def compare_database_precip():
''' Compare 'gold' and 'test' precip. '''
value = 'precip_z'
result = True
gold = collect(gold_cnx, plotorder, basins, start_date, end_date, value,
run_name_gold, edges, 'sum')
test = collect(test_cnx, plotorder_test, basins_test, start_date, end_date,
value, run_name_test, edges, 'sum')
test_result = gold[plotorder].values - test[plotorder_test].values
if np.sum(test_result) != 0:
result = False
gold = collect(gold_cnx, plotorder, basins, start_date, end_date, value,
run_name_gold, 'total', 'sum')
test = collect(test_cnx, plotorder_test, basins_test, start_date, end_date,
value, run_name_test, 'total', 'sum')
test_result = gold[plotorder].values - test[plotorder_test].values
if np.sum(test_result) != 0:
result = False
return result
def compare_database_depth():
''' Compare 'gold' and 'test' depth. '''
value = 'depth'
result = True
gold = collect(gold_cnx, plotorder, basins, start_date, end_date, value,
run_name_gold, edges, 'end')
test = collect(test_cnx, plotorder_test, basins_test, start_date, end_date,
value, run_name_test, edges, 'end')
test_result = gold[plotorder].values - test[plotorder_test].values
if np.sum(test_result) != 0:
result = False
print('\nFailed depth\ngold:\n{}\ntest:\n{}\n'.format(gold, test))
gold = collect(gold_cnx, plotorder, basins, start_date, end_date, value,
run_name_gold, 'total', 'end')
test = collect(test_cnx, plotorder_test, basins_test, start_date, end_date,
value, run_name_test, 'total', 'end')
test_result = gold[plotorder].values - test[plotorder_test].values
if np.sum(test_result) != 0:
result = False
print('\nFailed depth total\ngold:\n{}\ntest:\n{}\n'.format(
gold, test))
return result
def compare_database_unavail():
''' Compare 'gold' and 'test' swe_unavail. '''
value = 'swe_unavail'
result = True
gold = collect(gold_cnx, plotorder, basins, start_date, end_date, value,
run_name_gold, edges, 'end')
test = collect(test_cnx, plotorder_test, basins_test, start_date, end_date,
value, run_name_test, edges, 'end')
test_result = gold[plotorder].values - test[plotorder_test].values
if np.sum(test_result) != 0:
result = False
return result
def check_gold_results():
''' Check database 'gold' values '''
value = 'swe_vol'
gold_values = [3.075, 13.63, 9.543, 0.494]
gold = collect(gold_cnx, plotorder, basins, start_date, end_date, value,
run_name_gold, edges, 'end')
result = True
for ix, edge in enumerate(edges):
if (gold.iloc[ix, 0] - gold_values[ix]) != 0.0:
result = False
return result
def figures(cfg, process, db):
""" Set up and call snowav figures. See CoreConfig.ini and README.md for
more on config options and use.
swe_volume() must be called before cold_content() if you want to use
the same ylims for each.
Args
------
cfg: config class
process: process class
db: database class
"""
args = {
'report_start': cfg.report_start.date().strftime("%Y-%-m-%-d"),
'report_date': cfg.report_date.date().strftime("%Y-%-m-%-d"),
'run_name': cfg.run_name,
'start_date': cfg.start_date,
'end_date': cfg.end_date,
'directory': cfg.directory,
'figs_path': cfg.figs_path,
'edges': cfg.edges,
'plotorder': cfg.plotorder,
'labels': cfg.labels,
'lims': plotlims(cfg.plotorder),
'masks': cfg.masks,
'figsize': cfg.figsize,
'dpi': cfg.dpi,
'depthlbl': cfg.depthlbl,
'vollbl': cfg.vollbl,
'elevlbl': cfg.elevlbl,
'dplcs': cfg.dplcs,
'barcolors': cfg.barcolors,
'xlims': cfg.xlims,
'depth_clip': cfg.depth_clip,
'percent_min': cfg.clims_percent[0],
'percent_max': cfg.clims_percent[1],
'basins': cfg.basins,
'wy': cfg.wy,
'flag': False,
'flt_flag': cfg.flt_flag
}
