def get_eventbmap(pos) -> BMap:
#[(lo,la),(lo,la)]这种格式即可
BAIDU_AK = "HOTBRAfU1jGcQKHBX15ucKsfZO722eyN"
center = (117.20, 39.12)
c = BMap()
c.add_schema(
baidu_ak=BAIDU_AK,
center=[117.20, 39.12],
zoom=10,
is_roam=False,
)
sequence = []
for i in range(len(pos)):
c.add_coordinate(str(i), pos[i][0], pos[i][1]) #[(posindex,lo,la)]
sequence.append((str(i), 0.1)) #这里名字和pos要对应
c.add(
"投诉坐标", #系列名称
sequence,
type_="scatter", #"heatmap" 可以切换显示的类型热力图或散点图
label_opts=opts.LabelOpts(formatter="{b}"),
symbol_size=5)
c.set_series_opts(effect_opts=opts.EffectOpts(is_show=True),
label_opts=opts.LabelOpts(is_show=False))
c.add_control_panel(
scale_control_opts=opts.BMapScaleControlOpts(),
navigation_control_opts=opts.BMapNavigationControlOpts(),
maptype_control_opts=opts.BMapTypeControlOpts())
#c.set_global_opts(visualmap_opts=opts.VisualMapOpts())
return c
def test_bmap_map_control_panel(fake_writer):
bmap = (BMap().add_schema(
baidu_ak=FAKE_API_KEY, center=[
-0.118092, 51.509865
]).add_coordinate("London", -0.118092, 51.509865).add(
"bmap",
[list(z) for z in zip(TEST_LOCATION, TEST_VALUE)],
type_=ChartType.LINES,
label_opts=opts.LabelOpts(formatter="{b}"),
).add_control_panel(
copyright_control_opts=opts.BMapCopyrightTypeOpts(position=3),
maptype_control_opts=opts.BMapTypeControlOpts(
type_=BMapType.MAPTYPE_CONTROL_DROPDOWN),
scale_control_opts=opts.BMapScaleControlOpts(),
overview_map_opts=opts.BMapOverviewMapControlOpts(is_open=True),
navigation_control_opts=opts.BMapNavigationControlOpts(),
geo_location_control_opts=opts.BMapGeoLocationControlOpts(),
))
bmap.render()
content = fake_writer.call_args[0][1]
assert_in("new BMap.CopyrightControl", content)
assert_in("new BMap.MapTypeControl", content)
assert_in("new BMap.ScaleControl", content)
assert_in("new BMap.OverviewMapControl", content)
assert_in("new BMap.NavigationControl", content)
assert_in("new BMap.GeolocationControl", content)
def get_gridbmap(message) -> BMap:
BAIDU_AK = "HOTBRAfU1jGcQKHBX15ucKsfZO722eyN"
pos = (117.20, 39.12)
#jscode = "console.log('hi hi');"#可嵌入jscode
#jscode = "functions(param){bmap.addEventListener('click', function(e){alert(e.point.lng + ','+ e.point.lat);});}"
#每两个点画一条线
j = [[{
"coord": [117.20, 39.12]
}, {
"coord": [118.21, 41.12]
}], [{
"coord": [119.21, 41.12]
}, {
"coord": [115.21, 41.12]
}]]
c = (
BMap().add_schema(
baidu_ak=BAIDU_AK, center=[117.20, 39.12], zoom=12).add(
"",
type_="lines",
data_pair=j,
is_polyline=True,
is_large=False,
linestyle_opts=opts.LineStyleOpts(color="purple",
opacity=0.6,
width=1),
).set_series_opts(effect_opts=opts.EffectOpts(is_show=False),
label_opts=opts.LabelOpts(is_show=False)).
