Using a for loop to make a cartopy plot of lines from different latitude and longitude coordinates f-CodePudding

The goal for my code is to make a rough roadmap using the latitude and longitude of the exits on the pennsylvania turnpike drawing a line between each exit.

I am using a for loop to plot a line on the map every time it loops. This works if i hard code the latitude and longitude but as soon as i plug in my variables nothing gets plotted. Since the coordinates are in order I am just increasing the index every time it loops to get the next coordinates. I have printed the variables inside the loop and verified they have the desired value. I have tried putting the values in ordered pairs but the plot function didn't like me using nparrays. I'm not sure if there is something simple i am missing, but I appreciate any input.

import netCDF4 as nc
import numpy as np
import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs
from datetime import datetime, timedelta

# Open the file for highway metadata to read csv data
highway_metadata = open('milestone3data.csv', 'r')
metafile = csv.reader(highway_metadata, delimiter = ',')

# Create empty lists with highway data
highway_loc = []
highway_name = []
highway_lat = []
highway_lon = []
highway_dist = []

# Loop to transfer the csv file's data into the lists
for i in metafile:
    highway_loc.append(i[0])
    highway_name.append(i[1])
    highway_lat.append(float(i[2]))
    highway_lon.append(float(i[3]))
    highway_dist.append(i[4])

def road_map():

    enhighway_lat = enumerate(highway_lat)
    enhighway_lon = enumerate(highway_lon)
    orthographic = ccrs.Orthographic()
    platecarree = ccrs.PlateCarree()
    proj = ccrs.Orthographic(central_longitude = -75, central_latitude = 41)
    ax = plt.axes(projection=proj)
  # Set up the background
    ax.add_feature(cartopy.feature.COASTLINE)
    ax.add_feature(cartopy.feature.STATES)
    ax.set_extent((-85,-70,36,45),crs=ccrs.PlateCarree())

    for i,j in enhighway_lat:
        for k,l in enhighway_lon:
            if i or k <= 30:
                plt.plot([highway_lon[k], highway_lon[k 1]], [highway_lat[i], highway_lat[i 1]], color='black', linewidth=1, marker='o', markersize=3, transform=ccrs.PlateCarree())

    plt.savefig('cartopytest7.png')
    plt.show
road_map()

[This is my most recent output from the program][1]

  [1]: https://i.stack.imgur.com/lgFrN.png

CSV file contents: (mile marker, name of exit, latitude, longitude, miles from beginning of turnpike)

2,Gateway (Ohio Connection),40.90419167,-80.47158333,1.43
10,New Castle,40.83018056,-80.34196111,10.7
13,Beaver Valley,40.8143,-80.307925,12.87
28,Cranberry,40.67983889,-80.09537778,28.47
30,Warrendale,40.65533889,-80.06116667,31
39,Butler Valley,40.60913611,-79.91924444,39.1
48,Allegheny Valley,40.542025,-79.81022222,47.73
57,Pittsburgh,40.43808889,-79.74956944,56.44
67,Irwin,40.31342778,-79.65476111,67.22
75,New Stanton,40.22173333,-79.59573333,75.39
91,Donegal,40.10915,-79.35231944,90.69
110,Somerset,40.02033056,-79.05208056,109.91
146,Bedford,40.05013889,-78.48615,145.5
161,Breezewood,39.98721667,-78.24472778,161.5
180,Fort Littleton,40.05010556,-77.93954444,179.44
189,Willow Hill,40.09674167,-77.78441389,188.59
201,Blue Mountain,40.15755278,-77.58403333,201.29
226,Carlisle,40.22814722,-77.14782222,226.54
236,Gettysburg Pike,40.19569444,-76.95665556,236.22
242,Harrisburg West Shore,40.21216667,-76.85765278,241.87
247,Harrisburg East,40.21501111,-76.78060278,247.38
266,Lebanon-Lancaster,40.22974444,-76.43095,266.45
286,Reading,40.21805,-76.05189167,286.09
298,Morgantown,40.15990278,-75.88311667,298.33
312,Downingtown,40.06838611,-75.66450278,311.93
320,SR29,40.07641667,-75.52881944,319.33
326,Valley Forge,40.09296667,-75.39591111,326.62
333,Norristown,40.11101111,-75.27921389,333.28
339,Fort Washington,40.13231944,-75.17092222,338.36
340,Virginia Dr,40.13854444,-75.16268611,339.8
343,Willow Grove,40.16166111,-75.11271111,342.91
351,Bensalem,40.13200278,-74.96229444,351.49
352,Street Rd,40.13150833,-74.96445,351.89
353,Neshaminy Falls,40.12916667,-74.94150278,352.67

