Skip to content

Commit

Permalink
Update fire_evaluation.py - fix lint errors
Browse files Browse the repository at this point in the history
  • Loading branch information
@angehung5
angehung5 authored Sep 6, 2024
1 parent 1cc947a commit 5cf4b5d
Showing 1 changed file with 85 additions and 61 deletions.
146 changes: 85 additions & 61 deletions src/fire_evaluation.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,6 @@
import warnings
warnings.simplefilter(action='ignore')



def fire_flitering(lst, lat, lon, frp, dis_thres):
mask = np.zeros_like(frp, dtype=bool)
for x, y in lst:
Expand All @@ -25,89 +23,115 @@ def fire_flitering(lst, lat, lon, frp, dis_thres):

return np.array(frp*mask)


def main_driver(f_predic, frp_option, cor_option, lat_lim, lon_lim):

init_time = f_predic[-19:-7]
f_output = f_predic[f_predic.rindex('/')+1:-3]
frp_thres = 15 # small fires with FRP<15MW are not included
dis_thres = 15/110 # max spread distance (degree), fires beyond this distance are assumed as NEW fires
f_output = f_predic[f_predic.rindex('/') + 1 : -3]


'''Reading Data'''
"""Reading Data"""
## normalization coef
readin = pd.read_csv('./model/model_normalization_coef.txt')
readin = pd.read_csv("./model/model_normalization_coef.txt")
readin = np.array(readin)
a = readin[0, -1]
b = readin[1, -1]
a = readin[0, -1]
b = readin[1, -1]
del readin



## initial fire mask
for files in os.listdir('./input/'+init_time):
if fnmatch.fnmatch(files, f"*{'f00'}*") and os.path.isfile(os.path.join('./input/'+init_time, files)):
f_init = './input/'+init_time+'/'+files

readin = Dataset(f_init)
fsize = int((readin['input'][:].shape[1]-1)/2)
lat_init = np.round(readin['frame_lat'][:, fsize, fsize], 3)
lon_init = np.round(readin['frame_lon'][:, fsize, fsize], 3)
frp_init = np.array(np.append(np.expand_dims(lat_init, axis=1), np.expand_dims(lon_init, axis=1), axis=1))
for files in os.listdir("./input/" + init_time):
if fnmatch.fnmatch(files, f"*{'f00'}*") and os.path.isfile(
os.path.join('./input/' + init_time, files)
):
f_init = "./input/" + init_time + "/" + files

readin = Dataset(f_init)
fsize = int((readin["input"][:].shape[1] - 1) / 2)
lat_init = np.round(readin["frame_lat"][:, fsize, fsize], 3)
lon_init = np.round(readin["frame_lon"][:, fsize, fsize], 3)
frp_init = np.array(
np.append(
np.expand_dims(lat_init, axis=1), np.expand_dims(lon_init, axis=1), axis=1
)
)
readin.close()
del [readin, fsize, lat_init, lon_init]



## forecast
readin = Dataset(f_predic)
time = readin['time'][0]
lat = np.round(readin['grid_lat'][:], 3)
lon = np.round(readin['grid_lon'][:], 3)
frp_pre = readin['grid_predic'][0, :, :] # lat x alon
frame_lat = np.round(readin['frame_lat'][:], 3)
frame_lon = np.round(readin['frame_lon'][:], 3)
frame_pre = readin['frame_predic_ori'][:, :, :, 0] # frame x lat x lon
readin = Dataset(f_predic)
time = readin["time"][0]
lat = np.round(readin["grid_lat"][:], 3)
lon = np.round(readin["grid_lon"][:], 3)
frp_pre = readin["grid_predic"][0, :, :] # lat x alon
frame_lat = np.round(readin["frame_lat"][:], 3)
frame_lon = np.round(readin["frame_lon"][:], 3)
frame_pre = readin["frame_predic_ori"][:, :, :, 0] # frame x lat x lon

if cor_option == 0:
frame_post = readin['frame_predic_post'][:, :, :, 0] # frame x lat x lon
frame_post = readin["frame_predic_post"][:, :, :, 0] # frame x lat x lon
elif cor_option == 1:
frame_post = readin['frame_predic_frp'][:, :, :, 0] # frame x lat x lon
frame_post = readin["frame_predic_frp"][:, :, :, 0] # frame x lat x lon
readin.close()
del readin

date = time[:8]
hour = time[8:10]