if cfg.flt_flag:
args['flight_dates'] = cfg.flight_diff_dates
fig_names = {}
connector = cfg.connector
edges_str = [str(x) for x in list(cfg.edges)] # + ['total']
##########################################################################
# For each figure, collect 2D array image, by-elevation #
# DataFrame, and set any figure-specific args inputs #
##########################################################################
if cfg.flt_flag:
names, df = flt_image_change(cfg.update_file,
cfg.update_numbers,
cfg.end_date,
cfg.flight_outputs,
cfg.pre_flight_outputs,
cfg.masks,
cfg.flt_image_change_clims,
cfg.barcolors,
cfg.edges,
cfg.connector,
cfg.plotorder,
cfg.wy,
cfg.depth_factor,
cfg.basins,
cfg.run_name,
cfg.figsize,
cfg.depthlbl,
cfg.elevlbl,
cfg.vollbl,
cfg.dplcs,
cfg.figs_path,
dpi=cfg.dpi,
logger=cfg._logger)
if len(names) == 0:
cfg.flt_flag = False
else:
cfg.assign_vars({'flight_diff_fig_names': names})
cfg.assign_vars({'flight_delta_vol_df': df})
if cfg.swi_flag:
image = np.zeros_like(cfg.outputs['swi_z'][0])
for n in range(cfg.ixs, cfg.ixe):
image = image + cfg.outputs['swi_z'][n] * cfg.depth_factor
params = {
Results: [('date_time', 'ge', cfg.start_date),
('date_time', 'le', cfg.end_date),
('variable', 'eq', 'swi_vol'),
('run_id', 'eq', cfg.run_id), ('value', 'ge', 0),
('elevation', 'gt', '0')],
}
df = db.query(params)
df = df.groupby('elevation').sum()
df.rename(columns={'value': cfg.plotorder[0]}, inplace=True)
df = df[cfg.plotorder].reindex(edges_str)
title = 'Accumulated SWI\n{} to {}'.format(args['report_start'],
args['report_date'])
swi(cfg.masks,
image,
df,
cfg.plotorder,
plotlims(cfg.plotorder),
cfg.edges,
cfg.labels,
cfg.barcolors,
cfg.vollbl,
cfg.elevlbl,
cfg.depthlbl,
cfg.clims_percent,
title,
cfg.figsize,
cfg.figs_path,
cfg.swi_volume_fig_name,
cfg.dplcs,
cfg.xlims,
dpi=200,
logger=None)
if cfg.image_change_flag:
image = (cfg.outputs['swe_z'][cfg.ixe] -
cfg.outputs['swe_z'][cfg.ixs]) * cfg.depth_factor
start = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['start_date'], 'swe_vol',
args['run_name'], args['edges'], 'end')
end = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'swe_vol',
args['run_name'], args['edges'], 'end')
df = end - start
title = 'Change in SWE Depth\n{} to {}'.format(args['report_start'],
args['report_date'])
image_change(cfg.masks,
image,
df,
cfg.plotorder,
plotlims(cfg.plotorder),
cfg.edges,
cfg.labels,
cfg.barcolors,
cfg.clims_percent,
cfg.vollbl,
cfg.elevlbl,
cfg.depthlbl,
cfg.xlims,
cfg.figsize,
title,
cfg.dplcs,
cfg.figs_path,
cfg.volume_change_fig_name,
dpi=cfg.dpi,
logger=cfg._logger)
if cfg.swe_volume_flag:
df = collect(connector, cfg.plotorder, cfg.basins, cfg.start_date,
cfg.end_date, 'swe_vol', cfg.run_name, cfg.edges, 'end')
image = cfg.outputs['swe_z'][cfg.ixe] * cfg.depth_factor
args['image'] = image
title = 'SWE {}'.format(args['report_date'])
swe_ylims = swe_volume(cfg.masks,
image,
df,
cfg.plotorder,
plotlims(cfg.plotorder),
cfg.edges,
cfg.labels,
cfg.barcolors,
cfg.clims_percent,
title,
cfg.depthlbl,
cfg.vollbl,
cfg.elevlbl,
cfg.xlims,
cfg.dplcs,
cfg.figs_path,
cfg.swe_volume_fig_name,
cfg.figsize,
dpi=cfg.dpi,
logger=cfg._logger)
else:
swe_ylims = None
if cfg.cold_content_flag:
swe = cfg.outputs['swe_z'][cfg.ixe]
image = cfg.outputs['coldcont'][cfg.ixe] * 0.000001
title = 'Cold Content {}'.format(args['report_date'])
df = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'swe_unavail',
args['run_name'], args['edges'], 'end')
cold_content(cfg.masks,
swe,
image,
df,
cfg.plotorder,
plotlims(cfg.plotorder),
cfg.edges,
cfg.labels,
