| <!DOCTYPE qgis_style> | |
| <qgis_style version="2"> | |
| <symbols> | |
| <symbol alpha="1" force_rhr="0" clip_to_extent="1" type="fill" name="pencilish"> | |
| <layer class="MarkerLine" pass="0" locked="0" enabled="1"> | |
| <prop k="average_angle_length" v="4"/> | |
| <prop k="average_angle_map_unit_scale" v="3x:0,0,0,0,0,0"/> | |
| <prop k="average_angle_unit" v="MM"/> | |
| <prop k="interval" v="0.02"/> | |
| <prop k="interval_map_unit_scale" v="3x:0,0,0,0,0,0"/> |
The absolute easiest way to get a CSV into a postgresql table is to use ogr2ogr with AUTODETECT_TYPE=YES.
I learned a while back that this is what cartoDB uses to import your CSV into postgis (with a lot of other parameters added)
ogr2ogr -f PostgreSQL PG:"host=localhost user=postgres dbname=postgres password=password" docs.csv -oo AUTODETECT_TYPE=YES
| Mute these words in your settings here: https://twitter.com/settings/muted_keywords | |
| ActivityTweet | |
| generic_activity_highlights | |
| generic_activity_momentsbreaking | |
| RankedOrganicTweet | |
| suggest_activity | |
| suggest_activity_feed | |
| suggest_activity_highlights | |
| suggest_activity_tweet |
| <html> | |
| <head> | |
| <title>Deckgl RGB PointCloud + Mapbox</title> | |
| <script src="https://unpkg.com/deck.gl@^7.0.0/dist.min.js"></script> | |
| <script src="https://api.tiles.mapbox.com/mapbox-gl-js/v0.54.0/mapbox-gl.js"></script> | |
| <link rel="stylesheet" type="text/css" href="https://api.tiles.mapbox.com/mapbox-gl-js/v0.54.0/mapbox-gl.css"> | |
| <style> | |
| body { | |
| background-color: #000000; | |
| margin: 0; |
| SELECT json_build_object( | |
| 'type', 'FeatureCollection', | |
| 'crs', json_build_object( | |
| 'type', 'name', | |
| 'properties', json_build_object( | |
| 'name', 'EPSG:4326' | |
| ) | |
| ), | |
| 'features', json_agg( | |
| json_build_object( |
| #! /bin/bash -ex | |
| # Convert Landsat 8 GeoTIFF images into RGB pan-sharpened JPEGs. | |
| # | |
| # Requirements: | |
| # * gdal http://www.mapbox.com/tilemill/docs/guides/gdal/ | |
| # * Dan Stahlke's https://github.com/gina-alaska/dans-gdal-scripts | |
| # * convert (image-magick) | |
| # | |
| # Reference info: |
| Zoom | Tile size at equator (km) | Resolution at equator (m) |
|---|---|---|
| 0 | 22568 | 88155 |
| 1 | 11284 | 44078 |
| 2 | 7656 | 29904 |
| 3 | 4577 | 17881 |
| 4 | 2443 | 9544 |
| 5 | 1244 | 4861 |
| 6 | 625 | 2442 |
| 7 | 313 | 1223 |
| license: mit |
| import base64 as b64 | |
| import numpy as np | |
| import cv2 | |
| import matplotlib.pyplot as plt | |
| from ipywidgets import interact, interactive, fixed | |
| from IPython.display import Image, display | |
| import ipywidgets as widgets | |
| from itertools import tee, izip | |
| WINDOW_SIZE = 41 # size of window to use when computing averages. Endpoint images outside |
