tastatham

<style> 
/* change background colours around elements */
.mapboxgl-ctrl.mapboxgl-ctrl-attrib {
  background-color: rgba(86, 1, 1, 0.7);
}
.mapboxgl-ctrl.mapboxgl-ctrl-attrib a {
  color: #d17d61 !important;
}
/* change background colours around elements */
.mapboxgl-ctrl-group {

tastatham

---
title: "R Notebook"
output: html_notebook
---
```{r}
# create list of countries who qualified and their placement in the wc

qualified <- c('Spain','Nigeria','Egypt','Costa Rica','Japan','Tunisia', 'France','Switzerland','Portugal', 'Russia','Colombia','Peru','Senegal','United Kingdom','Denmark','Brazil','Germany','Iran (Islamic Republic of)','Korea, Republic of','Morocco', 'Belgium','Croatia','Saudi Arabia','Uruguay','Iceland','Argentina','Panama','Poland','Australia','Mexico','Sweden','Serbia')

# knocked out of group stage

tastatham

var beforeMap = new mapboxgl.Map({
    container: 'before',
    style: 'mapbox://styles/tastatham1/cjjy2a3sd4lx02sqcse1jkgyd',
    center: [0, 43.825234],
	pitch:20,
    zoom: 4
	
});

var afterMap = new mapboxgl.Map({

tastatham

# Load pkgs and data
import geopandas as gpd
data = gpd.read_file("https://gist.githubusercontent.com/HTenkanen/456ec4611a943955823a65729c9cf2aa/raw/be56f5e1e5c06c33cd51e89f823a7d770d8769b5/ykr_basegrid.geojson")
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

# Subset argentina as single ply
argentina = world[world['name'] == 'Argentina' ]
                  
# Define engine
engine = create_engine("postgresql+psycopg2://[user]:[password]@localhost:5432/[my_db]")

tastatham

# Import modules 
from dask_geomodeling.raster import RasterBlock
from dask_geomodeling.raster import base
from dask_geomodeling.geometry import base

# Define paths 
arg_rast_path = 'raster.tif'
arg_vec_path = 'vector.shp'

"""

tastatham

import dask
import dask_geomodeling
request = {
    "mode": "vals",
    "bbox": (138000, 480000, 139000, 481000),
    "projection": "epsg:28992",
    "width": 256,
    "height": 256
}
graph, name = add.get_compute_graph(**request) 

tastatham

def compute_zonal_stats(raster, vector, fid, col, statistics,tile,mode):

    """
    Calculate zonal statistics using dask
    
   
    Parameters
    ----------
    
    raster             : A GeoDataFrame to create multiple copies based on the list of density thresholds

tastatham

import pandas as pd
import geopandas as gpd

def multi_ring_buffers(gdf, number, distance):
    
    """
    Apply a function to a GeoDataFrame containing Point data and compute constant multi-ring buffers
    
    Parameters
    ----------

tastatham

import pandas
import geopandas
import rioxarray
from shapely.geometry import box

def _polygonize(rioxarray_obj):
    
    """"""
    
    poly_ls = []

tastatham

def spatial_shuffle(ddf, by="hilbert", column=None, npartitions=20, p=10, **kwargs):
    
    """
    A function that spatially shuffles a Dask-GeoSeries object by a method
    or a user-defined column

    Parameters
    ----------
    by : str
        partitioning method or column