Michael Dorman michaeldorman
michaeldorman
/ code_01_download_ims_daily
Created
November 17, 2022 21:09
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| from selenium import webdriver | |
| import time | |
| driver = webdriver.Firefox() | |
| # Loop | |
| for i in range(1940, 1951): | |
| for j in list(range(1, 12)): | |
| # Variable selection | |
| driver.get("https://ims.data.gov.il/he/ims/2") | |
| time.sleep(3) |
michaeldorman
/ download_ims_daily.py
Created
December 21, 2021 09:48
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| from selenium import webdriver | |
| import time | |
| driver = webdriver.Firefox() | |
| # Loop | |
| for i in range(1950, 2022): | |
| for j in list(range(1, 12)): | |
| # Variable selection | |
| driver.get("https://ims.data.gov.il/he/ims/2") | |
| time.sleep(3) |
michaeldorman
/ test.py
Created
December 15, 2021 13:33
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| import numpy as np | |
| import pandas as pd | |
| import geopandas as gpd | |
| import rasterio | |
| # numpy | |
| a = np.array([3, 8, -2, 43, 12, 1, 8]) | |
| b = np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]]) | |
| c = np.arange(1, 25).reshape((2, 3, 4)) | |
| m = np.array([[ np.nan, np.nan, np.nan, np.nan, np.nan, 3., 3.], |
michaeldorman
/ distance_between_nearest_points_along_line.ipynb
Created
November 9, 2021 07:07
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michaeldorman
/ bgu_logo
Last active
August 21, 2021 10:57
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| MULTIPOLYGON (((0.164551 0.268229, 0.162651 0.165419, 0.163411 0.141818, 0 0.141818, 0.015191 0.155382, 0.0493164 0.208876, 0.0709636 0.289497, 0.0705296 0.376574, 0.0593533 0.441894, 0.0534397 0.462999, 0.0604926 0.457303, 0.0782335 0.443414, 0.101617 0.426161, 0.119358 0.414008, 0.125488 0.410319, 0.129666 0.407824, 0.142524 0.400771, 0.160157 0.391656, 0.17399 0.384819, 0.179579 0.382107, 0.175672 0.362739, 0.164551 0.268229)), ((0.192219 0.226346, 0.198133 0.312554, 0.215603 0.392469, 0.236708 0.443414, 0.247017 0.458062, 0.256565 0.471733, 0.291124 0.508572, 0.338596 0.555122, 0.378256 0.606174, 0.397299 0.653754, 0.398981 0.670031, 0.400987 0.689725, 0.388672 0.750597, 0.351292 0.837131, 0.299804 0.918457, 0.261339 0.968045, 0.247288 0.983344, 0.249132 0.966743, 0.24235 0.915528, 0.219021 0.849393, 0.187011 0.785428, 0.15625 0.723958, 0.13661 0.665419, 0.137912 0.610135, 0.170085 0.558485, 0.223469 0.520019, 0.243001 0.510796, 0.239746 0.506401, 0.231879 0.495335, 0.222168 0.480849, 0.215332 0.469889, 0 |
michaeldorman
/ ggplot2 + sf example
Created
May 14, 2021 20:09
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| library(ggplot2) | |
| library(sf) | |
| # Prepare layer | |
| dat = data.frame( | |
| name = c("Beer-Sheva Center", "Beer-Sheva University", "Dimona"), | |
| lon = c(34.79844, 34.81283, 35.01163), | |
| lat = c(31.24329, 31.26028, 31.06862) | |
| ) | |
| dat = st_as_sf(dat, coords = c("lon", "lat"), crs = 4326) |
michaeldorman
/ transparent colors in ggplot2
Created
February 15, 2021 19:12
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| library(tidyverse) | |
| library(wesanderson) | |
| mean_steps <- read.csv("data.csv", stringsAsFactors = FALSE) | |
| cols = c("#FF0000", "#00A08A", "#F2AD00") | |
| cols2 = paste0(cols, "80") | |
| cols = c(rbind(cols2, cols)) | |
| ggplot(data=mean_steps,aes(x = trial, y = mean_same, color = paste(block, actor))) + | |
| stat_summary(fun="mean",position=position_dodge(width=0.1), |
michaeldorman
/ st_rasterize_example.R
Created
January 2, 2021 09:48
Rasterizing points, lines and polygons to raster with `st_rasterize`, using the default algorithms (top) and `options="ALL_TOUCHED=TRUE"` (bottom).
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| library(stars) | |
| multipoint = st_as_sfc("MULTIPOINT ((10 40), (40 30), (20 20), (30 10))")[[1]] | |
| multilinestring = st_as_sfc("MULTILINESTRING ((10 10, 20 20, 10 40),(40 40, 30 30, 40 20, 30 10))")[[1]] | |
| multipolygon = st_as_sfc("MULTIPOLYGON (((40 40, 20 45, 45 30, 40 40)),((20 35, 10 30, 10 10, 30 5, 45 20, 20 35),(30 20, 20 15, 20 25, 30 20)))")[[1]] | |
| dat = c(st_sfc(multipoint), st_sfc(multilinestring), st_sfc(multipolygon)) | |
| dat = st_sf(dat, data.frame(value = 1, type = c("Points", "Lines", "Polygons"))) | |
| grid = st_as_stars(st_bbox(st_buffer(dat, 3)), dx = 3, dy = 3) |
michaeldorman
/ arrange stars plots on page
Created
September 27, 2020 17:14
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| library(stars) | |
| library(classInt) | |
| # Data | |
| r = read_stars(system.file("tif/L7_ETMs.tif", package = "stars")) | |
| # Plot | |
| b = classIntervals(r[[1]], 10, "equal") | |
| b = b$brks | |
| for(i in 1:dim(r)[3]) { |
michaeldorman
/ script1_mean_ndvi_30m.js
Created
May 20, 2020 07:54
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| // US area polygon | |
| var pol = ee.Geometry.Polygon([ [ [ -80.919630492025277, 30.699135009797704 ], [ -80.871245451372644, 30.336014265533166 ], [ -80.762754341973988, 29.906426353226227 ], [ -80.504997201528766, 29.330160083879278 ], [ -80.083106700408266, 28.673401576509857 ], [ -80.070233511479728, 28.651960676800226 ], [ -80.058638153313169, 28.629988680787292 ], [ -80.04835227119456, 28.607547474440747 ], [ -80.039403769248054, 28.584700211077717 ], [ -80.031816742625793, 28.561511131077758 ], [ -80.025611421049575, 28.538045379128882 ], [ -80.020804123732901, 28.514368819546309 ], [ -80.0174072256752, 28.490547850204102 ], [ -80.01542913528462, 28.466649215616201 ], [ -80.0148742832517, 28.442739819698442 ], [ -80.015743122564871, 28.418886538736928 ], [ -80.018032139528088, 28.395156035079435 ], [ -80.021733875613705, 28.371614572058188 ], [ -80.026836959956768, 28.348327830641338 ], [ -80.033326152273503, 28.32536072829911 ], [ -80.041182395964384, 28.302777240558235 ], [ -80.050382881141516, 28.2806402 |
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