def create_storm_objects(self):
last_water_index, last_air_index, latest_change = -1, -1, -1
for x in range(0, len(self.sea_fnames)):
if self.sea_fnames[x] != '':
last_water_index = x
if self.air_fnames[x] != '':
last_air_index = x
if (last_water_index > -1 and last_air_index > -1) and \
(last_water_index > latest_change or last_air_index > latest_change):
so = StormOptions()
so.sea_fname = self.sea_fnames[last_water_index]
so.air_fname = self.air_fnames[last_air_index]
so.get_meta_data()
so.get_air_meta_data()
so.get_raw_water_level()
so.get_surge_water_level()
so.test_water_elevation_below_sensor_orifice_elvation()
so.get_wave_water_level()
self.storm_objects.append(so)
latest_change = x
elif last_air_index > -1 and last_air_index > latest_change:
so = StormOptions()
so.air_fname = self.air_fnames[last_air_index]
so.get_air_meta_data()
so.get_air_time()
so.get_raw_air_pressure()
self.storm_objects.append(so)
latest_change = x
def process_files(args):
so = StormOptions()
so.air_fname = args.air_fname
so.sea_fname = args.sea_fname
#check to see if the correct type of files were uploaded
if so.check_file_types() == False:
return 3
so.wind_fname = None
so.format_output_fname(args.output_fname)
so.timezone = args.tz_info
so.daylight_savings = args.daylight_savings
if args.baro_y_min is not None:
so.baroYLims.append(args.baro_y_min)
so.baroYLims.append(args.baro_y_max)
if args.wl_y_min is not None:
so.wlYLims.append(args.wl_y_min)
so.wlYLims.append(args.wl_y_max)
#check to see if the time series of the water and air file overlap
overlap = so.time_comparison()
#if there is no overlap
if overlap == 2:
return 4
try:
snc = Storm_netCDF()
so.netCDF['Storm Tide with Unfiltered Water Level'] = Bool(False)
so.netCDF['Storm Tide Water Level'] = Bool(True)
snc.process_netCDFs(so)
scv = StormCSV()
so.csv['Storm Tide Water Level'] = Bool(True)
so.csv['Atmospheric Pressure'] = Bool(True)
scv.process_csv(so)
sg = StormGraph()
so.graph[
'Storm Tide with Unfiltered Water Level and Wind Data'] = Bool(
False)
so.graph['Storm Tide with Unfiltered Water Level'] = Bool(True)
so.graph['Storm Tide Water Level'] = Bool(True)
so.graph['Atmospheric Pressure'] = Bool(True)
sg.process_graphs(so)
except:
return 5
#will be either 0 for perfect overlap or 1 for slicing some data
return overlap
last_date = mdates.date2num(last_date)
return np.linspace(first_date, last_date, len(time))
class Bool(object):
def __init__(self, val):
self.val = val
def get(self):
return self.val
if __name__ == '__main__':
so = StormOptions()
so.clip = False
so.air_fname = 'NCDAR00003_1511478_stormtide_unfiltered.nc'
so.sea_fname = 'NCDAR00003_1511478_stormtide_unfiltered.nc'
so.int_units = False
so.high_cut = 1.0
so.low_cut = 0.045
so.from_water_level_file = True
so.timezone = 'GMT'
so.daylight_savings = False
ss = StormStatistics()
for y in so.statistics:
so.statistics[y] = Bool(False)
def multi_water_level(self, path, title, mode='Raw'):
self.create_header()
ax = self.figure.add_subplot(self.grid_spec[1, 0:])
pos1 = ax.get_position() # get the original position
pos2 = [pos1.x0, pos1.y0, pos1.width, pos1.height + .06]
ax.set_position(pos2) # set a new position
#create the second graph title
first_title = "%s %s Water Level Time Series Comparison" % (title,
mode)
titleText = ax.text(0.5, 1.065,first_title, \
va='center', ha='center', transform=ax.transAxes)
ax.set_ylabel('Water Level in Feet')
ax.set_xlabel('Timezone GMT')
#plot major grid lines
ax.grid(b=True, which='major', color='grey', linestyle="-")
#x axis formatter for dates (function format_date() below)
ax.xaxis.set_major_formatter(ticker.FuncFormatter(self.format_date))
legend_list, label_list = [], []
air, sea, sea_file, air_file = False, False, '', ''
file_types = ['.nc']
for root, sub_folders, files in os.walk(path):
for file_in_root in files:
index = file_in_root.rfind('.')
if file_in_root[index:] in file_types:
file = ''.join([root, '\\', file_in_root])
try:
nc.get_pressure(file)
sea = True
sea_file = file
except:
try:
nc.get_air_pressure(file)
air = True
air_file = file
except:
pass
if sea and air:
sea, air = False, False
so = StormOptions()
so.air_fname = air_file
so.sea_fname = sea_file
so.timezone = 'GMT'
so.daylight_savings = False
so.get_meta_data()
so.get_air_meta_data()
so.get_raw_water_level()
so.get_surge_water_level()
so.test_water_elevation_below_sensor_orifice_elvation()
so.get_wave_water_level()
first_date = unit_conversion.convert_ms_to_date(
so.sea_time[0], pytz.UTC)
last_date = unit_conversion.convert_ms_to_date(
so.sea_time[-1], pytz.UTC)
first_date = mdates.date2num(first_date)
last_date = mdates.date2num(last_date)
self.time_nums = np.linspace(first_date, last_date,
len(so.sea_time))
lat = nc.get_variable_data(sea_file, 'latitude')
lon = nc.get_variable_data(sea_file, 'longitude')
stn_id = nc.get_global_attribute(
sea_file, 'stn_instrument_id')
stn_station = nc.get_global_attribute(
sea_file, 'stn_station_number')
if mode == 'Surge':
p1, = ax.plot(self.time_nums,
so.surge_water_level,
alpha=.5)
legend_list.append(p1)
label_list.append('STN Site ID: %s, STN Instrument ID: %s, Lat: %s, Lon: %s' \
%(stn_id, stn_station, lat, lon))
if mode == 'Wave':
p1, = ax.plot(self.time_nums,
so.wave_water_level,
alpha=.5)
legend_list.append(p1)
label_list.append('STN Site ID: %s, STN Instrument ID: %s, Lat: %s, Lon: %s' \
%(stn_id, stn_station, lat, lon))
if mode == 'Raw':
p1, = ax.plot(self.time_nums,
so.raw_water_level,
alpha=.5)
legend_list.append(p1)
label_list.append('STN Site ID: %s, STN Instrument ID: %s, Lat: %s, Lon: %s' \
%(stn_id, stn_station, lat, lon))
legend = ax.legend(legend_list,label_list
, \
bbox_to_anchor=(.95, 1.355), loc=1, borderaxespad=0.0, prop={'size':10.3},frameon=False,numpoints=1, \
title="EXPLANATION")
legend.get_title().set_position((-340, 0))
plt.savefig(''.join([title, mode]))