add_control_panel(
scale_control_opts=opts.BMapScaleControlOpts(),
navigation_control_opts=opts.BMapNavigationControlOpts(),
maptype_control_opts=opts.BMapTypeControlOpts(),
#copyright_control_opts=opts.BMapCopyrightTypeOpts(copyright_="我的")
#geo_location_control_opts=opts.BMapGeoLocationControlOpts()
#overview_map_opts=opts.BMapOverviewMapControlOpts(is_open=True),
)
#.add_js_funcs(jscode)
#.set_global_opts(title_opts=opts.TitleOpts(title="BMap-基本示例"))
)
return c
def get_bmap(pos) -> BMap:
BAIDU_AK = "HOTBRAfU1jGcQKHBX15ucKsfZO722eyN"
#center = (117.20, 39.12)
c = BMap()
c.add_schema(baidu_ak=BAIDU_AK,
center=[117.20, 39.12],
zoom=10,
is_roam=False)
sequence = []
for i in range(len(pos)):
#print(pos[i])
c.add_coordinate(pos[i][0], pos[i][2], pos[i][1])
sequence.append((str(i), 5))
c.add(
"投诉坐标", #系列名称
sequence,
type_="scatter", #"heatmap" 可以切换显示的类型热力图或散点图
label_opts=opts.LabelOpts(formatter="{b}"),
symbol_size=4 #scatter大小
)
#.add("bmap",
#[{"coord":[117.21, 39.13],"sim":10},{"coord":[117.20, 39.13],"sim":20},{"coord":[117.21, 39.12],"sim":5}],
#[list(z) for z in zip(Faker.provinces, Faker.values())],#zip将迭代对像打包成元组最后的结果是[['浙江',v1],['广东',v2]]
#[[117.21, 39.13],[117.20, 39.12],[117.22, 39.10],[117.25, 39.11],[117.19, 39.02],[117.20, 39.12]],
#type_="heatmap",
#label_opts=opts.LabelOpts(formatter="{b}"))
c.set_series_opts(
effect_opts=opts.EffectOpts(is_show=True),
label_opts=opts.LabelOpts(is_show=False),
)
c.add_control_panel(
scale_control_opts=opts.BMapScaleControlOpts(),
navigation_control_opts=opts.BMapNavigationControlOpts(),
maptype_control_opts=opts.BMapTypeControlOpts())
#copyright_control_opts=opts.BMapCopyrightTypeOpts(copyright_="我的")
#geo_location_control_opts=opts.BMapGeoLocationControlOpts()
#overview_map_opts=opts.BMapOverviewMapControlOpts(is_open=True),
#c.set_global_opts(visualmap_opts=opts.VisualMapOpts(pos_left="right"))
return c
})
coord = prepare_coord(load_street_pickle())
for s, (long, lat) in coord.items():
m.add_coordinate(s, long, lat)
speed, n_slice = read_speed()
# Match T-GCN expand 3 times... (don't know why)
idx_map = list(range(0, 114 - 12 - 3 - 1)) + list(range(114, 143 - 12 - 3))
pred_speed, n_slice1 = read_pred_speed()
assert len(idx_map) == n_slice1
m.add(series_name="actual",
type_="heatmap",
data_pair=get_data_pair(speed, 0)).add(
series_name="predict",
type_="heatmap",
data_pair=get_data_pair(pred_speed, 0),
).add_control_panel(
copyright_control_opts=opts.BMapCopyrightTypeOpts(position=3),
maptype_control_opts=opts.BMapTypeControlOpts(
type_=BMapType.MAPTYPE_CONTROL_DROPDOWN),
scale_control_opts=opts.BMapScaleControlOpts(),
overview_map_opts=opts.BMapOverviewMapControlOpts(is_open=True),
navigation_control_opts=opts.BMapNavigationControlOpts(),
geo_location_control_opts=opts.BMapGeoLocationControlOpts(),
).set_global_opts(
visualmap_opts=opts.VisualMapOpts(
min_=0,
max_=60,
range_color=['blue', 'blue', 'green', 'yellow', 'red']),
title_opts=opts.TitleOpts(title="Traffic Status of Xi'An"))
m.render('test.html')
def bmap_lines() -> BMap:
with open(
os.path.join("fixtures", "hangzhou-tracks.json"), "r", encoding="utf-8"
