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March 29, 2017 06:15
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Daily Polygon DataCube Visualisation.ipynb
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| { | |
| "cells": [ | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "# How to Count some Products\n\n## Count using polygons" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:18.067357+11:00", | |
| "end_time": "2017-03-29T06:14:25.798474Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "import datacube\nimport shapely\nimport shapely.geometry\nimport shapely.ops\nfrom IPython.display import HTML, SVG, display\nimport pandas as pd\nimport collections\nimport json\nfrom affine import Affine\nfrom rasterio import features\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport cartopy.crs as ccrs\nimport functools\n%matplotlib inline\n\ndc = datacube.Datacube(app='counting')", | |
| "execution_count": 1, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "### Find the valid data geometry for a single day" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:25.800584+11:00", | |
| "end_time": "2017-03-29T06:14:25.808284Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "@functools.lru_cache(maxsize=16384)\ndef shape_for_period(product, time, tolerance=10):\n \"\"\"\n Time is a tuple of strings\n \"\"\"\n datasets = dc.find_datasets(product=product, time=time)\n polys = shapely.ops.unary_union([shapely.geometry.asShape(ds.extent) for ds in datasets])\n return polys.simplify(tolerance=tolerance)", | |
| "execution_count": 2, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:25.811219+11:00", | |
| "end_time": "2017-03-29T06:14:26.977893Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "shape_for_period(product='ls8_nbar_albers', time=('2016-01-02', '2016-01-03'))", | |
| "execution_count": 3, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
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| }, | |
| "metadata": {}, | |
| "execution_count": 3 | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "ExecuteTime": { | |
| "end_time": "2017-03-16T01:22:22.951515Z", | |
| "start_time": "2017-03-16T12:22:22.947953+11:00" | |
| } | |
| }, | |
| "cell_type": "markdown", | |
| "source": "### Make shapes for a sequence of days" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": true, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:26.979648+11:00", | |
| "end_time": "2017-03-29T06:14:26.984615Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "def polys_for_days(days, product):\n for day in days:\n period = str(day), str(day + pd.Timedelta(1, 'D')) # looks like ('2016-01-01 10:00:00', '2016-01-02 10:00:00')\n shape = shape_for_period(time=period, product=product)\n if not shape.is_empty:\n yield day, shape", | |
| "execution_count": 4, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "## Find polygons for January 2014 Landsat 8 Nbar Albers" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:26.986236+11:00", | |
| "end_time": "2017-03-29T06:14:33.651089Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "ls8_days = pd.date_range('2014-01-01 10:00', end='2014-02-01') # LS8 2014\nls8_days = list(polys_for_days(ls8_days, product='ls8_nbar_albers'))", | |
| "execution_count": 5, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "## Have a quick look at what we've got, first 5 days" | |
| }, | |
| { | |
| "metadata": { | |
| "collapsed": false, | |
| "deletable": true, | |
| "scrolled": true, | |
| "editable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:33.656526+11:00", | |
| "end_time": "2017-03-29T06:14:33.678205Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "for date, shape in ls8_days[:5]:\n display(shape)", | |
| "execution_count": 6, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
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| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "## Define Australian Extents and a suitable Affine Translation for the whole contintent\nWe'll work in Australian Albers coordinates, and output a raster 1000 pixels wide." | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:33.680015+11:00", | |
| "end_time": "2017-03-29T06:14:33.875372Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "aus_albers = ccrs.epsg(3577)\nAUST_EXTENT = -2400000.00, 3000000.00, -5100000.00, -900000.00 # Australian Region\nwidth = 1024\nheight = 796\ndef affine_from_extent(extent, width=1024):\n \n x_min, x_max, y_min, y_max = extent\n\n x_res = int((x_max - x_min)) / width\n y_res = -x_res\n\n height = int((y_max - y_min) / x_res)\n print(height)\n\n transform = Affine.translation(x_min, y_max) * Affine.scale(x_res, -x_res)\n return transform\n\ntransform = affine_from_extent(AUST_EXTENT)", | |
