Bokeh 未从 GeoJson 正确渲染多边形（岛屿）
Bokeh is not rendering properly multipolygon (islands) from GeoJson
我正在 Bokeh 上渲染等值线图。我的地理数据是一个带有多边形和多边形的 GeoJSON。
我在渲染多边形时遇到问题：
如果我提取一个要素的所有几何形状（例如，四个岛屿，在一个列表中），它们的图不会 'cut' 在数字之间，它们看起来都是一个。
它显示了一些 'spiderweb' 东西，无序地穿过所有点。
如果我为岛屿创建一个列表（我假设这是正确的工作方式），Bokeh 不会绘制任何东西。甚至没有网格（只有工具栏）....并且没有显示任何错误。
可能是函数 'obtCoordMultipoligono' 的输出有问题。
我在岛上搜索过示例，但没有任何帮助。
提前致谢。
更新：
我添加我的片段。它们是原始的片段，但具有功能性。
这个想法是像 BokehGallery 上的 'Texas unemployment' 这样的输出，但是我的国家上面有岛屿。
我在 argentina.json 中的 GeoJSON（仅提取 1 个多边形；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
}
}
]
}
我的数据在PBIArg.csv:
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 的 GeoJSONDataSource。
，而不是遵循原来的 'Texas example'，您可以显着简化您的代码
使用您的 geojson 的简化示例可能如下所示：
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)
输出结果如下：
编辑：
这是使用下面评论中提到的整个 geojson 时的输出结果。
并放大南部的岛屿：
更新：具有可变数据的功能
我添加此功能是为了以交互方式编辑地理JSON，具体取决于传递的 JSON 数据。
geoJSON 现在有 'data' 属性 和国家国际代码 (属性: 'ISO_3166-2')。
JSON数据是这样的：
{
"AR-A": "7",
"AR-B": "53",
"AR-C": "46"
}
函数读取地理JSON并分配数据：
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
我正在 Bokeh 上渲染等值线图。我的地理数据是一个带有多边形和多边形的 GeoJSON。
我在渲染多边形时遇到问题：
如果我提取一个要素的所有几何形状（例如，四个岛屿，在一个列表中），它们的图不会 'cut' 在数字之间，它们看起来都是一个。 它显示了一些 'spiderweb' 东西，无序地穿过所有点。
如果我为岛屿创建一个列表（我假设这是正确的工作方式），Bokeh 不会绘制任何东西。甚至没有网格（只有工具栏）....并且没有显示任何错误。
可能是函数 'obtCoordMultipoligono' 的输出有问题。
我在岛上搜索过示例，但没有任何帮助。
提前致谢。
更新： 我添加我的片段。它们是原始的片段，但具有功能性。 这个想法是像 BokehGallery 上的 'Texas unemployment' 这样的输出，但是我的国家上面有岛屿。
我在 argentina.json 中的 GeoJSON（仅提取 1 个多边形；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
}
}
]
}
我的数据在PBIArg.csv:
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 的 GeoJSONDataSource。
使用您的 geojson 的简化示例可能如下所示：
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)
输出结果如下：
编辑：
这是使用下面评论中提到的整个 geojson 时的输出结果。
并放大南部的岛屿：
更新：具有可变数据的功能
我添加此功能是为了以交互方式编辑地理JSON，具体取决于传递的 JSON 数据。
geoJSON 现在有 'data' 属性 和国家国际代码 (属性: 'ISO_3166-2')。
JSON数据是这样的：
{
"AR-A": "7",
"AR-B": "53",
"AR-C": "46"
}
函数读取地理JSON并分配数据：
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