## spatial map - prediction
cmap = cm.get_cmap('jet').copy()
cmap.set_over('#9400D3')
fig, ax = plt.subplots(figsize=(18, 12)) # unit=100pixel
cmap = cm.get_cmap("jet").copy()
cmap.set_over("#9400D3")

fig, ax = plt.subplots(figsize=(18, 12))
h = ax.get_position()
ax.set_position([h.x0-0.04, h.y0, h.width+0.06, h.height])
for axis in ['top','bottom','left','right']:
ax.set_position([h.x0 - 0.04, h.y0, h.width + 0.06, h.height])
for axis in ["top","bottom","left","right"]:
ax.spines[axis].set_linewidth(3)

plt.title(date+' '+hour+'Z Fire Radiative Power - Prediction', fontsize=28, y=1.05)

m = Basemap(llcrnrlon=lon_lim[0],urcrnrlon=lon_lim[-1],llcrnrlat=lat_lim[0],urcrnrlat=lat_lim[-1], projection='mill')
m.drawcoastlines(color='k', linewidth=1)
m.drawcountries(color='k', linewidth=1)
m.drawstates(color='k', linewidth=1)
m.drawmeridians(np.arange(lon_lim[0], lon_lim[-1]+1, 10), color='none', labels=[0,0,0,1], fontsize=28)
m.drawparallels(np.arange(lat_lim[0], lat_lim[-1]+1, 5), color='none', labels=[1,0,0,0], fontsize=28)


plt.title(
date+" "+hour+"Z Fire Radiative Power - Prediction", fontsize=28, y=1.05
)

m = Basemap(
llcrnrlon=lon_lim[0],
urcrnrlon=lon_lim[-1],
llcrnrlat=lat_lim[0],
urcrnrlat=lat_lim[-1],
projection="mill"
)
m.drawcoastlines(color="k", linewidth=1)
m.drawcountries(color="k", linewidth=1)
m.drawstates(color="k", linewidth=1)
m.drawmeridians(
np.arange(lon_lim[0], lon_lim[-1] + 1, 10),
color="none",
labels=[0,0,0,1],
fontsize=28
)
m.drawparallels(
np.arange(lat_lim[0],lat_lim[-1] + 1, 5),
color="none",
labels=[1,0,0,0],
fontsize=28
)

x, y = m(lon[frp_pre!=0], lat[frp_pre!=0])
cs = m.scatter(x, y, marker='o', c=frp_pre[frp_pre!=0], s=120, edgecolor='k', cmap=cmap, vmin=0, vmax=200)

cs = m.scatter(
x,
y,
marker="o",
c=frp_pre[frp_pre!=0],
s=120,
edgecolor="k",
cmap=cmap,
vmin=0,
vmax=200
)

# colorbar
cb = plt.colorbar(cs, extend='max', orientation='vertical')
cb.set_ticks(np.arange(0, 200+1, 20))
cb.set_label('FRP (MW)', fontsize=28, fontweight='bold')
cb = plt.colorbar(cs, extend="max", orientation="vertical")
cb.set_ticks(np.arange(0, 200 + 1, 20))
cb.set_label("FRP (MW)", fontsize=28, fontweight="bold")
cb.ax.tick_params(labelsize=28)

plt.savefig('./output/'+init_time+'/'+f_output+'.jpg')
plt.savefig("./output/" + init_time + "/" + f_output + ".jpg")
plt.close()
del [fig, ax, h, m, x, y, cmap, cs, cb]

return 0

0 comments on commit 5cf4b5d

Please sign in to comment.