* Remove unused persistent poverty from score (#1835)
* Test a few datasets for overlap in the final score (#1835)
* Add remaining data sources (#1853)
* Apply code-review feedback (#1835)
* Rearrange a little for readabililty (#1835)
* Add tract test (#1835)
* Add test for score values (#1835)
* Check for unmatched source tracts (#1835)
* Cleanup numeric code to plaintext (#1835)
* Make import more obvious (#1835)
* temp update
* updating with fips check
* adding check on pfs
* updating with pfs test
* Update test_tiles_smoketests.py
* Fix lint errors (#1848)
* Add column names test (#1848)
* Mark tests as smoketests (#1848)
* Move to other score-related tests (#1848)
* Recast Total threshold criteria exceeded to int (#1848)
In writing tests to verify the output of the tiles csv matches the final
score CSV, I noticed TC/Total threshold criteria exceeded was getting
cast from an int64 to a float64 in the process of PostScoreETL. I
tracked it down to the line where we merge the score dataframe with
constants.DATA_CENSUS_CSV_FILE_PATH --- there where > 100 tracts in the
national census CSV that don't exist in the score, so those ended up
with a Total threshhold count of np.nan, which is a float, and thereby
cast those columns to float. For the moment I just cast it back.
* No need for low memeory (#1848)
* Add additional tests of tiles.csv (#1848)
* Drop pre-2010 rows before computing score (#1848)
Note this is probably NOT the optimal place for this change; it might
make more sense for each source to filter its own tracts down to the
acceptable tract list. However, that would be a pretty invasive change,
where this is central and plenty of other things are happening in score
transform that could be moved to sources, so for today, here's where the
change will live.
* Fix typo (#1848)
* Switch from filter to inner join (#1848)
* Remove no-op lines from tiles (#1848)
* Apply feedback from review, linter (#1848)
* Check the values oeverything in the frame (#1848)
* Refactor checker class (#1848)
* Add test for state names (#1848)
* cleanup from reviewing my own code (#1848)
* Fix lint error (#1858)
* Apply Emma's feedback from review (#1848)
* Remove refs to national_df (#1848)
* Account for new, fake nullable bools in tiles (#1848)
To handle a geojson limitation, Emma converted some nullable boolean
colunms to float64 in the tiles export with the values {0.0, 1.0, nan},
giving us the same expressiveness. Sadly, this broke my assumption that
all columns between the score and tiles csvs would have the same dtypes,
so I need to account for these new, fake bools in my test.
* Use equals instead of my worse version (#1848)
* Missed a spot where we called _create_score_data (#1848)
* Update per safety (#1848)
Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov>
* just testing that the boolean is preserved on gha
* checking drop tracts works
* adding a check to the agvalue calculation for nri
* updated with error messages
* update Python version on README; tuple typing fix
* Alaska tribal points fix (#1821)
* Bump mistune from 0.8.4 to 2.0.3 in /data/data-pipeline (#1777)
Bumps [mistune](https://github.com/lepture/mistune) from 0.8.4 to 2.0.3.
- [Release notes](https://github.com/lepture/mistune/releases)
- [Changelog](https://github.com/lepture/mistune/blob/master/docs/changes.rst)
- [Commits](https://github.com/lepture/mistune/compare/v0.8.4...v2.0.3)
---
updated-dependencies:
- dependency-name: mistune
dependency-type: indirect
...
Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* poetry update
* initial pass of score tests
* add threshold tests
* added ses threshold (not donut, not island)
* testing suite -- stopping for the day
* added test for lead proxy indicator
* Refactor score tests to make them less verbose and more direct (#1865)
* Cleanup tests slightly before refactor (#1846)
* Refactor score calculations tests
* Feedback from review
* Refactor output tests like calculatoin tests (#1846) (#1870)
* Reorganize files (#1846)
* Switch from lru_cache to fixture scorpes (#1846)
* Add tests for all factors (#1846)
* Mark smoketests and run as part of be deply (#1846)
* Update renamed var (#1846)
* Switch from named tuple to dataclass (#1846)
This is annoying, but pylint in python3.8 was crashing parsing the named
tuple. We weren't using any namedtuple-specific features, so I made the
type a dataclass just to get pylint to behave.
* Add default timout to requests (#1846)
* Fix type (#1846)
* Fix merge mistake on poetry.lock (#1846)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Jorge Escobar <jorge.e.escobar@omb.eop.gov>
Co-authored-by: Jorge Escobar <83969469+esfoobar-usds@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Matt Bowen <83967628+mattbowen-usds@users.noreply.github.com>
Co-authored-by: matt bowen <matthew.r.bowen@omb.eop.gov>
* Add notebook to generate test data (#1780)
* Add Abandoned Mine Land data (#1780)
Using a similar structure but simpler apporach compared to FUDs, add an
indicator for whether a tract has an abandonded mine.
