def tester_s1b():
"""show point shapefile with annotation"""
import cartopy.crs as ccrs
import geopandas as gpd
import numpy as np
import datetime
# tried cartopy.io.shapereader.Reader, fiona.open but
# geopanda probably makes most sense
df = gpd.read_file(shpfile)
arr = np.zeros(34 * 47).reshape([1, 47, 34, ])
ext = [-101.90, -101.86, 31.71, 31.75]
plotter_options = {
'imshow_options': None,
'contour_options': None,
'projection': ccrs.PlateCarree(),
'extent': [-101.90, -101.86, 31.71, 31.75],
'customize_once': [
lambda p: df.plot(ax=p.ax, column='kls', categorical=True, legend=True),
# seems like i have to iterate over records and add label. Also, position of label, leadline etc,
# i still need to search some tool for that, or manally adjust position which i dont want to...
lambda p: [p.ax.annotate(_.Site_Label, (_.geometry.x, _.geometry.y)) for _ in df.itertuples()
if _.Site_Label in ('F1', 'op3_w1', 'S4')],
lambda p: p.ax.gridlines(draw_labels=True),
]
}
p = Plotter(arr, [datetime.date(2020, 12, 4)], extent=ext, projection=ccrs.PlateCarree(),
plotter_options=plotter_options)
p(outdir / 'test_s1b.png')
def tester_bgm_w4():
"""wms, specify projection/extent"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'background_manager':
BackgroundManager(wms_options={
'wms':
'https://services.nationalmap.gov/arcgis/services/USGSNAIPImagery/ImageServer/WMSServer',
'layers': '0'
},
extent=[-465000.0, -460000.0, -902000.0,
-907000.0]), #lcc, the data's projection
'customize_once':
lambda p: p.ax.gridlines(draw_labels=True),
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_w4.png')
def tester_bg1():
"""load background tif file and use it"""
from plotter import calpost_reader as reader
import rasterio
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
b = rasterio.open(bgfile)
bext = [
b.transform[2], b.transform[2] + b.transform[0] * b.width,
b.transform[5] + b.transform[4] * b.height, b.transform[5]
]
plotter_options = {
'contour_options': {
'alpha': .2
},
'extent':
bext,
'projection':
ccrs.epsg(3857),
'customize_once':
lambda p: p.ax.imshow(b.read()[:3, :, :].transpose((1, 2, 0)),
extent=bext,
origin='upper')
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bg1.png')
def tester_s2():
"""show contour from calpost plus annotated points"""
from plotter import calpost_reader as reader
import geopandas as gpd
# source locations
df = gpd.read_file(shpfile)
df = df.to_crs(
'+proj=lcc +lat_1=33 +lat_2=45 +lat_0=40 +lon_0=-97 +x_0=0 +y_0=0 +a=6370000 +b=6370000 +units=m +no_defs')
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
plotter_options = {
'contour_options': {},
'customize_once': [
lambda p: df.plot(ax=p.ax, column='kls', categorical=True, legend=True, zorder=10),
lambda p: [p.ax.annotate(_.Site_Label, (_.geometry.x, _.geometry.y)) for _ in df.itertuples()
if _.Site_Label in ('F1', 'op3_w1', 'S4')],
lambda p: p.ax.gridlines(draw_labels=True),
]
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y,
plotter_options=plotter_options)
p(outdir / 'test_s2.png')
def tester_s1a():
"""show point shapefile"""
import cartopy.crs as ccrs
import geopandas as gpd
import numpy as np
import datetime
# tried cartopy.io.shapereader.Reader, fiona.open but
# geopanda probably makes most sense
df = gpd.read_file(shpfile)
arr = np.zeros(34 * 47).reshape([1, 47, 34, ])
ext = [-101.90, -101.86, 31.71, 31.75]
plotter_options = {
'imshow_options': None,
'contour_options': None,
'projection': ccrs.PlateCarree(),
'extent': [-101.90, -101.86, 31.71, 31.75],
'customize_once': [
lambda p: p.ax.scatter(df.geometry.x, df.geometry.y, color='r', marker='o'),
# lambda p: p.ax.set_xticks(np.arange(-101.90, -101.86, 0.01), crs=ccrs.PlateCarree()),
lambda p: p.ax.gridlines(draw_labels=True),
]
}
p = Plotter(arr, [datetime.date(2020, 12, 4)], extent=ext, projection=ccrs.PlateCarree(),
plotter_options=plotter_options)
p(outdir / 'test_s1a.png')
def tester_bgm_b4b():
"""background file, already processed to pseudo mercator, zoom in"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
bgm = BackgroundManager(bgfile=bgfile)
ext = bgm.extent
