------------------------
32 | 
33 | .. automodule:: lcc.db_tier.stars_provider
34 |     :members:
35 |     :undoc-members:
36 |     :show-inheritance:
37 | 
38 | lcc.db_tier.vizier_tap_base module
39 | ----------------------------------
40 | 
41 | .. automodule:: lcc.db_tier.vizier_tap_base
42 |     :members:
43 |     :undoc-members:
44 |     :show-inheritance:
45 | 
46 | 
47 | Module contents
48 | ---------------
49 | 
50 | .. automodule:: lcc.db_tier
51 |     :members:
52 |     :undoc-members:
53 |     :show-inheritance:
54 | 


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/docs/_sources/lcc.entities.txt:
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 1 | lcc.entities package
 2 | ====================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.entities.exceptions module
 8 | ------------------------------
 9 | 
10 | .. automodule:: lcc.entities.exceptions
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.entities.light_curve module
16 | -------------------------------
17 | 
18 | .. automodule:: lcc.entities.light_curve
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.entities.star module
24 | ------------------------
25 | 
26 | .. automodule:: lcc.entities.star
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | 
32 | Module contents
33 | ---------------
34 | 
35 | .. automodule:: lcc.entities
36 |     :members:
37 |     :undoc-members:
38 |     :show-inheritance:
39 | 


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/docs/_sources/lcc.stars_processing.deciders.txt:
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 1 | lcc.stars_processing.deciders package
 2 | =====================================
 3 | 
 4 | Subpackages
 5 | -----------
 6 | 
 7 | .. toctree::
 8 | 
 9 |     lcc.stars_processing.deciders.unsupervised
10 | 
11 | Submodules
12 | ----------
13 | 
14 | lcc.stars_processing.deciders.custom_decider module
15 | ---------------------------------------------------
16 | 
17 | .. automodule:: lcc.stars_processing.deciders.custom_decider
18 |     :members:
19 |     :undoc-members:
20 |     :show-inheritance:
21 | 
22 | lcc.stars_processing.deciders.neuron_decider module
23 | ---------------------------------------------------
24 | 
25 | .. automodule:: lcc.stars_processing.deciders.neuron_decider
26 |     :members:
27 |     :undoc-members:
28 |     :show-inheritance:
29 | 
30 | lcc.stars_processing.deciders.supervised_deciders module
31 | --------------------------------------------------------
32 | 
33 | .. automodule:: lcc.stars_processing.deciders.supervised_deciders
34 |     :members:
35 |     :undoc-members:
36 |     :show-inheritance:
37 | 
38 | 
39 | Module contents
40 | ---------------
41 | 
42 | .. automodule:: lcc.stars_processing.deciders
43 |     :members:
44 |     :undoc-members:
45 |     :show-inheritance:
46 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.stars_processing.deciders.unsupervised.txt:
--------------------------------------------------------------------------------
 1 | lcc.stars_processing.deciders.unsupervised package
 2 | ==================================================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.stars_processing.deciders.unsupervised.k_means_decider module
 8 | -----------------------------------------------------------------
 9 | 
10 | .. automodule:: lcc.stars_processing.deciders.unsupervised.k_means_decider
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | 
16 | Module contents
17 | ---------------
18 | 
19 | .. automodule:: lcc.stars_processing.deciders.unsupervised
20 |     :members:
21 |     :undoc-members:
22 |     :show-inheritance:
23 | 


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/docs/_sources/lcc.stars_processing.systematic_search.txt:
--------------------------------------------------------------------------------
 1 | lcc.stars_processing.systematic_search package
 2 | ==============================================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.stars_processing.systematic_search.stars_searcher module
 8 | ------------------------------------------------------------
 9 | 
10 | .. automodule:: lcc.stars_processing.systematic_search.stars_searcher
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.stars_processing.systematic_search.worker module
16 | ----------------------------------------------------
17 | 
18 | .. automodule:: lcc.stars_processing.systematic_search.worker
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | 
24 | Module contents
25 | ---------------
26 | 
27 | .. automodule:: lcc.stars_processing.systematic_search
28 |     :members:
29 |     :undoc-members:
30 |     :show-inheritance:
31 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.stars_processing.tools.txt:
--------------------------------------------------------------------------------
 1 | lcc.stars_processing.tools package
 2 | ==================================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.stars_processing.tools.params_estim module
 8 | ----------------------------------------------
 9 | 
10 | .. automodule:: lcc.stars_processing.tools.params_estim
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.stars_processing.tools.stats_manager module
16 | -----------------------------------------------
17 | 
18 | .. automodule:: lcc.stars_processing.tools.stats_manager
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.stars_processing.tools.visualization module
24 | -----------------------------------------------
25 | 
26 | .. automodule:: lcc.stars_processing.tools.visualization
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | 
32 | Module contents
33 | ---------------
34 | 
35 | .. automodule:: lcc.stars_processing.tools
36 |     :members:
37 |     :undoc-members:
38 |     :show-inheritance:
39 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.stars_processing.txt:
--------------------------------------------------------------------------------
 1 | lcc.stars_processing package
 2 | ============================
 3 | 
 4 | Subpackages
 5 | -----------
 6 | 
 7 | .. toctree::
 8 | 
 9 |     lcc.stars_processing.deciders
10 |     lcc.stars_processing.descriptors
11 |     lcc.stars_processing.systematic_search
12 |     lcc.stars_processing.tools
13 |     lcc.stars_processing.utilities
14 | 
15 | Submodules
16 | ----------
17 | 
18 | lcc.stars_processing.stars_filter module
19 | ----------------------------------------
20 | 
21 | .. automodule:: lcc.stars_processing.stars_filter
22 |     :members:
23 |     :undoc-members:
24 |     :show-inheritance:
25 | 
26 | 
27 | Module contents
28 | ---------------
29 | 
30 | .. automodule:: lcc.stars_processing
31 |     :members:
32 |     :undoc-members:
33 |     :show-inheritance:
34 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.stars_processing.utilities.txt:
--------------------------------------------------------------------------------
 1 | lcc.stars_processing.utilities package
 2 | ======================================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.stars_processing.utilities.base_decider module
 8 | --------------------------------------------------
 9 | 
10 | .. automodule:: lcc.stars_processing.utilities.base_decider
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.stars_processing.utilities.base_descriptor module
16 | -----------------------------------------------------
17 | 
18 | .. automodule:: lcc.stars_processing.utilities.base_descriptor
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.stars_processing.utilities.compare module
24 | ---------------------------------------------
25 | 
26 | .. automodule:: lcc.stars_processing.utilities.compare
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | lcc.stars_processing.utilities.sax module
32 | -----------------------------------------
33 | 
34 | .. automodule:: lcc.stars_processing.utilities.sax
35 |     :members:
36 |     :undoc-members:
37 |     :show-inheritance:
38 | 
39 | lcc.stars_processing.utilities.superv_base_decider module
40 | ---------------------------------------------------------
41 | 
42 | .. automodule:: lcc.stars_processing.utilities.superv_base_decider
43 |     :members:
44 |     :undoc-members:
45 |     :show-inheritance:
46 | 
47 | lcc.stars_processing.utilities.symbolic_representation module
48 | -------------------------------------------------------------
49 | 
50 | .. automodule:: lcc.stars_processing.utilities.symbolic_representation
51 |     :members:
52 |     :undoc-members:
53 |     :show-inheritance:
54 | 
55 | lcc.stars_processing.utilities.unsupervised_base module
56 | -------------------------------------------------------
57 | 
58 | .. automodule:: lcc.stars_processing.utilities.unsupervised_base
59 |     :members:
60 |     :undoc-members:
61 |     :show-inheritance:
62 | 
63 | 
64 | Module contents
65 | ---------------
66 | 
67 | .. automodule:: lcc.stars_processing.utilities
68 |     :members:
69 |     :undoc-members:
70 |     :show-inheritance:
71 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.txt:
--------------------------------------------------------------------------------
 1 | lcc package
 2 | ===========
 3 | 
 4 | Subpackages
 5 | -----------
 6 | 
 7 | .. toctree::
 8 | 
 9 |     lcc.bin
10 |     lcc.cli
11 |     lcc.data_manager
12 |     lcc.db_tier
13 |     lcc.entities
14 |     lcc.stars_processing
15 |     lcc.utils
16 | 
17 | Module contents
18 | ---------------
19 | 
20 | .. automodule:: lcc
21 |     :members:
22 |     :undoc-members:
23 |     :show-inheritance:
24 | 


--------------------------------------------------------------------------------
/docs/_sources/lcc.utils.txt:
--------------------------------------------------------------------------------
 1 | lcc.utils package
 2 | =================
 3 | 
 4 | Submodules
 5 | ----------
 6 | 
 7 | lcc.utils.commons module
 8 | ------------------------
 9 | 
10 | .. automodule:: lcc.utils.commons
11 |     :members:
12 |     :undoc-members:
13 |     :show-inheritance:
14 | 
15 | lcc.utils.data_analysis module
16 | ------------------------------
17 | 
18 | .. automodule:: lcc.utils.data_analysis
19 |     :members:
20 |     :undoc-members:
21 |     :show-inheritance:
22 | 
23 | lcc.utils.helpers module
24 | ------------------------
25 | 
26 | .. automodule:: lcc.utils.helpers
27 |     :members:
28 |     :undoc-members:
29 |     :show-inheritance:
30 | 
31 | lcc.utils.output_process_modules module
32 | ---------------------------------------
33 | 
34 | .. automodule:: lcc.utils.output_process_modules
35 |     :members:
36 |     :undoc-members:
37 |     :show-inheritance:
38 | 
39 | lcc.utils.stars module
40 | ----------------------
41 | 
42 | .. automodule:: lcc.utils.stars
43 |     :members:
44 |     :undoc-members:
45 |     :show-inheritance:
46 | 
47 | 
48 | Module contents
49 | ---------------
50 | 
51 | .. automodule:: lcc.utils
52 |     :members:
53 |     :undoc-members:
54 |     :show-inheritance:
55 | 


--------------------------------------------------------------------------------
/docs/_sources/modules.txt:
--------------------------------------------------------------------------------
1 | lcc
2 | ===
3 | 
4 | .. toctree::
5 |    :maxdepth: 4
6 | 
7 |    lcc
8 | 


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/docs/objects.inv:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/docs/objects.inv


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/lcc/__init__.py:
--------------------------------------------------------------------------------
1 | import logging
2 | 
3 | logging.basicConfig(level=logging.INFO)
4 | logging.debug("Logging configured")
5 | 


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/lcc/bin/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/bin/__init__.py


--------------------------------------------------------------------------------
/lcc/bin/create_project.py:
--------------------------------------------------------------------------------
 1 | import logging
 2 | import sys
 3 | import os
 4 | 
 5 | from lcc.data_manager.prepare_package import tree
 6 | from lcc.data_manager.prepare_package import rec
 7 | 
 8 | 
 9 | def main():
10 |     options = sys.argv[1:]
11 |     cur_loc = os.getcwd()
12 |     if not options:
13 |         path = cur_loc
14 |         proj_name = "project"
15 | 
16 |     elif len(options) == 1:
17 |         path = cur_loc
18 |         proj_name = options[0]
19 | 
20 |     elif len(options) == 2:
21 |         path = options[1] if options[1].startswith("/") else os.path.join(cur_loc, options[1])
22 |         proj_name = options[0]
23 |     else:
24 |         raise ValueError("Invalid number of parameters")
25 | 
26 |     d = tree()
27 | 
28 |     rec(d, os.path.join(path, proj_name))
29 | 
30 |     # Create settings file
31 |     lines = ["import os",
32 |              "\n",
33 |              "project_dir = '{0}'".format(os.path.join(path, proj_name)),
34 |              "\n",
35 |              "# Input locations",
36 |              "INP_LCS = os.path.join(project_dir, 'inp_lcs')",
37 |              "TUN_PARAMS = os.path.join(project_dir, 'tun_params')",
38 |              "QUERIES = os.path.join(project_dir, 'queries')",
39 |              "FILTERS = os.path.join(project_dir, 'filters')",
40 |              "RESULTS = os.path.join(project_dir, 'query_results')",
41 |              "\n",
42 |              "# Output locations"]
43 | 
44 |     logging.info("Creating project {} in the {}".format(proj_name, path))
45 |     with open(os.path.join(path, proj_name, "project_settings.py"), "w") as f:
46 |         for line in lines:
47 |             f.write(line + "\n")
48 | 
49 | 
50 | if __name__ == '__main__':
51 |     main()
52 | 


--------------------------------------------------------------------------------
/lcc/cli/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/cli/__init__.py


--------------------------------------------------------------------------------
/lcc/cli/lcc.py:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/python3
 2 | import logging
 3 | import sys
 4 | import os
 5 | import importlib.util
 6 | 
 7 | logging.basicConfig(level=logging.INFO)
 8 | 
 9 | 
10 | def main(path=None):
11 |     if len(sys.argv) > 1:
12 |         option = sys.argv[1]
13 |         sys.argv = sys.argv[:1] + sys.argv[2:]
14 | 
15 |         if option == "create_project":
16 |             logging.info("Creating the project...")
17 |             from lcc.bin.create_project import main
18 |             return main()
19 |         try:
20 |             path = path or os.getcwd()
21 |             spec = importlib.util.spec_from_file_location("module.name",
22 |                                                           os.path.join(path, 'project_settings.py'))
23 |             project_settings = importlib.util.module_from_spec(spec)
24 |             spec.loader.exec_module(project_settings)
25 |             logging.info("Settings file was loaded...")
26 |         except IOError:
27 |             raise IOError("""There are not 'project_settings.py' in the current directory.
28 |                         Create project first by 'lcc create_project'""")
29 | 
30 |         if option == "make_filter":
31 |             from lcc.bin.make_filter import main
32 |             return main(project_settings)
33 | 
34 |         elif option == "filter_stars":
35 |             from lcc.bin.filter_stars import main
36 |             return main(project_settings)
37 | 
38 |         elif option == "prepare_query":
39 |             logging.info("Creating query file...")
40 |             from lcc.bin.prepare_query import main
41 |             return main(project_settings)
42 |         else:
43 |             sys.stderr.write("""Invalid option. Parameter of lcc have
44 |                         to be 'make_filter', 'filter_stars' or 'prepare_query'""")
45 | 
46 |     else:
47 |         print("""Light Curves Classifier: Use one of the following commands: create_project, make_filter,
48 |         filter_stars, prepare_query""")
49 | 
50 | 
51 | if __name__ == '__main__':
52 |     main()
53 | 


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/lcc/data_manager/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/data_manager/__init__.py


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/lcc/data_manager/filter_serializer.py:
--------------------------------------------------------------------------------
 1 | import os
 2 | 
 3 | from lcc.utils.output_process_modules import loadFromFile
 4 | from lcc.utils.output_process_modules import saveIntoFile
 5 | 
 6 | 
 7 | class FiltersSerializer(object):
 8 |     '''
 9 |     This class is responsible for saving and reconstructing filter
10 |     objects from files
11 | 
12 |     Attributes
13 |     -----------
14 |     file_name : str
15 |         Name of the filter name
16 | 
17 |     path : str
18 |         Path to the filter location
19 |     '''
20 | 
21 |     def __init__(self, file_name, path):
22 |         '''
23 |         Parameters
24 |         ----------
25 |         file_name : str
26 |             Name of the filter name
27 | 
28 |         path : str
29 |             Path to the filter location
30 |         '''
31 | 
32 |         self.file_name = file_name
33 |         self.path = path
34 | 
35 |     def loadFilter(self):
36 |         """
37 |         Get stars filter object
38 | 
39 |         Returns
40 |         -------
41 |         BaseFilter instance
42 |             Constructed filter object
43 |         """
44 |         return self._loadFromPickle()
45 | 
46 |     def saveFilter(self, star_filter):
47 |         """
48 |         Parameters
49 |         ----------
50 |         star_filter : BaseFilter instance
51 |             Save object as pickle
52 | 
53 |         Returns
54 |         -------
55 |             None
56 |         """
57 |         if not os.path.exists(self.path):
58 |             os.makedirs(self.path)
59 |         saveIntoFile(star_filter, self.path, self.file_name)
60 | 
61 |     def _loadFromPickle(self):
62 |         return loadFromFile(os.path.join(self.path, self.file_name))
63 | 


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/lcc/data_manager/prepare_package.py:
--------------------------------------------------------------------------------
 1 | from collections import defaultdict
 2 | import os.path
 3 | 
 4 | 
 5 | def tree():
 6 |     return defaultdict(tree)
 7 | 
 8 | 
 9 | def rec(directory, current_path):
10 |     if len(directory):
11 |         for direc in directory:
12 |             rec(directory[direc], os.path.join(current_path, direc))
13 |     else:
14 |         if not os.path.exists(current_path):
15 |             os.makedirs(current_path)
16 | 
17 | 
18 | def prepare_run(directory, run_name):
19 |     d = tree()
20 |     rec(d, os.path.join(directory, run_name))
21 | 


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/lcc/db_tier/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/db_tier/__init__.py


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/lcc/db_tier/base_query.py:
--------------------------------------------------------------------------------
  1 | import abc
  2 | import warnings
  3 | 
  4 | import astropy.units as u
  5 | import numpy as np
  6 | 
  7 | from lcc.entities.exceptions import QueryInputError
  8 | 
  9 | 
 10 | class StarsCatalogue(abc.ABC):
 11 |     """Common class for all catalogs containing information about stars"""
 12 | 
 13 |     def getStars(self, load_lc=True):
 14 |         """
 15 |         Query `Star` objects
 16 | 
 17 |         Parameters
 18 |         ----------
 19 |         load_lc : bool
 20 |             Append light curves to star objects
 21 | 
 22 |         Returns
 23 |         -------
 24 |         list
 25 |             List of `Star` objects
 26 |         """
 27 |         # with futures.ProcessPoolExecutor() as executor:
 28 |         #     stars_gen = executor.map(self.getStar, self.queries)
 29 |         #     stars = []
 30 |         #     for st in stars_gen:
 31 |         #         stars += st
 32 |         #     return stars
 33 |         stars = []
 34 |         for query in self.queries:
 35 |             stars += self.getStar(query)
 36 |         return stars
 37 | 
 38 |     def coneSearch(self, coo, stars, delta_deg, nearest=False):
 39 |         """
 40 |         Filter results from cone search
 41 | 
 42 |         Parameters
 43 |         ----------
 44 |         coo : astropy.coordinates.sky_coordinate.SkyCoord
 45 |             Center of searching
 46 | 
 47 |         stars : list of `Star` objects
 48 |             Stars returned by query
 49 | 
 50 |         delta_deg: float, astropy.units.quantity.Quantity
 51 |             Radius from center of searching
 52 | 
 53 |         nearest : bool
 54 |             Nearest star to the center of searching is returned if it is True
 55 | 
 56 |         Returns
 57 |         --------
 58 |         list
 59 |             List of `Star` objects
 60 |         """
 61 |         try:
 62 |             if not isinstance(delta_deg, u.quantity.Quantity):
 63 |                 delta_deg = float(delta_deg) * u.deg
 64 | 
 65 |             distances = []
 66 |             passed_stars = []
 67 |             for star in stars:
 68 |                 if star.coo:
 69 |                     dist = coo.separation(star.coo)
 70 |                     if dist < delta_deg:
 71 |                         passed_stars.append(star)
 72 |                         distances.append(dist.degree)
 73 |                 else:
 74 |                     passed_stars.append(star)
 75 |                     distances.append(np.inf)
 76 | 
 77 |         except AttributeError:
 78 |             raise QueryInputError("Invalid query coordinates")
 79 | 
 80 |         if distances and (nearest or str(nearest).capitalize() == "True"):
 81 |             return [passed_stars[np.argmin(distances)]]
 82 | 
 83 |         return passed_stars
 84 | 
 85 |     def _getRanges(self, ra, dec, arcsec_delta):
 86 | 
 87 |         if not ra or not dec or not arcsec_delta:
 88 |             return "", "", "", ""
 89 |         else:
 90 |             delta = float(arcsec_delta) / 3600.
 91 |             return float(ra) - float(delta), float(ra) + float(delta), float(dec) - float(delta), float(dec) + float(delta)
 92 | 
 93 | 
 94 | class LightCurvesDb(StarsCatalogue):
 95 |     """This is common class for every database containing light curves"""
 96 | 
 97 |     def getStarsWithCurves(self, *args, **kwargs):
 98 |         warnings.warn("This method will be deprecated in the future version. Please used getStars() instead")
 99 |         return self.getStars(*args, **kwargs)
100 | 


