def create_map(iso, lon, lat):
creds = Credentials(username=CARTO_USER_NAME, api_key=CARTO_API_KEY)
set_default_credentials(creds)
dataset_name = 'onekmiso'
dataset_name = dataset_name + str(int(round(time.time() * 1000)))
to_carto(iso, dataset_name, if_exists='replace', log_enabled=True)
auth_client = APIKeyAuthClient(CARTO_BASE_URL, CARTO_API_KEY)
FACTOR = DPI / 72.0
map_name = 'tpl_' + dataset_name
create_named_map(auth_client, CARTO_USER_NAME, dataset_name, map_name, FACTOR, lon, lat)
return map_name
import pandas as pd
import geopandas as gpd
import numpy as np
import matplotlib.pyplot as plt
import shapely
from libpysal.weights import Queen
import pointpats
import pointpats.centrography
from cartoframes.auth import set_default_credentials
from cartoframes import read_carto
from cartoframes import to_carto
set_default_credentials('ebook-sds')
## The Meuse dataset from R gstat package
class GetMeuse():
def __init__(self):
self.data = read_carto('meuse')
self.data['log_zinc'] = np.log(self.data['zinc'])
self.data = self.data.to_crs({'init': 'epsg:28992'})
self.data_lonlat = self.data.to_crs({'init': 'epsg:4326'})
self.data_grid = read_carto('meuse_grid')
self.data_grid = self.data_grid.to_crs({'init': 'epsg:28992'})
self.data_grid_lonlat = self.data_grid.to_crs({'init': 'epsg:4326'})
def loadpred_krg(self):
self.data_krg = pd.read_csv('/tmp/meuse_krg.csv')
self.data_krg = gpd.GeoDataFrame(self.data_krg, geometry=gpd.points_from_xy(self.data_krg.x, self.data_krg.y))
logger = logging.getLogger()
for handler in logger.handlers:
logger.removeHandler(handler)
# manually set level
logger.setLevel(logging.INFO)
# print to console
console = logging.StreamHandler()
logger.addHandler(console)
logging.basicConfig(
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger.debug('Authenticate Carto credentials')
CARTO_USER = os.getenv('CARTO_WRI_RW_USER')
CARTO_KEY = os.getenv('CARTO_WRI_RW_KEY')
set_default_credentials(
username=CARTO_USER,
base_url="https://{user}.carto.com/".format(user=CARTO_USER),
api_key=CARTO_KEY)
# prepare request parameters
variables = ['o2', 'no3', 'po4']
depths = [
-0.49402499198913574,
-1.5413750410079956,
-2.6456689834594727,
-3.8194949626922607,
-5.078224182128906,
]
# define function for creating request
def build_wms_request(x, y, variable, depth):
xmin = x - 0.0
import geopandas as gpd
from cartoframes.auth import set_default_credentials
from cartoframes import read_carto
from cartoframes import to_carto
set_default_credentials("ebook-sds")
def get_table(tablename):
"""Retrieve tablename as a GeoDataFrame ordered by database id
Returns:
geopandas.GeoDataFrame: GeoDataFrame representation of table
"""
base_query = ("SELECT * FROM {tablename} ORDER BY cartodb_id ASC").format(
tablename=tablename)
data_carto = read_carto(base_query)
## Renaming the geometry column from 'the_geom' to 'geometry'
## (pysal expect the geometry column to be called 'geometry')
data = data_carto.copy()
data['geometry'] = data.geometry
data.drop(['the_geom'], axis=1, inplace=True)
data = gpd.GeoDataFrame(data, geometry='geometry')
data.crs = {"init": "epsg:4326"}
return data
def get_nyc_census_tracts():
"""Retrieve dataset on NYC Census Tracts
import pandas as pd
import geopandas as gpd
import numpy as np
import matplotlib.pyplot as plt
import shapely
from libpysal.weights import Queen
import pointpats
import pointpats.centrography
from cartoframes.auth import set_default_credentials
from cartoframes.data import Dataset
set_default_credentials('eschbacher')
## The Meuse dataset from R gstat package
class GetMeuse():
def __init__(self):
self.data = gpd.GeoDataFrame(
Dataset('meuse').download(decode_geom=True))
self.data['log_zinc'] = np.log(self.data['zinc'])
self.data.crs = {'init': 'epsg:4326'}
self.data = self.data.to_crs({'init': 'epsg:28992'})
self.data_lonlat = self.data.to_crs({'init': 'epsg:4326'})
self.data_grid = gpd.GeoDataFrame(
Dataset('meuse_grid').download(decode_geom=True))
self.data_grid.crs = {'init': 'epsg:4326'}
self.data_grid = self.data_grid.to_crs({'init': 'epsg:28992'})
self.data_grid_lonlat = self.data_grid.to_crs({'init': 'epsg:4326'})
