148 lines
3.5 KiB
Plaintext
148 lines
3.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline\n",
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"\n",
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"import numpy as np\n",
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"import fiona\n",
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"\n",
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"from matplotlib.patches import Polygon\n",
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"from shapely.geometry import shape, box\n",
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"from shapely.ops import cascaded_union\n",
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"\n",
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"## Fiona, IPython Notebook interaction\n",
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"## Live 8.5 * darkblue-b\n",
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"##"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Terminal Commands\n",
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"----------------------\n",
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"``Shell script can be executed with results stored into python variables``\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"shps = !ls /home/user/data/north_carolina/shape/*shp"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Task: quickly examine the bounding areas of a directory of shapefiles\n",
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"------------------------------------------------------------------\n",
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"* use ``fiona.open()`` to read data files on disk\n",
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"* save the filename and bounding box into a python ``dict``\n",
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"\n",
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".\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"td = {}\n",
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"\n",
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"for shp in shps:\n",
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" with fiona.open( shp, 'r') as inp:\n",
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" td[ inp.name ] = inp.bounds\n",
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"\n",
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"## Fiona inp.bounds => ( lower_lng, lower_lat, upper_lng, upper_lat)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"## Create shapely geometry from the coords\n",
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"## shapely/geometry/geo.py\n",
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"## box(minx, miny, maxx, maxy, ccw=True)\n",
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"\n",
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"nboxes = []\n",
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"for k,v in td.items():\n",
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" nboxes.append( box( v[0], v[1], v[2], v[3]) )\n",
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"\n",
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"print( 'Found BBOXs: ',len(nboxes))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"## create a single cascaded UNION too\n",
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"dst_poly = cascaded_union(nboxes)\n",
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"dst_poly.bounds"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"## Draw every BBOX for all files, transparently\n",
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"## use matplotlib.Polygon to draw; let autoscale calculate the area\n",
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"\n",
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"fig, ax = plt.subplots(figsize=(12,12))\n",
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"for polygon in nboxes:\n",
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" mpl_poly = Polygon(np.array(polygon.exterior), facecolor=\"y\", alpha=0.02)\n",
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" ax.add_patch(mpl_poly)\n",
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"\n",
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"## Indicate the exterior of the study area with a heavy line\n",
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"ax.add_patch( Polygon(np.array(dst_poly.exterior), fill=False, lw=4, ec=\"b\", alpha=0.9) )\n",
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"\n",
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"ax.relim()\n",
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"ax.autoscale()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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