--------------------------------------------------------------------------------
/lcc/db_tier/connectors/__init__.py:
--------------------------------------------------------------------------------
1 | from .asas import Asas
2 | from .catalina import Catalina
3 | from .corot import CorotBright, CorotFaint
4 | from .file_manager import FileManager
5 | from .kepler import Kepler
6 | from .macho import Macho
7 | from .ogleII import OgleII
8 | from .ogleIII import OgleIII
9 | 


--------------------------------------------------------------------------------
/lcc/db_tier/connectors/asas.py:
--------------------------------------------------------------------------------
 1 | import collections
 2 | import requests
 3 | 
 4 | from lcc.db_tier.base_query import LightCurvesDb
 5 | from lcc.db_tier.vizier_tap_base import VizierTapBase
 6 | 
 7 | 
 8 | class Asas(VizierTapBase, LightCurvesDb):
 9 |     """
10 |     Asas archive of variable stars. It inherits `VizierTapBase` - see
11 |     documentation of this class to class attributes description.
12 | 
13 |     As for all TAP queries it is possible to use "<" and ">" marks (for example
14 |     {"Per":">2.5}).
15 | 
16 |     Example
17 |     -------
18 |     queries = [{"ASAS": "000030-3937.5"},
19 |                {"ra": 0.4797, "dec": -67.1290, "delta": 10}]
20 |     client = StarsProvider.getProvider("Asas",queries)
21 |     stars = client.getStarsWithCurves(do_per=True)
22 |     """
23 | 
24 |     TAP_URL = "http://tapvizier.u-strasbg.fr/TAPVizieR/tap"
25 |     LC_URL = "http://cdsarc.u-strasbg.fr/viz-bin/nph-Plot/Vgraph/txt?II%2f264%2f.%2f{asas_id}&P=0"
26 | 
27 |     TABLE = "II/264/asas3"
28 | 
29 |     RA = "_RA"  # Deg
30 |     DEC = "_DE"  # Deg
31 | 
32 |     LC_META = {"color": "V",
33 |                "origin": "ASAS"}
34 | 
35 |     IDENT_MAP = {"asas": ("ASAS")}
36 |     MORE_MAP = collections.OrderedDict((("Per", "period"),
37 |                                         ("Class", "var_type"),
38 |                                         ("Jmag", "j_mag"),
39 |                                         ("Kmag", "k_mag"),
40 |                                         ("Hmag", "h_mag"),
41 |                                         ("LC", "lc_file")))
42 | 
43 |     QUERY_OPTIONS = ["ra", "dec", "delta", "nearest", "ASAS"]
44 | 
45 |     def _getLightCurve(self, star, do_per=False, *args, **kwargs):
46 |         url = self.LC_URL.format(asas_id=star.name)
47 |         if do_per:
48 |             per = star.more.get("period", None)
49 |             if per:
50 |                 url = url[:-1] + "%f" % per
51 |                 self.LC_META["xlabel"] = "Period"
52 |                 self.LC_META["xlabel_unit"] = "phase"
53 | 
54 |         response = requests.get(url)
55 |         time = []
56 |         mag = []
57 |         err = []
58 |         for line in response.iter_lines():
59 |             line = line.strip()
60 |             if not line.startswith((" ", "#")):
61 |                 parts = line.split(self.DELIM)
62 |                 if len(parts) == 3:
63 |                     time.append(float(parts[self.TIME_COL]))
64 |                     mag.append(float(parts[self.MAG_COL]))
65 |                     err.append(float(parts[self.ERR_COL]) / self.ERR_MAG_RATIO)
66 | 
67 |         return time, mag, err
68 | 
69 |     def get_name(self, star_info):
70 |         return star_info.get("ASAS")


--------------------------------------------------------------------------------
/lcc/db_tier/connectors/macho.py:
--------------------------------------------------------------------------------
 1 | import collections
 2 | 
 3 | from lcc.db_tier.base_query import LightCurvesDb
 4 | from lcc.db_tier.vizier_tap_base import VizierTapBase
 5 | 
 6 | 
 7 | class Macho(VizierTapBase, LightCurvesDb):
 8 |     """
 9 |     Client for MACHO database of variable stars. It inherits `VizierTapBase` - see
10 |     documentation of this class to class attributes description.
11 | 
12 |     EXAMPLES
13 |     --------
14 |     queries = [{"Field": 1 , "Tile": 3441, "Seqn": 25},
15 |                {'dec': -69.3948,'ra': 75.3546, 'delta': 10}]
16 |     client = StarsProvider.getProvider("Macho", queries)
17 |     stars = client.getStars()
18 |     """
19 | 
20 |     TABLE = "II/247/machovar"
21 |     LC_URL = "http://cdsarc.u-strasbg.fr/viz-bin/nph-Plot/w/Vgraph/txt?II%2f247%2f.%2f{macho_name}&F=b%2br&P={period}&-x&0&1&-y&-&-&-&--bitmap-size&600x400"
22 | 
23 |     LC_FILE = ""
24 | 
25 |     LC_META = {"xlabel": "Time",
26 |                "xlabel_unit": "MJD (JD-2400000.5)",
27 |                "origin": "MACHO"}
28 | 
29 |     IDENT_MAP = {"Macho": ("Field", "Tile", "Seqn")}
30 |     MORE_MAP = collections.OrderedDict((("Class", "var_type"),
31 |                                         ("Vmag", "v_mag"),
32 |                                         ("Rmag", "r_mag"),
33 |                                         ("rPer", "period_r"),
34 |                                         ("bPer", "period_b")))
35 | 
36 |     QUERY_OPTION = ["ra", "dec", "delta", "nearest", "Field", "Tile", "Seqn"]
37 | 
38 |     def get_name(self, star_info):
39 |         return "{:.0f}.{:.0f}.{:.0f}".format(star_info["Field"],
40 |                                              star_info["Tile"],
41 |                                              star_info["Seqn"])


--------------------------------------------------------------------------------
/lcc/db_tier/stars_provider.py:
--------------------------------------------------------------------------------
 1 | from lcc.data_manager.package_reader import PackageReader
 2 | 
 3 | 
 4 | class StarsProvider(object):
 5 |     """
 6 |     Stars provider is an interface between end-user and database connectors. All
 7 |     database connectors have to inherit `StarsCatalog` class.
 8 | 
 9 |     Attributes
10 |     ----------
11 |     STARS_PROVIDER : dict
12 | 
13 |     """
14 | 
15 |     STARS_PROVIDERS = PackageReader().getClassesDict("connectors")
16 | 
17 |     @classmethod
18 |     def getProvider(cls, obtain_method, *obtain_params):
19 |         """
20 |         Get database connector via name of its class
21 | 
22 |         Parameters
23 |         -----------
24 |         obtain_method : str
25 |             Name of connector class
26 |         obtain_params :  list of dicts
27 |             List of queries
28 | 
29 |         Returns
30 |         --------
31 |         instance
32 |             Constructed database connector or uninstanced  if there is
33 |             no queries
34 |         """
35 | 
36 |         if obtain_method not in cls.STARS_PROVIDERS:
37 |             raise AttributeError(
38 |                 "Unresolved stars provider\nAvaible stars providers: %s" % list(cls.STARS_PROVIDERS.keys()))
39 | 
40 |         provider = cls.STARS_PROVIDERS[obtain_method]
41 | 
42 |         if len(obtain_params) == 0:
43 |             return provider
44 |         return provider(*obtain_params)
45 | 


--------------------------------------------------------------------------------
/lcc/entities/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/entities/__init__.py


--------------------------------------------------------------------------------
/lcc/entities/exceptions.py:
--------------------------------------------------------------------------------
 1 | class InvalidFilesPath(IOError):
 2 |     pass
 3 | 
 4 | 
 5 | class StarAttributeError(Exception):
 6 |     pass
 7 | 
 8 | 
 9 | class InvalidFile(IOError):
10 |     pass
11 | 
12 | 
13 | class QueryInputError(ValueError):
14 |     pass
15 | 
16 | 
17 | class NoInternetConnection(Exception):
18 |     pass
19 | 
20 | 
21 | class MandatoryKeyInQueryDictIsMissing(Exception):
22 |     pass
23 | 
24 | 
25 | class FailToParseName(Exception):
26 |     pass
27 | 
28 | 
29 | class InvalidFilteringParams(Exception):
30 |     pass
31 | 
32 | 
33 | class ArgumentValidationError(Exception):
34 |     pass
35 | 
36 | 
37 | class InvalidArgumentNumberError(Exception):
38 |     pass
39 | 
40 | 
41 | class InvalidReturnType(Exception):
42 |     pass
43 | 
44 | 
45 | class NotFilterTypeClass(Exception):
46 |     pass
47 | 
48 | 
49 | class StarAttributeNotSpecified(AttributeError):
50 |     pass
51 | 
52 | 
53 | class LearningError(Exception):
54 |     pass
55 | 
56 | 
57 | class InvalidOption(Exception):
58 |     pass
59 | 


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/lcc/examples/download_from_ogle.sh:
--------------------------------------------------------------------------------
1 | ../bin/filter_stars.py -i examples/query_ogle.txt -o examples/ -d "OgleII"
2 | 


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/lcc/examples/filter_folders_by_abbefilter.sh:
--------------------------------------------------------------------------------
1 | ../bin/filter_stars.py -d FileManager -i examples/query_folders.txt -f examples/AbbeValue_quasar.filter -o examples
2 | 


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/lcc/examples/filter_ogle_by_histvario.sh:
--------------------------------------------------------------------------------
1 | ../bin/filter_stars.py -i examples/query_ogle.txt -o examples/ -d "OgleII" -f examples/HistVario_quasars.filter
2 | 
3 | 


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/lcc/examples/prepare_query_folders.sh:
--------------------------------------------------------------------------------
1 | ../bin/prepare_query.py -o examples/query_folders.txt -p path -r "lpv;dpv" -p files_limit -r 10
2 | 


--------------------------------------------------------------------------------
/lcc/examples/prepare_query_ogle.sh:
--------------------------------------------------------------------------------
1 | ../bin/prepare_query.py -o examples/query_ogle.txt -p starid -r 1:10 -p target -r lmc -p field_num -r 1
2 | 


--------------------------------------------------------------------------------
/lcc/examples/prepare_tuning_abbe_filter.sh:
--------------------------------------------------------------------------------
1 | ../bin/prepare_query.py -o examples/tuning_abbe_filter.txt  -p bins -r 10:150:10
2 | 


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/lcc/examples/prepare_tuning_color_filter.sh:
--------------------------------------------------------------------------------
1 | ../bin/prepare_query.py -o examples/tuning_color_index.txt -p colors -r '["v_mag-i_mag","b_mag-v_mag"];["v_mag","i_mag"]'
2 | 


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/lcc/examples/prepare_tuning_color_filter2.sh:
--------------------------------------------------------------------------------
1 | ../bin/prepare_query.py -o examples/tuning_color_index2.txt -p colors -r '["b_mag - r_mag"]'
2 | 


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/lcc/examples/prepare_tuning_histvario_filter.sh:
--------------------------------------------------------------------------------
1 | ../bin/prepare_query.py -o examples/tuning_histvario_filter.txt -p hist_days_per_bin -r "97;80" -p vario_days_per_bin -r 9 -p vario_alphabet_size -r 16 -p hist_alphabet_size -r 7
2 | 


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/lcc/examples/tune_abbe_filter_from_folders.sh:
--------------------------------------------------------------------------------
1 | ../bin/make_filter.py  -i examples/tuning_abbe_filter.txt -f AbbeValueFilter -s quasars -c some_stars -d GaussianNBDec -o examples/AbbeValue_quasar.filter -l examples/AbbeValue_quasar
2 | 


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/lcc/examples/tune_from_local_db.sh:
--------------------------------------------------------------------------------
1 | ../bin/make_filter.py  -i examples/tuning_color_index2.txt -f ColorIndexFilter -s LOCAL:milliquas:examples/query_localdb.txt -c LOCAL:milliquas:examples/query_localdb2.txt -d GaussianNBDec -o examples/ColorIndex_quasars.filter -l examples/ColorIndex_quasars_filter
2 | 


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/lcc/examples/tune_histvario_filter_from_folders.sh:
--------------------------------------------------------------------------------
1 | ../bin/make_filter.py  -i examples/tuning_histvario_filter.txt -f ComparingFilter -s quasars:20 -c cepheids:5 -c stars:15 -d GaussianNBDec -o examples/HistVario_quasars.filter -l examples/HistVario_quasars
2 | 


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/lcc/examples/tune_histvario_filter_from_ogle.sh:
--------------------------------------------------------------------------------
1 | ../bin/make_filter.py  -i examples/tuning_histvario_filter.txt -f ComparingFilter -s QUERY:OgleII:examples/query_ogle.txt -c cepheids:5 -d GaussianNBDec -o examples/HistVario.filter -l examples/HistVario_random
2 | 


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/lcc/stars_processing/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/stars_processing/__init__.py


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/lcc/stars_processing/deciders/__init__.py:
--------------------------------------------------------------------------------
1 | from .neuron_decider import NeuronDecider
2 | from .supervised_deciders import (QDADec, LDADec, TreeDec, GaussianNBDec, GradBoostDec,
3 |                                  SVCDec, AdaBoostDec, ExtraTreesDec, RandomForestDec)
4 | from .custom_decider import CustomDecider


--------------------------------------------------------------------------------
/lcc/stars_processing/deciders/unsupervised/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc/stars_processing/deciders/unsupervised/__init__.py


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/lcc/stars_processing/deciders/unsupervised/k_means_decider.py:
--------------------------------------------------------------------------------
 1 | from matplotlib import pyplot as plt
 2 | from sklearn.cluster.k_means_ import KMeans
 3 | 
 4 | import numpy as np
 5 | from lcc.stars_processing.utilities.unsupervised_base import UnsupervisedBase
 6 | 
 7 | 
 8 | class KMeansDecider(UnsupervisedBase):
 9 |     '''
10 |     classdocs
11 |     '''
12 | 
13 |     def __init__(self, threshold=0.5, n_clusters=3):
14 |         '''
15 |         Constructor
16 |         '''
17 |         params = {"n_clusters": n_clusters}
18 |         super(KMeansDecider, self).__init__(
19 |             classifier=KMeans, params=params, threshold=threshold)
20 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/__init__.py:
--------------------------------------------------------------------------------
 1 | """There are implementations of filters"""
 2 | 
 3 | from .abbe_value_descr import AbbeValueDescr
 4 | from .color_index_descr import ColorIndexDescr
 5 | from .curve_density_descr import CurveDensityDescr
 6 | from .curve_descr import CurveDescr
 7 | from .curves_shape_descr import CurvesShapeDescr
 8 | from .hist_shape_descr import HistShapeDescr
 9 | from .kurtosis_desc import KurtosisDescr
10 | from .property_desc import PropertyDescr
11 | from .skewness_desc import SkewnessDescr
12 | from .variogram_shape_descr import VariogramShapeDescr
13 | from .variogram_slope_descr import VariogramSlopeDescr
14 | from .position_descriptor import PositionDescriptor
15 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/abbe_value_descr.py:
--------------------------------------------------------------------------------
 1 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 2 | 
 3 | 
 4 | class AbbeValueDescr(BaseDescriptor):
 5 | 
 6 |     """
 7 |     AbbeValueDescr describes stars by Abbe values
 8 | 
 9 |     Attributes
10 |     ----------
11 |     bins : int
12 |         Dimension of reduced light curve from which Abbe value
13 |         is calculated
14 |     """
15 |     LABEL = "Abbe value"
16 |     LC_NEEDED = True
17 | 
18 |     def __init__(self, bins=None):
19 |         """
20 |         Parameters
21 |         ----------
22 |         bins : int
23 |             Dimension of reduced light curve from which Abbe value
24 |             is calculated
25 | 
26 |         """
27 |         self.bins = bins
28 | 
29 |     def getFeatures(self, star):
30 |         """
31 |         Get  Abbe value
32 | 
33 |         Parameters
34 |         -----------
35 |         star : lcc.entities.star.Star object
36 |             Star to process
37 | 
38 |         Returns
39 |         -------
40 |         float
41 |             Abbe value of the investigated star
42 |         """
43 |         if not self.bins:
44 |             bins = len(star.lightCurve.time)
45 |         else:
46 |             bins = self.bins
47 | 
48 |         return star.lightCurve.getAbbe(bins=bins)
49 | 
50 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/curve_density_descr.py:
--------------------------------------------------------------------------------
 1 | 
 2 | 
 3 | from lcc.utils.data_analysis import to_ekvi_PAA
 4 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 5 | 
 6 | 
 7 | class CurveDensityDescr(BaseDescriptor):
 8 |     """
 9 |     This filter throw out stars with low density light curves. It means light
10 |     curves with huge non observing gaps or light curves with low amount
11 |     of observations
12 | 
13 |     Attributes
14 |     ----------
15 |     """
16 | 
17 |     LABEL = "Curve density [points per time lag]"
18 |     LC_NEEDED = True
19 | 
20 |     def getFeatures(self, star):
21 |         """
22 |         Get density of the star's light curve
23 | 
24 |         Parameters
25 |         -----------
26 |         star : lcc.entities.star.Star object
27 |             Star to process
28 | 
29 |         Returns
30 |         -------
31 |         list, iterable, int, float
32 |             Density (points per time lag) of the investigated star
33 |         """
34 |         x, _ = to_ekvi_PAA(star.lightCurve.time, star.lightCurve.mag)
35 |         ren = x.max() - x.min()
36 |         return len(x) / ren
37 | 
38 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/hist_shape_descr.py:
--------------------------------------------------------------------------------
 1 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 2 | from lcc.stars_processing.utilities.compare import ComparativeBase
 3 | from lcc.stars_processing.utilities.symbolic_representation import SymbolicRepresentation
 4 | 
 5 | 
 6 | class HistShapeDescr(SymbolicRepresentation, ComparativeBase, BaseDescriptor):
 7 |     """
 8 |     This descriptor compares histograms of light curves of inspected star
 9 |     with the template
10 | 
11 |     Attributes
12 |     -----------
13 |     comp_stars : list
14 |         Template stars
15 | 
16 |     bins : int
17 |         Length of result histogram
18 | 
19 |     alphabet_size : int
20 |         Range of of used letters
21 | 
22 |     slide : bool
23 |         If True, words with different lengths are dynamically compared
24 |         by sliding shorter word thru longer
25 | 
26 |     slide : bool
27 |         If True, words with different lengths are dynamically compared
28 |         by sliding shorter word thru longer
29 | 
30 |     meth : str
31 |         Method key for calculating distance from comparative objects
32 | 
33 |         average     : take mean distance in each coordinate as
34 |                       object coordinate
35 |         closest     : take coordinate with closest distance as
36 |                       object coordinate
37 |         best'n'   : take best n scores of match, it can be integer or percentage float (0-1).
38 |                     for example best10 takes 10 best matches, best0.5 takes 50 % best matches of the total
39 |     """
40 | 
41 |     LABEL = ["Dissimilarity of the light curves histogram from the template"]
42 | 
43 |     def __init__(self, comp_stars, bins, alphabet_size, slide=False, meth="average"):
44 |         """
45 |         Parameters
46 |         -----------
47 |         comp_stars : list
48 |             Template stars
49 | 
50 |         hist_bins : int
51 |             Length of result histogram
52 | 
53 |         hist_alphabet_size : int
54 |             Range of of used letters
55 | 
56 |         slide : bool
57 |             If True, words with different lengths are dynamically compared
58 |             by sliding shorter word thru longer
59 | 
60 |         meth : str
61 |             Method key for calculating distance from comparative objects
62 | 
63 |             average     : take mean distance in each coordinate as
64 |                           object coordinate
65 |             closest     : take coordinate with closest distance as
66 |                           object coordinate
67 |             best'n'   : take best n scores of match, it can be integer or percentage float (0-1).
68 |                         for example best10 takes 10 best matches, best0.5 takes 50 % best matches of the total
69 |         """
70 |         self.comp_stars = comp_stars
71 |         self.bins = bins
72 |         self.alphabet_size = alphabet_size
73 |         self.slide = slide
74 |         self.meth = meth
75 | 
76 |     def getWord(self, star):
77 |         """
78 |         Parameters
79 |         -----------
80 |         Star object with light curve
81 | 
82 |         Returns
83 |         -------
84 |         str
85 |             String representation of light curve's histogram
86 |         """
87 |         return self._getWord(star.lightCurve.getHistogram(bins=self.bins)[0], self.bins, self.alphabet_size)
88 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/kurtosis_desc.py:
--------------------------------------------------------------------------------
 1 | import numpy as np
 2 | from scipy.stats import kurtosis
 3 | 
 4 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 5 | from lcc.utils.data_analysis import to_ekvi_PAA
 6 | 
 7 | 
 8 | class KurtosisDescr(BaseDescriptor):
 9 | 
10 |     """
11 |     KurtosisDescr describes stars by kurtosis
12 | 
13 |     Attributes
14 |     ----------
15 |     bins : int, NoneType
16 |         Dimension of reduced light curve. If it is `None` whole curve is taken.
17 | 
18 |     absolute : bool
19 |         Absolute value of kurtosis is taken if it is `True`
20 |     """
21 |     LABEL = "Kurtosis"
22 |     LC_NEEDED = True
23 | 
24 |     def __init__(self, bins=None, absolute=False):
25 |         """
26 |         Parameters
27 |         ----------
28 |         bins : int, NoneType
29 |             Dimension of reduced light curve. If it is `None` whole curve is taken.
30 | 
31 |         absolute : bool
32 |             Absolute value of kurtosis is taken if it is `True`
33 |         """
34 |         self.bins = bins
35 |         self.absolute = absolute
36 | 
37 |     def getFeatures(self, star):
38 |         """
39 |         Get  skewness
40 | 
41 |         Parameters
42 |         -----------
43 |         star : lcc.entities.star.Star object
44 |             Star to process
45 | 
46 |         Returns
47 |         -------
48 |         float
49 |             Kurtosis of investigated star
50 |         """
51 |         lc = star.lightCurve
52 |         if self.bins:
53 |             _, mags = to_ekvi_PAA(lc.time, lc.mag, self.bins)
54 |         else:
55 |             mags = lc.mag
56 |         kurt = kurtosis(mags)
57 | 
58 |         if self.absolute:
59 |             kurt = abs(kurt)
60 | 
61 |         return kurt
62 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/position_descriptor.py:
--------------------------------------------------------------------------------
 1 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 2 | 
 3 | 
 4 | class PositionDescriptor(BaseDescriptor):
 5 |     """
 6 |     Describe stars according their position on the sky
 7 |     """
 8 | 
 9 |     LABEL = ["Right ascension", "Declination"]
10 |     LC_NEEDED = False
11 | 
12 |     def getFeatures(self, star):
13 |         """
14 |         Get coordinates
15 | 
16 |         Parameters
17 |         -----------
18 |         star : lcc.entities.star.Star object
19 |             Star to process
20 | 
21 |         Returns
22 |         -------
23 |         list
24 |             Abbe value of the investigated star
25 |         """
26 |         if star.coo:
27 |             return [star.coo.ra.degree, star.coo.dec.degree]
28 |         else:
29 |             return [None, None]
30 | 
31 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/property_desc.py:
--------------------------------------------------------------------------------
 1 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 2 | 
 3 | 
 4 | class PropertyDescr(BaseDescriptor):
 5 |     """
 6 |     Descriptor which using star's attributes
 7 | 
 8 |     Attributes
 9 |     -----------
10 |     attribute_names : iterable, str
11 |         Keys of star's objects `more` attribute
12 | 	
13 | 	For example:
14 | 	    `["pm_ra", "pm_de"]`
15 | 
16 |     ifnot : str, NoneType
17 |         Value of coordinates which will be assigned if there is no
18 |         `attribute_name` value
19 | 
20 | 
21 |     """
22 | 
23 |     LABEL = "Star's property"
24 |     LC_NEEDED = False
25 | 
26 |     def __init__(self, attribute_names, ifnot=None):
27 |         """
28 |         Parameters
29 |         -----------
30 |         attribute_names : iterable, str
31 |             Keys of star's objects `more` attribute
32 | 
33 |         ifnot : str, NoneType
34 |             Value of coordinates which will be assigned if there is no
35 |             `attribute_name` value
36 |         """
37 |         if hasattr(attribute_names, "__iter__"):
38 |             attribute_names = list(attribute_names)
39 |         else:
40 |             attribute_names = [attribute_names]
41 | 
42 |         self.attribute_names = attribute_names
43 |         self.ifnot = ifnot
44 | 
45 |         self.LABEL = attribute_names
46 | 
47 |     def getFeatures(self, star):
48 |         """
49 |         Get desired attributes
50 | 
51 |         Parameters
52 |         -----------
53 |         star : lcc.entities.star.Star object
54 |             Star to process
55 | 
56 |         Returns
57 |         -------
58 |         list
59 |             Desired more attributes of the investigated star
60 |         """
61 |         coo = [star.more.get(attribute_name, self.ifnot)
62 |                for attribute_name in self.attribute_names]
63 |         if coo != self.ifnot:
64 |             try:
65 |                 coo = [float(c) for c in coo]
66 |             except ValueError:
67 |                 raise ValueError(
68 |                     "Attributes of stars for PropertyDescriptors have to be numbers.\nGot: %s" % coo)
69 | 
70 |         return coo
71 | 


