def create_figures():
"""Generate and save all relevant figures and text files."""
parser = argparse.ArgumentParser()
parser.add_argument('catalog1',
nargs='?',
type=str,
help='pick first catalog to download data from; to \
download data from all catalogs, use "preferred"; if \
using -sf, give catalog name')
parser.add_argument('catalog2',
nargs='?',
type=str,
help='pick second catalog to download data from; to \
download data from all catalogs, use "preferred"; if \
using -sf, give catalog name')
parser.add_argument('startyear',
nargs='?',
type=int,
help='pick starting year; if using -sf, give first \
year in catalog')
parser.add_argument('endyear',
nargs='?',
type=int,
help='pick end year (to get a single year of data, \
enter same year as startyear); if using -sf, give \
last year in catalog')
parser.add_argument('-mr',
'--magrange',
nargs=2,
type=float,
default=[-5, 12],
help='give the magnitude range for downloading data \
(default range is from -5 to 12)')
parser.add_argument('-sf',
'--specifyfiles',
nargs=2,
type=str,
help='specify two existing .csv files to use')
parser.add_argument('-fd',
'--forcedownload',
action='store_true',
help='forces downloading of data even if .csv file \
exists')
parser.add_argument('-nm',
'--nomatches',
action='store_false',
help='do not include list of matching events in HTML \
report')
args = parser.parse_args()
minmag, maxmag = args.magrange
if args.specifyfiles is None:
if not args.catalog1:
sys.stdout.write('No first catalog specified. Exiting...\n')
sys.exit()
elif not args.catalog2:
sys.stdout.write('No second catalog specified. Exiting...\n')
sys.exit()
elif not args.startyear:
sys.stdout.write('No starting year specified. Exiting...\n')
sys.exit()
elif not args.endyear:
sys.stdout.write('No ending year specified. Exiting...\n')
sys.exit()
cat1, cat2 = args.catalog1.lower(), args.catalog2.lower()
startyear, endyear = map(int, [args.startyear, args.endyear])
download = args.forcedownload
dirname = '%s-%s%s-%s' % (cat1, cat2, startyear, endyear)
if download:
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf1 = qcu.get_data(cat1,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
datadf2 = qcu.get_data(cat2,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
else:
# Python 2
try:
try:
datadf1 = pd.read_csv('%s/%s%s-%s.csv' %
(dirname, cat1, startyear, endyear))
datadf2 = pd.read_csv('%s/%s%s-%s.csv' %
(dirname, cat2, startyear, endyear))
except IOError:
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf1 = qcu.get_data(cat1,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
datadf2 = qcu.get_data(cat2,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
# Python 3
except:
try:
datadf1 = pd.read_csv('%s/%s%s-%s.csv' %
(dirname, cat1, startyear, endyear))
datadf2 = pd.read_csv('%s/%s%s-%s.csv' %
(dirname, cat2, startyear, endyear))
except FileNotFoundError:
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf1 = qcu.get_data(cat1,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
datadf2 = qcu.get_data(cat2,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
else:
from shutil import copy2
sfcat1, sfcat2 = args.specifyfiles
cat1, cat2 = args.catalog1, args.catalog2
dirname = '%s-%s%s-%s' % (cat1, cat2, args.startyear, args.endyear)
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf1, datadf2 = pd.read_csv(sfcat1), pd.read_csv(sfcat2)
try:
copy2(sfcat1, dirname)
copy2(sfcat2, dirname)
except shutil.SameFileError:
pass
if len(datadf1) == 0:
sys.stdout.write(('%s catalog has no data available for that time '
'period. Quitting...\n') % cat1.upper())
sys.exit()
if len(datadf2) == 0:
sys.stdout.write(('%s catalog has no data available for that time '
'period. Quitting...\n') % cat2.upper())
sys.exit()
cat1, cat2 = cat1.upper(), cat2.upper()
os.chdir(dirname)
basic_cat_sum(datadf1, cat1, dirname)
basic_cat_sum(datadf2, cat2, dirname)
datadf1.loc[:, 'convtime'] = [
' '.join(x.split('T')) for x in datadf1['time'].tolist()
]
datadf1.loc[:, 'convtime'] = datadf1['convtime'].astype('datetime64[ns]')
datadf1.loc[:, 'time'] = [qcu.to_epoch(x) for x in datadf1['time']]
datadf2.loc[:, 'convtime'] = [
' '.join(x.split('T')) for x in datadf2['time'].tolist()
]
datadf2.loc[:, 'convtime'] = datadf2['convtime'].astype('datetime64[ns]')
datadf2.loc[:, 'time'] = [qcu.to_epoch(x) for x in datadf2['time']]
datadf1, datadf2 = qcu.trim_times(datadf1, datadf2)
cat1ids, cat2ids, newcat1, newcat2 = match_events(datadf1, datadf2,
dirname)
if len(cat1ids) == 0:
sys.stdout.write('*** No matching events found ***\n')
comp_criteria(datadf1, cat1, cat1ids, datadf2, cat2, cat2ids, dirname)
#find_closest(datadf1, cat1, cat1ids, datadf2, dirname)
map_events(newcat1, cat1, newcat2, cat2, cat1ids, cat2ids, dirname)
map_unique_events(datadf1, cat1, cat1ids)
map_unique_events(datadf2, cat2, cat2ids)
make_az_dist(newcat1, cat1, newcat2, cat2, cat1ids, cat2ids, dirname)
compare_params(newcat1, cat1, newcat2, cat2, cat1ids, cat2ids, 'mag',
dirname)
compare_params(newcat1, cat1, newcat2, cat2, cat1ids, cat2ids, 'depth',
dirname)
make_diff_hist(newcat1,
newcat2,
cat1ids,
cat2ids,
'time',
0.5,
dirname,
xlabel='%s-%s time differences (sec)' %
(cat1.upper(), cat2.upper()))
make_diff_hist(newcat1,
newcat2,
cat1ids,
cat2ids,
'mag',
0.1,
dirname,
xlabel='%s-%s magnitude differences' %
(cat1.upper(), cat2.upper()))
make_diff_hist(newcat1,
newcat2,
cat1ids,
cat2ids,
'depth',
2,
dirname,
xlabel='%s-%s depth differences (km)' %
(cat1.upper(), cat2.upper()))
make_diff_hist(newcat1,
newcat2,
cat1ids,
cat2ids,
'distance',
2,
dirname,
xlabel='%s-%s distances (km)' %
(cat1.upper(), cat2.upper()))
return dirname, args.nomatches
def create_figures():
"""Generate and save all relevant figures and text files."""
