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#!/usr/bin/env python3
# Use the proper idiom in the main module ...
# NOTE: See https://docs.python.org/3.12/library/multiprocessing.html#the-spawn-and-forkserver-start-methods
if __name__ == "__main__":
# Import standard modules ...
import gzip
import json
import math
import os
# Import special modules ...
try:
import cartopy
cartopy.config.update(
{
"cache_dir" : os.path.expanduser("~/.local/share/cartopy_cache"),
}
)
except:
raise Exception("\"cartopy\" is not installed; run \"pip install --user Cartopy\"") from None
try:
import numpy
except:
raise Exception("\"numpy\" is not installed; run \"pip install --user numpy\"") from None
try:
import PIL
import PIL.Image
PIL.Image.MAX_IMAGE_PIXELS = 1024 * 1024 * 1024 # [px]
import PIL.ImageDraw
except:
raise Exception("\"PIL\" is not installed; run \"pip install --user Pillow\"") from None
try:
import shapely
import shapely.geometry
import shapely.wkb
except:
raise Exception("\"shapely\" is not installed; run \"pip install --user Shapely\"") from None
# Import my modules ...
try:
import pyguymer3
import pyguymer3.geo
import pyguymer3.image
except:
raise Exception("\"pyguymer3\" is not installed; run \"pip install --user PyGuymer3\"") from None
# **************************************************************************
# Define resolution ...
res = "i"
nLon = 3600 # [px]
nLat = 1800 # [px]
dLon = 360.0 / float(nLon) # [°/px]
dLat = 180.0 / float(nLat) # [°/px]
# Define speed ...
speed = 20.0 # [NM/hr]
# Define starting location ...
startingLon = -1.0 # [°]
startingLat = 50.5 # [°]
# Define combinations ...
combs = [
# Study convergence (changing just "nAng" and "prec") ...
(2, 9, 5000,),
(2, 17, 2500,),
(2, 33, 1250,),
]
# **************************************************************************
# Load colour tables ...
with open(f"{pyguymer3.__path__[0]}/data/json/colourTables.json", "rt", encoding = "utf-8") as fObj:
cts = json.load(fObj)
# Find the Shapefiles ...
sfiles = [
cartopy.io.shapereader.gshhs(
level = 1,
scale = res,
),
cartopy.io.shapereader.gshhs(
level = 5,
scale = res,
),
cartopy.io.shapereader.gshhs(
level = 6,
scale = res,
),
]
print("Making axes ...")
# Create axes ...
lons = numpy.linspace(
-180.0 + 0.5 * dLon,
+180.0 - 0.5 * dLon,
nLon,
dtype = numpy.float64,
) # [°]
lats = numpy.linspace(
+90.0 - 0.5 * dLat,
-90.0 + 0.5 * dLat,
nLat,
dtype = numpy.float64,
) # [°]
# Check if the direct distance array exists ...
if os.path.exists("directDist.bin"):
# Load direct distance array ...
directDist = numpy.fromfile(
"directDist.bin",
dtype = numpy.float64,
).reshape(nLat, nLon) # [m]
else:
# Create (and save) direct distance array ...
directDist = numpy.zeros((nLat, nLon), dtype = numpy.float64) # [m]
for iLon in range(nLon):
for iLat in range(nLat):
try:
directDist[iLat, iLon], _, _ = pyguymer3.geo.calc_dist_between_two_locs(
startingLon,
startingLat,
lons[iLon],
lats[iLat],
) # [m]
except:
print(f"WARNING: Failed to find distance to ({lons[iLon]:+.9f}°,{lats[iLat]:+.9f}°), skipping.")
directDist[iLat, iLon] = -1.0 # [m]
directDist.tofile("directDist.bin")
# **************************************************************************
# Loop over combinations ...
for cons, nAng, prec in combs:
print(f"Processing \"cons={cons:.2e}, nAng={nAng:d}, prec={prec:.2e}\" ...")
# **********************************************************************
# Initialize images ...
absDiff = numpy.full((nLat, nLon), 1.0e9, dtype = numpy.float64) # [m]
relDiff = numpy.full((nLat, nLon), 1.0e9, dtype = numpy.float64) # [%]
# **********************************************************************
# Create short-hands ...
# NOTE: Say that 40,000 metres takes 1 hour at 20 knots.
freqLand = 24 * 40000 // prec # [#]
freqSimp = 40000 // prec # [#]
# Deduce directory name ...
dname = f"res={res}_cons={cons:.2e}_tol=1.00e-10/nAng={nAng:d}_prec={prec:.2e}/freqLand={freqLand:d}_freqSimp={freqSimp:d}_lon={startingLon:+011.6f}_lat={startingLat:+010.6f}/limit"
# Loop over sailing distances ...
for sailingDist in range(5, 30005, 5):
# Skip if this distance cannot exist (because the precision is too
# coarse) and determine the step count ...
if (1000 * sailingDist) % prec != 0:
continue
istep = ((1000 * sailingDist) // prec) - 1 # [#]
# Deduce file name and skip if it is missing ...
fname = f"{dname}/istep={istep + 1:06d}.wkb.gz"
if not os.path.exists(fname):
continue
# Load [Multi]LineString ...
with gzip.open(fname, mode = "rb") as gzObj:
limit = shapely.wkb.loads(gzObj.read())