--------------------------------------------------------------------------------
/lcc/stars_processing/descriptors/skewness_desc.py:
--------------------------------------------------------------------------------
 1 | import numpy as np
 2 | from scipy.stats import skew
 3 | 
 4 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 5 | from lcc.utils.data_analysis import to_ekvi_PAA
 6 | 
 7 | 
 8 | class SkewnessDescr(BaseDescriptor):
 9 | 
10 |     """
11 |     SkewnessDescr describes stars by skewness
12 | 
13 |     Attributes
14 |     ----------
15 |     bins : int, NoneType
16 |         Dimension of reduced light curve. If it is `None` whole curve is taken.
17 | 
18 |     absolute : bool
19 |         Absolute value of skewness is taken if it is `True`
20 |     """
21 |     LABEL = "Skewness"
22 |     LC_NEEDED = True
23 | 
24 |     def __init__(self, bins=None, absolute=False):
25 |         """
26 |         Parameters
27 |         ----------
28 |         bins : int, NoneType
29 |             Dimension of reduced light curve. If it is `None` whole curve is taken.
30 | 
31 |         absolute : bool
32 |             Absolute value of skewness is taken if it is True
33 |         """
34 |         self.bins = bins
35 |         self.absolute = absolute
36 | 
37 |     def getFeatures(self, star):
38 |         """
39 |         Get skewness
40 | 
41 |         Parameters
42 |         -----------
43 |         star : lcc.entities.star.Star object
44 |             Star to process
45 | 
46 |         Returns
47 |         -------
48 |         float
49 |             Skewness of the investigated star
50 |         """
51 |         lc = star.lightCurve
52 |         if self.bins:
53 |             _, mags = to_ekvi_PAA(lc.time, lc.mag, self.bins)
54 |         else:
55 |             mags = lc.mag
56 |         sk = skew(mags)
57 | 
58 |         if self.absolute:
59 |             sk = abs(sk)
60 |         return sk
61 | 
62 | 
63 | 


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/lcc/stars_processing/descriptors/variogram_shape_descr.py:
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 1 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 2 | from lcc.stars_processing.utilities.compare import ComparativeBase
 3 | from lcc.stars_processing.utilities.symbolic_representation import SymbolicRepresentation
 4 | 
 5 | 
 6 | class VariogramShapeDescr(SymbolicRepresentation, ComparativeBase, BaseDescriptor):
 7 |     """
 8 |     This descriptor compares variograms of light curves of inspected star
 9 |     with the template in symbolic representation.
10 | 
11 |     Attributes
12 |     -----------
13 |     comp_stars : list
14 |         Template stars
15 | 
16 |     bins : int
17 |         Number of bins
18 | 
19 |     alphabet_size : int
20 |         Range of of used letters
21 | 
22 |     slide : bool
23 |         If True, words with different lengths are dynamically compared
24 |         by sliding shorter word thru longer
25 | 
26 |     meth : str
27 |         Method key for calculating distance from comparative objects
28 | 
29 |         average     : take mean distance in each coordinate as
30 |                       object coordinate
31 |         closest     : take coordinate with closest distance as
32 |                       object coordinate
33 |         best'n'   : take best n scores of match, it can be integer or percentage float (0-1).
34 |                     for example best10 takes 10 best matches, best0.5 takes 50 % best matches of the total
35 |     """
36 | 
37 |     LABEL = ["Dissimilarity of the light curve's variogram from the template"]
38 | 
39 |     def __init__(self, comp_stars, bins, alphabet_size, slide=False, meth="average"):
40 |         """
41 |         Parameters
42 |         -----------
43 |         comp_stars : list
44 |             Template stars
45 | 
46 |         bins : int
47 |             Number of bins
48 | 
49 |         alphabet_size : int
50 |             Range of of used letters
51 | 
52 |         slide : bool
53 |             If True, words with different lengths are dynamically compared
54 |             by sliding shorter word thru longer
55 | 
56 |         meth : str
57 |             Method key for calculating distance from comparative objects
58 | 
59 |             average     : take mean distance in each coordinate as
60 |                           object coordinate
61 |             closest     : take coordinate with closest distance as
62 |                           object coordinate
63 |             best'n'   : take best n scores of match, it can be integer or percentage float (0-1).
64 |                         for example best10 takes 10 best matches, best0.5 takes 50 % best matches of the total
65 |         """
66 |         self.comp_stars = comp_stars
67 |         self.bins = bins
68 |         self.alphabet_size = alphabet_size
69 |         self.slide = slide
70 |         self.meth = meth
71 | 
72 |     def getWord(self, star):
73 |         """
74 |         Parameters
75 |         -----------
76 |         Star object with a light curve
77 | 
78 |         Returns
79 |         --------
80 |         str
81 |             String representation of light curve's variogram
82 |         """
83 |         return self._getWord(star.lightCurve.getVariogram(bins=self.bins)[1],
84 |                              self.bins, self.alphabet_size)
85 | 


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/lcc/stars_processing/descriptors/variogram_slope_descr.py:
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 1 | import numpy as np
 2 | from lcc.stars_processing.utilities.base_descriptor import BaseDescriptor
 3 | 
 4 | 
 5 | class VariogramSlopeDescr(BaseDescriptor):
 6 |     """
 7 |     This filter sorting stars according slopes of their variograms
 8 | 
 9 |     Attributes
10 |     ----------
11 |     days_per_bin : float
12 |         Rate between light curve dimension and days
13 | 
14 |     absolute : bool
15 |         If True absolute value of slope is taken
16 |     """
17 | 
18 |     LABEL = "Light curve's variogram slope"
19 |     LC_NEEDED = True
20 | 
21 |     def __init__(self, days_per_bin, absolute=False):
22 |         """
23 |         Parameters
24 |         ----------
25 |         days_per_bin : float
26 |             Rate between light curve dimension and days
27 | 
28 |         absolute : bool
29 |             If True absolute value of slope is taken
30 |         """
31 |         self.days_per_bin = days_per_bin
32 |         self.absolute = absolute
33 | 
34 |     def getFeatures(self, star):
35 |         """
36 |         Get variogram slope
37 | 
38 |         Parameters
39 |         -----------
40 |         star : lcc.entities.star.Star object
41 |             Star to process
42 | 
43 |         Returns
44 |         -------
45 |         float
46 |             Variogram slope of the investigated star
47 |         """
48 |         x, y = star.lightCurve.getVariogram(
49 |             days_per_bin=self.days_per_bin)
50 |         slope = np.polyfit(x, y, 1)[0]
51 |         if self.absolute:
52 |             return abs(slope)
53 |         return slope
54 | 
55 | 


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/lcc/stars_processing/stars_filter.pyc:
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/lcc/stars_processing/systematic_search/__init__.py:
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/lcc/stars_processing/systematic_search/worker.py:
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 1 | 
 2 | import multiprocessing
 3 | import os
 4 | 
 5 | import redis
 6 | from rq import Worker
 7 | 
 8 | import keras
 9 | 
10 | connection = redis.Redis(host=os.environ.get("LCC_REDIS_HOST", "localhost"),
11 |                          port=os.environ.get("LCC_REDIS_PORT", 6379))
12 | 
13 | 
14 | def run_worker(burst=False):
15 |     w = Worker(queues=[os.environ.get("LCC_QUEUE_NAME", "lcc")], connection=connection)
16 |     w.work(burst=burst)
17 | 
18 | 
19 | def run_workers(n_workers=None, burst=False):
20 |     if not n_workers:
21 |         n_workers = int(os.environ.get("LCC_WORKERS_NUM", "4"))
22 |     jobs = [multiprocessing.Process(target=run_worker, args=(burst,)) for _ in range(n_workers)]
23 | 
24 |     for i in range(len(jobs)):
25 |         print("Running the worker {}..".format(i))
26 |         jobs[i].start()
27 | 
28 | 
29 | if __name__ == '__main__':
30 |     run_workers()
31 | 
32 | 
33 | 


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/lcc/stars_processing/tools/__init__.py:
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/lcc/stars_processing/utilities/__init__.py:
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1 | '''There are managers responsible for stars to have certain parameters for filtering'''


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/lcc/stars_processing/utilities/compare.py:
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  1 | import abc
  2 | import logging
  3 | 
  4 | import numpy as np
  5 | 
  6 | from lcc.entities.exceptions import QueryInputError
  7 | from lcc.utils.helpers import convert_input_value
  8 | 
  9 | 
 10 | class ComparativeBase(abc.ABC):
 11 |     """
 12 |     This class is responsible for comparing light curves of inspected stars
 13 |     with the template stars
 14 | 
 15 |     Attributes
 16 |     -----------
 17 |     compar_stars : list, iterable
 18 |         List of Star objects which represent searched group of star objects
 19 |     """
 20 | 
 21 |     def compareTwoStars(self, *args, **kwargs):
 22 |         raise NotImplemented()
 23 | 
 24 |     def loadCompStars(self, comp_stars):
 25 |         """
 26 |         Load comparative stars for the template sample
 27 | 
 28 |         Parameters
 29 |         ----------
 30 |         comp_stars : list
 31 |             Stars for the template
 32 | 
 33 |         Returns
 34 |         -------
 35 |             None
 36 |         """
 37 |         self.comp_stars = comp_stars
 38 | 
 39 |     def getFeatures(self, star):
 40 |         """
 41 |         Get difference in symbolic space of the investigated star from the template
 42 | 
 43 |         Parameters
 44 |         -----------
 45 |         star : lcc.entities.star.Star object
 46 |             Star to process
 47 | 
 48 |         Returns
 49 |         -------
 50 |         list
 51 |             Difference in symbolic space of the investigated star from the template
 52 |         """
 53 |         if hasattr(self, "meth"):
 54 |             meth = self.meth
 55 |         else:
 56 |             meth = "average"
 57 | 
 58 |         coords = [x for x in self._filtOneStar(star, search_opt="all") if x is not None]
 59 |         logging.debug("Coords: %s" % coords)
 60 | 
 61 |         if meth == "closest":
 62 |             return np.min(coords)
 63 | 
 64 |         elif meth == "average":
 65 |             return np.mean(coords)
 66 | 
 67 |         elif meth.startswith("best"):
 68 |             n = convert_input_value(meth[4:])
 69 | 
 70 |             if isinstance(n, float):
 71 |                 n = int(len(coords)*n)
 72 | 
 73 |             if isinstance(n, str):
 74 |                 n = 1
 75 | 
 76 |             if not meth:
 77 |                 raise QueryInputError("""Unresolved coordinates calculation method. String 'best' has to
 78 |                 be followed by integer or float number""")
 79 | 
 80 |             return np.mean(np.sort(coords)[:n])
 81 | 
 82 |         else:
 83 |             raise QueryInputError("Unresolved coordinates calculation method")
 84 | 
 85 |     def _filtOneStar(self, star, *args, **kwargs):
 86 |         """
 87 |         Calculate distances of inspected star and template stars
 88 | 
 89 |         Parameters
 90 |         -----------
 91 |         star: Star object
 92 |             Star to filter
 93 | 
 94 |         Returns
 95 |         --------
 96 |         list
 97 |             List of all dissimilarities of inspected star to template stars
 98 |         """
 99 | 
100 |         coordinates = []
101 |         # Try every template star
102 |         for comp_star in self.comp_stars:
103 |             if comp_star.lightCurve and star.lightCurve:
104 |                 coordinates.append(self.compareTwoStars(star, comp_star))
105 |             else:
106 |                 coordinates.append(None)
107 |         return coordinates
108 | 


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/lcc/stars_processing/utilities/superv_base_decider.py:
--------------------------------------------------------------------------------
  1 | import numpy as np
  2 | 
  3 | 
  4 | from lcc.entities.exceptions import LearningError, QueryInputError
  5 | from lcc.stars_processing.utilities.base_decider import BaseDecider
  6 | from lcc.utils.helpers import check_depth
  7 | 
  8 | 
  9 | class SupervisedBase(BaseDecider):
 10 |     """
 11 |     Base class for `sklearn` library supervised classes transformed
 12 |     to the package content. It is not intended to use this directly,
 13 |     but thru certain method subclasses.
 14 | 
 15 |     Attributes
 16 |     ----------
 17 |     threshold : float
 18 |         Border probability value (objects with probability higher then this
 19 |         value is considered as searched object)
 20 | 
 21 |     learner : sklearn object
 22 |         Learner object for desired method of supervised learning
 23 |     """
 24 | 
 25 |     def __init__(self, clf, threshold=0.5):
 26 |         """
 27 |         Parameters
 28 |         -----------
 29 |         threshold: float
 30 |             Border probability value (objects with probability higher then this
 31 |             value is considered as searched object)
 32 | 
 33 |         learner: sklearn instance
 34 |             Learner object for desired method of supervised learning
 35 |         """
 36 | 
 37 |         self.threshold = threshold
 38 |         self.learner = clf
 39 | 
 40 |     def learn(self, right_coords, wrong_coords):
 41 |         """
 42 |         Learn to recognize objects
 43 | 
 44 |         Parameters
 45 |         -----------
 46 |         right_coords: iterable
 47 |             List of coordinates (list of numbers) of searched objects
 48 | 
 49 |         wrong_coords: iterable
 50 |             List of coordinates (list of numbers) of contamination objects
 51 | 
 52 |         Returns
 53 |         --------
 54 |         NoneType
 55 |             None
 56 |         """
 57 |         right_coords = list(right_coords)
 58 |         wrong_coords = list(wrong_coords)
 59 | 
 60 |         if not len(right_coords) or not len(wrong_coords):
 61 |             raise QueryInputError(
 62 |                 "Decider can't be learned on an empty sample\nGot\tsearched:%s\tothers%s" % (right_coords, wrong_coords))
 63 | 
 64 |         y = [1 for i in range(len(right_coords))]
 65 |         y += [0 for i in range(len(wrong_coords))]
 66 |         self.X = np.array(right_coords + wrong_coords)
 67 |         self.y = np.array(y)
 68 | 
 69 |         if not self.X.any() or not self.y.any():
 70 |             raise QueryInputError(
 71 |                 "No stars have an attribute which are needed by filter")
 72 | 
 73 |         try:
 74 |             self.learner.fit(self.X, self.y)
 75 |         except Exception as e:
 76 |             raise LearningError(str(e) +
 77 |                                 "\nCould not learn decider on the dataset:\nX = %s\n\nlabels = %s" % (self.X, self.y))
 78 | 
 79 |     def evaluate(self, coords):
 80 |         """
 81 |         Get probability of membership
 82 | 
 83 |         Parameters
 84 |         ----------
 85 |         coords : list of lists
 86 |             List of prameter space coordinates
 87 | 
 88 |         Returns
 89 |         -------
 90 |         list of floats
 91 |             List of probabilities
 92 |         """
 93 |         # TODO:
 94 |         # if coords != np.ndarray: coords = np.array( coords )
 95 |         # checkDepth(coords, 2)
 96 |         prediction = self.learner.predict_proba(coords)[:, 1]
 97 |         check_depth(prediction, 1)
 98 |         where_are_NaNs = np.isnan(prediction)
 99 |         prediction[where_are_NaNs] = 0
100 |         return prediction
101 | 