) as f:
j = json.load(f)
c = (
BMap()
.add_schema(
baidu_ak=BAIDU_MAP_AK,
center=[120.13066322374, 30.240018034923],
zoom=14,
is_roam=True,
map_style={
"styleJson": [
{
"featureType": "water",
"elementType": "all",
"stylers": {"color": "#d1d1d1"},
},
{
"featureType": "land",
"elementType": "all",
"stylers": {"color": "#f3f3f3"},
},
{
"featureType": "railway",
"elementType": "all",
"stylers": {"visibility": "off"},
},
{
"featureType": "highway",
"elementType": "all",
"stylers": {"color": "#fdfdfd"},
},
{
"featureType": "highway",
"elementType": "labels",
"stylers": {"visibility": "off"},
},
{
"featureType": "arterial",
"elementType": "geometry",
"stylers": {"color": "#fefefe"},
},
{
"featureType": "arterial",
"elementType": "geometry.fill",
"stylers": {"color": "#fefefe"},
},
{
"featureType": "poi",
"elementType": "all",
"stylers": {"visibility": "off"},
},
{
"featureType": "green",
"elementType": "all",
"stylers": {"visibility": "off"},
},
{
"featureType": "subway",
"elementType": "all",
"stylers": {"visibility": "off"},
},
{
"featureType": "manmade",
"elementType": "all",
"stylers": {"color": "#d1d1d1"},
},
{
"featureType": "local",
"elementType": "all",
"stylers": {"color": "#d1d1d1"},
},
{
"featureType": "arterial",
"elementType": "labels",
"stylers": {"visibility": "off"},
},
{
"featureType": "boundary",
"elementType": "all",
"stylers": {"color": "#fefefe"},
},
{
"featureType": "building",
"elementType": "all",
"stylers": {"color": "#d1d1d1"},
},
{
"featureType": "label",
"elementType": "labels.text.fill",
"stylers": {"color": "#999999"},
},
]
},
)
.add(
"",
type_="lines",
data_pair=j,
is_polyline=True,
is_large=True,
linestyle_opts=opts.LineStyleOpts(color="purple", opacity=0.6, width=1),
)
.add_control_panel(
maptype_control_opts=opts.BMapTypeControlOpts(
type_=BMapType.MAPTYPE_CONTROL_DROPDOWN
),
scale_control_opts=opts.BMapScaleControlOpts(),
overview_map_opts=opts.BMapOverviewMapControlOpts(is_open=True),
)
.set_global_opts(title_opts=opts.TitleOpts(title="BMap-杭州热门步行路线"))
)
return c
is_show_zoom_info=True, # 是否显示级别提示信息
is_enable_geo_location=True, # 控件是否集成定位功能
), # 若下面还有add_contorl_panel里面的空间调整，这里必须有“，”，若没有，可以没有逗号
opts.BMapOverviewMapControlOpts( # 缩略地图控件
# position=0, # 等同于anchor_top_left，1、2、3分别为右上，左下，右下
# offset_height=50, # 距离上部偏移量
# offset_width=10, # 距离左右偏移量
is_open=True,
),
opts.BMapScaleControlOpts( # 比例尺控件
# position=0, # 等同于anchor_top_left，1、2、3分别为右上，左下，右下
# offset_height=50, # 距离上部偏移量
# offset_width=10, # 距离左右偏移量
),
opts.BMapTypeControlOpts( # 切换地图类型的控件
# position=0,
type_=2, # MAPTYPE_CONTROL_HORIZONTAL/DROPDOWN/MAP，按钮水平方式展示为0,下拉列表为1，图片方式为2（设置该类型后无法指定 maptypes 属性）
),
opts.BMapCopyrightTypeOpts( # 版权控件，您可以在地图上添加自己的版权信息
# position=0,
# offset_height=50, # 距离上部偏移量
# offset_width=10, # 距离左右偏移量
copyright_="made by shh", # Copyright 的文本内容, 可以放入 HTML 标签
),
opts.BMapGeoLocationControlOpts( # 地图定位的控件，使用 HTML5 浏览器定位功能
# position=0,
# offset_height=50, # 距离上部偏移量
# offset_width=10, # 距离左右偏移量
is_show_address_bar=True, # 是否显示定位信息面板。默认显示定位信息面板
is_enable_auto_location=True, # 添加控件时是否进行定位。默认添加控件时不进行定位
)
)