cfg.barcolors,
title,
cfg.vollbl,
cfg.elevlbl,
cfg.figsize,
cfg.dplcs,
cfg.xlims,
cfg.figs_path,
cfg.cold_content_fig_name,
ylims=swe_ylims,
dpi=cfg.dpi,
logger=cfg._logger)
if cfg.density_flag:
image = cfg.outputs['density'][cfg.ixe]
title = 'Density {}'.format(args['report_date'])
density(cfg.masks,
image,
process.density,
cfg.plotorder,
plotlims(cfg.plotorder),
cfg.edges,
cfg.barcolors,
cfg.clims_percent,
title,
cfg.xlims,
cfg.figsize,
cfg.figs_path,
cfg.density_fig_name,
dpi=cfg.dpi,
logger=cfg._logger)
if cfg.basin_total_flag:
wy_start = datetime(cfg.wy - 1, 10, 1)
swi_summary = collect(connector, cfg.plotorder, cfg.basins, wy_start,
cfg.end_date, 'swi_vol', cfg.run_name, 'total',
'daily')
df_swe = collect(connector, cfg.plotorder, cfg.basins, wy_start,
cfg.end_date, 'swe_vol', cfg.run_name, 'total',
'daily')
df_swi = swi_summary.cumsum()
basin_total(cfg.plotorder,
cfg.labels,
cfg.end_date,
cfg.barcolors,
df_swi,
df_swe,
cfg.wy,
cfg.vollbl,
cfg.figsize,
cfg.figs_path,
cfg.basin_total_fig_name,
dpi=cfg.dpi,
flight_dates=cfg.flight_diff_dates,
logger=cfg._logger,
flight_flag=cfg.flt_flag)
if cfg.precip_depth_flag:
swi_image = np.zeros_like(cfg.outputs['swi_z'][0])
for n in range(cfg.ixs, cfg.ixe):
swi_image = swi_image + cfg.outputs['swi_z'][n] * cfg.depth_factor
swi_df = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'swi_z',
args['run_name'], args['edges'], 'sum')
precip_df = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'precip_z',
args['run_name'], args['edges'], 'sum')
rain_df = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'rain_z',
args['run_name'], args['edges'], 'sum')
precip_image = process.precip_total * cfg.depth_factor
rain_image = process.rain_total * cfg.depth_factor
title = 'Depth of SWI, Precipitation, and Rain\n{} to {}'.format(
args['report_start'], args['report_date'])
precip_depth(swi_image,
precip_image,
rain_image,
swi_df,
precip_df,
rain_df,
cfg.plotorder,
cfg.barcolors,
plotlims(cfg.plotorder),
cfg.masks,
cfg.edges,
cfg.labels,
cfg.clims_percent,
cfg.depthlbl,
cfg.elevlbl,
title,
cfg.xlims,
cfg.figs_path,
cfg.precip_fig_name,
logger=cfg._logger)
if cfg.diagnostics_flag:
wy_start = datetime(cfg.wy - 1, 10, 1)
precip = collect(connector, args['plotorder'], args['basins'],
wy_start, args['end_date'], 'precip_z',
args['run_name'], args['edges'], 'daily')
precip_per = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'precip_z',
args['run_name'], args['edges'], 'daily')
swe = collect(connector, args['plotorder'], args['basins'], wy_start,
args['end_date'], 'swe_z', args['run_name'],
args['edges'], 'daily')
swe_per = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'swe_z',
args['run_name'], args['edges'], 'daily')
rho = collect(connector, args['plotorder'], args['basins'], wy_start,
args['end_date'], 'density', args['run_name'],
args['edges'], 'daily')
rho_per = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'density',
args['run_name'], args['edges'], 'daily')
snow_line = collect(connector, args['plotorder'], args['basins'],
wy_start, args['end_date'], 'snow_line',
args['run_name'], args['edges'], 'daily')
snow_line_per = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'],
'snow_line', args['run_name'], args['edges'],
'daily')
evap_z = collect(connector, args['plotorder'], args['basins'],
wy_start, args['end_date'], 'evap_z',
args['run_name'], args['edges'], 'daily')
evap_z_per = collect(connector, args['plotorder'], args['basins'],
args['start_date'], args['end_date'], 'evap_z',
args['run_name'], args['edges'], 'daily')