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/lcc/stars_processing/utilities/symbolic_representation.py:
--------------------------------------------------------------------------------
 1 | import abc
 2 | import logging
 3 | 
 4 | import numpy as np
 5 | 
 6 | from lcc.stars_processing.utilities.sax import SAX
 7 | 
 8 | 
 9 | class SymbolicRepresentation(abc.ABC):
10 |     """
11 |     This common class for all descriptors based on symbolic representation
12 |     of data.
13 |     """
14 | 
15 |     def compareTwoStars(self, star, comp_star):
16 |         """
17 |         Compare two stars according to a filter implementation
18 | 
19 |         Parameters
20 |         ----------
21 |         star : `Star` instance
22 |             Star to compare
23 | 
24 |         comp_star : `Star` instance
25 |             Star to compare
26 | 
27 |         Returns
28 |         -------
29 |         float
30 |             Dissimilarity of two stars
31 |         """
32 |         curve_len = np.max(
33 |             [len(star.lightCurve.mag), len(comp_star.lightCurve.mag)])
34 | 
35 |         if not self.slide or not hasattr(self, "getWords"):
36 |             inspected_word = self.getWord(star)
37 |             comp_word = self.getWord(comp_star)
38 |             logging.debug("Comparing {0} and {1}".format(inspected_word, comp_word))
39 |             score = self._getDissmilarity(inspected_word, comp_word, curve_len)
40 | 
41 |         else:
42 |             one_word, words = self.getWords(comp_star, star)
43 |             logging.debug("Comparing {0} and {1}".format(one_word, words))
44 |             score = self._getDissmilaritySlide(one_word, words)
45 | 
46 |         logging.debug("Score is {}".format(score))
47 |         return score
48 | 
49 |     def _getWord(self, x, word_size, alphabet_size):
50 |         self.sax = SAX(word_size, alphabet_size)
51 |         return self.sax.to_letter_rep(x)[0]
52 | 
53 |     def _getDissmilaritySlide(self, sliding_word, words):
54 |         """
55 |         This method go through string curve of a star and trying to match filter
56 |         sentence pattern.
57 |         """
58 |         best_score = 1e9
59 |         for word in words:
60 |             score = self.sax.compare_strings(word, sliding_word)
61 |             if score < best_score:
62 |                 best_score = score
63 |         return best_score
64 | 
65 |     def _getDissmilarity(self, inspected_word, filter_word, curve_len):
66 |         """
67 |         This method go through string curve of a star and trying to match filter
68 |         sentence pattern.
69 |         """
70 |         if not inspected_word or not filter_word:
71 |             raise Exception("There are no words for comparing")
72 | 
73 |         shift = 0
74 |         # Case of shorter filter word then star word
75 |         if len(filter_word) < len(inspected_word):
76 |             word_a = filter_word
77 |             word_b = inspected_word
78 |         else:
79 |             word_b = filter_word
80 |             word_a = inspected_word
81 | 
82 |         a_word_size = len(word_a)
83 |         b_word_size = len(word_b)
84 |         # Shift shorter word through longer word and look for match
85 |         best_score = 1e9
86 |         while a_word_size + shift <= b_word_size:
87 |             word = word_b[shift:shift + a_word_size]
88 |             score = self.sax.compare_strings(word, word_a)
89 |             if score < best_score:
90 |                 best_score = score
91 |             shift += 1
92 |             if not self.slide:
93 |                 break
94 |         return best_score
95 | 


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/lcc/stars_processing/utilities/unsupervised_base.py:
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 1 | from matplotlib import pyplot as plt
 2 | 
 3 | import numpy as np
 4 | from lcc.stars_processing.utilities.base_decider import BaseDecider
 5 | from lcc.entities.exceptions import QueryInputError
 6 | 
 7 | 
 8 | class UnsupervisedBase(BaseDecider):
 9 |     '''
10 |     classdocs
11 |     '''
12 | 
13 |     def __init__(self,  classifier, params, threshold=0.5, **kwargs):
14 |         super(UnsupervisedBase, self).__init__(**kwargs)
15 |         self.classifier = classifier(**params)
16 | 
17 |     def learn(self, coords):
18 |         coords = [c for c in coords if not np.NaN in c and not None in c]
19 |         if coords:
20 |             self.X = np.array(coords)
21 |             self.classifier.fit(coords)
22 |         else:
23 |             raise QueryInputError("No coordinates for learning")
24 | 
25 |     def evaluate(self, star_coords):
26 |         return self.classifier.predict(star_coords)
27 | 


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/lcc/utils/__init__.py:
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/lcc/utils/output_process_modules.py:
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 1 | 
 2 | import os
 3 | import pickle
 4 | 
 5 | from lcc.entities.exceptions import InvalidFilesPath, InvalidFile
 6 | 
 7 | 
 8 | def saveIntoFile(obj, path=".", file_name="saved_object.pickle",
 9 |                  folder_name=None):
10 |     """
11 |     This  method serialize object (save it into file)
12 | 
13 |     obj : object
14 |         Object to serialize
15 | 
16 |     path : str
17 |         Path to the folder
18 | 
19 |     file_name : str
20 |         Name of result file
21 | 
22 |     folder_name : str
23 |         Name of folder
24 | 
25 |     Returns
26 |     -------
27 |         None
28 |     """
29 | 
30 |     path_with_name = "%s/%s" % (path, file_name)
31 |     if folder_name:
32 |         os.makedirs(path_with_name + folder_name)
33 |         path_with_name = "%s/%s/%s" % (path, folder_name, file_name)
34 |     try:
35 |         with open(path_with_name, "wb") as output:
36 |             pickle.dump(obj, output, pickle.HIGHEST_PROTOCOL)
37 |         print("Object has been saved into %s/%s" % (path, file_name))
38 |     except IOError:
39 |         raise InvalidFilesPath("Path: %s\tfile name: %s" % (path, file_name))
40 | 
41 | 
42 | def loadFromFile(file_name="saved_object.pickle"):
43 |     """
44 |     Open object from file
45 | 
46 |     Parameters
47 |     ----------
48 |     file_name : str
49 |         Name of the serialized file
50 | 
51 |     Returns
52 |     -------
53 |     object
54 |         Loaded object
55 |     """
56 | 
57 |     try:
58 |         with open(file_name, "rb") as inputToLoad:
59 |             loaded_object = pickle.load(inputToLoad)
60 |         return loaded_object
61 |     except IOError:
62 |         raise InvalidFilesPath
63 |     except ImportError as e:
64 |         raise InvalidFile(
65 |             "Structure of project has been changed since saving this object: %s" % str(e))
66 |     except TypeError:
67 |         return pickle.load(file_name)
68 | 


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/lcc_web/web/LCCwebApp/.gitignore:
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1 | /__init__.pyc
2 | /settings.pyc
3 | /urls.pyc
4 | /wsgi.pyc
5 | 


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/lcc_web/web/LCCwebApp/urls.py:
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 1 | """LCCwebApp URL Configuration
 2 | 
 3 | The `urlpatterns` list routes URLs to views. For more information please see:
 4 |     https://docs.djangoproject.com/en/1.10/topics/http/urls/
 5 | Examples:
 6 | Function views
 7 |     1. Add an import:  from my_app import views
 8 |     2. Add a URL to urlpatterns:  url(r'^$', views.home, name='home')
 9 | Class-based views
10 |     1. Add an import:  from other_app.views import Home
11 |     2. Add a URL to urlpatterns:  url(r'^$', Home.as_view(), name='home')
12 | Including another URLconf
13 |     1. Import the include() function: from django.conf.urls import url, include
14 |     2. Add a URL to urlpatterns:  url(r'^blog/', include('blog.urls'))
15 | """
16 | from django.conf.urls import url, include
17 | from django.contrib import admin
18 | import os
19 | 
20 | app_patterns = [
21 |     url(r'^admin/', admin.site.urls),
22 |     url(r'', include('interface.urls')),
23 | ]
24 | urlpatterns = app_patterns
25 | 
26 | if os.environ.get('DOCKYARD_APP_CONTEXT') is not None:
27 |     prefix = os.environ['DOCKYARD_APP_CONTEXT']
28 |     urlpatterns = [
29 |         url(r'^' + prefix + '/', include(app_patterns))
30 |     ]
31 | 


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/lcc_web/web/LCCwebApp/wsgi.py:
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 1 | """
 2 | WSGI config for LCCwebApp project.
 3 | 
 4 | It exposes the WSGI callable as a module-level variable named ``application``.
 5 | 
 6 | For more information on this file, see
 7 | https://docs.djangoproject.com/en/1.10/howto/deployment/wsgi/
 8 | """
 9 | 
10 | import os
11 | 
12 | from django.core.wsgi import get_wsgi_application
13 | 
14 | os.environ.setdefault("DJANGO_SETTINGS_MODULE", "LCCwebApp.settings")
15 | 
16 | application = get_wsgi_application()
17 | 


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/lcc_web/web/interface/.gitignore:
--------------------------------------------------------------------------------
1 | /__init__.pyc
2 | /admin.pyc
3 | /forms.pyc
4 | /helpers.pyc
5 | /models.pyc
6 | /urls.pyc
7 | /views.pyc
8 | 


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/lcc_web/web/interface/admin.py:
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1 | from django.contrib import admin
2 | 
3 | # Register your models here.
4 | 
5 | from .models import DbQuery, StarsFilter
6 | 
7 | admin.site.register(DbQuery)
8 | admin.site.register(StarsFilter)


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/lcc_web/web/interface/apps.py:
--------------------------------------------------------------------------------
1 | from __future__ import unicode_literals
2 | 
3 | from django.apps import AppConfig
4 | 
5 | 
6 | class InterfaceConfig(AppConfig):
7 |     name = 'interface'
8 | 


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/lcc_web/web/interface/forms.py:
--------------------------------------------------------------------------------
 1 | from django import forms
 2 | 
 3 | 
 4 | class LoginForm(forms.Form):
 5 | 
 6 |     user_name = forms.CharField(label='Your name', max_length=100)
 7 |     password = forms.CharField(widget=forms.PasswordInput)
 8 | 
 9 | 
10 | 


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/lcc_web/web/interface/migrations/.gitignore:
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1 | /__init__.pyc
2 | 


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/lcc_web/web/interface/migrations/0001_initial.py:
--------------------------------------------------------------------------------
 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-13 18:11
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.conf import settings
 6 | from django.db import migrations, models
 7 | import django.db.models.deletion
 8 | import django.utils.timezone
 9 | 
10 | 
11 | class Migration(migrations.Migration):
12 | 
13 |     initial = True
14 | 
15 |     dependencies = [
16 |         migrations.swappable_dependency(settings.AUTH_USER_MODEL),
17 |     ]
18 | 
19 |     operations = [
20 |         migrations.CreateModel(
21 |             name='DbQuery',
22 |             fields=[
23 |                 ('id', models.AutoField(primary_key=True, serialize=False)),
24 |                 ('status', models.CharField(default='Not started', max_length=15)),
25 |                 ('start_date', models.DateTimeField(default=django.utils.timezone.now)),
26 |                 ('finish_date', models.DateTimeField(default=None)),
27 |                 ('used_filters', models.IntegerField()),
28 |                 ('connectors', models.ManyToManyField(related_name='_dbquery_connectors_+', to='interface.DbQuery')),
29 |                 ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
30 |             ],
31 |         ),
32 |         migrations.CreateModel(
33 |             name='StarsFilter',
34 |             fields=[
35 |                 ('id', models.AutoField(primary_key=True, serialize=False)),
36 |                 ('status', models.CharField(default='Not started', max_length=15)),
37 |                 ('start_date', models.DateTimeField(default=django.utils.timezone.now)),
38 |                 ('finish_date', models.DateTimeField(default=None)),
39 |                 ('deciders', models.ManyToManyField(related_name='_starsfilter_deciders_+', to='interface.StarsFilter')),
40 |                 ('descriptors', models.ManyToManyField(related_name='_starsfilter_descriptors_+', to='interface.StarsFilter')),
41 |                 ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
42 |             ],
43 |         ),
44 |     ]
45 | 


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/lcc_web/web/interface/migrations/0002_auto_20170313_1922.py:
--------------------------------------------------------------------------------
 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-13 18:22
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0001_initial'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.RemoveField(
16 |             model_name='starsfilter',
17 |             name='deciders',
18 |         ),
19 |         migrations.RemoveField(
20 |             model_name='starsfilter',
21 |             name='descriptors',
22 |         ),
23 |     ]
24 | 


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/lcc_web/web/interface/migrations/0003_auto_20170313_1933.py:
--------------------------------------------------------------------------------
 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-13 18:33
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations, models
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0002_auto_20170313_1922'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.AlterField(
16 |             model_name='starsfilter',
17 |             name='finish_date',
18 |             field=models.DateTimeField(default=None, null=True),
19 |         ),
20 |     ]
21 | 


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/lcc_web/web/interface/migrations/0004_auto_20170313_1952.py:
--------------------------------------------------------------------------------
 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-13 18:52
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations, models
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0003_auto_20170313_1933'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.AddField(
16 |             model_name='starsfilter',
17 |             name='deciders',
18 |             field=models.TextField(default=''),
19 |         ),
20 |         migrations.AddField(
21 |             model_name='starsfilter',
22 |             name='descriptors',
23 |             field=models.TextField(default=''),
24 |         ),
25 |         migrations.RemoveField(
26 |             model_name='dbquery',
27 |             name='connectors',
28 |         ),
29 |         migrations.AddField(
30 |             model_name='dbquery',
31 |             name='connectors',
32 |             field=models.TextField(default=''),
33 |         ),
34 |     ]
35 | 


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/lcc_web/web/interface/migrations/0005_dbquery_queries.py:
--------------------------------------------------------------------------------
 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-15 09:21
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations, models
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0004_auto_20170313_1952'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.AddField(
16 |             model_name='dbquery',
17 |             name='queries',
18 |             field=models.IntegerField(default=None),
19 |             preserve_default=False,
20 |         ),
21 |     ]
22 | 


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/lcc_web/web/interface/migrations/0006_auto_20170315_1023.py:
--------------------------------------------------------------------------------
 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-15 09:23
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations, models
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0005_dbquery_queries'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.AlterField(
16 |             model_name='dbquery',
17 |             name='finish_date',
18 |             field=models.DateTimeField(default=None, null=True),
19 |         ),
20 |         migrations.AlterField(
21 |             model_name='dbquery',
22 |             name='queries',
23 |             field=models.IntegerField(default=None, null=True),
24 |         ),
25 |         migrations.AlterField(
26 |             model_name='dbquery',
27 |             name='used_filters',
28 |             field=models.IntegerField(default=''),
29 |         ),
30 |     ]
31 | 


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/lcc_web/web/interface/migrations/0007_auto_20170315_1029.py:
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 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.10 on 2017-03-15 09:29
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations, models
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0006_auto_20170315_1023'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.AlterField(
16 |             model_name='dbquery',
17 |             name='used_filters',
18 |             field=models.TextField(default=''),
19 |         ),
20 |     ]
21 | 


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/lcc_web/web/interface/migrations/0008_auto_20180405_2036.py:
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 1 | # -*- coding: utf-8 -*-
 2 | # Generated by Django 1.11.1 on 2018-04-05 18:36
 3 | from __future__ import unicode_literals
 4 | 
 5 | from django.db import migrations, models
 6 | 
 7 | 
 8 | class Migration(migrations.Migration):
 9 | 
10 |     dependencies = [
11 |         ('interface', '0007_auto_20170315_1029'),
12 |     ]
13 | 
14 |     operations = [
15 |         migrations.AlterField(
16 |             model_name='dbquery',
17 |             name='used_filters',
18 |             field=models.TextField(default='---'),
19 |         ),
20 |     ]
21 | 


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/lcc_web/web/interface/models.py:
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 1 | from __future__ import unicode_literals
 2 | 
 3 | from django.db import models
 4 | from django.utils import timezone
 5 | import json
 6 | # Create your models here.
 7 | 
 8 | 
 9 | class StarsFilter(models.Model):
10 |     id = models.AutoField(primary_key=True)
11 |     user = models.ForeignKey('auth.User')
12 |     status = models.CharField(default="Not started", max_length=15)
13 |     start_date = models.DateTimeField(
14 |         default=timezone.now)
15 |     finish_date = models.DateTimeField(null=True, default=None)
16 |     deciders = models.TextField(default="")
17 |     descriptors = models.TextField(default="")
18 | 
19 | 
20 | class DbQuery(models.Model):
21 |     id = models.AutoField(primary_key=True)
22 |     user = models.ForeignKey('auth.User')
23 |     status = models.CharField(default="Not started", max_length=15)
24 |     start_date = models.DateTimeField(
25 |         default=timezone.now)
26 |     finish_date = models.DateTimeField(null=True, default=None)
27 |     queries = models.IntegerField(null=True, default=None)
28 |     used_filters = models.TextField(default="---")
29 |     connectors = models.TextField(default="")
30 | 


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/lcc_web/web/interface/static/css/popup.css:
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 1 | /* The Modal (background) */
 2 | .modal {
 3 |     display: none; /* Hidden by default */
 4 |     position: fixed; /* Stay in place */
 5 |     z-index: 1; /* Sit on top */
 6 |     padding-top: 100px; /* Location of the box */
 7 |     left: 0;
 8 |     top: 0;
 9 |     width: 100%; /* Full width */
10 |     height: 100%; /* Full height */
11 |     overflow: auto; /* Enable scroll if needed */
12 |     background-color: rgb(0,0,0); /* Fallback color */
13 |     background-color: rgba(0,0,0,0.4); /* Black w/ opacity */
14 | }
15 | 
16 | /* Modal Content */
17 | .modal-content {
18 |     position: relative;
19 |     background-color: #fefefe;
20 |     margin: auto;
21 |     padding: 0;
22 |     border: 1px solid #888;
23 |     width: 80%;
24 |     box-shadow: 0 4px 8px 0 rgba(0,0,0,0.2),0 6px 20px 0 rgba(0,0,0,0.19);
25 |     -webkit-animation-name: animatetop;
26 |     -webkit-animation-duration: 0.4s;
27 |     animation-name: animatetop;
28 |     animation-duration: 0.4s
29 | }
30 | 
31 | /* Add Animation */
32 | @-webkit-keyframes animatetop {
33 |     from {top:-300px; opacity:0} 
34 |     to {top:0; opacity:1}
35 | }
36 | 
37 | @keyframes animatetop {
38 |     from {top:-300px; opacity:0}
39 |     to {top:0; opacity:1}
40 | }
41 | 
42 | /* The Close Button */
43 | .close {
44 |     color: white;
45 |     float: right;
46 |     font-size: 28px;
47 |     font-weight: bold;
48 | }
49 | 
50 | .close:hover,
51 | .close:focus {
52 |     color: #000;
53 |     text-decoration: none;
54 |     cursor: pointer;
55 | }
56 | 
57 | .modal-header {
58 |     padding: 2px 16px;
59 |     background-color: #001b47;
60 |     color: white;
61 | }
62 | 
63 | .modal-body {padding: 2px 16px;
64 | }
65 | 
66 | .modal-footer {
67 |     padding: 2px 16px;
68 |     background-color: #001b47;
69 |     color: white;
70 | }


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/lcc_web/web/interface/static/css/reset.css:
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1 | /* Eric Meyer's Reset CSS v2.0 - http://cssreset.com */
2 | html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,img,ins,kbd,q,s,samp,small,strike,strong,sub,sup,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td,article,aside,canvas,details,embed,figure,figcaption,footer,header,hgroup,menu,nav,output,ruby,section,summary,time,mark,audio,video{border:0;font-size:100%;font:inherit;vertical-align:baseline;margin:0;padding:0}article,aside,details,figcaption,figure,footer,header,hgroup,menu,nav,section{display:block}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:none}table{border-collapse:collapse;border-spacing:0}


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/lcc_web/web/interface/static/js/custom.js:
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 1 | 
 2 | 
 3 | $(document).ready(function(){
 4 | 
 5 | 	$('ul.dropdown').superfish({
 6 | 		autoArrows: true,
 7 | 		animation: {height:'show'}
 8 | 	});  
 9 | 
10 | });


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/lcc_web/web/interface/static/js/form_select_stars_copy.js:
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 1 | $().ready(function() {  
 2 |      $('#add').click(function() {  
 3 |         !$('.select1 option:selected').remove().appendTo('.select2'); 
 4 |         unpackElements('select2', 'select1', 'descriptors_l'); 
 5 |         unpackElements('select2', 'select1', 'connectors_l')
 6 |      });  
 7 |      $('#remove').click(function() {  
 8 |         document.getElementsByClassName("select2")
 9 |         !$('.select2 option:selected').remove().appendTo('.select1');  
10 |         unpackElements('select2', 'select1', 'descriptors_l');
11 |         unpackElements('select2', 'select1', 'connectors_l')
12 |      }); 
13 | 
14 | 
15 |      $('#add2').click(function() {  
16 |         !$('.select7 option:selected').remove().appendTo('.select8');
17 |         unpackElements('select8', 'select7', 'deciders_l')
18 |      });  
19 |      $('#remove2').click(function() {  
20 |         !$('.select8 option:selected').remove().appendTo('.select7');  
21 |         unpackElements('select8', 'select7', 'deciders_l')
22 |      });  
23 |      
24 |    
25 |      $('#add3').click(function() {  
26 |         !$('.unselect_con option:selected').remove().appendTo('.select_con');
27 |         unpackElements('select_con', 'unselect_con', 'connectors_l')
28 |      });  
29 |      $('#remove3').click(function() {  
30 |         !$('.select_con option:selected').remove().appendTo('.unselect_con');  
31 |         unpackElements('select_con', 'unselect_con', 'connectors_l')
32 |      });  
33 |  });
34 | 


