""" FireGdf_sfs
Module for creating geojson summary for temporal evolution of each single fire
(large active fires up to the present time step)
Large fires are fires with area > falim
List of geojson types
---------------------
* fperim(''): fire basic attributes and perimeter geometry
* fline('FL'): active fire line geometry
* NFP('NFP'): new fire pixels
List of functions
-----------------
* make_fire_history
* merge_fires
* save_gdf_1fire
* save_gdf_trng
Modules required
----------------
* FireObj
* FireIO
* FireConsts
"""
import os
import warnings
import multiprocessing
warnings.simplefilter(action='ignore', category=FutureWarning)
# Use a logger to record console output
from FireLog import logger
from FireConsts import number_of_multi_proc_workers
import time
def getdd(layer):
''' Get attributes names and formats for different gpkg layers
'''
# # attributes name and data types (in addition to geometries)
if layer == "perimeter":
dd = {
"n_pixels": "int", # number of total pixels
"n_newpixels": "int", # number of new pixels
"farea": "float", # fire size
"fperim": "float", # fire perimeter length
"flinelen": "float", # active fire front line length
"duration": "float", # fire duration
"pixden": "float", # fire pixel density
"meanFRP": "float", # mean FRP of the new fire pixels
"t": "datetime64",
}
elif layer == "fireline":
dd = {
"t": "datetime64",
}
elif layer == "newfirepix":
dd = {
"t": "datetime64",
}
elif layer == "nfplist":
dd = {
"x": "float",
"y": "float",
"frp": "float",
"DS": "float",
"DT": "float",
"ampm": "str",
"datetime": "datetime64",
"sat": "str",
}
return dd
def find_largefires(allfires, falim=4):
""" Given an allfires object, extract large fires to be used for single fire
recording. Only active fires or sleepers are considered.
Parameters
----------
allfires : Allfires obj
the allfires object at a given time step
falim : float
the area threshold (km) for large fire
Returns
-------
large_ids : list
the list of large fire IDs
"""
large_ids = [
fid
for fid in (allfires.fids_active + allfires.fids_sleeper)
if allfires.fires[fid].farea > falim
]
return large_ids
def find_mergefires_ct(allfires, fid):
""" Find fires that are merged to fire (fid) at time t and started before t
Parameters
----------
allfires : Allfires obj
the allfires object at a given time step
fid : int
the target fire ID
t : tuple (y,m,d,ampm)
the target merging time
Returns
-------
fids_m : list
the list of fire IDs that are merged to fire (fid) at time t
"""
t = allfires.t
# fids_m = list(sorted([h[0] for h in allfires.heritages if
# ((allfires.fires[h[0]].t_ed == t) & (allfires.fires[h[0]].t_st != t)
# & (h[1] == fid))]))
fids_m = []
for h in allfires.heritages:
if h[1] == fid:
if h[0] in allfires.fids:
f_m = allfires.fires[h[0]]
if (f_m.t_ed == t) & (f_m.t_st != t):
fids_m.append(h[0])
fids_m = list(sorted(fids_m))
return fids_m
def merge_fires(gdf_1d, fid, t, sfkeys):
""" merge fire perimeters of all fires with the same merge id
Parameters
----------b
gdf : geopandas DataFrame
the gdf containing all entries that should be merged
fid: the mergeid of the fire
Returns
-------
gdf_diss : geopandas DataFrame
the gdf containing a merged geometry and summary stats
"""
from datetime import date
import FireObj, FireTime
# dissolve the dataframe
gdf_1d["mergeid"] = fid
gdf_diss = gdf_1d.dissolve(by="mergeid")
# gdf_sf.loc[t_m,'geometry'] = gdf_sf.loc[t_m,'geometry'].union(gs_t_m['geometry'])
# replace some values with sums
if "n_pixels" in sfkeys:
gdf_diss.loc[fid, "n_pixels"] = sum(gdf_1d.n_pixels)
if "n_newpixels" in sfkeys:
gdf_diss.loc[fid, "n_newpixels"] = sum(gdf_1d.n_newpixels)
if "farea" in sfkeys:
gdf_diss.loc[fid, "farea"] = sum(gdf_1d.farea)
if "fperim" in sfkeys:
gdf_diss.loc[fid, "fperim"] = sum(gdf_1d.fperim)
if "flinelen" in sfkeys:
gdf_diss.loc[fid, "flinelen"] = sum(gdf_1d.flinelen)
if "t" in sfkeys:
gdf_diss.loc[fid, "t"] = FireTime.t2dt(t)
# weighted average computed for averages
if ("pixden" in sfkeys) & ("farea" in sfkeys):
gdf_1d = gdf_1d.assign(
pixweigh=gdf_1d["pixden"] * gdf_1d["farea"]
) ## IS THIS CORRECT?