for group in X.groupby('labels'):
c = c.add(series_name=group[0],
type_="scatter",
is_large=True,
large_threshold=2000,
symbol_size=5,
label_opts=opts.LabelOpts(is_show=False),
tooltip_opts=opts.TooltipOpts(formatter='{c}'),
data_pair=[
list(z)
for z in zip(list(group[1].index), group[1]['labels'])
])
c = (c.add_control_panel(
navigation_control_opts=opts.BMapNavigationControlOpts(
position=BMapType.ANCHOR_TOP_LEFT),
maptype_control_opts=opts.BMapTypeControlOpts()))
c = c.set_global_opts(title_opts=opts.TitleOpts(title="Clusters of Crime"))
c.render(name + 'scatter.html')
# In[393]:
map_c = pd.read_csv('dbscanoutput.csv')[:10000]
map_c.columns = ['x', 'y', 'labels']
gp_col = 'labels'
x = -87.65005
y = 41.85003
a = map_c.groupby(gp_col).count()
a = a.rename(columns={
'labels': 'labels',
'x': 'count',
'y': 'a'
def plot_map(point_data, path):
point_data = point_data[point_data['remarks'] != 'no_result']
data = point_data[['lat_BaiDu', 'long_BaiDu', 'behavior', 'label']].copy()
data.columns = ['lat', 'lon', 'behavior', 'label']
# 地图中心
map_center = [data['lon'].mean(), data['lat'].mean()]
# 初始化百度地图
bd_map = BMap(init_opts=opts.InitOpts(width="1920px", height="1080px"))
bd_map.add_schema(baidu_ak=KEY,
center=map_center,
zoom=8, is_roam=True,
map_style=None,
)
color = ['red', 'green', 'blue', 'yellow', 'gold', 'cyan', 'magenta', 'purple']
behavior_list = data.drop_duplicates(['behavior'])['behavior'].copy() # 剔除重复的数据文件路径
i = 0
for behavior in behavior_list:
behavior_data = data[data['behavior'] == behavior]
# behavior_color = color_choice() # 从color列表中随机抽取一个颜色
behavior_color = color[i]
i = i + 1
map_data = []
# 利用BMap.add_coordinate 将坐标值赋值给一个地点名称，并增加近BMap对象地理信息中
for j in range(len(behavior_data)):
name = behavior + str(j)
longitude = behavior_data['lon'].iloc[j]
latitude = behavior_data['lat'].iloc[j]
bd_map.add_coordinate(name=name,
longitude=longitude,
latitude=latitude
)
map_data.append((name, 1))
# 将地点增加到百度地图
bd_map = bd_map.add(
series_name=behavior,
type_="scatter",
data_pair=map_data,
symbol_size=20,
effect_opts=opts.EffectOpts(),
label_opts=opts.LabelOpts(formatter="{b}", position="left", is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color=behavior_color),
)
# 显示聚类分析的结果
label_list = data.drop_duplicates(['label'])['label'].copy()
map_data = []
for label in label_list:
if label == -1:
continue
else:
label_data = data[data['label'] == label]
# 将聚类点命名增加至地图地名空间
name = '高风险路段_' + str(label)
bd_map.add_coordinate(name=name,
longitude=label_data['lon'].mean(),
latitude=label_data['lat'].mean()
)
map_data.append((name, len(label_data)))
# 将地点增加到百度地图
bd_map = bd_map.add(
series_name='高风险行为频发路段',
type_="scatter",
data_pair=map_data,
symbol_size=50,
# blur_size=500,
is_selected=True, # 是否选中图例
effect_opts=opts.EffectOpts(),
label_opts=opts.LabelOpts(formatter="{b}", position="right", is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='rgba(138,43,226, 0.8)'),
)
# 将绘图结果输出至网页文件
bd_map = bd_map.add_control_panel(maptype_control_opts=opts.BMapTypeControlOpts(position=1),
)
# 设置图例
bd_map = bd_map.set_global_opts(legend_opts=opts.LegendOpts(is_show=True,