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/lcc_web/web/interface/static/js/show_filt_by_id.js:
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1 | function show_filter(job_id, filtid)
2 | {
3 |     window.location.href = '/lcc/stars_filter/'+job_id+'/?filtid='+filtid;
4 | }
5 | 


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/lcc_web/web/interface/templates/batteries/change_filt_popup.html:
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 1 | <style>
 2 | /* TODO:  */
 3 | .modal {
 4 |     display: none; /* Hidden by default */
 5 |     position: fixed; /* Stay in place */
 6 |     z-index: 1; /* Sit on top */
 7 |     padding-top: 100px; /* Location of the box */
 8 |     left: 0;
 9 |     top: 0;
10 |     width: 100%; /* Full width */
11 |     height: 100%; /* Full height */
12 |     overflow: auto; /* Enable scroll if needed */
13 |     background-color: rgb(0,0,0); /* Fallback color */
14 |     background-color: rgba(0,0,0,0.4); /* Black w/ opacity */
15 | }
16 | 
17 | /* Modal Content */
18 | .modal-content {
19 |     background-color: #fefefe;
20 |     margin: auto;
21 |     padding: 20px;
22 |     border: 1px solid #888;
23 |     width: 80%;
24 | }
25 | 
26 | /* The Close Button */
27 | .close {
28 |     color: #aaaaaa;
29 |     float: right;
30 |     font-size: 28px;
31 |     font-weight: bold;
32 | }
33 | 
34 | .close:hover,
35 | .close:focus {
36 |     color: #000;
37 |     text-decoration: none;
38 |     cursor: pointer;
39 | }
40 | </style>
41 | </head>
42 | <body>
43 | 
44 | <h2>Modal Example</h2>
45 | 
46 | <!-- Trigger/Open The Modal -->
47 | <button id="myBtn">Open Modal</button>
48 | 
49 | <!-- The Modal -->
50 | <div id="myModal" class="modal">
51 | 
52 |   <!-- Modal content -->
53 |   <div class="modal-content">
54 |     <span class="close">&times;</span>
55 |     <p>Some text in the Modal..</p>
56 |     <form action="/action_page.php" method="get">
57 |     First name: <input type="text" name="fname"><br>
58 |     Last name: <input type="text" name="lname"><br>
59 |     <input type="submit" value="Submit">
60 |   </form>
61 |   </div>
62 | 
63 | </div>
64 | 
65 | <script>
66 | // Get the modal
67 | var modal = document.getElementById('myModal');
68 | 
69 | // Get the button that opens the modal
70 | var btn = document.getElementById("myBtn");
71 | 
72 | // Get the <span> element that closes the modal
73 | var span = document.getElementsByClassName("close")[0];
74 | 
75 | // When the user clicks the button, open the modal
76 | btn.onclick = function() {
77 |     modal.style.display = "block";
78 | }
79 | 
80 | // When the user clicks on <span> (x), close the modal
81 | span.onclick = function() {
82 |     modal.style.display = "none";
83 | }
84 | 
85 | // When the user clicks anywhere outside of the modal, close it
86 | window.onclick = function(event) {
87 |     if (event.target == modal) {
88 |         modal.style.display = "none";
89 |     }
90 | }
91 | </script>


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/lcc_web/web/interface/templates/interface/404.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | 
 3 | {% block input_form %}
 4 | 
 5 | <h1 align="middle">Error 404</h1>
 6 | <h3 align="middle">This url doesn't exist</h3>
 7 | 
 8 | {% endblock %}
 9 | 
10 | 


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/lcc_web/web/interface/templates/interface/500.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | 
 3 | {% block input_form %}
 4 | 
 5 | <h1 align="middle">Huups..</h1>
 6 | <h2 align="middle">Unexpected server error </h2>
 7 | <p align="middle">Please chceck validity of your input. Web is still not "incorret input friendly".<br>
 8 | Also please note that the Web Interface is still in developement and some bugs could pop up. In this case don't hesitate <br>
 9 | and write the maintainer od this site (see "Contancts").
10 | </p>
11 | 
12 | {% endblock %}
13 | 
14 | 


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/lcc_web/web/interface/templates/interface/base_template2.html:
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 1 | {% load static %}
 2 | 
 3 | <!DOCTYPE html>
 4 | <html>
 5 | <head>
 6 |     <title>Light Curves Classifier</title>
 7 |     <link rel="stylesheet" type="text/css" href="{% static 'css/styles.css' %}">
 8 |     <meta charset="utf-8">
 9 |     <link href="https://fonts.googleapis.com/css?family=Fjalla+One" rel="stylesheet">
10 |     <script src="http://code.jquery.com/jquery-1.9.1.js"></script>
11 |     
12 |     <script type="text/javascript" src="{% static 'js/bootstrap-filestyle.min.js' %}"> </script>
13 |     <script type="text/javascript" src="{% static 'js/bootstrap.min.js' %}" charset="utf-8"></script>    
14 |     <link href="{% static 'css/bootstrap.min.css' %}" rel="stylesheet">
15 |     <script type="text/javascript" src="//ajax.googleapis.com/ajax/libs/jquery/1.9.1/jquery.min.js" charset="utf-8"></script>
16 |     
17 |     <script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
18 |     
19 |     <script src="{% static 'js/form_select_stars_copy.js' %}"></script>
20 |     
21 |     <script>
22 |     $(document).ready(function() 
23 |     {
24 |     $('#loader').hide();
25 | 
26 |     $('form').submit(function() 
27 |     {
28 |         $('#loader').show();
29 |     }) 
30 |     })
31 | </script>
32 |     <script>
33 |     function unpackElements(show_id, hide_id, write_to) {
34 |         var in_txt = "";
35 |         var x = document.getElementsByClassName(show_id)[0].options;
36 |         for (i = 0; i < x.length; i++) { 
37 |             var divOne = document.getElementById(x[i].value);
38 |             divOne.style.display = "inline";
39 |             in_txt += x[i].value+";";
40 |             
41 |         }
42 |         document.getElementById(write_to).value = in_txt;
43 |         
44 |         var y = document.getElementsByClassName(hide_id)[0].options;
45 |         for (i = 0; i < y.length; i++) { 
46 |             var divOne = document.getElementById(y[i].value);
47 |             divOne.style.display = "none"; 
48 |         }
49 |         
50 |     }    
51 |     </script>
52 |     
53 |     <script>
54 |     function selectAll(field){
55 |         for (var j = 0; j < field.length; j++)
56 |         {
57 |             var selectBox = document.getElementsByClassName(field)[0].options;   
58 |             for (var i = 0; i < selectBox.length; i++) 
59 |             { 
60 |                  selectBox[i].selected = true; 
61 |             } 
62 |         }
63 |     }
64 |     </script>
65 |     
66 | 
67 | </head>
68 | <body>
69 |     <div id="heading">
70 |             <table class="header0" align="center">
71 |                 <tr class="container_header">
72 |                     <th><a id="logo" href="{% url 'home' %}" title="Home">
73 |                         <img class="logo-icon" alt="Logo webu" src={% static 'img/logo.png' %}>
74 |                         </a>
75 |                     </th>
76 |                     <th><span id="nadpis">Light Curves Classifier - Web Interface</span></th> 
77 |                 </tr>
78 |             </table>
79 |     </div>
80 |     <div class="menu">
81 |         <ul class="navigation">
82 |             <li><a class="active" href="{% url 'show' %}">Show stars</a></li>
83 |             <li><a class="#" href="{% url 'make_filter' %}">Make filter</a></li>
84 |             <li><a href="{% url 'unsup' %}">Unsupervised</a></li>
85 |             <li><a href="{% url 'search' %}">Systematic filtering</a></li>
86 |             <li><a href="{% url 'all_filters' %}">Jobs: Filters</a></li>
87 |             <li><a href="{% url 'all_results' %}">Jobs: Queries</a></li>
88 |         </ul>
89 |         </div>            
90 |     </div>
91 |     
92 |     {% block input_form %}
93 |     {% endblock %}
94 | </body>
95 | </html>
96 | 


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/lcc_web/web/interface/templates/interface/browse.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | {% load static %}
 3 | 
 4 | {% block input_form %}
 5 | 
 6 | 
 7 | 
 8 | <script type="text/javascript" src="{% static 'js/popup.js' %}"> </script>
 9 | 
10 | 
11 |     {{ page_title }}
12 |     {{ page_info }}
13 | 
14 | {% if lcs %}
15 | <div align="middle" id="plotLC" style="width:100%;height:100%"></div>
16 | <script>
17 | {% include "visual/plotLC.js" %}
18 | </script>
19 | {% endif %}
20 | 
21 | <form id="form1" align="middle" action='#' onclick="" method='post' enctype="multipart/form-data">{% csrf_token %}
22 |     <div style="margin: auto;">
23 |     <input style="margin: auto;" type='file' class="filestyle" data-classIcon="icon-plus" data-input="false" data-classButton="btn btn-primary" multiple name='my_file' data-buttonText='Load stars' />
24 |     <input align="middle" style="background-color:#a3a1a1;font-weight: 900;height:40px;color:#000000;" type='submit' class="filestyle" data-classIcon="icon-plus" data-classButton="btn btn-primary" name='sub' value='Show' />
25 |         <input align="middle" style="background-color:#a3a1a1;font-weight: 900;height:40px;color:#000000;" type='submit' class="filestyle" data-classIcon="icon-plus" data-classButton="btn btn-primary" name='clear' value='Clear' />
26 |     </div>
27 | </form>   
28 | 
29 | {% endblock %}
30 | 


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/lcc_web/web/interface/templates/interface/contact.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | {% load static %}
 3 | 
 4 | {% block input_form %}
 5 | 
 6 | 
 7 | <h1 align="middle">Contact</h1>
 8 | 
 9 |     The author of Web Interface and Light Curves Classifier is Martin Vo. <br>
10 |     <b>Email:</b> vo.martin@post.cz.
11 |     <br><br>
12 | 
13 | 
14 | 
15 | 
16 | 
17 | {% endblock %}


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/lcc_web/web/interface/templates/interface/create_user.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | {% load static %}
 3 | 
 4 | {% block input_form %}
 5 | 
 6 | 
 7 | <h1 align="middle">Registration</h1>
 8 | 
 9 | <form action='/lcc/new_user/' method='post'>
10 |     {% csrf_token %}
11 |     <p><label>User name:</label> {{ form.username }}</p>
12 | 
13 |     <p><label>Password:</label> {{ form.password1 }}</p>
14 |     <p><label>Password again:</label> {{ form.password2 }}</p>
15 |     <p><label></label><input type="submit" value="Submit" /></p>
16 | </form>
17 | 
18 | 
19 | 
20 | 
21 | {% endblock %}


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/lcc_web/web/interface/templates/interface/error_page.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | 
 3 | {% block input_form %}
 4 | 
 5 | <h1 align="middle">Error occured</h1>
 6 | <h3 align="middle">{{ error_m|safe }}</h3>
 7 | 
 8 | {% endblock %}
 9 | 
10 | 


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/lcc_web/web/interface/templates/interface/header_scr.html:
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 1 | <script>
 2 |     $(document).ready(function() 
 3 |     {
 4 |     $('#loader').hide();
 5 | 
 6 |     $('form').submit(function() 
 7 |     {
 8 |         $('#loader').show();
 9 |     }) 
10 |     })
11 |     </script>
12 |     <script>
13 |     function unpackElements(show_id, hide_id, write_to) {
14 |         var in_txt = "";
15 |         var x = document.getElementsByClassName(show_id)[0].options;
16 |         for (i = 0; i < x.length; i++) { 
17 |             var divOne = document.getElementById(x[i].value);
18 |             divOne.style.display = "inline";
19 |             in_txt += x[i].value+";";
20 |             
21 |         }
22 |         document.getElementById(write_to).value = in_txt;
23 |         
24 |         var y = document.getElementsByClassName(hide_id)[0].options;
25 |         for (i = 0; i < y.length; i++) { 
26 |             var divOne = document.getElementById(y[i].value);
27 |             divOne.style.display = "none"; 
28 |         }
29 |         
30 |     }    
31 |     </script>
32 |     
33 |     <script>
34 |     function selectAll(field){
35 |         for (var j = 0; j < field.length; j++)
36 |         {
37 |             var selectBox = document.getElementsByClassName(field)[0].options;   
38 |             for (var i = 0; i < selectBox.length; i++) 
39 |             { 
40 |                  selectBox[i].selected = true; 
41 |             } 
42 |         }
43 |     }
44 |     </script>
45 |     
46 | 


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/lcc_web/web/interface/templates/interface/jobs.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | 
 3 | {% block input_form %}
 4 | 
 5 | <script>
 6 | function delete_job( job_id, job_type) {
 7 |     var txt;
 8 |     var r = confirm("Do you really want to delete job: "+job_id);
 9 |     if (r == true) {
10 |         txt = "You pressed OK!";
11 |     } else {
12 |         txt = "You pressed Cancel!";
13 |     }
14 |     window.location.href = {{ delete_prefix | safe }}+job_type+"/"+job_id;
15 |     
16 | }
17 | </script>
18 | 
19 | 
20 | <table align="middle" width="80%" >
21 | {% for column in header %}
22 |     <th style="text-align: center;">{{ column }}</th>
23 | {% endfor %}
24 | {% for row_job in table %}
25 |         <tr>
26 |         {% for column in row_job.0 %}
27 |             <td>{{ column | safe}}</td>
28 |         {% endfor %}
29 |         {% if stars_filter %}
30 |             <td><a style="text-decoration:none; color:#0146b5;"  href="{% url 'stars_filter' job_id=row_job.1 %}">Show</a></th>
31 |             <td><a style="text-decoration:none; color:#0146b5;" onclick="delete_job({{ row_job.1 }}, 'stars_filter')" >Delete</a></th>
32 |         {% else %}
33 |             <td><a style="text-decoration:none; color:#0146b5;"  href="{% url 'result' job_id=row_job.1 %}">Show</a></th>
34 |             <td><a style="text-decoration:none; color:#0146b5;" onclick="delete_job({{ row_job.1 }}, 'result')" >Delete</a></th>
35 |         {% endif %}
36 |         
37 |             
38 |         </tr>
39 | {% endfor %}
40 | </table>
41 | 
42 | {% endblock %}
43 | 


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/lcc_web/web/interface/templates/interface/login.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | 
 3 | {% block input_form %}
 4 | <h1>Log in</h1>
 5 | <form action="" method="post">
 6 |     {% csrf_token %}
 7 |     <p><label>User name:</label>{{ form.user_name }}</p>
 8 |     <p><label>Password:</label>{{ form.password }}</p>
 9 |     <input type="text" style="visibility: hidden;" id="goto_f" name="goto_f" value="{{ goto }}" />
10 |     <input type="submit" value="Submit" />
11 | </form>
12 | 
13 |     <i><small>Don't have account? Signup for free: </small></i><a href="{% url 'create_user' %}">SignUp</a>
14 | 
15 | {% endblock %}
16 | 


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/lcc_web/web/interface/templates/interface/manage_modules.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | {% load static %}
 3 | 
 4 | {% block input_form %}
 5 | 
 6 |     <script>
 7 |     function open_on_click(cont, path, i) {
 8 |        document.getElementById("module_cont").innerHTML = cont[i];
 9 |        document.getElementById("module_cont").rows = cont[i].split("\n").length;
10 |        document.getElementById("module_cont").style.display = "block";
11 |        document.getElementById("save_but").style.display = "block";
12 |        document.getElementById("save_but").style.display = "block";
13 |        document.getElementById("delete_but").style.display = "block";
14 |        document.getElementById("mod_path").value = path
15 |         document.getElementById("file_name").innerHTML = path.split("/")[path.split("/").length-1];
16 | 
17 |     }
18 |     </script>
19 | 
20 |     <script>
21 |     function new_module(path) {
22 |         var name = window.prompt("Name of the file? (without .py suffix)");
23 |         document.getElementById("save_but").style.display = "block";
24 |         document.getElementById("module_cont").style.display = "block";
25 |         document.getElementById("mod_path").value = path+"/"+name+".py"
26 |         document.getElementById("file_name").innerHTML = name+".py";
27 |         document.getElementById("module_cont").innerHTML = "";
28 |     }
29 | 
30 |     </script>
31 | 
32 |     {{ page_info }}
33 | 
34 |    <p>On this page you can add or manage own modules. You can add new descriptors,
35 |                 deciders or connectors.</p>
36 |     <form id="save_form" align="middle" action='#' onclick="" method='post' enctype="multipart/form-data">{% csrf_token %}
37 |         <input style="display:none" type="text" name="mod_path"  id="mod_path" value="">
38 |         <h3 allign="middle" id="file_name"></h3>
39 |         <textarea  align="middle" id="module_cont" name="module_cont" rows="0" cols="50" style="display:none"></textarea>
40 |         <p>
41 |         <input id='save_but'  style="background-color:#a3a1a1;font-weight: 900;height:40px;color:#000000;display:none;" type='submit' class="filestyle" data-classIcon="icon-plus" data-classButton="btn btn-primary" name='save_but' value='Save' />
42 |         <input id='delete_but'  style="background-color:#a3a1a1;font-weight: 900;height:40px;color:#000000;display:none;" type='submit' class="filestyle" data-classIcon="icon-plus" data-classButton="btn btn-primary" name='delete_but' value='Delete' />
43 |             </p>
44 |     </form>
45 | 
46 |     <h2>Descriptors</h2>
47 |     <input id='new_desc' onclick="new_module('{{ descr_path }}')" type='button' name='new_decs' value='New descriptor' />
48 | 
49 |         <ul>
50 |         {%  for desc in descriptors %}
51 |             <li onclick="open_on_click({{ descriptors_cont }}, '{{ descr_path }}/{{ desc }}', {{ forloop.counter0 }})">{{ desc }}</li>
52 |         {%  endfor %}
53 |         </ul>
54 | 
55 |     <h2>Connectors</h2>
56 |     <input onclick="new_module('{{ con_path }}')" type='button' value='New connector' />
57 |         <ul>
58 |         {%  for con in connectors %}
59 |             <li onclick="open_on_click({{ cone_cont }}, '{{ con_path }}/{{ con }}', {{ forloop.counter0 }})">{{ con }}</li>
60 |         {%  endfor %}
61 |         </ul>
62 | 
63 |     <h2>Deciders</h2>
64 |     <input onclick="new_module('{{ deci_path }}')" type='button' value='New decider' />
65 |         <ul>
66 |         {%  for deci in deciders %}
67 |             <li onclick="open_on_click({{ dec_cont }}, '{{ deci_path }}/{{ deci }}', {{ forloop.counter0 }})">{{ deci }}</li>
68 |         {%  endfor %}
69 |         </ul>
70 | 
71 | 
72 | 
73 | 
74 | 
75 | 
76 | {% endblock %}


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/lcc_web/web/interface/templates/interface/results.html:
--------------------------------------------------------------------------------
 1 | {% extends 'interface/base_template.html' %}
 2 | 
 3 | {% block input_form %}
 4 | 
 5 | 
 6 | 
 7 | <h1 align="middle">Job: {{ job_id }}</h1>
 8 | 
 9 | {% if act_num_queries != num_queries %}
10 |     <p>Progress: {{ act_num_queries }} remaining jobs ( Total queries: {{ num_queries }})</p>
11 | {% endif %}
12 | 
13 | {% if zip_url %} 
14 |     <h3>It is done</h3>
15 |     <h4>Passed stars: {{ passed_n.0 }}</h4>
16 |     <h4>Not passed stars: {{ passed_n.1 }}</h4>
17 |     <a class="button" href="./../{{ zip_url }}">Download the result</a>
18 | {% endif %}
19 | 
20 | <h2>Query info:</h2>
21 | <p><small>Info: Only top 50 results are displayed</small></p>
22 | 
23 | {{ job_info_html|safe }}
24 | 
25 | {{ status_table|safe }}
26 | 
27 | 
28 | 
29 | 
30 | {% endblock %}
31 | 
32 | 