gdf_diss.loc[fid, "pixden"] = sum(gdf_1d.pixweigh) / sum(gdf_1d.farea)
if ("meanFRP" in sfkeys) & ("n_pixels" in sfkeys):
gdf_1d = gdf_1d.assign(FRPweigh=gdf_1d["meanFRP"] * gdf_1d["n_pixels"])
gdf_diss.loc[fid, "meanFRP"] = sum(gdf_1d.FRPweigh) / sum(gdf_1d.n_pixels)
# here need some column dropping...
gdf_diss = gdf_diss.reset_index().drop(columns="mergeid")
return gdf_diss
def make_sf(t, regnm, layer, fids_m, fid):
""" At a given time step, create single row DataFrame for a target fire fid
- read snapshot gpkg files for the time step (t, regnm, layer)
- extract records (sfkeys) for target fire and fires merged to it (fids_m)
- merge the extracted records
- create gdf ready for making single fire time series
Parameters
----------
t : tuple, (int,int,int,str)
the year, month, day and 'AM'|'PM' of time
regnm : str
the study region name (used for reading previous day's data)
fids_m : list
the list of fire IDs needed to merge (1-element list is ok)
sfkeys : list
the attributes (geometry excluded) used for making single fire time series
Returns
-------
gdf_1d : Geopandas DataFrame
the 1-row gdf for the single fire
"""
import FireIO, FireTime
import pandas as pd
import geopandas as gpd
from FireConsts import epsg
dd = getdd(layer)
sfkeys = list(dd.keys())
# extract rows for fires merged to the target fire
gdf = FireIO.load_gpkgobj(
t, regnm, layer=layer
) # read daily gdf: active and sleeper only
# extract rows with fireID in fids_m only
if gdf is None:
return None
idx = [i for i in fids_m if i in list(gdf.index)]
if len(idx) == 0: # if no rows satistying condition, return None
return None
gdf_1d = gdf.loc[idx] # extract all fires merged to fid
gdf_1d = gdf_1d[
sfkeys + ["geometry"]
] # drop some columns not used in single fire gpkg
gdf_1d = gdf_1d.reset_index().drop(columns="fireID")
# if there are multiple rows (fires), merge them
if len(gdf_1d) > 1:
gdf_1d = merge_fires(gdf_1d, fid, t, sfkeys)
# # make sure the fireID is correct (this is needed to merge all fires)
# gdf_1d['fireID'] = fid
# # change index to date; maybe no need to drop FireID?
# gdf_1d.index = [FireTime.t2dt(t)]
return gdf_1d
def make_sf_nfplist(allfires, t, regnm, fids):
""" At a given time step, create single row DataFrame for all newly detected
pixels associated with fires fids.