bgm.extent = [
2 / 3 * ext[0] + 1 / 3 * ext[1],
1 / 3 * ext[0] + 2 / 3 * ext[1],
2 / 3 * ext[2] + 1 / 3 * ext[3],
1 / 3 * ext[2] + 2 / 3 * ext[3],
]
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'background_manager': bgm,
'customize_once': lambda p: p.ax.gridlines(draw_labels=True),
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_b4b.png')
def tester_s4():
"""show contour from calpost with background in different projection plus annotated points"""
from plotter import calpost_reader as reader
import rasterio
import cartopy.crs as ccrs
import geopandas as gpd
# source locations
df = gpd.read_file(shpfile)
df = df.to_crs('EPSG:3857')
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
b = rasterio.open(bgfile)
bext = [b.transform[2], b.transform[2] + b.transform[0] * b.width,
b.transform[5] + b.transform[4] * b.height, b.transform[5]]
plotter_options = {
'contour_options': {'alpha': .5},
'extent': bext, 'projection': ccrs.epsg(3857),
'customize_once': [
lambda p: p.ax.imshow(b.read()[:3, :, :].transpose((1, 2, 0)),
extent=bext, origin='upper'),
lambda p: df.plot(ax=p.ax, column='kls', categorical=True, legend=True, zorder=10),
lambda p: [p.ax.annotate(_.Site_Label, (_.geometry.x, _.geometry.y)) for _ in df.itertuples()
if _.Site_Label in ('F1', 'op3_w1', 'S4')],
lambda p: p.ax.gridlines(draw_labels=True),
]}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_s4.png')
def tester_bgm_b3():
"""specify extent/projection and bg image"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'background_manager':
BackgroundManager(
bgfile=bgfile_lcc,
projection=ccrs.epsg(3857),
),
'customize_once':
lambda p: p.ax.gridlines(draw_labels=True),
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_b3.png')
def tester_bgm_w2b():
"""specify projection/extent, then wms"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'background_manager':
BackgroundManager(
projection=ccrs.epsg(3857),
extent=[-11344200.0, -11338900.0, 3724300.0, 3731100.0]),
'customize_once': [
lambda p: p.ax.add_wms(
'https://services.nationalmap.gov/arcgis/services/USGSNAIPImagery/ImageServer/WMSServer',
layers='0'),
lambda p: p.ax.gridlines(draw_labels=True),
]
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_w2b.png')
def tester_tc4():
"""show contour from geotiff with background in different projection"""
import rasterio
import datetime
import cartopy.crs as ccrs
import numpy as np
r = rasterio.open(tiffile)
arr = r.read(1)
arr = arr.reshape(1, *arr.shape)
# print(arr.shape)
ext = [r.transform[2], r.transform[2] + r.transform[0] * r.width,
r.transform[5] + r.transform[4] * r.height, r.transform[5]]
# background
b = rasterio.open(bgfile)
bext = [b.transform[2], b.transform[2] + b.transform[0] * b.width,
b.transform[5] + b.transform[4] * b.height, b.transform[5]]
plotter_options = {
'contour_options': {'alpha': .5},
'extent': bext, 'projection': ccrs.epsg(3857),
'customize_once': lambda p: p.ax.imshow(b.read()[:3, :, :].transpose((1, 2, 0)),
extent=bext, origin='upper')}
p = Plotter(arr, tstamps=[datetime.date(2020, 12, 4)], extent=ext, plotter_options=plotter_options)
p(outdir / 'test_tc4.png')
def tester_bg3():
"""specify extent, and use caropy.io.img_tiles.GootleTiles"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
import cartopy.io.img_tiles as cimgt
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
bext = [-11344200.0, -11338900.0, 3724300.0, 3731100.0]
plotter_options = {
'contour_options': {
'alpha': .2
},
'extent':
bext,
'projection':
ccrs.epsg(3857),
# GoogleMap, we may need license
'customize_once':
lambda p: p.ax.add_image(cimgt.GoogleTiles(style='satellite'), 15)
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bg3.png')
def tester_bg4():
"""specify extent, and use NAIP images with cartopy.io.ogc_clients.WMSRasterSource"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
# import cartopy.io.ogc_clients as cogcc
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
def my_add_naip(p):
img = p.ax.add_wms(
'https://services.nationalmap.gov/arcgis/services/USGSNAIPImagery/ImageServer/WMSServer',
layers='0')
