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grid_gen_tool.py
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grid_gen_tool.py
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import sys
import os
# For basemap in bad conda builds
proj_lib = os.environ["CONDA_PREFIX"] + '/share/proj/'
os.environ["PROJ_LIB"] = proj_lib
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
from numpy.linalg import inv
from math import sin, cos, sqrt, atan2, asin, acos, atan, degrees, radians
import time
import scipy.io as sio
import argparse
class Click():
def __init__(self, ax, func, button=1):
self.ax=ax
self.func=func
self.button=button
self.press=False
self.move = False
self.c1=self.ax.figure.canvas.mpl_connect('button_press_event', self.onpress)
self.c2=self.ax.figure.canvas.mpl_connect('button_release_event', self.onrelease)
self.c3=self.ax.figure.canvas.mpl_connect('motion_notify_event', self.onmove)
def onclick(self,event):
if event.inaxes == self.ax:
if event.button == self.button:
self.func(event)
def onpress(self,event):
self.press=True
def onmove(self,event):
if self.press:
self.move=True
def onrelease(self,event):
if self.press and not self.move:
self.onclick(event)
self.press=False; self.move=False
def calc_dist(glon_A1,glat_A1,glon_B1,glat_B1):
global x_sign
# Distance Calculation
rlat_A1 = radians(glat_A1)
rlon_A1 = radians(glon_A1)
rlat_B1 = radians(glat_B1)
rlon_B1 = radians(glon_B1)
d_rlon = rlon_B1 - rlon_A1
d_rlat = rlat_B1 - rlat_A1
# Haversine formulation
a = sin(d_rlat / 2)**2 + cos(rlat_A1) * cos(rlat_B1) * sin(d_rlon / 2)**2
# c = 2 * asin2(sqrt(a)) = same as below based on pythagorean relationships
c = 2 * atan2(sqrt(a), sqrt(1 - a))
distance = Re * c
# Calculate Rotation Matrices:
# Rotate first point to Prime Meridian
R1 = np.array((( cos(rlon_A1), sin(rlon_A1), 0),\
(-sin(rlon_A1), cos(rlon_A1), 0),\
( 0 , 0 , 1)))
# Rotates first point to equator
R2 = np.array((( cos(rlat_A1), 0, sin(rlat_A1)),\
( 0 , 1, 0 ),\
(-sin(rlat_A1), 0, cos(rlat_A1))))
# Original 3D (x,y,z) coordinates of A and B
A1 = coord_3D(rlon_A1, rlat_A1)
B1 = coord_3D(rlon_B1, rlat_B1)
# Twice-rotated 3D Coordinates of A and B
A2 = np.dot(R2,np.dot(R1,A1))
B2 = np.dot(R2,np.dot(R1,B1))
# Lat/Lon of twice-rotated A and B
rlat_A2, rlon_A2 = new_latlon(A2[0],A2[1],A2[2])
rlat_B2, rlon_B2 = new_latlon(B2[0],B2[1],B2[2])
#Calculate angle theta between A2 and equator
d = (cos(rlat_B2)-cos(rlon_B2)*cos(distance/Re))/ \
(sin(rlon_B2)*sin(distance/Re))
if glat_B1-glat_A1 == 0:
x_sign=1
else:
x_sign=np.sign(glat_B1-glat_A1)
theta = x_sign*acos(d)
# Rotates first point to equator
R3 = np.array(((1, 0, 0),\
(0, np.cos(theta), np.sin(theta)),\
(0, -np.sin(theta), np.cos(theta))))
return distance, R1, R2, R3
def grid_gen(event,debug=True):
global MEEP, glat_A1, glon_A1, rlons_3, R1, R2, R3
c_glon, c_glat = m(event.xdata,event.ydata,inverse=True)
# PLOT FIRST POINT A
if MEEP<1:
glon_A1 = c_glon; glat_A1 = c_glat
#glon_A1 = event.xdata; glat_A1 = event.ydata
m.plot(glon_A1,glat_A1,'bo',latlon=True)
plt.draw()
