MAINT: Updating changelog, fixing documentation, updating conda envir…

…onment files, bumping version, and additing file to update podpac from zip-file-folder install.

CHANGELOG.md

@@ -1,5 +1,38 @@
 # Changelog
 
+## 2.2.0
+### Introduction
+
+Wrapping Landsat8, Sentinel2, and MODIS data and improving interpolation.
+
+### Features
+* Added `datalib.satutils` which wraps Landsat8 and Sentinel2 data
+* Added `datalib.modis_pds` which wraps MODIS products ["MCD43A4.006", "MOD09GA.006", "MYD09GA.006", "MOD09GQ.006", "MYD09GQ.006"]
+* Added settings['AWS_REQUESTER_PAYS'] and `authentication.S3Mixing.aws_requester_pays` attribute to support Sentinel2 data
+* Added `issubset` method to Coordinates which allows users to test if a coordinate is a subset of another one
+* Added environmental variables in Lambda function deployment allowing users to specify the location of additional 
+dependencies (`FUNCTION_DEPENDENCIES_KEY`) and settings (`SETTINGS`). This was in support the WMS service. 
+* Intake nodes can now filter inputs by additional data columns for .csv files / pandas dataframes by using the pandas
+`query` method. 
+* Added documentation on `Interpolation` and `Wrapping Datasets`
+
+### Bug Fixes
+* Added `dims` attributes to `Compositor` nodes which indicates the dimensions that sources are expected to have. This 
+fixes a bug where `Nodes` throw and error if Coordinates contain extra dimensions when the `Compositor` sources are missing
+those dimensions.
+* `COSMOSStations` will no longer fail for sites with no data or one data point. These sites are now automatically filtered. 
+* Fixed `core.data.file_source` closing files prematurely due to using context managers
+* Fixed heterogenous interpolation (where lat/lon uses a different interpolator than time, for example)
+* `datalib.TerrainTiles` now accesses S3 anonymously by default. Interpolation specified at the compositor level are 
+also now passed down to the sources. 
+
+### Breaking changes
+* Fixed `core.algorithm.signal.py` and in the process removed `SpatialConvolution` and `TemporalConvolutions`. Users now
+have to label the dimensions of the kernel -- which prevents results from being modified if the eval coordinates are 
+transposed. This was a major bug in the `Convolution` node, and the new change obviates the need for the removed Nodes, 
+but it may break some pipelines. 
+
+
 ## 2.1.0
 ### Introduction
 

dist/local_Windows_install/update_podpac.bat

@@ -0,0 +1,24 @@
+@echo off
+call bin\set_local_conda_path.bat
+call bin\fix_hardcoded_absolute_paths.bat
+call bin\activate_podpac_conda_env.bat
+
+cd podpac
+echo "Updating PODPAC"
+git fetch
+for /f %%a in ('git describe --tags --abbrev^=0 origin/master') do git checkout %%a
+cd ..
+echo "Updating PODPAC EXAMPLES"
+cd podpac-examples
+git fetch
+for /f %%a in ('git describe --tags --abbrev^=0 origin/master') do git checkout %%a
+cd ..
+cd podpac
+cd dist
+echo "Updating CONDA ENVIRONMENT"
+conda env update -f windows_conda_environment.yml
+cd ..
+cd ..
+
+
+

dist/windows_conda_environment.yml

@@ -25,5 +25,5 @@ dependencies:
   - jupyterlab
   - ipyleaflet
   - ipympl
-prefix: D:\podpac-1.3.0\miniconda\envs\podpac
+  - sat-search
 

doc/source/design.rst

@@ -17,7 +17,7 @@ Node
 **Nodes** describe the components of your analysis.
 These include data sources, combined data sources (**Compositors**), algorithms, and the assembly of data sources.
 Nodes are assembled into :ref:`design_pipelines`, which can be output to a text file or pushed to the cloud
-with minimal configuration. **Nodes** are design to **FAIL ON EVAL**, not fail when instantiated. This is order to defer
+with minimal configuration. **Nodes** are designed to **FAIL ON EVAL**, not fail when instantiated. This is in order to defer
 expensive operations till the user really wants them. 
 