Parameters
----------
t : tuple, (int,int,int,str)
the year, month, day and 'AM'|'PM' of time
regnm : str
the study region name (used for reading previous day's data)
fids : list
the list of fire IDs needed to merge (1-element list is ok)
sfkeys : list
the attributes (geometry excluded) used for making single fire time series
Returns
-------
gdf_1d : Geopandas DataFrame
the 1-row gdf for the single fire
"""
import FireIO, FireTime
import pandas as pd
import geopandas as gpd
from FireConsts import epsg
dd = getdd('nfplist')
sfkeys = list(dd.keys())
if t != allfires.t:
allfires = FireIO.load_fobj(t, regnm, activeonly=False)
# record all nfps for all fires with fids to make nfplist at t
gdf_1d = None
for fid in fids:
if fid in allfires.fids_valid: # only record newpixels for valid fires
f = allfires.fires[fid]
plist = []
for p in f.newpixels:
p_attrs = []
for k in sfkeys:
p_attrs.append(getattr(p, k))
plist.append(p_attrs)
if len(plist) > 0:
df = pd.DataFrame(plist)
df.columns = sfkeys
gdf_1f = gpd.GeoDataFrame(
df,
crs="epsg:" + str(epsg),
geometry=gpd.points_from_xy(df.x, df.y),
)
# also add t variable (detection 12-hourly time step)
gdf_1f['t'] = FireTime.t2dt(t)
if gdf_1d is None:
gdf_1d = gdf_1f
else:
gdf_1d = gdf_1d.append(gdf_1f)
del allfires
return gdf_1d
def make_sfts_1f(allfires,f, fid, fids_m, regnm, layer="perimeter"):
""" create the single large fire gpkg file at time t.
In this approximate approach, the snapshots for fid between t_st and t_ed are
extracted and concategated. In addition, the snapshots for fires merged to
this fire (with heritage target as fid) are also added (except for the t_ed
when the fire with fid already contains the contributions from these merged
fires).
Parameters
----------
allfires : Allfires obj
the allfires object at a given time step
fid : int
the target fire ID
regnm : str
the study region name (used for reading previous day's data)
Returns
-------
gdf_all : Geopandas DataFrame
the full time series gdf for the single fire
"""
import FireTime, FireIO
# loop over all merged fires
endloop = False # flag to control the ending of the loop
t = list(f.t_st) # t is the time (year,month,day,ampm) for each step
gdf_all = None
while endloop == False:
if layer == 'nfplist':
gdf_1d = make_sf_nfplist(allfires, t, regnm, fids_m+[fid])
else:
gdf_1d = make_sf(t, regnm, layer, fids_m+[fid], fid)
# append daily row to gdf_all
# if FireTime.t_dif(t, f.t_st) == 0:
if (gdf_1d is not None):
if (gdf_all is None):
gdf_all = gdf_1d
else:
gdf_all = gdf_all.append(gdf_1d, ignore_index=True)
# - if t reaches ted, set endloop to True to stop the loop
if FireTime.t_dif(t, f.t_ed) == 0:
endloop = True
# - update t with the next time stamp
t = FireTime.t_nb(t, nb="next")
return gdf_all
def update_sfts_1f(allfires, allfires_pt, fid, regnm, layer="perimeter"):
""" update the single large fire gpkg file at time t
Parameters
----------
allfires : Allfires obj
the allfires object at a given time step
fid : int
the target fire ID
regnm : str
the study region name (used for reading previous day's data)
Returns
-------
gdf_all : Geopandas DataFrame
the full time series gdf for the single fire
"""
import FireTime, FireIO
import geopandas as gpd
# the target single large fire and target time
f = allfires.fires[fid]
t = allfires.t
dd = getdd(layer)
sfkeys = list(dd.keys())
# try to read small fire file at previous time step (gdf_sf_pt)
t_pt = allfires_pt.t
gdf_sf_pt = FireIO.load_gpkgsfs(t_pt, fid, regnm, layer=layer)
