Bokeh无法从GeoJson中正确渲染多边形(岛屿)
Nat*_*cha 2 python geojson bokeh
我在Bokeh上渲染了一个等值线图.我的地理数据是一个带有多边形和多边形的GeoJSON.
我在渲染Multipolygons时遇到问题:
如果我提取一个特征的所有几何形状(例如,在一个列表中的四个岛),它们的图形不会在图形之间"切割",它们似乎都是一个.它显示了一些"蜘蛛网"的东西,所有的点都是不规则的.
如果我为岛创建一个列表(我认为这是正确的工作方式),Bokeh不会绘制任何内容.甚至不是网格(只有工具栏)....并且不显示任何错误.
可能是函数'obtCoordMultipoligono'的输出存在问题.
我在岛上搜寻了一些例子,但没有什么可以帮助我.
提前致谢.
更新: 我添加了我的代码段.它们是原始的,但功能性的碎片.这个想法是像BokehGallery上的"德州失业"这样的输出,但是我的国家有它的岛屿.
我在argentina.json中的 GeoJSON (仅提取1个多字形;我没有多边形问题):
{
"type": "FeatureCollection",
"features": [
{
"geometry": {
"type": "MultiPolygon",
"coordinates": [
[
[
[
-59.68266601562502,
-52.231640624999976
],
[
-59.74658203124997,
-52.25087890624999
],
[
-59.76445312499996,
-52.2421875
],
[
-59.784863281249955,
-52.2046875
],
[
-59.78593749999999,
-52.156152343749966
],
[
-59.79331054687498,
-52.134179687500016
],
[
-59.75322265624999,
-52.14140624999998
],
[
-59.681005859375034,
-52.18007812499995
],
[
-59.68266601562502,
-52.231640624999976
]
]
],
[
[
[
-58.438818359375006,
-52.011035156249974
],
[
-58.432714843750006,
-52.09902343749996
],
[
-58.512841796874966,
-52.071093750000045
],
[
-58.54140625000002,
-52.02841796874996
],
[
-58.49707031249997,
-51.99941406250001
],
[
-58.46054687499998,
-52.0015625
],
[
-58.438818359375006,
-52.011035156249974
]
]
],
[
[
[
-61.01875,
-51.7857421875
],
[
-60.94726562499997,
-51.79951171875005
],
[
-60.87597656250003,
-51.79423828125004
],
[
-60.91616210937494,
-51.89697265625001
],
[
-60.94755859374996,
-51.94628906250002
],
[
-61.031982421875,
-51.94248046875004
],
[
-61.11577148437493,
-51.87529296875003
],
[
-61.14501953125003,
-51.83945312500001
],
[
-61.05166015625002,
-51.81396484374997
],
[
-61.01875,
-51.7857421875
]
]
],
[
[
[
-60.11171875000002,
-51.39589843749998
],
[
-60.24882812499996,
-51.39599609375
],
[
-60.27587890624997,
-51.36318359374997
],
[
-60.275341796874955,
-51.28056640625002
],
[
-60.17138671875,
-51.273437499999986
],
[
-60.06982421875,
-51.307910156249996
],
[
-60.07646484374993,
-51.34257812500004
],
[
-60.11171875000002,
-51.39589843749998
]
]
]
]
},
"type": "Feature",
"properties": {
"perimeter": 0,
"vista": "mim",
"provincia": "Islas Malvinas",
"objectid": 24,
"prov": 0,
"bounds": [
0,
0
],
"provif3_": 27.0,
"ogc_fid": 26,
"provif3_id": 26.0
}
}
]
}
我在PBIArg.csv中的数据:
24,AR-V,Islas,13245
我的代码:
<!-- language: lang-py -->
import json,pprint,csv
pp = pprint.PrettyPrinter(indent=4)
from bokeh.io import output_file, show
from bokeh.models import HoverTool
from bokeh.plotting import figure, show, output_file, ColumnDataSource
import pandas as pd
from osgeo import ogr
fname = r'islas.json' # constante hasta conseguir algo mejor
dname = r'PBIArg.csv' # variable estadística a graficar.
paleta = ["#FFF5F0", "#FEE0D2", "#FCBBA1", "#FC9272", "#FB6A4A", "#EF3B2C", "#CB181D", "#99000D"]
def colorante(rate,max_value,min_value,paleta):
try:
intensidad = int(float(len(paleta)-1) * float(rate - min_value) / float(max_value - min_value))
return paleta[intensidad]
except:
intensidad = int(float(len(paleta)-1) * float(rate - min_value) / float(max_value - min_value))
return paleta[intensidad]
def obtCoordMultipoligono(pcia):
mpoly = ogr.CreateGeometryFromJson(pcia)
print('pcia-MPOLY tiene esta cantidad de islas: ', mpoly.GetGeometryCount())
coordX,coordY = [],[]
# idx poly mpoly
for idx, poly in enumerate(mpoly): #itero mpoly
print('POLY tiene esta cantidad de islas: ', poly.GetGeometryCount())
innerX,innerY = [],[]
# ind
for ind in range(0, poly.GetGeometryCount()): #itero poly
innerPoly = poly.GetGeometryRef(ind)
print('INNERPOLY tiene esta cantidad de PUNTOS: ', innerPoly.GetPointCount())
lastX,lastY = [],[]
for i in range(0, innerPoly.GetPointCount()): #itero innerpoly
# GetPoint returns a tuple not a Geometry
punto = innerPoly.GetPoint(i)
print('pto obtenido en X',punto[0])
# Asigno a lista local
lastX.append(punto[0])
lastY.append(punto[1])
print('LastX:')
pp.pprint(lastX)
innerX.append(lastX)
innerY.append(lastY)
print('InnerX:')
pp.pprint(innerX)
coordX.append(innerX)
coordY.append(innerY)
print('CoordX:')
pp.pprint(coordX)
dictCoord = dict(coordX=coordX,coordY=coordY)
print('DictCoord:')
pp.pprint(dictCoord)
return dictCoord
############ MAIN ##################
######## Leo csv estadísticas ########
with open(dname, 'r') as f:
'''Leo el CSV, creo diccio de pciaID: estadísticaPcial.