CodePudding user response：

Okay, based on the discussion above, see below for a solution.

Notes:

Am using pandas DataFames to easily work with the .csv file. the names field is the column names.
Am not using orthographic projection at all.
Am iterating through the list of highway exits one exit at a time; at each index, am extracting the current and next exits' data - am sure there's a more 'pythonic' way to do this, but this is readable at least.
edit: the final index in the loop is length-1

import netCDF4 as nc
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import pandas as pd

def road_map():    
    # Open the file for highway metadata to read csv data
    highway_metadata = pd.read_csv('milestone3data.csv', names=["loc", "name", "lat", "lon", "dist"])

    proj = ccrs.PlateCarree(central_longitude = -75)
    ax   = plt.axes(projection=proj)
    ax.add_feature(cartopy.feature.COASTLINE)
    ax.add_feature(cartopy.feature.STATES)
    ax.set_extent((-85,-70,36,45),crs=ccrs.PlateCarree())

    for i in range(len(highway_metadata)-1):
        start_lon = highway_metadata['lon'][i]
        start_lat = highway_metadata['lat'][i]
        end_lon   = highway_metadata['lon'][i 1]
        end_lat   = highway_metadata['lat'][i 1]
        plt.plot([start_lon, end_lon], [start_lat, end_lat], color='black', 
                 linewidth=1, marker='o', markersize=3, transform=ccrs.PlateCarree())
                  
    plt.savefig('cartopytest7.png')

if __name__ == '__main__':
    road_map()

This produces the following image:

And, based on this image of the Pennsylvania Turnpike from Wikipedia (source=

CodePudding user response：

It looked like you were trying to do something rather complicated with your plt.plot() statement. You have the list of longitudes and the list of lattitudes; that's all you need for plotting between the points in matplotlib, there's no need for enumerate or looping over lists. The following line should do the trick.

plt.plot(highway_lon, highway_lat, color='black', linewidth=1, marker='o', markersize=3, transform=ccrs.PlateCarree())

Here's the code with some unecessary bits removed.

import csv
import numpy as np
import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs

# Open the file for highway metadata to read csv data
highway_metadata = open('milestone3data.csv', 'r')
metafile = csv.reader(highway_metadata, delimiter = ',')

# Create empty lists with highway data
highway_loc = []
highway_name = []
highway_lat = []
highway_lon = []
highway_dist = []

# Loop to transfer the csv file's data into the lists
for i in metafile:
    highway_loc.append(i[0])
    highway_name.append(i[1])
    highway_lat.append(float(i[2]))
    highway_lon.append(float(i[3]))
    highway_dist.append(i[4])

def road_map():
    fig = plt.figure(figsize=(10, 10))
    proj = ccrs.Orthographic(central_longitude = -75, 
                             central_latitude = 41)
    ax = plt.axes(projection=proj)
    ax.set_extent((-85,-70,36,45),crs=ccrs.PlateCarree())
    # Set up the background
    ax.add_feature(cartopy.feature.COASTLINE)
    ax.add_feature(cartopy.feature.STATES)

    plt.plot(highway_lon, highway_lat, 
             color='black', linewidth=1, marker='o', markersize=3, 
             transform=ccrs.PlateCarree())

    plt.savefig('cartopytest7.png')
    plt.show
    
road_map()