# TODO how can i save this...?, or should I save this?
# background
bext = [-11344200.0, -11338900.0, 3724300.0, 3731100.0]
plotter_options = {
'contour_options': {
'alpha': .2
},
'extent': bext,
'projection': ccrs.epsg(3857),
# 'customize_once': lambda p: p.ax.add_wms(
# 'https://services.nationalmap.gov/arcgis/services/USGSNAIPImagery/ImageServer/WMSServer',
# layers='0'
# )
'customize_once': my_add_naip,
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bg4.png')
def tester_r1():
"""show numpy array"""
import numpy as np
import datetime
np.random.seed(1)
arr = np.random.random(34 * 47).reshape([1, 47, 34, ])
# print(arr)
ext = [-464400, -906700, -461000, -902000]
p = Plotter(arr, [datetime.date(2020, 12, 4)], extent=ext)
p(outdir / 'test_r1.png')
def tester_pc2():
"""show contour from calpost"""
from plotter import calpost_reader as reader
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
plotter_options = {'contour_options': {}}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y,
plotter_options=plotter_options)
p(outdir / 'test_pc2.png')
def tester_tc2():
"""show contour from geotiff"""
import rasterio
import datetime
r = rasterio.open(tiffile)
arr = r.read(1)
arr = arr.reshape(1, *arr.shape)
# print(arr.shape)
ext = [r.transform[2], r.transform[2] + r.transform[0] * r.width,
r.transform[5] + r.transform[4] * r.height, r.transform[5]]
# print(ext)
p = Plotter(arr, [datetime.date(2020, 12, 4)], extent=ext, plotter_options={'contour_options': {}})
p(outdir / 'test_tc2.png')
def tester_pr2b_v(quiet=False):
"""animate calpost raster"""
from plotter import calpost_reader as reader
import tempfile
from pathlib import Path
import shlex
import subprocess
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
plotter_options = {
'imshow_options': {
'origin': 'lower', # showing array as image require to specifie that grater y goes upward
}
}
# since calpost tells x,y coordinates of each point, it is easier just pass those coords
# dont forget that calpost has distance in km
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
tstamps = dat['ts']
with tempfile.TemporaryDirectory() as wdir:
workdir = Path(wdir)
#print(workdir)
# function to save one time frame
def saveone(i):
ts = tstamps[i]
pname = workdir / f'{i:04}.png'
#print(pname)
footnote = str(ts)
p(pname, tidx=i, footnote=footnote)
n = len(tstamps)
for i, ts in enumerate(tstamps):
saveone(i)
# make mpeg file
if quiet:
loglevel = '-loglevel error'
else:
loglevel = ''
cmd = f'ffmpeg {loglevel} -i "{workdir / "%04d.png"}" -vframes 2880 -crf 3 -vcodec libx264 -pix_fmt yuv420p -f mp4 -y "{outdir / "test_pr2b.mp4"}"'
#print(cmd)
#print(shlex.split(cmd))
subprocess.run(shlex.split(cmd), check=True)
def tester_pr2b():
"""show calpost raster"""
from plotter import calpost_reader as reader
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
plotter_options = {
'imshow_options': {
'origin': 'lower', # showing array as image require to specifie that grater y goes upward
}
}
# since calpost tells x,y coordinates of each point, it is easier just pass those coords
# dont forget that calpost has distance in km
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_pr2b.png')
def tester_bgm_n0():
"""no background or anything"""
from plotter import calpost_reader as reader
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'customize_once': lambda p: p.ax.gridlines(draw_labels=True),
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_n0.png')
def tester_pc3():
"""show contour from calpost in different projection"""
from plotter import calpost_reader as reader
import rasterio
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
b = rasterio.open(bgfile)