* Adding some detail to dataset readmes
Just a thought!
* Apply feedback from revieiw (#1780)
* Fixup bad string that broke test (#1780)
* Update a string that I should have renamed (#1780)
* Reduce number of threads to reduce memory pressure (#1780)
* Try not running geo data (#1780)
* Run the high-memory sets separately (#1780)
* Actually deduplicate (#1780)
* Add flag for memory intensive ETLs (#1780)
* Document new flag for datasets (#1780)
* Add flag for new datasets fro rebase (#1780)
Co-authored-by: Emma Nechamkin <97977170+emma-nechamkin@users.noreply.github.com>
* Add spatial join method (#1871)
Since we'll need to figure out the tracts for a large number of points
in future tickets, add a utility to handle grabbing the tract geometries
and adding tract data to a point dataset.
* Add FUDS, also jupyter lab (#1871)
* Add YAML configs for FUDS (#1871)
* Allow input geoid to be optional (#1871)
* Add FUDS ETL, tests, test-datae noteobook (#1871)
This adds the ETL class for Formerly Used Defense Sites (FUDS). This is
different from most other ETLs since these FUDS are not provided by
tract, but instead by geographic point, so we need to assign FUDS to
tracts and then do calculations from there.
* Floats -> Ints, as I intended (#1871)
* Floats -> Ints, as I intended (#1871)
* Formatting fixes (#1871)
* Add test false positive GEOIDs (#1871)
* Add gdal binaries (#1871)
* Refactor pandas code to be more idiomatic (#1871)
Per Emma, the more pandas-y way of doing my counts is using np.where to
add the values i need, then groupby and size. It is definitely more
compact, and also I think more correct!
* Update configs per Emma suggestions (#1871)
* Type fixed! (#1871)
* Remove spurious import from vscode (#1871)
* Snapshot update after changing col name (#1871)
* Move up GDAL (#1871)
* Adjust geojson strategy (#1871)
* Try running census separately first (#1871)
* Fix import order (#1871)
* Cleanup cache strategy (#1871)
* Download census data from S3 instead of re-calculating (#1871)
* Clarify pandas code per Emma (#1871)
* added tribalId for Supplemental dataset (#1804)
* Setting zoom levels for tribal map (#1810)
* NRI dataset and initial score YAML configuration (#1534)
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* update be staging gha
* checkpoint
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* checkpoint
* PR Review
* renoving source url
* tests
* stop execution of ETL if there's a YAML schema issue
* update be staging gha
* adding source url as class var again
* clean up
* force cache bust
* gha cache bust
* dynamically set score vars from YAML
* docsctrings
* removing last updated year - optional reverse percentile
* passing tests
* sort order
* column ordening
* PR review
* class level vars
* Updating DatasetsConfig
* fix pylint errors
* moving metadata hint back to code
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
* Correct copy typo (#1809)
* Add basic test suite for COI (#1518)
* Update COI to use new yaml (#1518)
* Add tests for DOE energy budren (1518
* Add dataset config for energy budren (1518)
* Refactor ETL to use datasets.yml (#1518)
* Add fake GEOIDs to COI tests (#1518)
* Refactor _setup_etl_instance_and_run_extract to base (#1518)
For the three classes we've done so far, a generic
_setup_etl_instance_and_run_extract will work fine, for the moment we
can reuse the same setup method until we decide future classes need more
flexibility --- but they can also always subclass so...
* Add output-path tests (#1518)
* Update YAML to match constant (#1518)
* Don't blindly set float format (#1518)
* Add defaults for extract (#1518)
* Run YAML load on all subclasses (#1518)
* Update description fields (#1518)
* Update YAML per final format (#1518)
* Update fixture tract IDs (#1518)
* Update base class refactor (#1518)
Now that NRI is final I needed to make a small number of updates to my
refactored code.
