Marc Weber mhweber
mhweber
/ LineLengthsPolys.R
Last active
August 29, 2015 14:07
This piece gets some summary statistics on spatial line data frame lengths within spatial polygon data frames in R
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| library(rgeos);library( rgdal) | |
| polys <- readOGR('.','polys') | |
| lines <- readOGR('.','lines') | |
| if (proj4string(polys) == proj4string(lines){ | |
| plot(polys); plot(lines, add=T, color='Blue') | |
| lines$LENGTHKM <- SpatialLinesLengths(lines)*0.001 # assumes lines are in projection using meters | |
| line.sum <- over(polys, lines[6], fn=sum) | |
| line.mean <- over(polys, lines[6], fn=mean) | |
| line.min <- over(polys, lines[6], fn=min) | |
| line.max <- over(polys, lines[6], fn=max) |
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| # Create data frame 1 | |
| x = c("ID1","ID2","ID3","ID4","ID5") | |
| y = c("C1","C2","C3","C4","C5") | |
| d1 = data.frame("SiteID" = x, "Value" = y) | |
| d1 | |
| # Create lookup table | |
| x = c("ID2","ID5") | |
| y = c("C5","C2") | |
| lookup = data.frame("SiteID" = x, "Value" = y) | |
| lookup |
mhweber
/ Recode_PatMatch.R
Created
September 16, 2015 15:10
A reminder snippet on how to recode a data frame variable based on pattern matching another variable in the same data frame
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| x = c("AA","BB","A:B", "CC","C:A") | |
| df = data.frame("ID" = x) | |
| df | |
| df$colons[grep(":", df$ID)] ='yes' | |
| df$colons[is.na(df$colons)] ='no' | |
| df |
mhweber
/ dbf2DF.py
Last active
October 15, 2019 21:20
— forked from ryan-hill/dbf2DF.py
Import DBF file to Pandas data frame in Python
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| import pysal as ps | |
| import pandas as pd | |
| ''' | |
| Arguments | |
| --------- | |
| dbfile : DBF file - Input to be imported | |
| upper : Condition - If true, make column heads upper case | |
| ''' | |
| def dbf2DF(dbfile, upper=True): #Reads in DBF files and returns Pandas DF | |
| db = ps.open(dbfile) #Pysal to open DBF |
mhweber
/ SpatialLinesEndPoints.R
Created
February 1, 2016 21:23
Function to build a spatial points data frame of end nodes using a spatial lines data frame - function is a modification of SpatialLinesMidPoints in the R maptools package.
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| SpatialLinesEndPoints = function(sldf){ | |
| Lns <- slot(sldf, "lines") | |
| hash_lns <- sapply(Lns, function(x) length(slot(x, "Lines"))) | |
| N <- sum(hash_lns) | |
| endpoints <- matrix(NA, ncol = 2, nrow = N) | |
| Ind <- integer(length = N) | |
| ii <- 1 | |
| for (i in 1:length(Lns)) { | |
| Lnsi <- slot(Lns[[i]], "Lines") | |
| for (j in 1:hash_lns[i]) { |
mhweber
/ RasterizeShapefile.R
Created
February 5, 2016 16:06
Simple method to rasterize a shapefile using the raster package in R
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| library(raster) | |
| ## grab US counties shapefile in Oregon | |
| shp <- shapefile("C:/Users/mweber/Temp/OR_counties.shp") | |
| ## no dropping of projection metadata | |
| r <- raster(shp,nrows=100,ncols=150) | |
| r <- rasterize(shp,r,fun="first") | |
| plot(shp,axes=TRUE,border="grey") |
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "execution_count": 52, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ |
mhweber
/ Check Polygon Intersections
Created
May 4, 2016 22:56
A function using shapely geometries to check for any intersecting polygons
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| import geopandas as gpd | |
| from itertools import combinations | |
| Feat1 = gpd.GeoDataFrame.from_file('Feat1.shp') | |
| Feat2 = gpd.GeoDataFrame.from_file('Feat2.shp') | |
| Feat3= gpd.GeoDataFrame.from_file('Feat3.shp') | |
| # gather geometries in iterable a list | |
| shapes = [Feat1, Feat2, Feat3] | |
| # or to show catching overlap try |
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| import georasters as gr | |
| import matplotlib.pyplot as plt | |
| r1 = gr.from_file('wshed1') | |
| NDV, xsize, ysize, GeoT, Projection, DataType = gr.get_geo_info('wshed1') | |
| # change the data type from uint8 to uint32 | |
| r1.datatype=4 | |
| r1 = r1*2546909 | |
| r2 = gr.from_file('wshed2') |
mhweber
/ geopandas_clip.py
Created
June 17, 2016 17:16
A quick and dirty poor man's clip using geopandas. First does a union between a plot shapefile and an overlapping features shapefilie, then subsets where attributes of the features shapefile are not null to get the features clipped to boundaries of plots.
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| Plots = gpd.GeoDataFrame.from_file('Plots.shp') | |
| Plots.plot() | |
| Features = gpd.GeoDataFrame.from_file('Features.shp') | |
| Features.plot() | |
| # union features | |
| Both = overlay(Plots, Features, how="union") | |
| Both.head() | |
| # 'clip' by getting rid of union features where attributes for plot are null in the union | |
| Clips = Both[pd.notnull(Both['ORIG_FID'])] | |
| Clips.plot() |
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