This information is likely to quickly become outdated when Qualtrics next changes the formatting of the QSF file. This guide was started February 2017. I hope that it is a useful introduction to understanding the contents of the QSF file that one can download from Qualtrics.
This document includes:
| library(rayshader) | |
| library(rayrender) | |
| popdata = raster::raster("gpw_v4_population_density_rev11_2020_15_min.tif") | |
| population_mat = rayshader:::flipud(raster_to_matrix(popdata)) | |
| above1 = population_mat > 1 | |
| above5 = population_mat > 5 | |
| above10 = population_mat > 10 |
| library(raster) | |
| library(rayshader) | |
| #Load QGIS georeference image (see https://www.qgistutorials.com/en/docs/3/georeferencing_basics.html) | |
| testindia = raster::stack("1870_southern-india_modified.tif") | |
| #Set bounding box for final map (cut off edges without data, introduced via reprojection) | |
| india_bb = raster::extent(c(68,92,1,20)) | |
| cropped_india = raster::crop(testindia, india_bb) | |
| #Convert to RGB array |
| #Calibration and Holdouts periods for data split | |
| date_start = ['2013-04-01','2014-04-01','2015-04-01','2016-04-01'] | |
| calibration_period_end = ['2015-03-31','2016-03-31','2017-03-31','2018-03-31'] | |
| date_end = ['2016-03-31','2017-03-31','2018-03-31','2019-03-31'] | |
| #Arrays where to store the results of cross validation | |
| accuracies_1y = [] | |
| holdouts_1y = [] | |
| predictions_1y = [] |
| # taken from https://medium.com/@pouryaayria/k-fold-target-encoding-dfe9a594874b | |
| from sklearn import base | |
| from sklearn.model_selection import KFold | |
| class KFoldTargetEncoderTrain(base.BaseEstimator, | |
| base.TransformerMixin): | |
| def __init__(self,colnames,targetName, | |
| n_fold=5, verbosity=True, | |
| discardOriginal_col=False): | |
| self.colnames = colnames |
Instructions tested with a Raspberry Pi 2 with an 8GB memory card. Probably also works fine on a Raspberry Pi 3.
Download the latest Raspbian Jessie Light image. Earlier versions of Raspbian won't work.
Write it to a memory card using Etcher, put the memory card in the RPi and boot it up.
| library(tigris) | |
| library(tidycensus) | |
| library(tidyverse) | |
| library(sf) | |
| ma_income <- get_acs(geography = "county subdivision", | |
| variables = "B19013_001", | |
| state = "MA") | |
| ma_subs <- county_subdivisions(state = "MA", cb = TRUE, class = "sf") %>% |
| Only including this file so the title of the gist isn't `.gitignore` |
| def joyplot(data, ax=None, | |
| flatten = .1, #rescale the height of each distribution to avoid overlap. If large, will flatten out each of the KDEs | |
| linecolor='k', | |
| shadecolor='w', | |
| alpha=1, | |
| shade=True, | |
| line_kws = None, | |
| kde_kws=None, | |
| fig_kws=None, | |
| shade_kws=None): |