MEEP+=1
# CALCULATE AND PLOT SECOND POINT (B) ALONG GC LINE
# 1) Calculate distance of AB
# 2) Generate rotation matrices (R1, R2) to put AB
# on equator with terminus at the prime meridian
# (becomes A'B')
# 3) Calculate grid positions along A'B' given resolution and
# starting at (0,0); ceil(dist(AB)/resolution).
# 4) Plot inv(R1)*inv(R2)*inv(R3)*A'B' and new points
elif MEEP<2:
init_distance, R1, R2, R3 = calc_dist(glon_A1,glat_A1,c_glon,c_glat)
npts = int(abs(np.ceil(init_distance/grid_res)))+1
# Longitudes (radians) are regularly spaced (grid_res)
rlons_3 = (grid_res/Re)*np.arange(npts)
# Along equator all points are at lat = 0
# Get x,y,z coordinates
X3 = coord_3D(rlons_3, np.zeros(npts))
# Rotate back to original position
X1 = np.dot(inv(R1),np.dot(inv(R2),np.dot(inv(R3),X3)))
# Convert to geographic coordinates and plot
glats = np.zeros(npts)
glons = np.zeros(npts)
for nt in range(npts):
lat, lon = new_latlon(X1[0,nt], X1[1,nt], X1[2,nt])
glats[nt] = degrees(lat)
glons[nt] = degrees(lon)
map_x, map_y = m(degrees(lon),degrees(lat))
if m.is_land(map_x,map_y):
m.plot(glons[nt],glats[nt],'go',zorder=3,latlon=True)
else:
m.plot(glons[nt],glats[nt],'bo',zorder=3,latlon=True)
m.drawgreatcircle(glons[0], glats[0], glons[-1], glats[-1],del_s=10,color='k', lw=2.)
plt.draw()
# Rotate back to original position
X1 = np.dot(inv(R1),np.dot(inv(R2),np.dot(inv(R3),X3)))
# Convert to geographic coordinates and plot
glats = np.zeros(npts)
glons = np.zeros(npts)
for nt in range(npts):
lat, lon = new_latlon(X1[0,nt], X1[1,nt], X1[2,nt])
glats[nt] = degrees(lat)
glons[nt] = degrees(lon)
if m.is_land(glons[nt],glats[nt]):
m.plot(glons[nt],glats[nt],'go',zorder=3)
else:
m.plot(glons[nt],glats[nt],'bo',zorder=3)
m.drawgreatcircle(glons[0], glats[0], glons[-1], glats[-1],del_s=10,color='k', lw=2.)
plt.draw()
MEEP+=1
elif MEEP<3:
C1 = coord_3D(radians(c_glon),radians(c_glat))
C3 = np.dot(R3,np.dot(R2,np.dot(R1,C1)))
# Determine direction to send meridians based on position
# of C relative to AB
merid_dir = np.sign(C3[-1])
rlat_C3, rlon_C3 = new_latlon(C3[0],C3[1],C3[2])
# minimmum distance from equator:
min_dist = Re*rlat_C3
npts = int(abs(np.ceil(min_dist/grid_res)))+1
rlons_3 = np.tile(rlons_3,(npts,1))
rlats_3 = merid_dir*np.tile((grid_res/Re)*np.arange(npts).reshape(npts,1),(1,rlons_3.shape[1]))
X3 = coord_3D(rlons_3, rlats_3)
nj = X3.shape[1]
ni = X3.shape[2]
#calculate distances in rotated coordinate system
km_m=1000.