# if no gdf_sf_pt, create historical time series using the make_sfts_1f()
# if the running is fast enough, no need to use the code in the 'else' part...
if gdf_sf_pt is None:
# find all fires merged to this fire at any time step
fids_m = list(sorted([h[0] for h in allfires.heritages if h[1] == fid]))
gdf_all = make_sfts_1f(allfires,f,fid, fids_m, regnm, layer=layer)
# when gdf_sf_pt is present, to save time, read it and add fires just merged at t
else:
# use gdf_sf_pt as basis, and only need to add changes at t and newly merged fires
gdf_all = gdf_sf_pt
# find all fires merged to this fire at present time step
fids_m = find_mergefires_ct(allfires, fid)
# loop over all merged fires and add to gdf_all
for fid_m in fids_m:
# create historical time series of all newly merged fires at t_pt
# using the same approach as the case of gdf_sf_pt==None
f_pt = allfires_pt.fires[fid_m]
fids_mm = list(sorted([h[0] for h in allfires_pt.heritages if h[1] == fid_m]))
gdf_all_m = make_sfts_1f(allfires_pt,f_pt, fid_m, fids_mm, regnm, layer=layer)
# combine all existing gdf_all_m
gdf_all = gdf_all.append(gdf_all_m, ignore_index=True)
# also add current fire record at present time time step (for fid at t only)
if layer == 'nfplist':
gdf_ct = make_sf_nfplist(allfires, t, regnm, [fid])
else:
gdf_ct = make_sf(t, regnm, layer, [fid], fid)
# for k,tp in dd.items():
# gdf_ct[k] = gdf_ct[k].astype(tp)
gdf_all = gdf_all.append(gdf_ct, ignore_index=True)
if gdf_all is None:
print('Warning gdf_all is None. Returning...')
return gdf_all
# 4. force the correct dtypes
for k, tp in dd.items():
gdf_all[k] = gdf_all[k].astype(tp)
if layer == 'nfplist':
gdf_all['t'] = gdf_all['t'].astype('datetime64')
# gdf_all = gdf_all.reset_index()
return gdf_all
def save_sfts_all(queue: multiprocessing.Queue, t, regnm, layers=["perimeter", "fireline", "newfirepix", "nfplist"]):
"""Wrapper to create and save gpkg files at a time step for all large fires
Parameters
----------
t : tuple, (int,int,int,str)
the year, month, day and 'AM'|'PM' of time
regnm : str
region name
"""
import FireTime, FireIO, FireObj
tstart = time.time()
# read allfires object
logger.info(f'Load allfires..')
allfires = FireIO.load_fobj(t, regnm, activeonly=False)
t_pt = FireTime.t_nb(t, nb="previous")
try:
# read allfires object at previous time step
logger.info(f'Load allfires_pt...')
allfires_pt = FireIO.load_fobj(t_pt, regnm, activeonly=False)
except:
allfires_pt = FireObj.Allfires(t_pt)
# find all large active fires and sleepers
logger.info(f'Finding largefires...')
large_ids = find_largefires(allfires)
# loop over all fires, and create/save gpkg files for each single fire
for fid in large_ids:
logger.info(f'Adding {fid} to queue')
queue.put([allfires, allfires_pt, fid, regnm, layers])
tend = time.time()
logger.info(f'Time sending to queue for timestep {t} with multiproc: {(tend-tstart)/60.} minutes')
def worker_save_sfts_1f(queue: multiprocessing.Queue):
"""pop off the queue and call `save_sfts_1f`
:param queue:
:return:
"""
while True:
payload = queue.get()
# check for poison pill
if payload is None:
break
# unpack
allfires, allfires_pt, fid, regnm, layers = payload
logger.info(f'[ WORKER {os.getpid()} ]: writing out LF={fid}')
save_sfts_1f(allfires, allfires_pt, fid, regnm, layers)
def save_sfts_1f(allfires, allfires_pt, fid, regnm, layers=["perimeter", "fireline", "newfirepix", "nfplist"]):
"""Wrapper to create and save gpkg files at a time step for all large fires
Parameters
----------
t : tuple, (int,int,int,str)
the year, month, day and 'AM'|'PM' of time
regnm : str
region name
"""
import FireIO
logger.info(f'Generating LF data for fid {fid}')
tstart = time.time()
f = allfires.fires[fid]
if "perimeter" in layers:
tstart = time.time()
gdf_fperim = update_sfts_1f(allfires, allfires_pt, fid, regnm, layer="perimeter")
tend = time.time()
logger.info(f"{(tend-tstart)/60.} minutes used for updating perimeter layer.")