 .. image:: /_static/img/node.png

doc/source/interpolation.md

@@ -6,9 +6,9 @@ PODPAC allows users to specify various different interpolation schemes for nodes
 increased granularity, and even lets users write their own interpolators. 
 
 Relevant example notebooks include:
-* https://github.com/creare-com/podpac-examples/blob/master/notebooks/4-advanced/interpolation.ipynb
-* https://github.com/creare-com/podpac-examples/blob/master/notebooks/2-combining-data/automatic-interpolation-and-regridding.ipynb
-* https://github.com/creare-com/podpac-examples/blob/master/notebooks/examples/drought-monitor/03-data-access-harmonization-processing.ipynb
+* [Advanced Interpolation](https://github.com/creare-com/podpac-examples/blob/master/notebooks/4-advanced/interpolation.ipynb)
+* [Basic Interpolation](https://github.com/creare-com/podpac-examples/blob/master/notebooks/2-combining-data/automatic-interpolation-and-regridding.ipynb)
+* [Drought Monitor Data Access Harmonization Processing](https://github.com/creare-com/podpac-examples/blob/master/notebooks/examples/drought-monitor/03-data-access-harmonization-processing.ipynb)
 
 ## Examples
 Consider a `DataSource` with `lat`, `lon`, `time` coordinates that we will instantiate as: 

doc/source/wrapping-datasets.md

@@ -4,11 +4,11 @@ Wrapping a new dataset is challenging because you have to understand all of the
 
 ## Rules
 1. When evaluating a node with a set of coordinates:
-   a. The evaluation coordinates must include ALL of the dimensions present in the source dataset
-   b. The evaluation coordinates MAY contain additional dimensions NOT present in the source dataset, and the source may ignore these
+   1. The evaluation coordinates must include ALL of the dimensions present in the source dataset
+   1. The evaluation coordinates MAY contain additional dimensions NOT present in the source dataset, and the source may ignore these
 2. When returning data from a data source node:
-   a. The ORDER of the evaluation coordinates MUST be preserved (see `UnitsDataArray.part_transpose`)
-   b. Any multi-channel data must be returned using the `output` dimension which is ALWAYS the LAST dimension
+   1. The ORDER of the evaluation coordinates MUST be preserved (see `UnitsDataArray.part_transpose`)
+   1. Any multi-channel data must be returned using the `output` dimension which is ALWAYS the LAST dimension
 3. Nodes should be **lightweight** to instantiate and users should expect *fail on eval*. Easy checks should be performed on initialization, but anything expensive should be delayed. 
 
 ## Guide
@@ -17,8 +17,8 @@ In theory, to wrap a new `DataSource`:
 2. Implement a method for opening/accessing the data, or use an existing generic data node and hard-code certain attributes
 3. Implement the `get_coordinates(self)` method
 4. Implement the `get_data(self, coordinates, coordinates_index)` method
-    a. `coordinates` is a `podpac.Coordinates` object and it's in the same coordinate system as the data source (i.e. a subset of what comes out of `get_coordinates`)
-    b. `coordinates_index` is a list (or tuple?) of slices or boolean arrays or index arrays to indexes into the output of `get_coordinates()` to produce `coordinates` that come into this function. 
+    1. `coordinates` is a `podpac.Coordinates` object and it's in the same coordinate system as the data source (i.e. a subset of what comes out of `get_coordinates`)
+    2. `coordinates_index` is a list (or tuple?) of slices or boolean arrays or index arrays to indexes into the output of `get_coordinates()` to produce `coordinates` that come into this function. 
 
 In practice, the real trick is implementing a compositor to put multiple tiles together to look like a single `DataSource`. We tend to use the `podpac.compositor.OrderedCompositor` node for this task, but it does not handle interpolation between tiles. Instead, see the `podpac.core.compositor.tile_compositor` module. 
 

podpac/version.py

@@ -17,7 +17,7 @@
 ##############
 MAJOR = 2
 MINOR = 2
-HOTFIX = 0
+HOTFIX = 1
 ##############