bext = [b.transform[2], b.transform[2] + b.transform[0] * b.width,
b.transform[5] + b.transform[4] * b.height, b.transform[5]]
plotter_options = {'extent': bext, 'projection': ccrs.epsg(3857),
'contour_options': {}}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_pc3.png')
def tester_pr2a():
"""show calpost raster"""
from plotter import calpost_reader as reader
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
g = dat['grid']
ext = [g['x0'], g['x0'] + g['nx'] * g['dx'],
g['y0'], g['y0'] + g['ny'] * g['dy'], ]
# distance in calpost is in km
ext = [_ * 1000 for _ in ext]
plotter_options = {
'imshow_options': {
'origin': 'lower', # showing array as image require to specifie that grater y goes upward
}
}
p = Plotter(dat['v'], dat['ts'], extent=ext,
plotter_options=plotter_options)
p(outdir / 'test_pr2a.png')
def tester_bgm_b1a():
"""background file, dont have to tell its projection"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'background_manager': BackgroundManager(bgfile=bgfile),
'customize_once': lambda p: p.ax.gridlines(draw_labels=True),
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_b1a.png')
def tester_tc3():
"""show contour from geotiff in different projection"""
import rasterio
import datetime
import cartopy.crs as ccrs
r = rasterio.open(tiffile)
arr = r.read(1)
arr = arr.reshape(1, *arr.shape)
# print(arr.shape)
ext = [r.transform[2], r.transform[2] + r.transform[0] * r.width,
r.transform[5] + r.transform[4] * r.height, r.transform[5]]
# background
b = rasterio.open(bgfile)
bext = [b.transform[2], b.transform[2] + b.transform[0] * b.width,
b.transform[5] + b.transform[4] * b.height, b.transform[5]]
plotter_options = {'contour_options': {}, 'extent': bext, 'projection': ccrs.epsg(3857)}
p = Plotter(arr, [datetime.date(2020, 12, 4)], extent=ext, plotter_options=plotter_options)
p(outdir / 'test_tc3.png')
def tester_bg2():
"""load background tif file and use extent without showing it"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
bext = [-11344200.0, -11338900.0, 3724300.0, 3731100.0]
plotter_options = {
'contour_options': {
'alpha': .2
},
'extent': bext,
'projection': ccrs.epsg(3857),
# 'customize_once': lambda p: p.ax.imshow(b.read()[:3, :, :].transpose((1, 2, 0)),
# extent=bext, origin='upper')
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bg2.png')
def tester_bgm_n4():
"""specify only extent without bg image"""
from plotter import calpost_reader as reader
import cartopy.crs as ccrs
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# background
plotter_options = {
'contour_options': {
'alpha': .2
},
'background_manager':
BackgroundManager(extent=[-465000.0, -460000.0, -902000.0, -907000.0
]), # lcc extent larger than modeling
'customize_once':
lambda p: p.ax.gridlines(draw_labels=True),
}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y, plotter_options=plotter_options)
p(outdir / 'test_bgm_n4.png')
def tester_pc2_v(quiet=False):
"""animate contour from calpost"""
from plotter import calpost_reader as reader
import tempfile
from pathlib import Path
import shlex
import subprocess
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
plotter_options = {'contour_options': {}}
x = dat['x'] * 1000
y = dat['y'] * 1000
p = Plotter(dat['v'], dat['ts'], x=x, y=y,
plotter_options=plotter_options)
tstamps = dat['ts']
with tempfile.TemporaryDirectory() as wdir:
workdir = Path(wdir)
# function to save one time frame
def saveone(i):
ts = tstamps[i]
pname = workdir / f'{i:04}.png'
footnote = str(ts)
p(pname, tidx=i, footnote=footnote)
n = len(tstamps)
for i, ts in enumerate(tstamps):
saveone(i)
# make mpeg file
if quiet:
loglevel = '-loglevel error'