dx=Re*km_m*((rlons_3[:,1:]-rlons_3[:,:-1]))*np.cos((rlats_3[:,:-1]))
dy=Re*km_m*((rlats_3[1:,:]-rlats_3[:-1,:]))
X3 = X3.reshape(3,nj*ni)
if debug:
debug_plot(X3,np.identity(3),nj,ni,'yo')
debug_plot(X3,R3,nj,ni,'ro')
debug_plot(np.dot(inv(R3),X3),R2,nj,ni,'mo')
#
# Rotate back to original position
X1 = np.dot(inv(R1),np.dot(inv(R2),np.dot(inv(R3),X3)))
X1 = X1.reshape(3,nj,ni)
glats = np.zeros((nj,ni))
glons = np.zeros((nj,ni))
for jj in range(nj):
for ii in range(ni):
lat, lon = new_latlon(X1[0,jj,ii], X1[1,jj,ii], X1[2,jj,ii])
glats[jj,ii] = degrees(lat)
glons[jj,ii] = degrees(lon)
angle_dx=np.zeros((nj,ni))
angle_dx[:,1:-1] = np.arctan2(glats[:,2:]-glats[:,:-2],(glons[:,2:]-glons[:,:-2])*np.cos(np.deg2rad(glats[:,1:-1])))
angle_dx[:,0] = np.arctan2(glats[:,1]-glats[:,0],(glons[:,1]-glons[:,0])*np.cos(np.deg2rad(glats[:,0])))
angle_dx[:,-1] = np.arctan2(glats[:,-1]-glats[:,-2],(glons[:,-1]-glons[:,-2])*np.cos(np.deg2rad(glats[:,-1])))
angle_dx = angle_dx * 180.0/np.pi
m.plot(glons,glats,'bo',latlon=True)
plt.draw()
# SAVE AS 2D ARRAY... pre land-masking
#np.savez('grid_lat_lon', x=glats, y=glons,dx=dx,dy=dy,angle_dx=angle_dx)
f=sio.netcdf.netcdf_file('ocean_hgrid.nc','w',2)
nyp=f.createDimension('nyp',nj)
nxp=f.createDimension('nxp',ni)
ny=f.createDimension('ny',nj-1)
nx=f.createDimension('nx',ni-1)
yv=f.createVariable('y','f8',('nyp','nxp'))
xv=f.createVariable('x','f8',('nyp','nxp'))
dyv=f.createVariable('dy','f8',('ny','nxp'))
dxv=f.createVariable('dx','f8',('nyp','nx'))
areav=f.createVariable('area','f8',('ny','nx'))
anglev=f.createVariable('angle_dx','f8',('nyp','nxp'))
yv.units='degrees_N'
xv.units='degrees_E'
areav.units='m2'
anglev.units='degrees'
dyv.units='m'
dxv.units='m'
yv[:]=glats
xv[:]=glons
dxv[:]=dx
dyv[:]=dy
areav[:]=0.25*((dx[0:-1,:]+dx[1:,:])*(dy[:,0:-1]+dy[:,1:]))
anglev[:]=angle_dx
f.close()
MEEP+=1
#plt.figure();plt.pcolor(glats); plt.colorbar()
#plt.figure();plt.pcolor(glons); plt.colorbar()
#plt.show()
def coord_3D(rlon,rlat):
x = Re*np.cos(rlat)*np.cos(rlon)
y = Re*np.cos(rlat)*np.sin(rlon)
z = Re*np.sin(rlat)
return np.array(((x), (y), (z)))
def new_latlon(x,y,z):
lat = asin(z/np.abs(Re))
lon = atan(y/x)
if x<0:
lon+=np.pi
if lon > np.pi:
lon-= 2*np.pi
return lat,lon
def debug_plot(X,R,nj,ni,kwarg):
Xn = np.dot(inv(R),X)
Xn = Xn.reshape(3,nj,ni)
tlats = np.zeros((nj,ni))
tlons = np.zeros((nj,ni))
for jj in range(nj):
for ii in range(ni):
lat, lon = new_latlon(Xn[0,jj,ii], Xn[1,jj,ii], Xn[2,jj,ii])
tlats[jj,ii] = degrees(lat)
tlons[jj,ii] = degrees(lon)
m.plot(tlons,tlats,kwarg,latlon=True)
plt.draw()
MEEP=0
# approximate radius of earth in km
Re = 6378.13
parser = argparse.ArgumentParser(description='''Generate Regional domain model''')
parser.add_argument('--resolution', type=float, help='''Nominal resolution''',default=0.)
parser.add_argument('--proj', type=str, help='''Projection to use''',default='default')
args=parser.parse_args()
fig = plt.figure(figsize=(11.7,8.3))
plt.subplots_adjust(left=0.05,right=0.95,top=0.90,bottom=0.05,wspace=0.15,hspace=0.05)
ax = plt.subplot(111)
#if args.proj == 'default':
# m = Basemap(resolution='l')
#elif args.proj == 'npstere':
m = Basemap(projection='npstere',boundinglat=40,lon_0=60,resolution='l')
#else:
# print('unknown projection type')
m.drawmapboundary(fill_color='azure')
m.fillcontinents(color='palegoldenrod',lake_color='azure')
m.drawcoastlines()
m.drawparallels(np.arange(-90.,120.,30.),labels=[1,0,0,0])
m.drawmeridians(np.arange(0.,420.,60.),labels=[0,0,0,1])
if args.resolution == 0.:
grid_res = float(input("Grid resolution in km: "))
else:
grid_res=args.resolution
click = Click(ax, grid_gen)
#fig.canvas.mpl_connect("button_press_event", onclick)
plt.show()