tstart = time.time()
FireIO.save_gpkgsfs(allfires.t, fid, regnm, gdf_fperim=gdf_fperim)
tend = time.time()
logger.info(f"{(tend-tstart)/60.} minutes used for I/O data perimeter layer.")
if "fireline" in layers:
gdf_fline = update_sfts_1f(allfires,allfires_pt, fid, regnm, layer="fireline")
FireIO.save_gpkgsfs(allfires.t, fid, regnm, gdf_fline=gdf_fline)
if "newfirepix" in layers:
gdf_nfp = update_sfts_1f(allfires,allfires_pt, fid, regnm, layer="newfirepix")
FireIO.save_gpkgsfs(allfires.t, fid, regnm, gdf_nfp=gdf_nfp)
if "nfplist" in layers:
gdf_nfplist = update_sfts_1f(allfires,allfires_pt, fid, regnm, layer="nfplist")
FireIO.save_gpkgsfs(allfires.t, fid, regnm, gdf_nfplist=gdf_nfplist)
tend = time.time()
logger.info(f"{(tend-tstart)/60.} minutes used to save Largefire data for fid {fid}.")
def save_sfts_trng(
tst, ted, regnm, layers=["perimeter", "fireline", "newfirepix", "nfplist"]
):
"""Wrapper to create and save all gpkg files for a time period
Parameters
----------
tst : tuple, (int,int,int,str)
the year, month, day and 'AM'|'PM' at start time
ted : tuple, (int,int,int,str)
the year, month, day and 'AM'|'PM' at end time
regnm : str
region name
"""
import FireTime
# loop over all days during the period
endloop = False # flag to control the ending olf the loop
t = list(tst) # t is the time (year,month,day,ampm) for each step
queue = multiprocessing.Queue()
workers = []
for i in range(number_of_multi_proc_workers):
p = multiprocessing.Process(target=worker_save_sfts_1f, args=(queue,))
p.start()
workers.append(p)
while endloop == False:
print("Single fire saving", t)
logger.info('Single fire saving: '+str(t))
tstart = time.time()
# create and save all gpkg files at time t
try:
save_sfts_all(queue, t, regnm, layers=layers)
except Exception as exc:
logger.exception(exc)
tend = time.time()
logger.info(f"{(tend-tstart)/60.} minutes used to save Largefire data for this time.")