* Remove old comment (#1518)
* Fix type signature and return (#1518)
* Update per code review (#1518)
Co-authored-by: Jorge Escobar <83969469+esfoobar-usds@users.noreply.github.com>
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
Co-authored-by: Vim <86254807+vim-usds@users.noreply.github.com>
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* update be staging gha
* checkpoint
* update be staging gha
* NRI dataset and initial score YAML configuration
* checkpoint
* adding data checks for release branch
* passing tests
* adding INPUT_EXTRACTED_FILE_NAME to base class
* lint
* columns to keep and tests
* checkpoint
* PR Review
* renoving source url
* tests
* stop execution of ETL if there's a YAML schema issue
* update be staging gha
* adding source url as class var again
* clean up
* force cache bust
* gha cache bust
* dynamically set score vars from YAML
* docsctrings
* removing last updated year - optional reverse percentile
* passing tests
* sort order
* column ordening
* PR review
* class level vars
* Updating DatasetsConfig
* fix pylint errors
* moving metadata hint back to code
Co-authored-by: lucasmbrown-usds <lucas.m.brown@omb.eop.gov>
we wanted to implement a slightly different FEMA AG LOSS indicator. Here, we take the 90th percentile only of tracts that have agvalue, and then we also floor the denominator of the rate calculation (loss/total value) at $408k
* WIP on parallelizing
* switching to get_tmp_path for nri
* switching to get_tmp_path everywhere necessary
* fixing linter errors
* moving heavy ETLs to front of line
* add hold
* moving cdc places up
* removing unnecessary print
* moving h&t up
* adding parallel to geo post
* better census labels
* switching to concurrent futures
* fixing output
* per tract collect all diaster total annual expected loss - numerator
* add updated numerators
* EALP columns are missing on tox check - this will ensure only EALP columns that exist are subet on
* EALB columns are missing on tox check - this will ensure only EALP columns that exist are subet on
* reverted to incorporate megatracts
* updated unit tests
* fix tests
* add transform
* remove print statement
* input reflects input from FEMA risks for tracts
* revise tests and update fixtures - clean up tests and main transform function
* added more records
* remove references to Blocks in keyword args in tests
* linting
* addressed latest PR feedback
* remove imports and update arguments to be compatible for 1.1.0
* remove block reference in test
* change precision to 10 digits - refactor tests to accomdate this
Co-authored-by: Saran Ahluwalia <sarahluw@cisco.com>
* Adds dev dependencies to requirements.txt and re-runs black on codebase
* Adds test and code for national risk index etl, still in progress
* Removes test_data from .gitignore
* Adds test data to nation_risk_index tests
* Creates tests and ETL class for NRI data
* Adds tests for load() and transform() methods of NationalRiskIndexETL
* Updates README.md with info about the NRI dataset
* Adds to dos
* Moves tests and test data into a tests/ dir in national_risk_index
* Moves tmp_dir for tests into data/tmp/tests/
* Promotes fixtures to conftest and relocates national_risk_index tests:
The relocation of national_risk_index tests is necessary because tests
can only use fixtures specified in conftests within the same package
* Fixes issue with df.equals() in test_transform()
* Files reformatted by black
* Commit changes to other files after re-running black
* Fixes unused import that caused lint checks to fail
* Moves tests/ directory to app root for data_pipeline
* Adds new methods to ExtractTransformLoad base class:
- __init__() Initializes class attributes
- _get_census_fips_codes() Loads a dataframe with the fips codes for
census block group and tract
- validate_init() Checks that the class was initialized correctly
- validate_output() Checks that the output was loaded correctly
* Adds test for ExtractTransformLoad.__init__() and base.py
* Fixes failing flake8 test
* Changes geo_col to geoid_col and changes is_dataset to is_census in yaml
* Adds test for validate_output()
* Adds remaining tests
* Removes is_dataset from init method
* Makes CENSUS_CSV a class attribute instead of a class global:
This ensures that CENSUS_CSV is only set when the ETL class is for a
non-census dataset and removes the need to overwrite the value in
mock_etl fixture
* Re-formats files with black and fixes broken tox tests
* Add pytest to tox run in CI/CD
* Try fixing tox dependencies for pytest
* update poetry to get ci/cd passing
* Run poetry export with --dev flag to include dev dependencies such as pytest
* WIP updating test fixtures to include PDF
* Remove dev dependencies from reqs and add pytest to envlist to make build faster
* passing score_post tests
* Add pytest tox (#729)
* Fix failing pytest
* Fixes failing tox tests and updates requirements.txt to include dev deps
* pickle protocol 4
Co-authored-by: Shelby Switzer <shelby.switzer@cms.hhs.gov>
Co-authored-by: Jorge Escobar <jorge.e.escobar@omb.eop.gov>
Co-authored-by: Billy Daly <williamdaly422@gmail.com>
Co-authored-by: Jorge Escobar <83969469+esfoobar-usds@users.noreply.github.com>
* Adds dev dependencies to requirements.txt and re-runs black on codebase
* Adds test and code for national risk index etl, still in progress
* Removes test_data from .gitignore
* Adds test data to nation_risk_index tests
* Creates tests and ETL class for NRI data
* Adds tests for load() and transform() methods of NationalRiskIndexETL
* Updates README.md with info about the NRI dataset
* Adds to dos
* Moves tests and test data into a tests/ dir in national_risk_index
* Moves tmp_dir for tests into data/tmp/tests/
* Promotes fixtures to conftest and relocates national_risk_index tests:
The relocation of national_risk_index tests is necessary because tests
can only use fixtures specified in conftests within the same package
* Fixes issue with df.equals() in test_transform()
* Files reformatted by black
* Commit changes to other files after re-running black
* Fixes unused import that caused lint checks to fail
* Moves tests/ directory to app root for data_pipeline