# Loop over lines ...
for line in pyguymer3.geo.extract_lines(limit, onlyValid = False):
# Loop over coordinates ...
for lon, lat in line.coords:
# Deduce indices and skip if there isn't a direct distance ...
iLon = max(0, min(nLon - 1, math.floor((lon + 180.0) / dLon))) # [px]
iLat = max(0, min(nLat - 1, math.floor(( 90.0 - lat) / dLat))) # [px]
if directDist[iLat, iLon] < 0.0:
continue
# Update differences ...
delta = float(sailingDist * 1000) - directDist[iLat, iLon] # [m]
absDiff[iLat, iLon] = min(
absDiff[iLat, iLon],
delta,
) # [m]
relDiff[iLat, iLon] = min(
relDiff[iLat, iLon],
delta / directDist[iLat, iLon],
) # [%]
# **********************************************************************
print(" > Cleaning arrays ...")
# Remove pixels which are numerical noise (e.g., ones where it is
# quicker to sail than go directly) ...
numpy.place(absDiff, absDiff < 0.0, 0.0) # [m]
numpy.place(relDiff, relDiff < 0.0, 0.0) # [%]
print(f" > Maximum absolute value = {absDiff[absDiff < 1.0e9].max():.6e} m.")
print(f" > Maximum relative value = {relDiff[relDiff < 1.0e9].max():.6e} %.")
# **********************************************************************
print(" > Scaling array ...")
# Convert to useful units ...
# NOTE: 1.0e9 / 1852.0 / speed = 26997.84017278618 ≥ 1.0e4
absDiff /= 1852.0 # [NM]
absDiff /= speed # [hr]
print(f" > Maximum absolute value = {absDiff[absDiff < 1.0e4].max():.6e} hr.")
# **********************************************************************
# NOTE: Maximum absolute value = 1.435046e+07 m.
# NOTE: Maximum relative value = 1.276112e+01 %.
# NOTE: Maximum absolute value = 3.874313e+02 hr.
# NOTE: Maximum absolute value = 7.169781e+06 m.
# NOTE: Maximum relative value = 3.577232e+00 %.
# NOTE: Maximum absolute value = 1.935686e+02 hr.
# **********************************************************************
print(" > Making PNGs ...")
# Create image ...
absDiffImg = numpy.zeros((nLat, nLon, 3), dtype = numpy.uint8)
for iLat in range(nLat):
for iLon in range(nLon):
if absDiff[iLat, iLon] < 1.0e4:
color = round(
min(
255.0,
255.0 * absDiff[iLat, iLon].astype(numpy.float64) / 200.0,
)
)
absDiffImg[iLat, iLon, :] = cts["rainbow"][color][:]
else:
absDiffImg[iLat, iLon, :] = 255
absDiffImg = PIL.Image.fromarray(absDiffImg)
# Create image ...
relDiffImg = numpy.zeros((nLat, nLon, 3), dtype = numpy.uint8)
for iLat in range(nLat):
for iLon in range(nLon):
if relDiff[iLat, iLon] < 1.0e9:
color = round(
min(
255.0,
255.0 * relDiff[iLat, iLon].astype(numpy.float64) / 4.0,
)
)
relDiffImg[iLat, iLon, :] = cts["rainbow"][color][:]
else:
relDiffImg[iLat, iLon, :] = 255
relDiffImg = PIL.Image.fromarray(relDiffImg)
# Create drawing objects ...
absDiffDraw = PIL.ImageDraw.Draw(absDiffImg)
relDiffDraw = PIL.ImageDraw.Draw(relDiffImg)
# Loop over Shapefiles ...
for sfile in sfiles:
# Loop over records ...
for record in cartopy.io.shapereader.Reader(sfile).records():
# Loop over Polygons ...
for poly in pyguymer3.geo.extract_polys(record.geometry, onlyValid = False, repair = False):
# Initialize list ...
coords = [] # [px], [px]
# Loop over coordinates in exterior ring ...
for coord in poly.exterior.coords:
# Deduce location and append to list ...
x = max(0.0, min(float(nLon), (coord[0] + 180.0) / dLon)) # [px]
y = max(0.0, min(float(nLat), ( 90.0 - coord[1]) / dLat)) # [px]
coords.append((x, y)) # [px], [px]
# Draw exterior ring ...
absDiffDraw.line(coords, fill = (255, 255, 255), width = 1)
relDiffDraw.line(coords, fill = (255, 255, 255), width = 1)
# Save PNG ...
absDiffImg.save(f"../res={res}_cons={cons:.2e}_nAng={nAng:d}_prec={prec:.2e}_lon={startingLon:+011.6f}_lat={startingLat:+010.6f}_abs.png")
pyguymer3.image.optimize_image(f"../res={res}_cons={cons:.2e}_nAng={nAng:d}_prec={prec:.2e}_lon={startingLon:+011.6f}_lat={startingLat:+010.6f}_abs.png", strip = True)
# Save PNG ...
relDiffImg.save(f"../res={res}_cons={cons:.2e}_nAng={nAng:d}_prec={prec:.2e}_lon={startingLon:+011.6f}_lat={startingLat:+010.6f}_rel.png")
pyguymer3.image.optimize_image(f"../res={res}_cons={cons:.2e}_nAng={nAng:d}_prec={prec:.2e}_lon={startingLon:+011.6f}_lat={startingLat:+010.6f}_rel.png", strip = True)
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