parser = argparse.ArgumentParser()
parser.add_argument('catalog',
nargs='?',
type=str,
help='pick which catalog to download data from; to \
download data from all catalogs, use "preferred"')
parser.add_argument('startyear',
nargs='?',
type=int,
help='pick starting year')
parser.add_argument('endyear',
nargs='?',
type=int,
help='pick end year (to get a single year of data, \
enter same year as startyear)')
parser.add_argument('-mr',
'--magrange',
type=float,
nargs=2,
default=[-5, 12],
help='give the magnitude range for downloading data \
(default range is from -5 to 12)')
parser.add_argument('-tw',
'--timewindow',
type=float,
default=2,
help='change time window for finding duplicates \
(default is 2 seconds)')
parser.add_argument('-dw',
'--distwindow',
type=float,
default=15,
help='change distance window for finding duplicates \
(default is 15 kilometers)')
parser.add_argument('-sf',
'--specifyfile',
type=str,
help='specify existing .csv file to use')
parser.add_argument('-fd',
'--forcedownload',
action='store_true',
help='forces downloading of data even if .csv file \
exists')
args = parser.parse_args()
minmag, maxmag = args.magrange
if args.specifyfile is None:
if not args.catalog:
sys.stdout.write('No catalog specified. Exiting...\n')
sys.exit()
elif not args.startyear:
sys.stdout.write('No starting year specified. Exiting...\n')
sys.exit()
elif not args.endyear:
sys.stdout.write('No ending year specified. Exiting...\n')
sys.exit()
catalog = args.catalog.lower()
startyear, endyear = map(int, [args.startyear, args.endyear])
download = args.forcedownload
dirname = '%s%s-%s' % (catalog, startyear, endyear) if catalog else\
'preferred%s-%s' % (startyear, endyear)
if download:
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf = qcu.get_data(catalog,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
else:
# Python 2
try:
try:
datadf = pd.read_csv('%s/%s.csv' % (dirname, dirname))
except IOError:
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf = qcu.get_data(catalog,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
# Python 3
except:
try:
datadf = pd.read_csv('%s/%s.csv' % (dirname, dirname))
except FileNotFoundError:
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf = qcu.get_data(catalog,
dirname,
startyear=startyear,
endyear=endyear,
minmag=minmag,
maxmag=maxmag)
else:
from shutil import copy2
dirname = '.'.join(args.specifyfile.split('.')[:-1])
try:
os.makedirs(dirname)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
datadf = pd.read_csv(args.specifyfile)
copy2(args.specifyfile, dirname)
if len(datadf) == 0:
sys.stdout.write(('Catalog has no data available for that time period.'
' Quitting...\n'))
sys.exit()
timewindow = args.timewindow
distwindow = args.distwindow
datadf = datadf.sort_values(by='time').reset_index(drop=True)
datadf.loc[:, 'ms'] = datadf['time'].str[-4:-1].astype('float')
os.chdir(dirname)
dup1, dup2 = list_duplicates(datadf,
dirname,
timewindow=timewindow,
distwindow=distwindow)
basic_cat_sum(datadf, dirname, dup1, dup2, timewindow, distwindow)
largest_ten(datadf, dirname)
# generate figures
map_detecs(datadf, dirname, title='Detection locations')
map_detecs(datadf, dirname, mindep=50, title='Detections deeper than 50km')
map_detec_nums(datadf, dirname, title='Detection density')
make_hist(datadf,
'mag',
0.1,
dirname,
xlabel='Magnitude',
title='Magnitude histogram')
make_hist(datadf,
'depth',
1,
dirname,
xlabel='Depth (km)',
title='Depth histogram')
make_hist(datadf,
'depth',
0.5,
dirname,
maxval=20,
xlabel='Depth (km)',
title='Zoomed depth histogram')
make_hist(datadf,
'ms',
20,
dirname,
xlabel='Milliseconds',
title='Histogram of milliseconds')
make_time_hist(datadf, 'hour', dirname, title='Events per Hour of the Day')
make_time_hist(datadf, 'day', dirname, title='Events per Day')
graph_time_sep(datadf, dirname)
cat_mag_comp(datadf, dirname)
graph_mag_time(datadf, dirname)
cumul_moment_release(datadf, dirname)
graph_event_types(datadf, dirname)
cat_dup_search(datadf, dirname)
med_mag(datadf, dirname)
graph_mag_count(datadf, dirname)
return dirname