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/lcc_web/web/interface/templates/interface/search.html:
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 1 | {% extends 'interface/base_template.html' %}
 2 | {% load static %}
 3 | 
 4 | {% block input_form %}
 5 | 
 6 | 
 7 | <div id="loader" style="position: fixed; top:0; left:0; width:100%; height: 100%; background: url('{% static 'img/loader.gif' %}') center center #efefef"></div>
 8 | 
 9 | <form action='#' onclick="unpackElements('select2', 'select1', 'connectors_l');" method='post' enctype="multipart/form-data">{% csrf_token %}
10 |     
11 |     <div id="selector1">  
12 |     <h3 class="selector1_header">Available connectors</h3>
13 |         <select name="deselected_con[]" id="deselected_con" multiple="multiple" class="select1">
14 |             {% for connector in connectors %}
15 |                 <option value="{{ connector }}">{{ connector }}</option> 
16 |             {% endfor %}
17 |                 
18 |                 
19 |           </select>  
20 |           <a href="#/" class="button"  id="add" >Add &gt;&gt;</a>  
21 |     </div>  
22 |     <div id="selector2"> 
23 |     <h3 class="selector2_header">Selected items</h3> 
24 |         <select name="selected_con[]" id="selected_con" multiple="multiple" class="select2"></select>  
25 |         
26 |         <a href="#/" class="button button-reversed" id="remove">&lt;&lt; Remove</a> 
27 |     </div> 
28 |     
29 |         <div class="desc_inputs1">
30 |         {% for field in avail_fields %}
31 |             <div id="{{ field.0 }}" style="display: none;">
32 |             <h2 id="{{ field.0 }}_head" class="desc_header"> {{ field.0 }}</h2>
33 |             <div>
34 |             <label class="desc_lab" align="left">Query</label>
35 |                 <input id={{ field.0 }}_query_file style="font-weight: 900;height:40px;color:#000000;" type='file' class="filestyle" data-classIcon="icon-plus" data-input="false" data-classButton="btn btn-primary" multiple name='{{ field.0 }}_query_file' data-buttonText='Load query file' />
36 |             <textarea name="{{ field.0 }}" rows="3" cols="25" value="{{ co.1 }}">{{ field.1|safe }}</textarea>
37 |            </div>
38 |            
39 |             </div>
40 |         {% endfor %}
41 |         </div>
42 | 
43 |     
44 |     <input id='connectors_l' type='text' style="display: none"; name='connectors_l' />
45 |     
46 | 
47 |     <div id="buttons">   
48 |         <h2 align="left">Load filter objects</h2>
49 |         <p align="left"><small>all stars will be downloaded if no filter is specified</small></p>
50 |         <input style="font-weight: 900;height:40px;color:#000000;" type='file' class="filestyle" data-classIcon="icon-plus" data-input="false" data-classButton="btn btn-primary" multiple name='filter_file' data-buttonText='Load filters' />
51 |         <input onclick="scroll(0,0);" style="background-color:#a3a1a1;font-weight: 900;height:40px;color:#000000;" type='submit' class="filestyle" data-classIcon="icon-plus" data-classButton="btn btn-primary" name='sub' value='Submit' />
52 |     </div>
53 |     
54 | </form>
55 | 
56 | {% include "interface/to_inter.html" %}
57 | 
58 | {% endblock %}


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/lcc_web/web/interface/templates/interface/show_unsup.html:
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  1 | {% extends 'interface/base_template.html' %}
  2 | 
  3 | {% block input_form %}
  4 | 
  5 | 
  6 |  
  7 | <script>
  8 | function plotSelected(id){
  9 |     var data = [];
 10 |     var lcs = {{ lcs }};
 11 |     var labels = {{ labels|safe }};
 12 |     var x_data = lcs[id][0];
 13 |     var y_data = lcs[id][1];
 14 |     
 15 |     var this_data = {
 16 |                x: x_data,
 17 |                y: y_data,
 18 |                mode: 'markers',
 19 |                error_y: {
 20 |                   type: 'data',
 21 |                   array: lcs[id][2],
 22 |                   visible: true,
 23 |                   color: '#85144B'
 24 |                             }};
 25 |     data.push(this_data);
 26 |                 
 27 |     
 28 |       
 29 |     var layout = {
 30 |       title: labels[id],
 31 |       autosize: true,
 32 |       width: 800,
 33 |       height: 600,
 34 |       margin: {
 35 |         l: 65,
 36 |         r: 50,
 37 |         b: 65,
 38 |         t: 90,
 39 |       },
 40 |       xaxis: {
 41 |         title: "Time"
 42 |         },
 43 |       yaxis: {
 44 |         title: "Mag",
 45 |         autorange: 'reversed'}
 46 |     };
 47 |     
 48 |     Plotly.newPlot('lc_plot', data, layout);
 49 |     }
 50 | </script>
 51 | 
 52 | 
 53 | <div align="middle" id="myplot" style="width:100%;height:100%"></div>
 54 | <script>
 55 | var myPlot = document.getElementById('myplot')
 56 | 
 57 | var layout = {
 58 |   legend: {
 59 |     x: 1500,
 60 |     y: 1000
 61 |     },
 62 |   autosize: true,  
 63 |   width: 800,
 64 |   height: 600,
 65 |   margin: {
 66 |     l: 65,
 67 |     r: 50,
 68 |     b: 65,
 69 |     t: 90,
 70 |   }
 71 | };
 72 | 
 73 | var traces = [[1,2,3,4,5],[4,5,6,7,8]];
 74 | var x_data = traces[0];
 75 | var y_data = traces[1];
 76 | var t = {
 77 | x: x_data, y: y_data,
 78 | mode: 'markers',
 79 | marker: {
 80 |     size: 8,
 81 |     text: ["a","b","c","d","e"],
 82 |     symbol: 'circle',
 83 |     line: {
 84 |     color: 'rgb(204, 204, 204)',
 85 |     width: 1},
 86 |     opacity: 0.8},
 87 | type: 'scatter2d'};
 88 | var data = [t];
 89 |     
 90 | Plotly.newPlot('myplot', data, layout);
 91 | 
 92 | myPlot.on('plotly_click', function(data){
 93 |     for(var i=0; i < data.points.length; i++){
 94 |     plotSelected(data.points[i].pointNumber);
 95 |     alert(data.points[i].pointNumber);
 96 |     }
 97 | });
 98 | 
 99 | 
100 | 
101 | 
102 | </script>
103 | 
104 | <div align="middle" id="lc_plot" style="width:100%;height:100%"></div>
105 | 
106 | 
107 | {% endblock %}


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/lcc_web/web/interface/templates/interface/to_inter.html:
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 1 | {% for click_obj_id, popup_txt_id, popup_cont in to_inter %}
 2 | <!-- Trigger/Open The Modal -->
 3 | <!-- <button id="myBtn">Open Modal</button> -->
 4 | 
 5 | <!-- The Modal -->
 6 | <div id="{{ popup_txt_id }}" class="modal">
 7 | 
 8 |   <!-- Modal content -->
 9 |   <div class="modal-content">
10 |     <div align="left" class="modal-header">
11 |       <span  class="close" id="{{ popup_txt_id }}_close">&times;</span>
12 |       <h2>{{ popup_txt_id|slice:"0:-6" }}</h2>
13 |     </div>
14 |     <div align="left" class="modal-body">
15 |       <p>{{ popup_cont|safe }}</p>
16 |     </div>
17 |     <div class="modal-footer">
18 |       <h3>Modal Footer</h3>
19 |     </div>
20 |   </div>
21 | </div>
22 | {% endfor %}
23 | 
24 | <script>
25 | {% for click_obj_id, popup_txt_id, popup_cont in to_inter %}    
26 |     
27 |     
28 |     // When the user clicks the button, open the modal 
29 |     document.getElementById("{{ click_obj_id }}").onclick = function() {
30 |         document.getElementById('{{ popup_txt_id }}').style.display = "block";
31 |     }
32 |     
33 |     // When the user clicks on <span> (x), close the modal
34 |     document.getElementById("{{ popup_txt_id }}_close").onclick = function() {
35 |         document.getElementById('{{ popup_txt_id }}').style.display = "none";
36 |     }
37 |     
38 |     
39 | {% endfor %}
40 | </script>


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/lcc_web/web/interface/templates/visual/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/lcc_web/web/interface/templates/visual/__init__.py


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/lcc_web/web/interface/templates/visual/plot2D.js:
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 1 | var myPlot = document.getElementById('plot2d')
 2 | 
 3 | var x_data = {{ probab_data.0 }};
 4 | var y_data = {{ probab_data.1 }};
 5 | 
 6 | var data = [{
 7 |            x: x_data,
 8 |            y: y_data,
 9 |            name: "Probability distribution"
10 |         }];
11 |     
12 | var traces = {{ coo_data }};
13 | var zeroes = {{ zeroes }};
14 | var point_labels = {{ point_labels|safe }};
15 | var labels = {{ coo_plot_labels|safe }};
16 | var colors = {{ colors|safe }};
17 | for (i=0; i < traces.length; i++){
18 |     var trace_points = {
19 |       x: traces[i][0],
20 |       y: zeroes[i],
21 |       text: point_labels[i],
22 |       type: "scatter",
23 |       mode: 'markers',
24 |       name: labels[i],
25 |       opacity: 0.9,
26 |       marker: {
27 |          color: colors[i],
28 |          size:14,
29 |       },
30 |     };
31 | 
32 |     data.push(trace_points);
33 |     }
34 | 
35 | 
36 | for (i=0; i < traces.length; i++){
37 | 
38 | 
39 |     var trace_hist = {
40 |       x: traces[i][0],
41 |       type: "histogram",
42 |       histnorm: 'probability',
43 |       showlegend: false,
44 |       opacity: 0.7,
45 |       marker: {
46 |          color: colors[i],
47 |       },
48 |     };
49 | 
50 |     data.push(trace_hist);
51 |     }
52 |         
53 |   
54 | var layout = {
55 |   title: "{{ probab_plot_title }}",
56 |   autosize: false,
57 |     font: {
58 |     size: 25
59 |   },
60 |   margin: {
61 |     l: 65,
62 |     r: 50,
63 |     b: 65,
64 |     t: 90,
65 |   },
66 |   xaxis: {
67 |     title: "{{ probab_plot_axis.0 }}"},
68 | 
69 |   yaxis: {
70 |     title: "Probability"}
71 | };
72 | 
73 | Plotly.newPlot('plot2d', data, layout);
74 | 
75 | myPlot.on('plotly_click', function(data){
76 |     var len1 = {{ coo_data.0.0|length }};
77 |     var a = 1;
78 |     if (len1 < 2)
79 |     {
80 |         a = 0;
81 |     }
82 | 
83 | 
84 |     plotSelected(data.points[0].pointNumber, data.points[0].curveNumber,len1);
85 | });


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/lcc_web/web/interface/templates/visual/plot3D.js:
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 1 | 
 2 | var traces = {{ coo_data }};
 3 | var labels = {{ coo_plot_labels|safe }};
 4 | 
 5 | var data = [];
 6 | for (i=0; i < traces.length; i++){
 7 |     var x_data = traces[i][0];
 8 |     var y_data = traces[i][1];
 9 |     var z_data = traces[i][2];
10 |     var t = {
11 |     x: x_data, y: y_data, z: z_data,
12 |     name: labels[i],
13 |     mode: 'markers',
14 |     marker: {
15 |         size: 8,
16 |         symbol: 'circle',
17 |         line: {
18 |         color: 'rgb(204, 204, 204)',
19 |         width: 1},
20 |         opacity: 0.8},
21 |     type: 'scatter3d'};
22 |     data.push(t);
23 |     }
24 | 
25 | var layout = {
26 |    title: "{{ coo_plot_title }}",
27 |    scene: {
28 |       xaxis: {
29 |           title: "{{ coo_plot_axis.0 }}"
30 |           },
31 |       yaxis: {
32 |           title: "{{ coo_plot_axis.1 }}"
33 |           },
34 |       zaxis: {
35 |           title: "{{ coo_plot_axis.2 }}"
36 |           }
37 |         },
38 |    margin: {
39 |     l: 0,
40 |     r: 0,
41 |     b: 0,
42 |     t: 0
43 |   }};
44 | Plotly.newPlot('plot3d', data, layout);


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/lcc_web/web/interface/templates/visual/plot3D_scatter.js:
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 1 | function plot3D_scat() {
 2 |     var opt = document.getElementsByName("plot_axis")[0].value.split(":");
 3 |     var i = opt[0]-1;
 4 |     var j = opt[1]-1;
 5 |     var k = opt[2]-1;
 6 |     var coo_data = {{ space_coords }};
 7 |     var x = coo_data[i];
 8 |     var y = coo_data[j];
 9 |     var axis = {{ all_axis|safe }};
10 |         
11 |     if (isNaN(k)){    
12 |         var z = coo_data[k];
13 |             
14 |         var trace = {
15 |             x:x, y: y, 
16 |             mode: 'markers',
17 |             marker: {
18 |                 size: 12,
19 |                 line: {
20 |                 color: 'rgba(217, 217, 217, 0.14)',
21 |                 width: 0.5},
22 |                 opacity: 0.8},
23 |             type: 'scatter'
24 |         };
25 |         
26 |         var data = [trace];
27 |         var layout = {  
28 |             xaxis: {
29 |                 title: axis[i]
30 |                     },
31 |             yaxis: {
32 |                 title: axis[j]
33 |                     },
34 |             margin: {
35 |             l: 0,
36 |             r: 0,
37 |             b: 0,
38 |             t: 0
39 |           }};
40 |     
41 |     }
42 |     
43 |     else {      
44 |         var z = coo_data[k];
45 |         
46 |             
47 |         var trace = {
48 |             x:x, y: y, z: z,
49 |             mode: 'markers',
50 |             marker: {
51 |                 size: 12,
52 |                 line: {
53 |                 color: 'rgba(217, 217, 217, 0.14)',
54 |                 width: 0.5},
55 |                 opacity: 0.8},
56 |             type: 'scatter3d'
57 |         };
58 |         
59 |         var data = [trace];
60 |         var layout = {    
61 |             autosize: true,    
62 |             scene : {
63 |                 xaxis: {
64 |                     title: axis[i]
65 |                         },
66 |                 yaxis: {
67 |                     title: axis[j]
68 |                         },
69 |                 zaxis: {
70 |                     title: axis[k]
71 |                         }},
72 |             margin: {
73 |             l: 0,
74 |             r: 0,
75 |             b: 0,
76 |             t: 0
77 |           }};
78 |         
79 |     }
80 |     
81 |     
82 |     
83 |     Plotly.newPlot('plot3d_scat', data, layout);
84 |     }


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plot3D_scatter_superv.js:
--------------------------------------------------------------------------------
  1 | function plot3D_scat() {
  2 |     var this_plot = document.getElementById('plot3d_scat')
  3 |     var opt = document.getElementsByName("plot_axis")[0].value.split(":");
  4 |     var i = opt[0]-1;
  5 |     var j = opt[1]-1;
  6 |     var k = opt[2]-1;
  7 |     var coo_data_or = {{ space_coords }};
  8 |     var colors = {{ colors|safe }};
  9 |     var axis = {{ all_axis|safe }};
 10 |     var labels = ["Searched test sample", "Searched train sample", "Contamination test sample", "Contamination train sample"];
 11 | 
 12 |     var data = [];
 13 |     for (var ind = 0; ind < 4; ind++){
 14 |         var xx = coo_data_or[ind][i];
 15 |         var yy = coo_data_or[ind][j];
 16 |         var zz = coo_data_or[ind][k];
 17 | 
 18 |         if (isNaN(k)){
 19 | 
 20 |             var trace = {
 21 |                 x:xx, y: yy,
 22 |                 mode: 'markers',
 23 |                 name: labels[ind],
 24 |                 marker: {
 25 |                     size: 12,
 26 |                     color: colors[ind],
 27 |                     line: {
 28 |                     width: 0.5},
 29 |                     opacity: 0.8},
 30 |                 type: 'scatter'
 31 |             };
 32 | 
 33 |             data.push(trace);
 34 |             var layout = {
 35 |                 xaxis: {
 36 |                     title: axis[i]
 37 |                         },
 38 |                 yaxis: {
 39 |                     title: axis[j]
 40 |                         },
 41 |                 margin: {
 42 |                 l: 0,
 43 |                 r: 0,
 44 |                 b: 0,
 45 |                 t: 0
 46 |               }};
 47 | 
 48 |         }
 49 | 
 50 |         else {
 51 | 
 52 | 
 53 |             var trace = {
 54 |                 x:xx, y: yy, z: zz,
 55 |                 mode: 'markers',
 56 |                 name: labels[ind],
 57 |                 text: point_labels[ind],
 58 |                 marker: {
 59 |                     color: colors[ind],
 60 |                     size: 12,
 61 |                     line: {
 62 |                     width: 0.5},
 63 |                     opacity: 0.8},
 64 |                 type: 'scatter3d'
 65 |             };
 66 | 
 67 |             data.push(trace);
 68 | 
 69 |             var layout = {
 70 |                 autosize: true,
 71 |                 scene : {
 72 |                     xaxis: {
 73 |                         title: axis[i]
 74 |                             },
 75 |                     yaxis: {
 76 |                         title: axis[j]
 77 |                             },
 78 |                     zaxis: {
 79 |                         title: axis[k]
 80 |                             }},
 81 |                 margin: {
 82 |                 l: 0,
 83 |                 r: 0,
 84 |                 b: 0,
 85 |                 t: 0
 86 |               }};
 87 | 
 88 |         }
 89 |     }
 90 |     
 91 |     
 92 |     Plotly.newPlot('plot3d_scat', data, layout);
 93 | 
 94 | 
 95 |     this_plot.on('plotly_click', function(data){
 96 |     var len1 = coo_data_or[0][0].length;
 97 |     var a = 1;
 98 |     if (len1 < 2){
 99 |         a = 0;
100 |         }
101 |     plotSelected(data.points[0].pointNumber, data.points[0].curveNumber,len1);
102 |     });
103 |     }


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plot3D_surface.js:
--------------------------------------------------------------------------------
 1 | var myPlot = document.getElementById('plot3d_surface')
 2 | 
 3 | var x_data = {{ probab_data.0 }};
 4 | var y_data = {{ probab_data.1 }};
 5 | var z_data = {{ probab_data.2 }};
 6 | 
 7 | var data = [{
 8 |            x: x_data,
 9 |            y: y_data,
10 |            z: z_data,
11 |            type: 'contour'
12 |         }];
13 |   
14 | var layout = {
15 |     showlegend: true,
16 |   legend: {
17 |     x: 1500,
18 |     y: 1000
19 |     },
20 |   title: "Probability plot",
21 |   xaxis: {
22 |     title: "{{ probab_plot_axis.0 }}"},
23 |   yaxis: {
24 |     title: "{{ probab_plot_axis.1 }}",
25 |     y: -1900},
26 |   autosize: true
27 | };
28 | 
29 | var traces = {{ coo_data }};
30 | var labels = {{ coo_plot_labels|safe }};
31 | var colors = {{ colors|safe }};
32 | var point_labels = {{ point_labels|safe }};
33 | for (i=0; i < traces.length; i++){
34 |     var x_data = traces[i][0];
35 |     var y_data = traces[i][1];
36 |     var t = {
37 |     x: x_data, y: y_data,
38 |     mode: 'markers',
39 |     name: labels[i],
40 |     text: point_labels[i],
41 |     marker: {
42 |         size: 8,
43 |         symbol: 'circle',
44 |         color: colors[i],
45 |         line: {
46 |         color: "#000000",
47 |         width: 1.5},
48 |         opacity: 1},
49 |     type: 'scatter2d'};
50 |     data.push(t);
51 |     }
52 | 
53 | Plotly.newPlot('plot3d_surface', data, layout);
54 | 
55 | myPlot.on('plotly_click', function(data){
56 |     var len1 = traces[0][0].length;
57 |     var a = 1;
58 |     if (len1 < 2){
59 |         a = 0;
60 |         }
61 |     plotSelected(data.points[0].pointNumber, data.points[0].curveNumber,len1);  
62 |     });
63 | 