item_height=50,
),
title_opts=opts.TitleOpts(title="新奥危险货物运输高风险路段聚类分析图"),
)
bd_map = bd_map.render(path)
# 用浏览器打开文件
webbrowser.open(path)
return bd_map
def plot_scatter_map(route_data, path):
route_data = route_data[route_data['speed'] > 10.0]
data = route_data[['lat_BaiDu', 'long_BaiDu', 'behavior', 'label']].copy()
data.columns = ['lat', 'lon', 'behavior', 'label']
# 地图中心
map_center = [data['lon'].mean(), data['lat'].mean()]
# 初始化百度地图
bd_map = BMap(init_opts=opts.InitOpts(width="1920px", height="1080px"))
bd_map.add_schema(
baidu_ak=KEY,
center=map_center,
zoom=8,
is_roam=True,
map_style=None,
)
color = [
'red', 'green', 'blue', 'yellow', 'gold', 'cyan', 'magenta', 'purple'
]
# 将数据分为异常路段和正常路段
normal_route = data[data['label'] <= -0.0].copy()
risk_route = data[data['label'] > 0.0].copy()
# 绘制正常路段散点图，颜色为绿色
normal_map_data = []
# 利用BMap.add_coordinate 将坐标值赋值给一个地点名称，并增加近BMap对象地理信息中
for i in range(len(normal_route)):
name = 'low_risk' + str(i)
longitude = normal_route['lon'].iloc[i]
latitude = normal_route['lat'].iloc[i]
bd_map.add_coordinate(name=name,
longitude=longitude,
latitude=latitude)
normal_map_data.append((name, -1))
# 绘制高风险路段散点图，颜色为红色
risk_map_data = []
# 利用BMap.add_coordinate 将坐标值赋值给一个地点名称，并增加近BMap对象地理信息中
for j in range(len(risk_route)):
name = 'high_risk' + str(j)
longitude = risk_route['lon'].iloc[j]
latitude = risk_route['lat'].iloc[j]
bd_map.add_coordinate(name=name,
longitude=longitude,
latitude=latitude)
risk_map_data.append((name, -1))
# 将低风险轨迹散点标识在百度地图上
bd_map = bd_map.add(
series_name='低风险路段',
type_="scatter",
data_pair=normal_map_data,
symbol_size=10,
effect_opts=opts.EffectOpts(),
label_opts=opts.LabelOpts(formatter="{b}",
position="left",
is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='green'),
)
# 将高风险轨迹散点标识在百度地图上
bd_map = bd_map.add(
series_name='高风险路段',
type_="scatter",
data_pair=risk_map_data,
symbol_size=20,
effect_opts=opts.EffectOpts(),
label_opts=opts.LabelOpts(formatter="{b}",
position="left",
is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='red'),
)
# 将绘图结果输出至网页文件
bd_map = bd_map.add_control_panel(
maptype_control_opts=opts.BMapTypeControlOpts(position=1), )
# 设置图例
bd_map = bd_map.set_global_opts(
legend_opts=opts.LegendOpts(
is_show=True,
item_height=50,
),
title_opts=opts.TitleOpts(title="新奥危险货物运输高风险路段聚类分析图"),
)
# 将地图加载到网页
bd_map = bd_map.render(path)
# 用浏览器打开文件
webbrowser.open(path)
return bd_map
is_polyline=True,
data_pair=all_map_data,
linestyle_opts=opts.LineStyleOpts(opacity=0.8, width=5),
effect_opts=opts.EffectOpts(),
label_opts=opts.LabelOpts(formatter="{b}",
position="left",
is_show=False),
itemstyle_opts=opts.ItemStyleOpts(color='green'),
# 如果不是最新版本的话可以注释下面的参数（效果差距不大）
progressive=200,
progressive_threshold=500,
)
# 将绘图结果输出至网页文件
bd_map = bd_map.add_control_panel(
maptype_control_opts=opts.BMapTypeControlOpts(position=1), )
# 设置图例
bd_map = bd_map.set_global_opts(
legend_opts=opts.LegendOpts(
is_show=True,
item_height=50,
),
title_opts=opts.TitleOpts(title="新奥危险货物运输高风险路段聚类分析图"),
)
# 将地图加载到网页
bd_map = bd_map.render(lines_file_dir)
# 用浏览器打开文件
webbrowser.open(lines_file_dir)
# # 地图中心