if FireTime.t_dif(t, ted) == 0:
endloop = True
# - update t with the next time stamp
t = FireTime.t_nb(t, nb="next")
# add poison pill to stop work
for i in range(number_of_multi_proc_workers):
queue.put(None)
# wait all writer workers
for p in workers:
p.join()
def combine_sfts(regnm,yr,addFRAP=False):
''' Combine all large fire time series to a gpkg data, with the option to add fire name from FRAP data
used for a large region
Parameters
----------
regnm : str
the name of the region
yr : int
year
addFRAP : bool
if set to true, add fire name/id from FRAP database (require FRAP data and AT_FRAP function)
'''
import FireIO, os
from AT import AT_FRAP
import geopandas as gpd
from glob import glob
import pandas as pd
from FireTime import dt_dif
strdir = FireIO.get_gpkgsfs_dir(yr,regnm)
if addFRAP:
vFRAP = AT_FRAP.getFRAPyr(yr)
if vFRAP is not None:
vFRAP.geometry = vFRAP.geometry.buffer(0)
# get a list of all fids
fids = []
for f in glob(strdir+'/*.gpkg'):
fid = int(os.path.basename(f).split('.')[0].split('_')[0][1:])
fids.append(fid)
# loop over all fids
gdf_perim_all, gdf_fline_all, gdf_nfp_all, gdf_nfplist_all = None, None, None, None
for fid in set(fids):
print(fid,end=',')
# for each fire, find the last gpkg file
fnmlast = sorted(glob(strdir+'/F'+str(fid)+'_*.gpkg'))[-1]
# read the data (four layers)
gdf_perim = FireIO.gpd_read_file(fnmlast,layer='perimeter').to_crs(epsg=4326)
gdf_fline = FireIO.gpd_read_file(fnmlast,layer='fireline').to_crs(epsg=4326)
gdf_nfp = FireIO.gpd_read_file(fnmlast,layer='newfirepix').to_crs(epsg=4326)
gdf_nfplist = FireIO.gpd_read_file(fnmlast,layer='nfplist').to_crs(epsg=4326)
# add fire ID to the gdf
gdf_perim['FireID'] = fid
gdf_fline['FireID'] = fid
gdf_nfp['FireID'] = fid
gdf_nfplist['FireID'] = fid
# add duration to fline, nfp, and nfplist
t0 = pd.to_datetime(gdf_perim.iloc[0].t)
gdf_fline['duration'] = pd.to_datetime(gdf_fline['t']).apply(lambda x: dt_dif(x,t0))
gdf_nfp['duration'] = pd.to_datetime(gdf_nfp['t']).apply(lambda x: dt_dif(x,t0))
gdf_nfplist['duration'] = pd.to_datetime(gdf_nfplist['t']).apply(lambda x: dt_dif(x,t0))
# add FRAP fire name and id
if addFRAP:
if vFRAP is not None:
gFEDS = gdf_perim.iloc[-1].geometry
FRAPid,FRAPfnm = AT_FRAP.get_FRAPidfnm_from_geometry(vFRAP,gFEDS,fid)
if FRAPid is not None:
gdf_perim['FRAPid'] = FRAPid
gdf_perim['FRAPfnm'] = FRAPfnm
gdf_fline['FRAPid'] = FRAPid
gdf_fline['FRAPfnm'] = FRAPfnm
gdf_nfp['FRAPid'] = FRAPid
gdf_nfp['FRAPfnm'] = FRAPfnm
gdf_nfplist['FRAPid'] = FRAPid
gdf_nfplist['FRAPfnm'] = FRAPfnm
else:
gdf_perim['FRAPid'] = -1
gdf_perim['FRAPfnm'] = ''
gdf_fline['FRAPid'] = -1
gdf_fline['FRAPfnm'] = ''
gdf_nfp['FRAPid'] = -1
gdf_nfp['FRAPfnm'] = ''
gdf_nfplist['FRAPid'] = -1
gdf_nfplist['FRAPfnm'] = ''
# combine all fids
if (gdf_perim_all is None):
gdf_perim_all = gdf_perim
gdf_fline_all = gdf_fline
gdf_nfp_all = gdf_nfp
gdf_nfplist_all = gdf_nfplist
else:
gdf_perim_all = gdf_perim_all.append(gdf_perim,ignore_index=True)
gdf_fline_all = gdf_fline_all.append(gdf_fline,ignore_index=True)
gdf_nfp_all = gdf_nfp_all.append(gdf_nfp,ignore_index=True)
gdf_nfplist_all = gdf_nfplist_all.append(gdf_nfplist,ignore_index=True)