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plotLC.js:
--------------------------------------------------------------------------------
 1 | var data = [];
 2 | var lcs = {{ lcs }};
 3 | var labels = {{ labels|safe }};
 4 | for (i=0; i < {{ lcs|length }}; i++){
 5 |     var x_data = lcs[i][0];
 6 |     var y_data = lcs[i][1];
 7 |     
 8 |     var this_data = {
 9 |                x: x_data,
10 |                y: y_data,
11 |                name: labels[i],
12 |                mode: 'markers',
13 |                error_y: {
14 |                   type: 'data',
15 |                   array: lcs[i][2],
16 |                   visible: true,
17 |                   color: '#85144B'
18 |                             }};
19 |     data.push(this_data);
20 |             
21 | }
22 |   
23 | var layout = {
24 |   title: "Light Curve",
25 |   autosize: true,
26 |     font: {
27 |     size: 25
28 |   },
29 |   width: 800,
30 |   height: 600,
31 |   margin: {
32 |     l: 65,
33 |     r: 50,
34 |     b: 65,
35 |     t: 90,
36 |   },
37 |   xaxis: {
38 |     title: "Time [days]"
39 |     },
40 |   yaxis: {
41 |     title: "Magnitude [mag]",
42 |     autorange: 'reversed'}
43 | };
44 | 
45 | Plotly.newPlot('plotLC', data, layout);


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plotLC_selected.js:
--------------------------------------------------------------------------------
 1 | function plotSelected(id, group=0, len=0){
 2 |     var lc_data = [];
 3 |     var lcs = {{ lcs }};
 4 |     var labels = {{ labels|safe }};
 5 |     var point_labels = {{ point_labels|safe }};
 6 |     
 7 |     if (group < 3) {
 8 |         var iid = id + (group-1)*len
 9 |     }
10 |     else if (group == 3) {
11 |         var iid = id + point_labels[0].length + point_labels[1].length
12 |     }
13 |     else {
14 |         var iid = id + point_labels[0].length + point_labels[1].length + point_labels[2].length
15 |     }
16 |     var x_data = lcs[iid][0];
17 |     var y_data = lcs[iid][1];
18 |     var err_data = lcs[iid][2];
19 |     
20 |     var this_data = {
21 |                x: x_data,
22 |                y: y_data,
23 |                mode: 'markers',
24 |                error_y: {
25 |                   type: 'data',
26 |                   array: err_data,
27 |                   visible: true,
28 |                   color: '#85144B'
29 |                             }};
30 |     lc_data.push(this_data);
31 |                 
32 |     
33 |       
34 |     var layout = {
35 |       title: labels[iid],
36 |       autosize: true,
37 |         font: {
38 |     size: 25
39 |   },
40 |       margin: {
41 |         l: 65,
42 |         r: 50,
43 |         b: 65,
44 |         t: 90,
45 |       },
46 |       xaxis: {
47 |         title: "Time"
48 |         },
49 |       yaxis: {
50 |         title: "Mag",
51 |         autorange: 'reversed'}
52 |     };
53 |     
54 |     Plotly.newPlot('lc_plot', lc_data, layout);
55 |     }


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plotROC.js:
--------------------------------------------------------------------------------
 1 | var x_data = {{ roc_data.0 }};
 2 | var y_data = {{ roc_data.1 }};
 3 | 
 4 | var data = [{
 5 |            x: x_data,
 6 |            y: y_data,
 7 |         }];
 8 |   
 9 | var layout = {
10 |   title: "ROC",
11 |   autosize: false,  
12 |   width: 600,
13 |   height: 500,
14 |   margin: {
15 |     l: 65,
16 |     r: 50,
17 |     b: 65,
18 |     t: 90,
19 |   },
20 |   xaxis: {
21 |     title: "False positive rate",
22 |     range: [0,1]},
23 |   yaxis: {
24 |     title: "True positive rate",
25 |     range: [0 , 1]}
26 | };
27 | 
28 | Plotly.newPlot('plotROC', data, layout);


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plotUnsup2D.js:
--------------------------------------------------------------------------------
  1 | var myPlot = document.getElementById('plot2dUnsup')
  2 | 
  3 | var x_data = {{ probab_data.0 }};
  4 | var y_data = {{ probab_data.1 }};
  5 | 
  6 | var data = [{
  7 |            x: x_data,
  8 |            y: y_data,
  9 |            name: "Probability distribution",
 10 |            opacity: 0.6
 11 |         }];
 12 |         
 13 |         
 14 | var trace0 = {
 15 |   x: {{ coo_data.0 }},
 16 |   type: "histogram",
 17 |   histnorm: 'probability',
 18 |   name: "Histogram",
 19 |   opacity: 0.7,
 20 |   marker: {
 21 |      color: 'green',
 22 |   },
 23 | };
 24 | 
 25 | var trace1 = {
 26 |   x: {{ coo_data.0 }},
 27 |   y: {{ zeroes }},
 28 |   text: {{ coo_plot_labels|safe }},
 29 |   type: "scatter",
 30 |   mode: 'markers',
 31 |   name: "Stars",
 32 |   opacity: 0.9,
 33 |   marker: {
 34 |      color: 'blue',
 35 |      size:10,
 36 |   },
 37 | };
 38 | 
 39 | var trace2 = {
 40 |   x: [{{ centroids.0.0 }}],
 41 |   y: [0],
 42 |   type: "line",
 43 |   name: "Centroid 1",
 44 |   opacity: 0.4,
 45 |   mode: 'markers',
 46 |   marker: {
 47 |      color: 'red',
 48 |      size: 20,
 49 |   },
 50 | };
 51 | 
 52 | var trace3 = {
 53 |   x: [{{ centroids.0.1 }}],
 54 |   y: [0],
 55 |   type: "line",
 56 |   name: "Centroid 2",
 57 |   opacity: 0.4,
 58 |   mode: 'markers',
 59 |   marker: {
 60 |      color: 'red',
 61 |      size: 20,
 62 |   },
 63 | };
 64 | 
 65 | data.push(trace1);
 66 | data.push(trace0);
 67 | 
 68 | data.push(trace2);
 69 | data.push(trace3);
 70 |         
 71 |   
 72 | var layout = {
 73 |   title: "{{ probab_plot_title }}",
 74 |   autosize: false,
 75 |   width: 700,
 76 |   height: 500,
 77 |   margin: {
 78 |     l: 65,
 79 |     r: 50,
 80 |     b: 65,
 81 |     t: 90,
 82 |   },
 83 |   xaxis: {
 84 |     title: "{{ probab_plot_axis.0 }}"},
 85 |   yaxis: {
 86 |     title: "Probability"}
 87 | };
 88 | 
 89 | Plotly.newPlot('plot2dUnsup', data, layout);
 90 | 
 91 | myPlot.on('plotly_click', function(data){
 92 |     for (var i = 0; i < data.points.length; i ++){
 93 |     
 94 |         if (data.points[i].curveNumber == 1){
 95 |             plotSelected(data.points[i].pointNumber);
 96 |         }
 97 |         
 98 |         
 99 |     }
100 |     
101 |     
102 |     
103 | });


--------------------------------------------------------------------------------
/lcc_web/web/interface/templates/visual/plotUnsupSpace.js:
--------------------------------------------------------------------------------
 1 | var myPlot = document.getElementById('plotUnsup')
 2 | 
 3 | var x_data = {{ probab_data.0 }};
 4 | var y_data = {{ probab_data.1 }};
 5 | var z_data = {{ probab_data.2 }};
 6 | 
 7 | var data = [{
 8 |            x: x_data,
 9 |            y: y_data,
10 |            z: z_data,
11 |            type: 'contour'
12 |         }];
13 |   
14 | var layout = {
15 |   legend: {
16 |     x: 1500,
17 |     y: 1000
18 |     },
19 |   overlaying: 'y',
20 |   side: "right",
21 |   title: "{{ probab_plot_title }}",
22 |   xaxis: {
23 |     title: "{{ probab_plot_axis.0 }}"},
24 |   yaxis: {
25 |     title: "{{ probab_plot_axis.1 }}",
26 |     y: -1600},
27 |   autosize: true,
28 |   margin: {
29 |     l: 65,
30 |     r: 50,
31 |     b: 65,
32 |     t: 90,
33 |   }
34 | };
35 | 
36 | var traces = {{ coo_data }};
37 | var labels = {{ coo_plot_labels|safe }};
38 | var t = {
39 |     x: traces[0], y: traces[1],
40 |     mode: 'markers',
41 |     name: "Sample",
42 |     text: labels,
43 |     marker: {
44 |         size: 8,
45 |         symbol: 'circle',
46 |         line: {
47 |         color: 'rgb(204, 204, 204)',
48 |         width: 1},
49 |         opacity: 0.8},
50 |     type: 'scatter2d'};
51 | data.push(t);
52 | 
53 | 
54 | var cent = {{ centroids }};
55 | var tc = {
56 |     x: cent[0], y: cent[1],
57 |     mode: 'markers',
58 |     name: "Clusters center",
59 |     text: ["Centroid1", "Centroid2"],
60 |     marker: {
61 |         size: 18,
62 |         symbol: 'circle',
63 |         line: {
64 |         color: 'rgb(204, 204, 204)',
65 |         width: 1},
66 |         opacity: 0.8},
67 |     type: 'scatter2d'};
68 | data.push(tc);
69 |     
70 | 
71 | Plotly.newPlot('plotUnsup', data, layout);
72 | 
73 | myPlot.on('plotly_click', function(data){
74 |     plotSelected(data.points[0].pointNumber);
75 |     
76 | });


--------------------------------------------------------------------------------
/lcc_web/web/interface/tests.py:
--------------------------------------------------------------------------------
1 | from django.test import TestCase
2 | 
3 | # Create your tests here.
4 | 


--------------------------------------------------------------------------------
/lcc_web/web/interface/urls.py:
--------------------------------------------------------------------------------
 1 | import interface.views as views
 2 | from django.conf.urls import url
 3 | from interface.lcc_views import jobs, searching, filtering, visualization
 4 | 
 5 | urlpatterns = [
 6 |     url(r'^$', views.home, name='home'),
 7 |     url(r'^manage_modules', views.manage_modules, name='manage_modules'),
 8 |     url(r'^new_user', views.create_user, name='create_user'),
 9 |     url(r'^contact', views.contact, name='contact'),
10 |     url(r'^guide', views.guide, name='guide'),
11 |     url(r'^logs', views.show_logs, name='show_logs'),
12 |     url(r'^login', views.login_view, name='login_view'),
13 |     url(r'^logout', views.logout_view, name='logout_view'),
14 |     url(r'^show', visualization.stars, name='show'),
15 |     url(r'^unsup', visualization.unsup_clust, name='unsup'),
16 |     url(r'^make_filter$', filtering.upload_form, name='make_filter'),
17 |     url(r'^delete/(?P<job_type>\D+)/(?P<job_id>\d+)',
18 |         views.delete_job, name='delete_job'),
19 |     url(r'^stars_filter/(?P<job_id>[a-zA-Z0-9]*)',
20 |         filtering.show, name='stars_filter'),
21 |     url(r'^search', searching.upload_form, name='search'),
22 |     url(r'^result/(?P<job_id>[a-zA-Z0-9]*)', searching.show, name='result'),
23 |     url(r'^stars_filters', jobs.all_filters, name='all_filters'),
24 |     url(r'^results*', jobs.all_results, name='all_results'),
25 |     url(r'^download/(?P<file_name>[a-zA-Z0-9]*)', jobs.download_file, name='download')]
26 | 
27 | 
28 | # run_workers(n_workers=int(os.environ.get("LCC_RQ_WORKERS", 1)))
29 | 


--------------------------------------------------------------------------------
/lcc_web/web/manage.py:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env python
 2 | import os
 3 | import sys
 4 | 
 5 | 
 6 | if __name__ == "__main__":
 7 |     os.environ.setdefault("DJANGO_SETTINGS_MODULE", "LCCwebApp.settings")
 8 |     try:
 9 |         from django.core.management import execute_from_command_line
10 |     except ImportError:
11 |         # The above import may fail for some other reason. Ensure that the
12 |         # issue is really that Django is missing to avoid masking other
13 |         # exceptions on Python 2.
14 |         try:
15 |             import django
16 |         except ImportError:
17 |             raise ImportError(
18 |                 "Couldn't import Django. Are you sure it's installed and "
19 |                 "available on your PYTHONPATH environment variable? Did you "
20 |                 "forget to activate a virtual environment?"
21 |             )
22 |         raise
23 |     execute_from_command_line(sys.argv)
24 | 


--------------------------------------------------------------------------------
/lcc_web/web/requirements.in:
--------------------------------------------------------------------------------
 1 | tensorflow
 2 | keras
 3 | numpy
 4 | scipy
 5 | matplotlib
 6 | django==1.11.1
 7 | django-graphos
 8 | pandas
 9 | scikit-learn
10 | kplr
11 | astroML
12 | astropy
13 | requests
14 | bs4
15 | gunicorn
16 | tqdm
17 | redis
18 | rq
19 | 


--------------------------------------------------------------------------------
/lcc_web/web/requirements.txt:
--------------------------------------------------------------------------------
 1 | tensorflow==1.3.0
 2 | keras==2.0.8
 3 | numpy==1.13.0
 4 | scipy==0.19.1
 5 | matplotlib==2.0.2
 6 | Django==1.11.1
 7 | django-graphos==0.3.41
 8 | pandas==0.20.2
 9 | scikit-learn==0.18.1
10 | kplr==0.2.1
11 | astroML==0.3
12 | astropy==1.3.3
13 | requests==2.13.0
14 | bs4==0.0.1
15 | gunicorn==19.7.1
16 | tqdm==4.14.0
17 | 
18 | 


--------------------------------------------------------------------------------
/lcc_web/web/run_localy.sh:
--------------------------------------------------------------------------------
 1 | export DOCKYARD_SRC=web
 2 | export DOCKYARD_SRVHOME=/Users/martinvo/workspace/private2/LCCwebApp
 3 | export DOCKYARD_SRVPROJ=$DOCKYARD_SRVHOME/web
 4 | export DOCKYARD_SRVSAMPLE=$DOCKYARD_SRVHOME/sample_data
 5 | export DOCKYARD_SRVDATA=$DOCKYARD_SRVHOME/data
 6 | export DOCKYARD_SRVLOGS=$DOCKYARD_SRVHOME/logs
 7 | export DOCKYARD_SRVSTATIC=$DOCKYARD_SRVHOME/static/
 8 | export DOCKYARD_APP_CONTEXT=lcc
 9 | export DOCKYARD_PORT=8000
10 | export http_host=http://127.0.0.1:80
11 | 
12 | python3.6 manage.py migrate                  # Apply database migrations
13 | python3.6 manage.py collectstatic --noinput  # Collect static files
14 | 
15 | 
16 | service nginx start
17 | # Start Gunicorn processes
18 | echo Starting Gunicorn.
19 | exec gunicorn LCCwebApp.wsgi:application \
20 |     --name LCCwebApp \
21 |     --bind 127.0.0.1:$DOCKYARD_PORT \
22 |     --workers 3 \
23 |     --log-level=info \
24 |     --log-file=$DOCKYARD_SRVLOGS/gunicorn.log \
25 |     --access-logfile=$DOCKYARD_SRVLOGS/access.log
26 | 
27 | 


--------------------------------------------------------------------------------
/lcc_web/web/run_localy_dbg.sh:
--------------------------------------------------------------------------------
 1 | export PYTHONPATH=$PYTHONPAT:'/Users/martinvo/workspace/private2/LightCurvesClassifier'
 2 | export DOCKYARD_SRC=web
 3 | export DOCKYARD_SRVHOME=/Users/martinvo/workspace/private2/LightCurvesClassifier/lcc_web
 4 | export DOCKYARD_SRVPROJ=$DOCKYARD_SRVHOME/web
 5 | export DOCKYARD_SRVDATA=$DOCKYARD_SRVHOME/data
 6 | export DOCKYARD_SRVSAMPLE=$DOCKYARD_SRVHOME/sample_data
 7 | export DOCKYARD_SRVLOGS=$DOCKYARD_SRVHOME/logs
 8 | export DOCKYARD_SRVSTATIC=$DOCKYARD_SRVHOME/static/
 9 | export DOCKYARD_APP_CONTEXT=lcc
10 | export DOCKYARD_DEBUG=True
11 | 
12 | # python3.6 manage.py migrate                  # Apply database migrations
13 | # python3.6 manage.py makemigrations
14 | # python3.6 manage.py collectstatic --noinput  # Collect static files
15 | python3.6 manage.py runserver 0.0.0.0:8001
16 | 
17 | 


--------------------------------------------------------------------------------
/nginx.conf:
--------------------------------------------------------------------------------
 1 | server {
 2 |     client_max_body_size 5000M;
 3 |     proxy_connect_timeout 75s;
 4 |     proxy_read_timeout 300s;
 5 |     listen 80 default_server;
 6 | 
 7 |     location /lcc {
 8 |         proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
 9 |         proxy_set_header Host $http_host;
10 |         proxy_pass http://127.0.0.1:8000;
11 |     }
12 | 
13 |     location /lcc/static/ {
14 |         autoindex off;
15 |         alias /srv/static/;
16 |     }
17 | }
18 | 


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
 1 | numpy==1.12.1
 2 | pathos==0.2.0
 3 | scipy==0.19.0
 4 | matplotlib==2.0.0
 5 | pandas==0.20.1
 6 | pyfits==3.3 
 7 | scikit-learn==0.18.1
 8 | kplr==0.2.1
 9 | astroML==0.3
10 | astropy==1.3.2
11 | requests==2.13.0
12 | bs4==0.0.1
13 | tensorflow==1.3.0
14 | keras==2.0.8
15 | lxml==4.1.1
16 | tqdm==4.19.5
17 | redis
18 | rq


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/setup.cfg:
--------------------------------------------------------------------------------
1 | [metadata]
2 | description-file = README.md
3 | 


--------------------------------------------------------------------------------
/setup.py:
--------------------------------------------------------------------------------
 1 | from setuptools import setup, find_packages
 2 | 
 3 | setup(
 4 |   name='lcc',
 5 |   packages=find_packages(),
 6 |   version='1.2.4',
 7 |   description='Light Curves Classifier is package for classification stars by using their light curves and metadata',
 8 |   author='Martin Vo',
 9 |   author_email='mavrix@seznam.cz',
10 |   url='https://github.com/mavrix93/LightCurvesClassifier',
11 |   download_url='https://github.com/mavrix93/LightCurvesClassifier/archive/v1.0.0.tar.gz',
12 |   install_requires=["numpy", "scipy", "matplotlib", "pandas", "scikit-learn",
13 |                     "kplr", "astroML", "astropy", "requests", "bs4", "pathos", "tqdm", "keras",
14 |                     "redis", "rq"],
15 |   keywords=['light curves', 'machine-learning', 'astronomy', 'data-mining'],
16 |   entry_points={'console_scripts': ['lcc=lcc.cli.lcc:main']},
17 |   classifiers=[
18 |     'Development Status :: 4 - Beta',
19 |     'Programming Language :: Python :: 3',
20 |     'Programming Language :: Python :: 3.6'],
21 | )
22 | 
23 | 


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/test/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/test/__init__.py


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/test/cli/__init__.py:
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/test/db_tier/__init__.py:
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/test/db_tier/test_stars_searcher.py:
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 1 | 
 2 | 
 3 | from lcc.db_tier.connectors.ogleII import OgleII
 4 | from lcc.db_tier.stars_provider import StarsProvider
 5 | 
 6 | 
 7 | def test_OgleII():
 8 |     que2 = {"field": "LMC_SC3", "starid": 5}
 9 | 
10 |     queries = [{"field": "LMC_SC3", "starid": i} for i in range(1, 5)]
11 |     prov = StarsProvider.getProvider("OgleII", queries)
12 |     stars = prov.getStars()
13 | 
14 | 
15 | def test_OgleIII():
16 |     que1 = {"ra": 72.798405,
17 |             "dec": -69.00918, "delta": 5, "nearest": True}
18 | 
19 |     que3 = {"field": "LMC135.5", "starid": 19670}
20 | 
21 |     client = StarsProvider().getProvider("OgleIII", [que1, que3])
22 |     stars = client.getStars()
23 | 
24 |     assert len(stars) == 2
25 |     assert len(stars[0].lightCurve.mag) == 370
26 |     assert len(stars[1].lightCurve.mag) == 370
27 | 


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/test/intergation/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/test/intergation/__init__.py