| "execution_count": 7, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": "796\n", | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "## Define function for calcuating our heatmap\n\nIt takes a collection of polygons, rasterises each of them, and sums the resulting rasters to get a count of polygons that cover each point.\n" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:33.877741+11:00", | |
| "end_time": "2017-03-29T06:14:33.890773Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "def rasterize_polys_to_heatmap(polys, transform):\n output = np.zeros((height, width), dtype='int16')\n tmp_image = np.zeros((height, width), dtype='int16')\n for poly in polys:\n if not isinstance(poly, collections.Iterable):\n poly = [poly]\n features.rasterize(poly, (height, width), out=tmp_image, transform=transform, dtype='int16')\n output += tmp_image\n return output", | |
| "execution_count": 8, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "ExecuteTime": { | |
| "end_time": "2017-03-29T01:06:58.708288Z", | |
| "start_time": "2017-03-29T12:06:45.536565+11:00" | |
| } | |
| }, | |
| "cell_type": "markdown", | |
| "source": "output = polygon_heatmap((shape for date, shape in ls8_days), transform)" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "## Define function for plotting the heatmap over Australia" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": false, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:33.892454+11:00", | |
| "end_time": "2017-03-29T06:14:33.905445Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "def create_heatmap_plot(count_data, title):\n # Create figure and axes\n fig = plt.figure(figsize=(14, 10))\n ax = plt.axes(projection=aus_albers)\n\n # Setup some output\n plt.title(\"Count of available data by day\")\n ax.background_patch.set_visible(False)\n ax.outline_patch.set_visible(False)\n ax.coastlines()\n ax.gridlines()\n\n # Display our raster count\n img_ax = ax.imshow(count_data, extent=AUST_EXTENT, origin='upper', transform=aus_albers)\n\n # Add a colorbar\n cbar = plt.colorbar(img_ax, ax=ax)\n return fig, img_ax, cbar", | |
| "execution_count": 9, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": true, | |
| "deletable": true | |
| }, | |
| "cell_type": "markdown", | |
| "source": "# Easy to Use Display Heatmap function" | |
| }, | |
| { | |
| "metadata": { | |
| "editable": true, | |
| "collapsed": true, | |
| "deletable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:33.906897+11:00", | |
| "end_time": "2017-03-29T06:14:33.925233Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "def dates_heatmap(product, time_range):\n # Find all the days in the time range\n start_date, end_date = time_range\n start_date += ' 10:00' # Time offset\n days = pd.date_range(start_date, end=end_date)\n \n # Load up polygons for those days\n polygons = list(polys_for_days(days, product=product))\n \n # Create the heatmap\n return rasterize_polys_to_heatmap((shape for date, shape in polygons), transform)\n\ndef display_available_data(product, time_range):\n \"\"\"\n Provide time_range as a tuple of (start_date inclusive, end_date exclusive) strings. eg: ('2014-01-01', '2015-01-01')\n \"\"\"\n heatmap = dates_heatmap(product, time_range)\n \n # Plot\n return create_heatmap_plot(heatmap, 'Polygon Heatmap')\n", | |
| "execution_count": 10, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "collapsed": false, | |
| "deletable": true, | |
| "scrolled": false, | |
| "editable": true, | |
| "trusted": true, | |
| "ExecuteTime": { | |
| "start_time": "2017-03-29T17:14:33.927539+11:00", | |
| "end_time": "2017-03-29T06:14:50.836823Z" | |
| } | |
| }, | |
| "cell_type": "code", | |
| "source": "display_available_data('ls5_nbar_albers', ('2010-01-01', '2010-04-01'))", | |
| "execution_count": 11, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": "(<matplotlib.figure.Figure at 0x7f99b16822b0>,\n <matplotlib.image.AxesImage at 0x7f99a90def60>,\n <matplotlib.colorbar.Colorbar at 0x7f99a90a1908>)" | |
| }, | |
| "metadata": {}, | |
| "execution_count": 11 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": "<matplotlib.figure.Figure at 0x7f99b16822b0>", | |
| "image/png": 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XXlXCLrvacLky4w129nwH1/+qmk8/CPCb2zp54JddBIOw5ItF3Pv3OqZMH7nW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O5KMvZMkvTwZNWVzf7tCUaeUiPS2w6VIrI6Oe9Nm8ilbf717Y/wnm8dgyjN7HUDE2hWDFcliUwj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\nEkNp9t9/hMRQmkJ6mexb3fhPU6L6moxZLSIW5kK0CWhq/b7bm7ZIDB6tX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XuZl4PPF/ju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\ntR8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| "source": "", | |
| "execution_count": null, | |
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| "data": { | |
| "description": "Daily Polygon DataCube Visualisation.ipynb", | |
| "public": true | |
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| "nbformat": 4, | |
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| } |
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