Merge pull request #46 from ICESat2-SlideRule/widgets

add crs to geodataframes to address #43

Author: jpswinski

Dockerfile renamed to .github/workflows/Dockerfile

@@ -51,5 +51,6 @@ jobs:
         # Build a docker container and
         # push it to ECR so that it can
         # be deployed to ECS.
-        docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
+        docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG \
+          --file $GITHUB_ACTION_PATH/Dockerfile
         docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG

.github/workflows/aws-container.yml

@@ -9,6 +9,7 @@ dependencies:
   - ipykernel
   - ipywidgets
   - ipyleaflet
+  - tk
   - matplotlib
   - numpy
   - pandas

environment.yml

@@ -26,7 +26,6 @@
    "execution_count": null,
    "source": [
     "from sliderule import icesat2, ipysliderule, io\n",
-    "import time\n",
     "import logging\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
@@ -107,8 +106,6 @@
     "# sliderule asset and data release\n",
     "asset = SRwidgets.asset.value\n",
     "release = SRwidgets.release.value\n",
-    "# get sliderule submission time\n",
-    "submission_time = time.strftime('%Y%m%d%H%M%S',time.gmtime())\n",
     "\n",
     "# create an empty dataframe\n",
     "gdf = icesat2.__emptyframe()\n",
@@ -163,7 +160,7 @@
     "# output map of resource location\n",
     "f1, ax1 = plt.subplots(num=1, nrows=1, ncols=1, figsize=(10,6),\n",
     "    subplot_kw=dict(projection=cartopy.crs.PlateCarree()))\n",
-    "ax1.plot(gdf.geometry.values.x,gdf.geometry.values.y,'r.',\n",
+    "ax1.plot(gdf.geometry.x,gdf.geometry.y,'r.',\n",
     "    ms=1,transform=cartopy.crs.Geodetic())\n",
     "ax1.set_extent((-180,180,-90,90),crs=cartopy.crs.PlateCarree())\n",
     "# add coastlines with filled land and lakes\n",
@@ -182,12 +179,12 @@
     "f2, ax2 = plt.subplots(num=2, nrows=1, ncols=1, figsize=(10,6),\n",
     "    subplot_kw=dict(projection=cartopy.crs.PlateCarree()))\n",
     "# create scatter plot of elevations\n",
-    "sc = ax2.scatter(gdf.geometry.values.x,gdf.geometry.values.y,\n",
+    "sc = ax2.scatter(gdf.geometry.x,gdf.geometry.y,\n",
     "    c=gdf.h_mean,s=1,edgecolor='none',cmap=plt.cm.viridis,\n",
     "    transform=cartopy.crs.PlateCarree())\n",
     "# extract latitude and longitude of polygon\n",
     "for poly in m.regions:\n",
-    "    lon,lat = ipysliderule.coordinates(poly)\n",
+    "    lon,lat = io.from_region(poly)\n",
     "    ax2.plot(lon, lat, 'r', lw=1.5, transform=cartopy.crs.PlateCarree())\n",
     "# add coastlines with filled land and lakes\n",
     "ax2.add_feature(cartopy.feature.LAND, zorder=0, edgecolor='black')\n",
@@ -218,36 +215,66 @@
   {
    "cell_type": "markdown",
    "source": [
-    "#### Save GeoDataFrame to HDF5\n",
-    "Outputs as a [pytables](https://www.pytables.org/) HDF5 which is easily read back as a Geopandas GeoDataFrame"
+    "#### Save GeoDataFrame to output tile\n",
+    "- [pytables HDF5](https://www.pytables.org/): easily read back as a Geopandas GeoDataFrame\n",
+    "- [netCDF](https://www.unidata.ucar.edu/software/netcdf): interoperable with other programs"
    ],
    "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "source": [
-    "args = (submission_time,release)\n",
-    "io.to_file(gdf,\"ATL06-SR_{0}_{1}.h5\".format(*args),\n",
-    "    format='hdf', parameters=parms, regions=m.regions, verbose=True)"
+    "display(SRwidgets.filesaver)"
+   ],
+   "outputs": [],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "source": [
+    "# append sliderule api version to attributes\n",
+    "version = icesat2.get_version()\n",
+    "parms['version'] = version['icesat2']['version']\n",
+    "parms['commit'] = version['icesat2']['commit']\n",
+    "# save to file in format (HDF5 or netCDF)\n",
+    "io.to_file(gdf, SRwidgets.file,\n",
+    "    format=SRwidgets.format,\n",
+    "    driver='pytables',\n",
+    "    parameters=parms,\n",
+    "    regions=m.regions,\n",
+    "    verbose=True)"
    ],
    "outputs": [],
    "metadata": {}
   },
   {
    "cell_type": "markdown",
    "source": [
-    "#### Read GeoDataFrame from HDF5\n",
-    "Read the HDF5 back as a Geopandas GeoDataFrame for later use"
+    "#### Read GeoDataFrame from input file\n",
+    "- [pytables HDF5](https://www.pytables.org/)\n",
+    "- [netCDF](https://www.unidata.ucar.edu/software/netcdf)"
    ],
    "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "source": [
-    "args = (submission_time,release)\n",
-    "gdf = io.from_file(\"ATL06-SR_{0}_{1}.h5\".format(*args),format='hdf')"
+    "display(SRwidgets.fileloader)"
+   ],
+   "outputs": [],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "source": [
+    "# read from file in format (HDF5 or netCDF)\n",
+    "gdf = io.from_file(SRwidgets.file,\n",
+    "    format=SRwidgets.format,\n",
+    "    driver='pytables')"
    ],
    "outputs": [],
    "metadata": {}