else:
loglevel = ''
cmd = f'ffmpeg {loglevel} -i "{workdir / "%04d.png"}" -vframes 2880 -crf 3 -vcodec libx264 -pix_fmt yuv420p -f mp4 -y "{outdir / "test_pc2b.mp4"}"'
subprocess.run(shlex.split(cmd))
def tester_s5(quiet=True):
"""show contour from calpost with all the bells and whistles"""
from plotter import calpost_reader as reader
from plotter.plotter_util import LambertConformalTCEQ
import rasterio
import cartopy.crs as ccrs
import geopandas as gpd
import matplotlib.colors as colors
from shapely.geometry import Polygon
from adjustText import adjust_text
import tempfile
from pathlib import Path
import shlex
import subprocess
# background (extent is used as plot's extent)
b = rasterio.open(bgfile)
bext = [b.transform[2], b.transform[2] + b.transform[0] * b.width,
b.transform[5] + b.transform[4] * b.height, b.transform[5]]
# source locations
df = gpd.read_file(shpfile)
df = df.to_crs('EPSG:3857')
# read the data
title = 'Flare'
with open('../data/tseries_ch4_1min_conc_co_fl.dat') as f:
dat = reader.Reader(f, slice(60 * 12, 60 * 12 + 10))
# grab necessary info
arr = dat['v']
tstamps = dat['ts']
grid = dat['grid']
extent = [
grid['x0'], grid['x0'] + grid['nx'] * grid['dx'],
grid['y0'], grid['y0'] + grid['ny'] * grid['dy'],
]
# distance in calpost is in km
extent = [_ * 1000 for _ in extent]
x = dat['x'] * 1000
y = dat['y'] * 1000
# convert unit of array from g/m3 tp ppb
# mwt g/mol
# molar volume m3/mol
arr = arr / 16.043 * 0.024465403697038 * 1e9
# Mrinali/Gary's surfer color scale
cmap = colors.ListedColormap([
'#D6FAFE', '#02FEFF', '#C4FFC4', '#01FE02',
'#FFEE02', '#FAB979', '#EF6601', '#FC0100', ])
cmap.set_under('#FFFFFF')
# Define a normalization from values -> colors
bndry = [1, 10, 50, 100, 200, 500, 1000, 2000]
norm = colors.BoundaryNorm(bndry, len(bndry))
plotter_options = {
'extent': bext, 'projection': ccrs.epsg(3857),
'title': title,
'contour_options': {
'levels': bndry,
'cmap': cmap,
'norm': norm,
'alpha': .5,
},
'colorbar_options': {
'label': r'$CH_4$ (ppbV)',
},
'customize_once': [
# background
lambda p: p.ax.imshow(b.read()[:3, :, :].transpose((1, 2, 0)),
extent=bext, origin='upper'),
# emission points
lambda p: df.plot(ax=p.ax, column='kls', categorical=True, legend=False, zorder=10,
markersize=2,
# got red/blue/yellow from colorbrewer's Set1
cmap=colors.ListedColormap(['#e41a1c', '#377eb8', '#ffff33'])),
# emission point annotations
lambda p: adjust_text(
# make list of annotation
list(
# this part creates annotation for each point
p.ax.text(_.geometry.x, _.geometry.y, _.Site_Label, zorder=11, size=6)
# goes across all points but filter by Site_Label
for _ in df.itertuples() if _.Site_Label in ('F1', 'op3_w1', 'S4')
),
# draw arrow from point to annotation
arrowprops={'arrowstyle': '-'}
),
# modeled box
lambda p: p.ax.add_geometries(
[Polygon([(extent[x],extent[y]) for x,y in ((0,2), (0,3), (1,3), (1,2), (0,2))])],
crs=LambertConformalTCEQ(), facecolor='none', edgecolor='white', lw=.6,
),
]}
# make a plot template
p = Plotter(arr, dat['ts'], x=x, y=y, plotter_options=plotter_options)
# make a plot
p(outdir / 'test_s5.png')
# make an animation
with tempfile.TemporaryDirectory() as wdir:
workdir = Path(wdir)
# function to save one time frame
def saveone(i):
ts = tstamps[i]
pname = workdir / f'{i:04}.png'
footnote = str(ts)
p(pname, tidx=i, footnote=footnote)
n = len(tstamps)
for i, ts in enumerate(tstamps):
saveone(i)
# make mpeg file
if quiet:
loglevel = '-loglevel error'
else:
loglevel = ''
cmd = f'ffmpeg {loglevel} -i "{workdir / "%04d.png"}" -vframes 2880 -crf 3 -vcodec libx264 -pix_fmt yuv420p -f mp4 -y "{outdir / "test_pr2b.mp4"}"'
subprocess.run(shlex.split(cmd))