Geoplotting

# Import numpy and pyplot as well as cartopy.  
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

import cartopy
import cartopy.crs as ccrs

# Create a figure object and specify its size
# plt.figure(figsize=(8,8))

# Add a plot axis using the axis command.  Here, Matplotlib is told this will be a map axis with the projection= command.
# ax = plt.axes(projection=ccrs.Robinson())

# Draw the outline of the coastlines.
# ax.coastlines()  #Note 

# Let's visualize a few of the many projections that cartopy permits
# Uncomment the lines below to generate the figure.


### NOTE:  You can uncomment/comment a block of code by highlighting it and typing CTRL + /, that's "Control Slash".
projections = [ccrs.PlateCarree(),
                ccrs.Robinson(),
                ccrs.Mercator(),
                ccrs.Orthographic(),
                ccrs.InterruptedGoodeHomolosine(),
                ccrs.Mollweide()
               ]

i = 1
plt.figure(figsize=(10,5))
for proj in projections:
     #plt.figure()
     geoax = plt.subplot(3,2,i,projection=proj)
     #geoax.stock_img()
     geoax.coastlines()
     geoax.set_title(f'{type(proj)}')
     i+=1

# We set the bounds of the map using the set_extent() input.

extent = [-150, -50, 20, 50]

#ax = plt.axes(projection=ccrs.Mollweide())
#ax.set_extent(extent)
#ax.coastlines(resolution='50m')
#ax.stock_img()
#plt.show()

# Using the feature library, we can add geographic features, such as land masks, coastline boundaries, and rivers.


import cartopy.feature as cfeature

ax = plt.axes(projection=ccrs.Mollweide())
ax.set_extent(extent)
ax.coastlines(resolution='50m')
#ax.stock_img()

ax.add_feature(cfeature.LAND,zorder=1)
ax.add_feature(cfeature.COASTLINE,zorder=1)
ax.add_feature(cfeature.RIVERS,zorder=1)
ax.gridlines()

plt.show()

# Load the data file
# Go to https://earthquake.usgs.gov/earthquakes/search/
# Download all earthquakes in the past 30 days. Choose .csv under Other Options.
# Move that file into the directory where you are working and load it using the loadtxt command.
stations = np.loadtxt('query.csv',delimiter=',',skiprows=1,usecols=(1,2))

stations

# First just use a standard x-y plot to examine the stations. 
# Graph using symbols, e.g. '.' dots or 'o' circles or 's' squares.  
# Label the axes Lat and Lon - make sure you know which is which.  Remember Lat is restricted between -90 and 90.

plt.figure()  #create a figure objec

plt.scatter()
plt.plot(xdtata,ydata,)

plt.show()  #render all the objects 

# Define a bounding box in polar coordinates (Lat, Lon) that tells cartopy how to set the 
# map limits.  This is so the map scale will match the scale of the points being plotted. Ie, you don't want a map
# of the world, if all the points are in Narragansett Bay.
# Your box should have four sides - North, East, West, South.  The north and south limits are defined by the range of 
# your latitudes.  Similarly, the east and west limits are defined by the range of your longitudes.
# lat = stations[:,0].copy()


# Determine the limits of your bounding box.
# Go in order of BBox = [E,W,S,N] or [Left, Right, Bottom, Top]
# NOTE:  Try to use coding to introduce flexibility to the Bounding Box limits, rather than hardwire them.  
# This is important, because your data may change.  Here, it is helpful to use the lat/lon data to establish the 
# map limits.

# Define the bounding box extent and use that with the results from the cells above to make 
# a plot of all earthquakes in the past 30 days.

# BBox = [x0,x1,y0,y1], so [Lon_e, Lon_w,Lat_s,Lat_n]



# Create a figure object
fig = plt.figure(figsize=(15,10))


# Add axes and define a projection



# Add some features to make it pretty


# plot the earthquake locations on the map.  Specify the correct coordinate transform.



plt.show()

stations = np.loadtxt('all_hour.csv',delimiter=',',skiprows=1,usecols=(1,2))

# Define a bounding box in polar coordinates (Lat, Lon) 
lat = stations[:,0].copy()


# Go in order of BBox = [E,W,S,N] or [Left, Right, Bottom, Top]



# Add axes and define a projection



# Add some features to make it pretty


# plot the earthquake locations on the map.  Specify the correct coordinate transform.


#  Change the fill color of the continents

#  Add the location of a nearby city and mark it with a symbol and label.

# Note that zorder controls the layers. If you want something on top to show, it needs a higher zorder.