I am not sure if this is possible with folium. I want to take the polygons value of the city of Toronto and map it over an area of Glimakra, Sweden. This is for an article I am writing about living in the countryside is not much different than living in a big city.
I want to take this polygon border of Toronto
and place it over the Glimakra, Sweden area.
I wrote this code and because my geojson data file for Toronto placed Toronto where it should be from a GEO perspective.
import folium
m = folium.Map(
location=[56.30507180,14.13632150],
zoom_start=11
)
folium.GeoJson("toronto_geojson.geojson", name="geojson").add_to(m)
folium.LayerControl().add_to(m)
m.save("index.html")
m
My question is, how can I turn my toronto_geojson.geojson into a file with the polygon shape without the geojson stuff so that I can place the shape over any map area. Similar to how I can use the folium plugin HeatMap to place a heatmap over a map area.
Does anyone know the best practice to do this?
from folium.plugins import HeatMap
import os
m = folium.Map([56.30507180,14.13632150], tiles='Stamen Toner', zoom_start=6)
HeatMap(data).add_to(m)
m.save(os.path.join('heatmap.html'))
m
Related
I have loaded a raster using stars package and then created tiles over the raster. Now i subset the raster based on these tile.
tiles[[i]] <- st_bbox(c(xmin=x0,ymin=y0,xmax=x1,ymax=y1),crs=st_crs(r))
crop_tiles[[i]] <- r[tiles[[i]]]
Here r is raster loaded using read_stars("filename.tif").
Now i want to remove among the crop_tiles the empty ones. i.e the tiles where the raster values are NA
You can check if all values of a stars object named r are NA with:
all(is.na(r[[1]]))
then remove those tiles where the above is equal to TRUE.
For more specific code, please provide reproducible sample data in your question, thanks.
I have an unstructured grid vtk file that contains three different types of cells (Tetrahedral, Wedge and Hexahedral). This file contains multiple Scalars (8 attributes such as Pressure, Temperature e.t.c.) and a Single Vector (U,V,W) and I am trying to create a surface plot from this file for a Scalar or Vector at a time using the Vedo python wrapper for vtk. The vtk file contains a scalar or vector value for each cell, including the point coordinates.
I have read the documentation over and over, with examples here https://vtkplotter.embl.es/content/vtkplotter/index.html. These are the things that I have tried with the challenge that I am having with each method:
Method 1: Loading the file as a TetMesh
vp = Plotter()
test = load('Case_60.vtk')
vp.show(test)
This method doesn't plot Scalar Values and only shows points. No Solid Surface. Tried using a cuttertool() with it , it throws an error saying non-Tetrahedral Cell Encountered.
Method 2: Using the UGrid
ug = UGrid('Case_60.vtk')
show(ug)
This method plots as surface with a solid color. Does not seem to be picking the Scalars.
What is the proper way for me to display surface plot and display the scalar value for each cell? Is Vedo able to do what I'm trying to do?
You might need to specify which array is to be used for coloring, e.g.:
from vedo import *
ug = UGrid(datadir+'limb_ugrid.vtk')
print(ug.getArrayNames())
ug.selectCellArray('chem_0')
show(ug, axes=True)
if this doesn't work for your mesh please submit an issue here.
I want to automate a network topology diagram using python. I'm new to python so please bear with me. After doing some research I found out that I can use python to create graphml files which can be read by yEd.
I'm learning how to use Networkx to create the graphml files. So far I'm able to create nodes, connect them and add labels to the nodes (these labels would be the hostnames). Now I need to know how I can add labels to the edges (these labels would be the interfaces). For example:
Topology example
If possible I would like to know how to add a custom image for every node (by default the shape is a square but I would like to use a router png file).
If it is not possible then it would be helpful to know how to edit the height and width of the shape and also disabling arrows.
I've reviewed the docs on networkx website but I haven't found how to do these changes directly to the graph object. The only way I've seen it done is when drawing the graph, for example using the following function: nx.draw_networkx_labels(G, pos, labels, font_size=15, arrows=False), but this is not what I need because this is not saved to the graphml file.
If someone can guide me through this it would be really helpful, I'm attaching my code:
import networkx as nx
import matplotlib
import matplotlib.pyplot as plt
g = nx.DiGraph()
g.add_node('Hostname_A')
g.add_node('Hostname_B')
g.add_node('Hostname_C')
g.add_node('Hostname_D')
g.add_edge('Hostname_A','Hostname_B')
g.add_edge('Hostname_A','Hostname_C')
g.add_edge('Hostname_B','Hostname_D')
g.add_edge('Hostname_B','Hostname_C')
for node in g.nodes():
g.node[node]['label'] = node
nx.readwrite.write_graphml(g, "graph.graphml")
This is the solution:
for edge in g.edges():
g.edges[edge]['source'] = 'int gi0/0/0'
g.edges[edge]['destination'] = 'int gi0/0/1'
I am using the spatial plug-ins for TOS to perform the following task:
I have a dataset with X and Y coordinates. I have also a shapefile with multi polygons and two metadata attributes, name and Id. The idea is to look-up the names in the shapefile with the coordinates. With a point in polygon will be determined which polygon belongs a point to.
I am using the shapefile input component which points to the .shp file.
I am facing to hurdles:
I cannot retrieve the name and Id from the file. I can only see an attribute call the_geom. How can I read the metadata?
The second thing is, the file contains a multi polygon and I don't know how to iterate over it in order to perform a Contains or intersect with the points.
Any comment will be highly appreciated.
thanks for your input #chrki
I managed to solve my tasks in this way:
1) Create a generic schema under metadata:
As the .dbf file was in the same directory of the shapefile Talend automatically recognized the metadata:
2) This is the job overview:
3) I read the shape file using a sShapeFileInput component:
4) The shapefile contains multipolygons and I want to have polygons. My solution was to use a sSimplify component. I used the default settings.
5) The projection of the shapefile was "MGI / Austria Lambert" which corresponds to EPSG 31287. I want to re-project it as EPSG 4326 (GCS_WGS_1984) which is the one used by my input coordinates.
6) I read the x, y coordinates from a csv file.
7) With a s2DPointReplacer I converted the x,y coordinates as Point(x,y) (WKT)
8) Finally I created an expression in a tMap to get only the polygons and points with an intersection. I guess a "contains" would also work:
I hope this helps someone else.
Kind regards,
Paul
Ok, I am trying to upload a .csv file, get it into a spatial points data frame and set the projection system to WGS 84. I then want to determine the distance between each point This is what I have come up with but I
cluster<-read.csv(file = "cluster.csv", stringsAsFactors=FALSE)
coordinates(cluster)<- ~Latitude+Longitude
cluster<-CRS("+proj=longlat +datum=WGS84")
d<-dist2Line(cluster)
This returns an error that says
Error in .pointsToMatrix(p) :
points should be vectors of length 2, matrices with 2 columns, or inheriting from a SpatialPoints* object
But this isn't working and I will be honest that I don't fully comprehend importing and manipulating spatial data in R. Any help would be great. Thanks
I was able to determine the issue I was running into. With WGS 84, the longitude comes before the latitude. This is just backwards from how all the GPS data I download is formatted (e.g. lat-long). Hope this helps anyone else who runs into this issue!
thus the code should have been
cluster<-read.csv(file = "cluster.csv", stringsAsFactors=FALSE)
coordinates(cluster)<- ~Longitude+Latitude
cluster<-CRS("+proj=longlat +datum=WGS84")