# drop x and y columns for nfplist
gdf_nfplist_all = gdf_nfplist_all.drop(columns=['x','y'])
# save combined gdfs
fnmout = os.path.join(strdir,'largefires.gpkg')
gdf_perim_all.to_file(fnmout, driver="GPKG", layer="perimeter")
gdf_fline_all.to_file(fnmout, driver="GPKG", layer="fireline")
gdf_nfp_all.to_file(fnmout, driver="GPKG", layer="newfirepix")
gdf_nfplist_all.to_file(fnmout, driver="GPKG", layer="nfplist")
# return gdf_perim_all, gdf_fline_all, gdf_nfp_all, gdf_nfplist_all
def convert_sfts(regnm,yr,fids):
''' Convert a large fire time series to a gpkg data; usually used to process a single fire run
Parameters
----------
regnm : str
the name of the region
yr : int
year
fids : list of int
fire ids
'''
import FireIO, os
from AT import AT_FRAP
import geopandas as gpd
from glob import glob
import pandas as pd
from FireTime import dt_dif
strdir = FireIO.get_gpkgsfs_dir(yr,regnm)
# loop over all fids
gdf_perim_all, gdf_fline_all, gdf_nfp_all, gdf_nfplist_all = None, None, None, None
for fid in set(fids):
print(fid,end=',')
# for each fire, find the last gpkg file
fnmlast = sorted(glob(strdir+'/F'+str(fid)+'_*.gpkg'))[-1]
# read the data (four layers)
gdf_perim = FireIO.gpd_read_file(fnmlast,layer='perimeter').to_crs(epsg=4326)
gdf_fline = FireIO.gpd_read_file(fnmlast,layer='fireline').to_crs(epsg=4326)
gdf_nfp = FireIO.gpd_read_file(fnmlast,layer='newfirepix').to_crs(epsg=4326)
gdf_nfplist = FireIO.gpd_read_file(fnmlast,layer='nfplist').to_crs(epsg=4326)
# add fire ID to the gdf
gdf_perim['FireID'] = fid
gdf_fline['FireID'] = fid
gdf_nfp['FireID'] = fid
gdf_nfplist['FireID'] = fid
# add duration to fline, nfp, and nfplist
t0 = pd.to_datetime(gdf_perim.iloc[0].t)
gdf_fline['duration'] = pd.to_datetime(gdf_fline['t']).apply(lambda x: dt_dif(x,t0))
gdf_nfp['duration'] = pd.to_datetime(gdf_nfp['t']).apply(lambda x: dt_dif(x,t0))
gdf_nfplist['duration'] = pd.to_datetime(gdf_nfplist['t']).apply(lambda x: dt_dif(x,t0))
# combine all fids
if (gdf_perim_all is None):
gdf_perim_all = gdf_perim
gdf_fline_all = gdf_fline
gdf_nfp_all = gdf_nfp
gdf_nfplist_all = gdf_nfplist
else:
gdf_perim_all = gdf_perim_all.append(gdf_perim,ignore_index=True)
gdf_fline_all = gdf_fline_all.append(gdf_fline,ignore_index=True)
gdf_nfp_all = gdf_nfp_all.append(gdf_nfp,ignore_index=True)
gdf_nfplist_all = gdf_nfplist_all.append(gdf_nfplist,ignore_index=True)
# drop x and y columns for nfplist
gdf_nfplist_all = gdf_nfplist_all.drop(columns=['x','y'])
# save combined gdfs
fnmout = os.path.join(strdir,'largefires.gpkg')
gdf_perim_all.to_file(fnmout, driver="GPKG", layer="perimeter")
gdf_fline_all.to_file(fnmout, driver="GPKG", layer="fireline")
gdf_nfp_all.to_file(fnmout, driver="GPKG", layer="newfirepix")
gdf_nfplist_all.to_file(fnmout, driver="GPKG", layer="nfplist")
if __name__ == "__main__":
""" The main code to record time series of geojson data for a fire
"""
import time
t1 = time.time()
# set the start and end time
tst = (2020, 9, 5, "AM")
# ted=(2020,9,10,'PM')
ted = (2020, 11, 5, "PM")
# run creation
save_sfts_trng(tst, ted, regnm="Creek")
# save_sfts([2020, 9, 19, 'AM'],'Creek')
t2 = time.time()
print(f"{(t2-t1)/60.} minutes used to run code")