Le portail francophone de la géomatique

pytest

https://s3-ap-southeast-2.amazonaws.com/basemaps.temp/nz_colour_basemap/WMTSCapabilities.nz_colour_basemap.xml
https://s3-ap-southeast-2.amazonaws.com/basemaps.temp/nz_topo_basemap/WMTSCapabilities.nz_topo_basemap.xml
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		<link rel="stylesheet" href="css/theme/white.css">
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	<body>
		<div class="reveal">
			<div class="slides">
				<section>Slide 1</section>
				<section>Slide 2</section>
			</div>
		</div>
		<script src="js/reveal.js"></script>
		<script>
			Reveal.initialize();
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	</body>
</html>

.reveal .slides section .fragment.pointy.current-fragment::before{
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}

<section>
	<h3>Unordered list:</h3>
	<ul>
		<li class="fragment pointy">Fragment 1</li>
		<li class="fragment pointy">Fragment 2</li>
		<li class="fragment pointy">Fragment 3</li>
		<li class="fragment pointy">Fragment 4</li>
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opacity: 1;
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<section>
	<p>Here's a sentence where <span class="fragment bold">this</span>, <span class="fragment bold">this</span> and <span class="fragment bold">this</span> need to be highlighted.</p>
</section>

<script src="js/reveal.js"></script>
<script src="js/jquery-3.4.1.slim.min.js"></script>
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  color:pink;
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$id =  @atlas_featureid
[%concat('Rota ', "id")%]
MAPBOX_ACCESS_TOKEN = 'your_API_token'
%pylab inline
import pandas as pd
import seaborn as sns; sns.set()
import geopandas as gp
from h3 import h3
from shapely.ops import unary_union
from shapely.geometry.polygon import Polygon
from keplergl import KeplerGl
import json
import jinja2
def python_dict_to_json_file(dict_object, file_path):
try:
# Get a file object with write permission.
file_object = open(file_path, 'w')
# Save dict data into the JSON file.
json.dump(dict_object, file_object, indent=4)
print(file_path + " created. ")
except FileNotFoundError:
print(file_path + " not found. ")
def jinja_json_to_dict(env, template_name, **kwargs):
"""Convert JSON Jinja2 template to dictionary and apply variables from kwargs."""
template = env.get_template(template_name)
return json.loads(template.render(kwargs))

!wget [https:] 
!unzip gadm36_AUT_gpkg.zip

%ls

gadm36_AUT.gpkg license.txt
gadm36_AUT_gpkg.zip reproducible_kepler.ipynb

df = gp.read_file('gadm36_AUT.gpkg', driver='GPKG')
# fixup geometries to be a single polygon
polygons = df.geometry.apply(lambda x: list(x))[0]
polygons.append(polygons[0].intersection(polygons[1]).buffer(0.0001))
combined = [unary_union(polygons)]
df.geometry = combined
display(df.head())
df.plot()

gj = gp.GeoSeries([df.geometry[0]]).__geo_interface__
geoJson = gj['features'][0]['geometry']

res = 8
hexagons = pd.DataFrame(h3.polyfill(geoJson, res, geo_json_conformant=True), columns=['hexagons'])
hexagons['value'] = 1 # some dummy data we want to plot at the map
hexagons.head()

prototype_map = KeplerGl(height=700)
prototype_map.add_data(data=hexagons, name=f'res-{res}')
prototype_map

!mkdir templates

# uncomment to overwrite existing template
python_dict_to_json_file(prototype_map.config, 'templates/introduction.j2')

from jinja2 import Environment, PackageLoader, select_autoescape, FileSystemLoader
env = Environment(
loader=FileSystemLoader('templates/'),
autoescape=select_autoescape(['html', 'xml'])
)
eval_map = KeplerGl(height=700)
eval_map.add_data(data=hexagons, name=f'res-{res}')
config_dict = jinja_json_to_dict(env, 'introduction.j2')
eval_map.config = config_dict
eval_map

eval_map.save_to_html(file_name='eval_map.html')

echo $(date '+%Y-%m-%d') : "text I want to send" | tosheets -c a1 --spreadsheet=[idformyspreadsheet] -q '"' -d ':'

.\bash-weeknotes.sh "text I want to send as my CWT"

// [https:] compile group: 'com.uber', name: 'h3', version: '3.6.0'

spark-shell --packages 'com.uber:h3:3.6.0'

import com.uber.h3core.H3Core
import org.apache.spark.sql.expressions.UserDefinedFunction
import org.apache.spark.sql.DataFrame
@transient lazy val h3 = new ThreadLocal[H3Core] {
override def initialValue() = H3Core.newInstance()
}
def convertToH3Address(xLong: Double, yLat: Double, precision: Int): String = {
h3.get.geoToH3Address(yLat, xLong, precision)
}
val geoToH3Address: UserDefinedFunction = udf(convertToH3Address _)
def createSpatialIndexAddress(result: String,
XLongColumn: String,
YLatColumn: String,
precision: Int)(df: DataFrame): DataFrame = {
df.withColumn(
result,
geoToH3Address(col(XLongColumn), col(YLatColumn), lit(precision)))
}

val df = Seq((1,2), (3,4)).toDF("x", "y")
df.transform(createSpatialIndexAddress("h3","x", "y", 7)).show(false)
+---+---+---------------+
|x |y |h3 |
+---+---+---------------+
|1 |2 |877545796ffffff|
|3 |4 |8775642cdffffff|
+---+---+---------------+

