329 refactor joined timeseries class to allow adding fields

docs/sphinx/user_guide/index.rst

@@ -28,6 +28,8 @@ Before starting, make sure you have installed TEEHR and its dependencies as desc
 
 :doc:`Grouping and Filtering </user_guide/notebooks/06_grouping_and_filtering>`  :download:`(download notebook) </user_guide/notebooks/06_grouping_and_filtering.ipynb>`
 
+:doc:`Adding calculated fields </user_guide/notebooks/08_adding_calculated_fields>`  :download:`(download notebook) </user_guide/notebooks/08_adding_calculated_fields.ipynb>`
+
 .. toctree::
    :maxdepth: 2
    :hidden:
@@ -40,4 +42,5 @@ Before starting, make sure you have installed TEEHR and its dependencies as desc
    Read an Evaluation from S3 </user_guide/notebooks/07_read_from_s3>
    Joining Timeseries </user_guide/tutorials/joining_timeseries>
    Grouping and Filtering </user_guide/notebooks/06_grouping_and_filtering>
+   Adding calculated fields </user_guide/notebooks/08_adding_calculated_fields>
    Metrics </user_guide/metrics/metrics>

docs/sphinx/user_guide/notebooks/02_loading_local_data.ipynb

@@ -639,7 +639,7 @@
    "source": [
     "Now we have data in all the tables required to conduct an evaluation.  There is one more step to do before we can start \"slicing and dicing\" the data and looking at evaluation metrics - we need to generate the `joined_timeseries` data table.  The `joined_timeseries` table is essentially a materialized view that joins the `primary_timeseries` and `secondary_timeseries` based on `location_id`, `value_time`, `variable_name` and `unit_name`, adds the `location_attributes`, and adds any user defined fields.\n",
     "\n",
-    "Here we are going to execute the `create()` method on the `joined_timeseries` table class to generate the `joined_timeseries` \"materialized view\" from the data we just loaded into the domain, location and timeseries tables.  The user defined fields to be added are defined as part of the evaluation in the `[evaluation_dir]/scripts/user_defined_fields.py` Python script.  Note, it is possible to skip adding any user defined fields by setting `execute_udf=False` when calling the `create()` method.  Creating user defined fields can be a powerful tool to allow per-location, per-timestep fields to be added to the materialized `joined_timeseries` table.  This will be covered in more detail in future lessons.  For now, lets just set `execute_udf=True` and execute the `user_defined_fields.py` script."
+    "Here we are going to execute the `create()` method on the `joined_timeseries` table class to generate the `joined_timeseries` \"materialized view\" from the data we just loaded into the domain, location and timeseries tables.  The user defined fields to be added are defined as part of the evaluation in the `[evaluation_dir]/scripts/user_defined_fields.py` Python script.  Note, it is possible to skip adding any user defined fields by setting `execute_scripts=False` when calling the `create()` method.  Creating user defined fields can be a powerful tool to allow per-location, per-timestep fields to be added to the materialized `joined_timeseries` table.  This will be covered in more detail in future lessons.  For now, lets just set `execute_scripts=True` and execute the `user_defined_fields.py` script."
    ]
   },
   {
@@ -648,7 +648,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ev.joined_timeseries.create(execute_udf=True)"
+    "ev.joined_timeseries.create(execute_scripts=True)"
    ]
   },
   {

docs/sphinx/user_guide/notebooks/04_setup_simple_example.ipynb

@@ -420,7 +420,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ev.joined_timeseries.create(execute_udf=True)"
+    "ev.joined_timeseries.create(execute_scripts=True)"
    ]
   },
   {

pyproject.toml

@@ -38,6 +38,7 @@ arch = "^7.0.0"
 pandera = {extras = ["pyspark"], version = "^0.20.4"}
 netcdf4 = "1.6.5"
 bokeh = "^3.5.0"
+hvplot = "^0.11.1"
 
 [tool.poetry.group.test.dependencies]
 pytest = "^7.4.3"

src/teehr/__init__.py

@@ -22,6 +22,9 @@
     JoinedTimeseriesFilter
 )
 
+from teehr.models.calculated_fields.row_level import RowLevelCalculatedFields # noqa
+from teehr.models.calculated_fields.timeseries_aware import TimeseriesAwareCalculatedFields # noqa
+
 # For docs
 from teehr.evaluation.tables.base_table import (  # noqa
     BaseTable,