Abajo busco la estadísticaPcial max y min para luego calcular los colores'''
max_value, min_value = 0,0
datos = {}
for row in csv.reader(f):
estadistica = int(row[3])
datos[row[0]] = estadistica
if estadistica > max_value:
max_value = estadistica
if estadistica < min_value:
min_value = estadistica
######## Leo geojson ########
with open(fname, 'r') as f:
geojson = f.read()
geoDict = json.loads(geojson)
######## Parseo geojson ########
dictArg = {}
for pcia in geoDict['features']:
pciaID = str(pcia['properties']['objectid'])
nombrePcia = pcia['properties']['provincia']
coordX = []
coordY = []
if pcia['geometry']['type'] == 'Polygon':
for punto in pcia['geometry']['coordinates'][0]:
if len(punto) == 2:
coordX.append(punto[0])
coordY.append(punto[1])
elif pcia['geometry']['type'] == 'MultiPolygon':
multiJSON = json.dumps(pcia['geometry'])
dictCoord = obtCoordMultipoligono(multiJSON)
# print(dictCoord)
coordX = dictCoord['coordX']
coordY = dictCoord['coordY']
# Handling states without data
try:
info=int(datos[pciaID])
except KeyError:
info = 0
color = colorante(info,max_value,min_value,paleta)
dictPcia = dict(nombre=nombrePcia,coordX=coordX,coordY=coordY, info=info,color=color)
dictArg[pciaID] = dictPcia
print('dict',dictArg['19'])
######## saco coord de las pcias ########
provincias = {
codPcia: nombrePcia for codPcia, nombrePcia in dictArg.items()
}
# print(provincias)
pcia_xs = [provincia['coordX'] for provincia in provincias.values()]
pcia_ys = [provincia['coordY'] for provincia in provincias.values()]
nombres_provincias = [provincia['nombre'] for provincia in provincias.values()]
######## Saco estadísticas de las pcias ########
provincias_datos = [provincia['info'] for provincia in provincias.values()]
######## Coloreo el mapa a nivel datos ########
provincias_colores = [provincia['color'] for provincia in provincias.values()]
source = ColumnDataSource(data=dict(
x=pcia_xs,
y=pcia_ys,
color=provincias_colores,
nombre=nombres_provincias,
dato=provincias_datos,
))
TOOLS="pan,wheel_zoom,box_zoom,reset,hover,save"
p = figure(title="PBI de Argentina por provincia", tools=TOOLS)
p.patches('x', 'y', source=source,
fill_color='color', fill_alpha=0.9,
line_color='#767676', line_width=1.5)
hover = p.select_one(HoverTool)
hover.point_policy = "follow_mouse"
hover.tooltips = [
("State:", "@nombre"),
("Nº:", "@dato"),
]
output_file("PBIar.html", title="Testing islands in bokeh")
show(p)
如果您使用Bokeh,您可以显着简化代码,而不是遵循原始的"德克萨斯州示例" GeoJSONDataSource.
使用geojson的精简示例可能如下所示:
from bokeh.io import show, output_notebook, output_file
from bokeh.models import (
GeoJSONDataSource,
HoverTool,
LinearColorMapper
)
from bokeh.plotting import figure
from bokeh.palettes import Viridis6
with open(r'argentina.geojson', 'r') as f:
geo_source = GeoJSONDataSource(geojson=f.read())
color_mapper = LinearColorMapper(palette=Viridis6)
TOOLS = "pan,wheel_zoom,box_zoom,reset,hover,save"
p = figure(title="Argentina", tools=TOOLS, x_axis_location=None, y_axis_location=None, width=500, height=300)
p.grid.grid_line_color = None
p.patches('xs', 'ys', fill_alpha=0.7, fill_color={'field': 'objectid', 'transform': color_mapper},
line_color='white', line_width=0.5, source=geo_source)
hover = p.select_one(HoverTool)
hover.point_policy = "follow_mouse"
hover.tooltips = [("Provincia:", "@provincia")]
output_file("PBIar.html", title="Testing islands in bokeh")
show(p)
然后输出如下:
编辑:
这是使用整个geojson时输出的样子,如下面的注释中所述.
并放大了南部的岛屿:
更新:具有可变数据的功能
我添加了这个函数,以便以交互方式编辑geoJSON,具体取决于传递的JSON数据.
geoJSON现在具有'data'属性和state国际代码(property:'ISO_3166-2').
JSON数据是这样的:
{
"AR-A": "7",
"AR-B": "53",
"AR-C": "46"
}
该函数读取geoJSON并将数据设为:
def asignDataToStates(geo,data):
for pcia in geo['features']:
codPcia = str(pcia['properties']['ISO_3166-2'])
if codPcia in data.keys():
if data.values() != 0:
pcia['properties']['data'] = data[codPcia]
dataJson = json.dumps(geo,ensure_ascii=True)
return dataJson