examples/api_widgets_demo.ipynb

@@ -0,0 +1,2 @@
+jupyter labextension install --clean @jupyter-widgets/jupyterlab-manager \
+   jupyter-matplotlib jupyter-leaflet

postBuild

@@ -1,4 +1,15 @@
 requests
 setuptools_scm
 numpy
+ipykernel
+ipywidgets
+ipyleaflet
+tk
+matplotlib
+cartopy
+pandas
 geopandas
+h5py
+pyproj
+scipy
+shapely

requirements.txt

@@ -278,17 +278,22 @@ def __query_servers(max_workers):
 #
 #  __emptyframe
 #
-def __emptyframe():
-    return geopandas.pd.DataFrame()
+def __emptyframe(**kwargs):
+    # set default keyword arguments
+    kwargs['crs'] = "EPSG:4326"
+    return geopandas.GeoDataFrame(crs=kwargs['crs'])
 
 #
 #  __todataframe
 #
-def __todataframe(columns, delta_time_key="delta_time", lon_key="lon", lat_key="lat", index_key="time"):
+def __todataframe(columns, delta_time_key="delta_time", lon_key="lon", lat_key="lat", **kwargs):
+    # set default keyword arguments
+    kwargs['index_key'] = "time"
+    kwargs['crs'] = "EPSG:4326"
 
     # Check Empty Columns
     if len(columns) <= 0:
-        return __emptyframe()
+        return __emptyframe(**kwargs)
 
     # Generate Time Column
     delta_time = (columns[delta_time_key]*1e9).astype('timedelta64[ns]')
@@ -304,11 +309,11 @@ def __todataframe(columns, delta_time_key="delta_time", lon_key="lon", lat_key="
     df = geopandas.pd.DataFrame(columns)
 
     # Build GeoDataFrame (default geometry is crs="EPSG:4326")
-    gdf = geopandas.GeoDataFrame(df, geometry=geometry)
+    gdf = geopandas.GeoDataFrame(df, geometry=geometry, crs=kwargs['crs'])
 
     # Set index (default is Timestamp), can add `verify_integrity=True` to check for duplicates
     # Can do this during DataFrame creation, but this allows input argument for desired column
-    gdf.set_index(index_key, inplace=True)
+    gdf.set_index(kwargs['index_key'], inplace=True)
 
     # Sort values for reproducible output despite async processing
     gdf.sort_index(inplace=True)