v1.0.4

What's Changed

• [DEM-416] Add filepath to make_1_to_1_plot() by @tnigon in #68

Full Changelog: v1.0.3...v1.0.4

v1.0.3

What's Changed

• Remove pygeos dependency by @tnigon in #67

Full Changelog: v1.0.2...v1.0.3

v1.0.2

What's Changed

• update shapely by @tnigon in #66

Full Changelog: v1.0.1...v1.0.2

v1.0.1

What's Changed

• [DEM-362] Updates for Bayer Canola workflow by @marissakivi in #65

Full Changelog: v1.0.0...v1.0.1

v1.0.0

What's Changed

• [DEM 303] Adding functions from mosaic-modeling by @marissakivi in #64

Full Changelog: v0.1.9...v1.0.0

v0.1.5

Features

• Bumps version to stay in sync with db
• Minor fixes in support of DEM-51

v0.1.4

This update mostly supports the FeatureData and Predict classes that have a need to retrieve the training and prediction feature matrix, respectively. The features to construct can be defined in the config file via the FeatureData.group_feats key. Here is an example FeatureData.group_feats entry that generates the training feature matrix for cumulative precipitation, ET, solar radiation, and GDDs since planting:

"weather": {
    "date_origin_kwargs": {
        "table_name": "as_planted",
        "date_column": "date_plant",
        "select_extra": []
    },
    "features": [
        "sum(w.'precip_24h:mm') as 'precip_csp:mm'",
        "sum(w.'evapotranspiration_24h:mm') as 'evapotranspiration_csp:mm'",
        "sum(w.'global_rad_24h:MJ') as 'global_rad_csp:MJ'",
        "sum(w.'gdd_10C30C_2m_24h:C') as 'gdd_10C30C_2m_csp:C'"
    ]
}

Some notes:

• date_origin_kwargs defines the table/column that contains the "origin date" (the date to begin cumulation of weather data for). In this case, the plant date will be extracted from the date_plant column of the as_planted table (via a spatial query from each relevant observation).
• select_extra allows the user to select extra features that are present in the planting table (e.g., population, variety, etc.)
• features allows the user to include the desired weather features. Notice this is a list of SQL text strings, each of which get added to the query dynamically.

v0.1.3

Updates

Makes use of new features of db, including the closest_date_sql sql constructor to query the "reflectance" table for the raster with the closest date.

Screenshot of the metadata included in a prediction raster

JIRA Link

https://sentera.atlassian.net/browse/POT-68

v0.1.2

Changes from previous release

• Uses db v0.1.2
• Minor changes as a result of POT-55

v0.1.1

Changes from previous release:

• Uses release v0.1.1 of db
• Uses DBHandler.get_zonal_stats() rather than Python/GeoPandas to query Sentinel2 rasters (now in its own "reflectance" table)
• See DBHandler.get_zonal_stats() docstring for options in how reflectance data are queried.

See: POT-47