CREATE EXTENSION postgis;
CREATE EXTENSION ogr_fdw;

CREATE SERVER wfsserver 
  FOREIGN DATA WRAPPER ogr_fdw 
  OPTIONS (
    datasource 'WFS [geoservices.informatievlaanderen.be]     format 'WFS',
    config_options 'CPL_DEBUG=ON'
  );

CREATE FOREIGN TABLE haltes (
    fid bigint,
    shape Geometry(Point,31370),
    gml_id varchar,
    uidn double precision,
    oidn double precision,
    stopid double precision,
    naamhalte varchar,
    typehalte integer,
    lbltypehal varchar,
    codegem varchar,
    naamgem varchar
  ) 
  SERVER wfsserver 
  OPTIONS (
    layer 'Haltes:Halte'
  );

SET client_min_messages = DEBUG1;

SELECT gml_id, ST_AsText(shape) AS shape, naamhalte, lbltypehal
  FROM haltes 
  WHERE lbltypehal = 'Niet-belbus'
    AND shape && ST_MakeEnvelope(207950, 186590, 207960, 186600, 31370);

DEBUG:  OGR SQL: (LBLTYPEHAL = 'Niet-belbus')
DEBUG:  OGR spatial filter (207950 186590, 207960 186600)
-[ RECORD 1 ]-----------------------
gml_id     | Halte.10328
shape      | POINT(207956 186596)
naamhalte  | Lummen Frederickxstraat
lbltypehal | Niet-belbus

SET client_min_messages = DEBUG2;

SELECT gml_id, ST_AsText(shape) AS shape, naamhalte, lbltypehal
  FROM haltes 
  WHERE lbltypehal = 'Niet-belbus'
    AND shape && ST_MakeEnvelope(207950, 186590, 207960, 186600, 31370);

DEBUG:  GDAL None [0] WFS: [geoservices.informatievlaanderen.be] 
<Filter
  xmlns="http://www.opengis.net/ogc"
  xmlns:Haltes="informatievlaanderen.be/Haltes"
  xmlns:gml="http://www.opengis.net/gml">
  <And>
    <PropertyIsEqualTo>
      <PropertyName>LBLTYPEHAL</PropertyName>
      <Literal>Niet-belbus</Literal>
    </PropertyIsEqualTo>
    <BBOX>
      <PropertyName>Haltes:SHAPE</PropertyName>
      <gml:Box>
        <gml:coordinates>
          207950.0000000000000000,186590.0000000000000000
          207960.0000000000000000,186600.0000000000000000
        </gml:coordinates>
      </gml:Box>
    </BBOX>
  </And>
</Filter>

SELECT admin, ST_NPoints(the_geom), ST_MemSize(the_geom) 
FROM ne_10m_admin_0_countries 
ORDER BY ST_NPoints;

SELECT Count(*) 
FROM ne_10m_admin_0_countries 
WHERE ST_MemSize(the_geom) > 8192;

SELECT Count(*)
FROM ne_10m_admin_0_countries countries 
JOIN ne_10m_populated_places_simple places 
ON ST_Contains(countries.the_geom, places.the_geom)

CREATE TABLE ne_10m_admin_0_countries_subdivided AS
SELECT ST_SubDivide(the_geom) AS the_geom, admin 
FROM ne_10m_admin_0_countries;

SELECT Count(*)
FROM ne_10m_admin_0_countries_subdivided countries 
JOIN ne_10m_populated_places_simple places 
ON ST_Contains(countries.the_geom, places.the_geom)

if (window.'URLSearchParams') {
  // Support :)
}
const params = new URLSearchParams('version=1&name=john&lastname=nieve')
// or
const params = new URLSearchParams('?version=1&name=john&lastname=nieve')
const params = new URLSearchParams('https://some_api.com?paramA=valueA')
params.get('version')           // 1
params.get('name')              // john
params.get('name')              // john

params.set('lastname', 'stark')
params.get('lastname')          // stark

params.has('lastname')          // true
params.has('age')               // false
params.set('tags', 'bastard')
params.append('tags', 'lord')

params.get('tags')              // bastard
params.getAll('tags')           // ['bastard', 'lord']
params.delete('lastname')
params.toString()               // version=1&name=john&tags=bastard&tags=lord
const url = new URL('https://got-api.com?version=1&name=john&lastname=nieve');
const params = new URLSearchParams(url.search);

params.toString()   // version=1&name=john&lastname=nieve
import pandas as pd
import geopandas
import folium

graph = geopandas.read_file('data/population_test-routes-geom.csv')
graph.crs = {'init' :'epsg:4326'}

m = folium.Map([48.2, 16.4], zoom_start=10)

folium.Choropleth(
    graph[graph.geometry.length>0.001],
    line_weight=3,
    line_color='blue'
).add_to(m)

m

	hexagons	value
0	881f892551fffff	1
1	881e3221b7fffff	1
2	881e336729fffff	1
3	881e150427fffff	1
4	881e105937fffff	1

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