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/test/intergation/test_searcher.py:
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 1 | import time
 2 | import numpy as np
 3 | 
 4 | 
 5 | from lcc.entities.star import Star
 6 | from lcc.stars_processing.deciders import LDADec, QDADec, GradBoostDec
 7 | from lcc.stars_processing.descriptors import AbbeValueDescr
 8 | from lcc.stars_processing.stars_filter import StarsFilter
 9 | from lcc.stars_processing.systematic_search.stars_searcher import StarsSearcherRedis
10 | from lcc.stars_processing.systematic_search.worker import run_workers
11 | 
12 | 
13 | def test():
14 |     descriptors = [AbbeValueDescr()]
15 |     # deciders = [NeuronDecider(maxEpochs=800)]
16 |     deciders = [LDADec(), QDADec(), GradBoostDec()]
17 |     s_stars = [Star(name="Searched_{}".format(i)) for i in range(100)]
18 |     c_stars = [Star(name="Contam_{}".format(i)) for i in range(100)]
19 | 
20 |     x = np.linspace(0, 10, 100)
21 |     for st in s_stars:
22 |         st.putLightCurve([x, np.cos(x) - 0.5 + np.random.random_sample(100)])
23 | 
24 |     for st in c_stars:
25 |         st.putLightCurve([x, np.exp(x*np.random.random_sample(100))])
26 | 
27 |     filt = StarsFilter(descriptors, deciders)
28 |     filt.learn(s_stars, c_stars)
29 | 
30 |     searcher = StarsSearcherRedis([filt], db_connector="OgleII", save_path="/tmp/test_stars")
31 | 
32 |     queries = [{"field": "LMC_SC3", "starid": i} for i in range(1, 10)]
33 |     searcher.queryStars(queries)
34 | 
35 |     run_workers(n_workers=1)
36 | 
37 |     assert len(searcher.getPassedStars()) > 0
38 | 
39 |     time.sleep(2)
40 |     assert len(searcher.getStatus()) == len(queries)


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/test/resources/CurveShapeFilter.filter:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/test/resources/CurveShapeFilter.filter


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/test/resources/project_settings.py:
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 1 | import os
 2 | 
 3 | 
 4 | project_dir = os.path.dirname(os.path.abspath(__file__))
 5 | 
 6 | 
 7 | # Input locations
 8 | INP_LCS = os.path.join(project_dir)
 9 | TUN_PARAMS = os.path.join(project_dir)
10 | QUERIES = "/tmp"
11 | FILTERS = os.path.join(project_dir)
12 | RESULTS = os.path.join(project_dir)
13 | 
14 | 
15 | # Output locations
16 | 


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/test/resources/query_file.txt:
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1 | $


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/test/resources/query_local.txt:
--------------------------------------------------------------------------------
1 | #path
2 | qso


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/test/resources/query_ogle.txt:
--------------------------------------------------------------------------------
1 | #starid;field_num;target
2 | 1;1;lmc
3 | 1;2;lmc
4 | 1;3;lmc
5 | 1;4;lmc
6 | 1;5;lmc


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/test/resources/test_filter.pickle:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/test/resources/test_filter.pickle


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/test/resources/tune_lc_shape.txt:
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1 | #CurvesShapeDescr:alphabet_size;CurvesShapeDescr:days_per_bin;QDADec:threshold
2 | 5;30;0.1
3 | 5;30;0.18
4 | 5;30;0.26


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/test/stars_processing/__init__.py:
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/test/stars_processing/test_comp_descriptors.py:
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 1 | import unittest
 2 | 
 3 | import numpy as np
 4 | 
 5 | from lcc.entities.star import Star
 6 | from lcc.stars_processing.descriptors.curves_shape_descr import CurvesShapeDescr
 7 | from lcc.stars_processing.descriptors.hist_shape_descr import HistShapeDescr
 8 | from lcc.stars_processing.descriptors.variogram_shape_descr import VariogramShapeDescr
 9 | 
10 | 
11 | class TestComparative(unittest.TestCase):
12 | 
13 |     def setUp(self):
14 |         self.star1 = Star()
15 |         x = np.linspace(1, 10, 100)
16 |         x2 = x**2
17 |         self.star1.putLightCurve([x, x2 / x2[-1]])
18 |         self.star2 = Star()
19 |         self.star2.putLightCurve([x, np.cos(x)])
20 |         self.star3 = Star()
21 |         xx = np.linspace(1,45, 600)
22 |         self.star3.putLightCurve([xx, np.cos(xx + 0.1)*xx])
23 | 
24 |     def testCurveShape(self):
25 |         lcdes = CurvesShapeDescr([self.star2], 0.6, 10)
26 |         assert lcdes.getSpaceCoords(
27 |             [self.star3])[0] < lcdes.getSpaceCoords([self.star1])[0]
28 | 
29 |     def testHistShape(self):
30 |         hist = HistShapeDescr([self.star2], 10, 5)
31 |         assert hist.getSpaceCoords(
32 |             [self.star3])[0] > hist.getSpaceCoords([self.star1])[0]
33 | 
34 |     def testVarioShape(self):
35 |         vario = VariogramShapeDescr([self.star2], 10, 5)
36 |         assert vario.getSpaceCoords(
37 |             [self.star3]) > vario.getSpaceCoords([self.star1])
38 | 
39 | 
40 | if __name__ == "__main__":
41 |     unittest.main()
42 | 


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/test/stars_processing/test_deciders.py:
--------------------------------------------------------------------------------
 1 | import numpy as np
 2 | 
 3 | import lcc.stars_processing.deciders.supervised_deciders as dec
 4 | from lcc.stars_processing.deciders.neuron_decider import NeuronDecider
 5 | 
 6 | 
 7 | def set_up():
 8 |     deciders = [dec.AdaBoostDec(), dec.ExtraTreesDec(), dec.GaussianNBDec(), dec.LDADec(), dec.QDADec(),
 9 |                          dec.RandomForestDec(), dec.SVCDec(), dec.TreeDec(),
10 |                 NeuronDecider(hidden_neurons=10, maxEpochs=500)]
11 | 
12 |     return np.random.random_sample((100, 7)), np.random.random_sample((100, 7)) + 1, deciders
13 | 
14 | 
15 | def test():
16 |     search_sample1, others_sample1, deciders = set_up()
17 | 
18 |     eee = {}
19 |     for dec in deciders:
20 |         dec.learn(search_sample1, others_sample1)
21 |         p1 = dec.evaluate(search_sample1)
22 |         p2 = dec.evaluate(others_sample1)
23 |         eee[dec.__class__.__name__] = np.mean(p1) - np.mean(p2)
24 |         assert np.mean(p1) - np.mean(p2) > 0.95
25 | 
26 | 


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/test/stars_processing/test_descriptors.py:
--------------------------------------------------------------------------------
 1 | import logging
 2 | 
 3 | from lcc.data_manager.package_reader import PackageReader
 4 | from lcc.entities.star import Star
 5 | import unittest
 6 | import numpy as np
 7 | 
 8 | logging.basicConfig(level=logging.DEBUG)
 9 | 
10 | 
11 | class TestDescriptors(unittest.TestCase):
12 | 
13 |     n_stars = 10
14 | 
15 |     def setUp(self):
16 |         self.descriptors = PackageReader.getClassesDict("descriptors")
17 |         self.stars = []
18 |         for i in range(self.n_stars):
19 |             star = Star()
20 |             x = np.linspace(0, 100, 100)
21 |             y = np.sin(x**i)
22 |             y[0] = np.nan
23 |             x[:20] = np.linspace(-30, -10, 20)
24 |             star.putLightCurve([x, y])
25 |             self.stars.append(star)
26 | 
27 |     def testAbbe(self):
28 |         abbe_filter = self.descriptors["AbbeValueDescr"]
29 |         abbe_values = abbe_filter(bins=10).getSpaceCoords(self.stars)
30 |         self.assertTrue(len(abbe_values) == self.n_stars)
31 |         assert not np.isnan(abbe_values).all()
32 |         # TODO
33 |         # assert False not in [abbe_values[i] < abbe_values[i + 1] for i in range(len(abbe_values) - 1)]
34 | 
35 |     def testSkewness(self):
36 |         skewness_descr = self.descriptors["SkewnessDescr"]
37 |         sk_values = skewness_descr(bins=30).getSpaceCoords(self.stars)
38 |         assert not np.isnan(sk_values).all()
39 | 
40 |     def testComparative(self):
41 |         logging.debug("Starting comparative test")
42 |         descr = self.descriptors["HistShapeDescr"](self.stars[:4], 10, 10)
43 | 
44 | 
45 | if __name__ == "__main__":
46 |     unittest.main()
47 | 


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/test/stars_processing/test_params_estim.py:
--------------------------------------------------------------------------------
 1 | """
 2 | Created on Jan 25, 2017
 3 | 
 4 | @author: Martin Vo
 5 | """
 6 | 
 7 | import unittest
 8 | 
 9 | import numpy as np
10 | 
11 | from lcc.entities.star import Star
12 | from lcc.stars_processing.deciders.supervised_deciders import QDADec
13 | from lcc.stars_processing.descriptors.abbe_value_descr import AbbeValueDescr
14 | from lcc.stars_processing.descriptors.curves_shape_descr import CurvesShapeDescr
15 | from lcc.stars_processing.tools.params_estim import ParamsEstimator
16 | 
17 | 
18 | # TODO: Need to be fixed
19 | class Test(unittest.TestCase):
20 | 
21 |     def setUp(self):
22 |         N = 20
23 | 
24 |         x = np.linspace(0, 10, 100)
25 | 
26 |         self.template = []
27 |         for ii in range(N):
28 |             st = Star(name="TemplateStar%i" % ii)
29 |             st.putLightCurve([x, np.cos(x) + np.random.normal(x) * 0.1])
30 |             self.template.append(st)
31 | 
32 |         self.variables = []
33 |         for ii in range(N):
34 |             st = Star(name="VariableStar%i" % ii)
35 |             st.putLightCurve([x, np.sin(x) + np.random.normal(x) * 0.1])
36 |             self.variables.append(st)
37 | 
38 |         self.noisy = []
39 |         for ii in range(N):
40 |             st = Star(name="NonvariableStar%i" % ii)
41 |             st.putLightCurve([x, np.random.normal(x) * 2])
42 |             self.noisy.append(st)
43 | 
44 |     def testName(self):
45 |         deciders = [QDADec]
46 |         descriptors = [AbbeValueDescr, CurvesShapeDescr]
47 |         static_params = {"AbbeValueDescr": {"bins": 100},
48 |                          "CurvesShapeDescr": {"comp_stars": self.template}}
49 |         tuned_params = [{"CurvesShapeDescr": {"days_per_bin": 3, "alphabet_size": 10}},
50 |                         {"CurvesShapeDescr": {"days_per_bin": 0.5, "alphabet_size": 12}}]
51 |         
52 |         est = ParamsEstimator(self.variables, self.noisy, descriptors, deciders,
53 |                               tuned_params, static_params=static_params)
54 | 
55 |         star_filter, stat, best_params = est.fit()
56 |         assert best_params is not None
57 | 
58 | 
59 | if __name__ == "__main__":
60 |     unittest.main()
61 | 


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/test/stars_processing/test_stars_filter.py:
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 1 | import pickle
 2 | import os
 3 | 
 4 | import numpy as np
 5 | from lcc.stars_processing.deciders import LDADec, QDADec
 6 | 
 7 | from lcc.entities.star import Star
 8 | from lcc.stars_processing.descriptors.abbe_value_descr import AbbeValueDescr
 9 | from lcc.stars_processing.stars_filter import StarsFilter
10 | 
11 | 
12 | def setup():
13 |     descriptors = [AbbeValueDescr()]
14 |     # deciders = [NeuronDecider(maxEpochs=800)]
15 |     deciders = [LDADec(), QDADec()]
16 |     s_stars = [Star(name="Searched_{}".format(i)) for i in range(100)]
17 |     c_stars = [Star(name="Contam_{}".format(i)) for i in range(100)]
18 |     m_stars = [Star(name="Contam_{}".format(i)) for i in range(100)]
19 | 
20 |     x = np.linspace(0, 10, 100)
21 |     for st in s_stars:
22 |         st.putLightCurve([x, np.cos(x) - 0.5 + np.random.random_sample(100)])
23 | 
24 |     for st in c_stars:
25 |         st.putLightCurve([x, np.exp(x*np.random.random_sample(100))])
26 | 
27 |     filt = StarsFilter(descriptors, deciders)
28 |     return s_stars, c_stars, m_stars, filt
29 | 
30 | 
31 | def test_getAllPredictions():
32 |     s_stars, c_stars, m_stars, filt = setup()
33 |     filt.learn(s_stars[:80], c_stars[:80])
34 | 
35 |     sx = filt.getAllPredictions(s_stars[80:], with_features=True, check_passing=True)
36 |     cx = filt.getAllPredictions(c_stars[80:], with_features=True, check_passing=True)
37 | 
38 |     assert sx.columns.tolist() == cx.columns.tolist() == ["Abbe value", "LDADec", "QDADec", "passed_LDADec",
39 |                                                           "passed_QDADec", "passed"]
40 |     assert sx["passed"].sum() > cx["passed"].sum()
41 | 
42 |     # FIXME: Can't handle missing light curves
43 |     # mx = filt.getAllPredictions(m_stars, with_features=True, check_passing=True)
44 | 
45 | 
46 | def test_filtering():
47 |     s_stars, c_stars, _, filt = setup()
48 | 
49 |     filt.learn(s_stars[:80], c_stars[:80])
50 | 
51 |     ps = filt.evaluateStars(s_stars[80:])
52 |     cs = filt.evaluateStars(c_stars[80:])
53 | 
54 |     s_coo = filt.getSpaceCoordinates(s_stars)
55 |     c_coo = filt.getSpaceCoordinates(c_stars)
56 | 
57 |     assert ps.mean() - cs.mean() > ps.std() + cs.std()
58 | 
59 |     assert c_coo["Abbe value"].mean() - s_coo["Abbe value"].mean() > c_coo["Abbe value"].std() + s_coo[
60 |         "Abbe value"].std()
61 | 
62 |     ev = filt.getEvaluations(c_stars)
63 | 
64 |     with open(os.path.join(os.path.dirname(__file__), "../resources/test_filter.pickle"), "wb") as fi:
65 |         pickle.dump(filt, fi)
66 | 
67 | 


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/test/stars_processing/test_stars_searcher.py:
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 1 | import os
 2 | import pickle
 3 | 
 4 | import time
 5 | 
 6 | from lcc.stars_processing.systematic_search.stars_searcher import StarsSearcher, StarsSearcherRedis
 7 | 
 8 | 
 9 | def test_redis():
10 |     with open(os.path.join(os.path.dirname(__file__), "../resources/test_filter.pickle"), "rb") as fi:
11 |         st_filter = pickle.load(fi)
12 |     searcher = StarsSearcherRedis([st_filter], db_connector="OgleII", save_path="/tmp/test_stars")
13 | 
14 |     queries = [{"field": "LMC_SC3", "starid": i} for i in range(1, 10)]
15 |     searcher.queryStars(queries)
16 | 
17 |     assert len(searcher.getPassedStars()) > 0
18 | 
19 |     time.sleep(2)
20 |     # TODO: Fix me
21 |     assert len(searcher.getStatus()) >= int(len(queries) * 0.6)
22 | 
23 | 
24 | def test_sequential():
25 |     with open(os.path.join(os.path.dirname(__file__), "../resources/test_filter.pickle"), "rb") as fi:
26 |         st_filter = pickle.load(fi)
27 |     searcher = StarsSearcher([st_filter], save_path="/tmp", stat_file_path="/tmp/status.txt",
28 |                              db_connector="OgleII", multiproc=False, save_coords=True)
29 | 
30 |     queries = [{"field": "LMC_SC3", "starid": i} for i in range(1, 10)]
31 |     searcher.queryStars(queries)
32 | 
33 |     report = searcher.getStatus()
34 |     assert len(searcher.getPassedStars()) > 0
35 | 
36 |     # TODO: Fix me
37 |     # assert len(report) == len(queries)
38 |     assert len(report) >= int(len(queries) * 0.6)
39 | 
40 | 
41 | 
42 | 
43 | 


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/test/utils/__init__.py:
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https://raw.githubusercontent.com/mavrix93/LightCurvesClassifier/a0a51f033cb8adf45296913f0de0aa2568e0530c/test/utils/__init__.py


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/test/utils/test_data_analysis.py:
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 1 | import numpy as np
 2 | from lcc.utils.data_analysis import to_PAA, to_ekvi_PAA, compute_bins, fix_missing
 3 | 
 4 | 
 5 | def test_to_PAA():
 6 |     for _ in range(100):
 7 |         x = np.random.random_sample(np.random.randint(30, 700))
 8 | 
 9 |         bins = np.random.randint(5, 30)
10 |         assert len(to_PAA(x, bins)[0]) == bins
11 | 
12 | 
13 | def test_to_ekvi_PAA1():
14 |     n = 100
15 |     x = np.linspace(0, 1, n)
16 |     y = np.random.random_sample(n)
17 | 
18 |     bins = np.random.randint(5, 30)
19 | 
20 |     x_ekv1, y_ekv1 = to_ekvi_PAA(x, y,  bins)
21 |     x_ekv2, y_ekv2 = to_ekvi_PAA(x, y, len(x))
22 |     x_ekv3, y_ekv3 = to_ekvi_PAA(x, y, 3 * len(x))
23 | 
24 |     assert len(x_ekv1) == bins
25 |     assert len(x_ekv2) == len(x)
26 |     assert len(x_ekv3) == len(x)
27 |     assert np.nan not in y_ekv1
28 |     assert np.nan not in y_ekv2
29 |     assert np.nan not in y_ekv3
30 |     assert (y_ekv3 == y).all()
31 |     assert (y_ekv2 == y).all()
32 | 
33 |     for _ in range(100):
34 |         n = np.random.randint(30, 700)
35 |         x = np.random.random_sample(n)
36 | 
37 |         x1 = np.linspace(0, 1, n)
38 |         y = np.random.random_sample(n)
39 | 
40 |         bins = np.random.randint(5, 30)
41 | 
42 |         x_ekv1, y_ekv1 = to_ekvi_PAA(x, y,  bins)
43 |         x_ekv2, y_ekv2 = to_ekvi_PAA(x, y, len(x))
44 |         x_ekv3, y_ekv3 = to_ekvi_PAA(x, y, 3 * len(x))
45 |         x_ekv4, y_ekv4 = to_ekvi_PAA(x1, y, len(x1))
46 | 
47 |         assert len(x_ekv1) == bins
48 |         assert len(x_ekv2) == len(x)
49 |         assert len(x_ekv3) == len(x)
50 |         assert np.nan not in y_ekv1
51 |         assert np.nan not in y_ekv2
52 |         assert np.nan not in y_ekv3
53 |         assert (y_ekv4 == y).all()
54 | 
55 |         thr = 0.1
56 |         assert abs(y_ekv1.mean() - y.mean()) / (y_ekv1.mean() + y.mean()) < thr
57 |         assert abs(y_ekv2.mean() - y.mean()) / (y_ekv2.mean() + y.mean()) < thr
58 |         assert abs(y_ekv3.mean() - y.mean()) / (y_ekv3.mean() + y.mean()) < thr
59 | 
60 | 
61 | def test_compute_bins():
62 |     x1 = [1, 2, 3, 8, 9, 10]
63 |     x2 = [1, 2, 3, 4, 5, 6]
64 | 
65 |     assert compute_bins(x2, days_per_bin=1.9, set_min=2) == 3
66 |     assert compute_bins(x1, days_per_bin=3, set_min=2) == 3
67 | 
68 | 
69 | def test_fix_missing():
70 |     x = np.linspace(0, 10, 20)
71 |     y = x.copy()
72 |     x[:5] = np.linspace(-15, -10, 5)
73 | 
74 |     xx, yy = to_ekvi_PAA(x, y)
75 |     yy[0] = np.nan
76 |     yy[-1] = np.nan
77 | 
78 |     res1 = fix_missing(xx, yy, replace_at_borders=False)
79 | 
80 |     assert len(res1[0]) == len(res1[1])
81 |     assert len(res1[0]) == len(xx) - 2
82 |     assert not np.isnan(res1[0]).any()
83 |     assert not np.isnan(res1[1]).any()
84 | 
85 |     res2 = fix_missing(xx, yy, replace_at_borders=True)
86 | 
87 |     assert len(res2[0]) == len(res2[1])
88 |     assert len(res2[0]) == len(xx)
89 |     assert not np.isnan(res2[0]).any()
90 |     assert not np.isnan(res2[1]).any()
91 |     assert res2[1][0] == res2[1][1]
92 |     assert res2[1][-2] == res2[1][-1]
93 | 
94 |     # assert res1[0] == res2[0]
95 | 


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