Added js-py conversion module

examples/JavaScripts/ClippedComposite.ipynb

@@ -0,0 +1,187 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
+    "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/geemap/tree/master/examples/JavaScripts/ClippedComposite.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
+    "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/geemap/blob/master/examples/JavaScripts/ClippedComposite.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
+    "    <td><a target=\"_blank\"  href=\"https://mybinder.org/v2/gh/giswqs/geemap/master?filepath=examples/JavaScripts/ClippedComposite.ipynb\"><img width=58px src=\"https://mybinder.org/static/images/logo_social.png\" />Run in binder</a></td>\n",
+    "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/geemap/blob/master/examples/JavaScripts/ClippedComposite.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Install Earth Engine API\n",
+    "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geehydro](https://github.com/giswqs/geehydro). The **geehydro** Python package builds on the [folium](https://github.com/python-visualization/folium) package and implements several methods for displaying Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, `Map.centerObject()`, and `Map.setOptions()`.\n",
+    "The following script checks if the geehydro package has been installed. If not, it will install geehydro, which automatically install its dependencies, including earthengine-api and folium."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import subprocess\n",
+    "\n",
+    "try:\n",
+    "    import geehydro\n",
+    "except ImportError:\n",
+    "    print('geehydro package not installed. Installing ...')\n",
+    "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geehydro'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ee\n",
+    "import folium\n",
+    "import geehydro"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Authenticate and initialize Earth Engine API. You only need to authenticate the Earth Engine API once. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    ee.Initialize()\n",
+    "except Exception as e:\n",
+    "    ee.Authenticate()\n",
+    "    ee.Initialize()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create an interactive map \n",
+    "This step creates an interactive map using [folium](https://github.com/python-visualization/folium). The default basemap is the OpenStreetMap. Additional basemaps can be added using the `Map.setOptions()` function. \n",
+    "The optional basemaps can be `ROADMAP`, `SATELLITE`, `HYBRID`, `TERRAIN`, or `ESRI`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Map = folium.Map(location=[40, -100], zoom_start=4)\n",
+    "Map.setOptions('HYBRID')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add Earth Engine Python script "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Composite an image collection and clip it to a boundary.\n",
+    "\n",
+    "# Load Landsat 7 raw imagery and filter it to April-July 2000.\n",
+    "collection = ee.ImageCollection('LANDSAT/LE07/C01/T1') \\\n",
+    "    .filterDate('2000-04-01', '2000-07-01')\n",
+    "\n",
+    "# Reduce the collection by taking the median.\n",
+    "median = collection.median()\n",
+    "\n",
+    "# Load a table of state boundaries and filter.\n",
+    "fc = ee.FeatureCollection('TIGER/2016/States') \\\n",
+    "    .filter(ee.Filter.Or(\n",
+    "        ee.Filter.eq('NAME', 'Nevada'),\n",
+    "        ee.Filter.eq('NAME', 'Arizona')))\n",
+    "\n",
+    "# Clip to the output image to the Nevada and Arizona state boundaries.\n",
+    "clipped = median.clipToCollection(fc)\n",
+    "\n",
+    "# Display the result.\n",
+    "Map.setCenter(-110, 40, 5)\n",
+    "visParams = {'bands': ['B3',  'B2',  'B1'], 'gain': [1.4, 1.4, 1.1]}\n",
+    "Map.addLayer(clipped, visParams, 'clipped composite')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Display Earth Engine data layers "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><iframe 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style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x7fe2cd34b3a0>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Map.setControlVisibility(layerControl=True, fullscreenControl=True, latLngPopup=True)\n",
+    "Map"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

examples/JavaScripts/ClippedComposite.js

@@ -0,0 +1,22 @@
+// Composite an image collection and clip it to a boundary.
+
+// Load Landsat 7 raw imagery and filter it to April-July 2000.
+var collection = ee.ImageCollection('LANDSAT/LE07/C01/T1')
+    .filterDate('2000-04-01', '2000-07-01');
+
+// Reduce the collection by taking the median.
+var median = collection.median();
+
+// Load a table of state boundaries and filter.
+var fc = ee.FeatureCollection('TIGER/2016/States')
+    .filter(ee.Filter.or(
+        ee.Filter.eq('NAME', 'Nevada'),
+        ee.Filter.eq('NAME', 'Arizona')));
+
+// Clip to the output image to the Nevada and Arizona state boundaries.
+var clipped = median.clipToCollection(fc);
+
+// Display the result.
+Map.setCenter(-110, 40, 5);
+var visParams = {bands: ['B3', 'B2', 'B1'], gain: [1.4, 1.4, 1.1]};
+Map.addLayer(clipped, visParams, 'clipped composite');

examples/JavaScripts/ClippedComposite.py

@@ -0,0 +1,25 @@
+import ee 
+from ee_plugin import Map 
+
+# Composite an image collection and clip it to a boundary.
+
+# Load Landsat 7 raw imagery and filter it to April-July 2000.
+collection = ee.ImageCollection('LANDSAT/LE07/C01/T1') \
+    .filterDate('2000-04-01', '2000-07-01')
+
+# Reduce the collection by taking the median.
+median = collection.median()
+
+# Load a table of state boundaries and filter.
+fc = ee.FeatureCollection('TIGER/2016/States') \
+    .filter(ee.Filter.Or(
+        ee.Filter.eq('NAME', 'Nevada'),
+        ee.Filter.eq('NAME', 'Arizona')))
+
+# Clip to the output image to the Nevada and Arizona state boundaries.
+clipped = median.clipToCollection(fc)
+
+# Display the result.
+Map.setCenter(-110, 40, 5)
+visParams = {'bands': ['B3',  'B2',  'B1'], 'gain': [1.4, 1.4, 1.1]}
+Map.addLayer(clipped, visParams, 'clipped composite')