snow_line_per = snow_line_per.fillna(0)
first_row = snow_line_per.iloc[[0]].values[0]
snow_line_per = snow_line_per.apply(lambda row: row - first_row,
axis=1)
args['snow_line'] = snow_line
args['snow_line_per'] = snow_line_per
swe = swe.fillna(0)
swe_per = swe_per.fillna(0)
first_row = swe_per.iloc[[0]].values[0]
swe_per = swe_per.apply(lambda row: row - first_row, axis=1)
evap_z = evap_z.fillna(0)
evap_z_per = evap_z_per.fillna(0)
first_row = evap_z_per.iloc[[0]].values[0]
evap_z_per = evap_z_per.apply(lambda row: row - first_row, axis=1)
rho = rho.fillna(0)
rho_per = rho_per.fillna(0)
first_row = rho_per.iloc[[0]].values[0]
rho_per = rho_per.apply(lambda row: row - first_row, axis=1)
precip = precip.fillna(0)
precip_per = precip_per.fillna(0)
precip = precip.cumsum()
precip_per = precip_per.cumsum()
first_row = precip_per.iloc[[0]].values[0]
precip_per = precip_per.apply(lambda row: row - first_row, axis=1)
if cfg.diag_basins is None:
args['dbasins'] = copy.deepcopy(cfg.plotorder)
else:
args['dbasins'] = cfg.diag_basins
args['precip'] = precip
args['precip_per'] = precip_per
args['swe'] = swe
args['swe_per'] = swe_per
args['evap_z'] = evap_z
args['evap_z_per'] = evap_z_per
args['density'] = rho
args['density_per'] = rho_per
args['elevlbl'] = cfg.elevlbl
diagnostics(args, cfg._logger)
if cfg.stn_validate_flag:
px = (1, 1, 1, 0, 0, 0, -1, -1, -1)
py = (1, 0, -1, 1, 0, -1, 1, 0, -1)
login = {
'user': cfg.wxdb_user,
'password': cfg.wxdb_password,
'host': cfg.wxdb_host,
'port': cfg.wxdb_port
}
flag = stn_validate(cfg.all_dirs,
cfg.val_lbls,
cfg.val_client,
args['end_date'],
args['wy'],
cfg.snow_x,
cfg.snow_y,
cfg.val_stns,
px,
py,
login,
args['figs_path'],
cfg.stn_validate_fig_name,
cfg.dem,
logger=cfg._logger,
elevlbl=cfg.elevlbl,
nash_sut_flag=cfg.nash_sut_flag)
if not flag:
cfg.stn_validate_flag = False
else:
# assign fig name to cfg for use in report.py
cfg.assign_vars({'stn_validate_fig_name': ''})
if cfg.point_values:
cfg._logger.debug(" Beginning point values processing for "
"{}".format(cfg.point_values_csv))
flag = True
xy = (cfg.snow_x, cfg.snow_y)
headings = ['name', 'latitude', 'longitude', cfg.point_values_heading]
end_date_str = cfg.end_date.date().strftime("%Y-%m-%d")
course_date = cfg.point_values_date.date().strftime('%Y-%m-%d')
basin_name = cfg.plotorder[0].split(" ")[0].lower()
pv_date = cfg.point_values_date
nsubplots = (cfg.point_values_settings[3] *
cfg.point_values_settings[4] - 1) - 1
while flag:
df = pd.read_csv(cfg.point_values_csv)
for head in headings:
if head not in df.columns.tolist():
cfg._logger.warn(' Required csv column "{}" not found, '
'exiting point values'.format(head))
if head == cfg.point_values_heading:
cfg._logger.warning(' User specified [validate] '
'point_values_heading: {} not '
'found'.format(head))
flag = False
if pv_date is None:
cfg._logger.info(' Value in [validate] point_values_date '
'being assigned to {}'.format(end_date_str))
pv_date = cfg.end_date
if pv_date < cfg.start_date or pv_date > cfg.end_date:
cfg._logger.info(' Value in [validate] point_values_date '
'outside of range in [run] start_date - '
'end_date, point_values_date being assigned '
'to: {}'.format(end_date_str))
idx = -1
else:
x = np.abs([date - pv_date for date in cfg.outputs['dates']])
idx = x.argmin(0)
model_date = cfg.outputs['dates'][idx].date().strftime('%Y-%m-%d')
for value in cfg.point_values_properties:
filename = '{}_pixel_{}_{}.csv'.format(basin_name, value,
end_date_str)
csv_name = os.path.abspath(
os.path.join(cfg.figs_path, filename))
if len(df.name.unique()) > nsubplots:
cfg._logger.warn(' Number of subplots in '
'point_values() may not fit well with '
'given settings, consider changing '
'nrows and/or ncols in [validate] '
'point_values_settings')
flag = False
if value == 'swe_z':
factor = cfg.depth_factor
elif value == 'depth':
factor = 39.37
else:
factor = 1
array = cfg.outputs[value][idx] * factor
df_res = point_values_csv(array, value, df, xy, csv_name,
model_date, cfg.plotorder[0],
cfg.point_values_heading,
cfg._logger)
if cfg.point_values_flag:
head = cfg.point_values_heading
if head in df.columns.tolist():
point_values_figures(array, value, df_res, cfg.dem,
cfg.figs_path, cfg.veg_type,
model_date, course_date,
cfg.point_values_settings,
cfg.pixel, head, cfg._logger)
else:
cfg._logger.warn(' [validate] point_values_heading: '
'{} not in csv, skipping figures '
''.format(cfg.point_values_heading))
cfg.point_values_flag = False
# if everything is successful, set to False at the end
flag = False
if cfg.compare_runs_flag:
args['variables'] = ['swe_vol', 'swi_vol']
if cfg.flt_flag:
args['flag'] = True
else:
args['flag'] = False
dict = {}
for var in args['variables']:
dict[var] = {}
for wy, run in zip(cfg.compare_run_wys, cfg.compare_run_names):
wy_start = datetime(wy - 1, 10, 1)
df = collect(connector, args['plotorder'][0], args['basins'],
wy_start, args['end_date'], var, run, 'total',
'daily')
if wy != cfg.wy:
adj = cfg.wy - wy
df.index = df.index + timedelta(days=365 * adj)
if var == 'swi_vol':
df = df.cumsum()
dict[var][run] = df
args['dict'] = dict
compare_runs(args, cfg._logger)
if cfg.inflow_flag:
wy_start = datetime(cfg.wy - 1, 10, 1)
swi_summary = collect(connector, args['plotorder'], args['basins'],
wy_start, args['end_date'], 'swi_vol',
args['run_name'], 'total', 'daily')
df_swi = swi_summary.cumsum()
args['swi_summary'] = df_swi
if cfg.inflow_data is None:
raw = pd.read_csv(cfg.summary_csv,
skiprows=1,
parse_dates=[0],
index_col=0)
args['inflow_summary'] = raw[cfg.basin_headings]
else:
args['inflow_summary'] = pd.read_csv(cfg.summary_csv,
parse_dates=[0],
index_col=0)
args['inflow_headings'] = cfg.inflow_headings
args['basin_headings'] = cfg.basin_headings
inflow(args, cfg._logger)
if cfg.write_properties is not None:
write_properties(args['end_date'],
cfg.connector,
args['plotorder'],
args['basins'],
datetime(cfg.wy - 1, 10, 1),
args['run_name'],
args['figs_path'],
cfg.write_properties,
vollbl=args['vollbl'],
logger=cfg._logger)
if cfg.inputs_fig_flag:
if cfg.mysql is not None:
dbs = 'sql'
else:
dbs = 'sqlite'
df = get_existing_records(connector, dbs)
df = df.set_index('date_time')
df.sort_index(inplace=True)
ivalue = {}
p = []
for var in cfg.plots_inputs_variables:
ivalue[var] = {}
for basin in cfg.inputs_basins:
bid = args['basins'][basin]['basin_id']
ivalue[var][basin] = {}
for func in cfg.inputs_methods:
if 'percentile' in func:
nfunc = '{}_{}'.format(func,
str(cfg.inputs_percentiles[0]))
if ((var == cfg.plots_inputs_variables[0])
and (basin == cfg.inputs_basins[0])):
p.append(nfunc)
ivalue[var][basin][nfunc] = df[
(df['function'] == nfunc) & (df['variable'] == var)
& (df['basin_id'] == int(bid)) &
(df['run_name'] == args['run_name'])]
nfunc = '{}_{}'.format(func,
str(cfg.inputs_percentiles[1]))
if ((var == cfg.plots_inputs_variables[0])
and (basin == cfg.inputs_basins[0])):
p.append(nfunc)
ivalue[var][basin][nfunc] = df[
(df['function'] == nfunc) & (df['variable'] == var)
& (df['basin_id'] == int(bid)) &
(df['run_name'] == args['run_name'])]
else:
ivalue[var][basin][func] = df[
(df['function'] == func) & (df['variable'] == var)
& (df['basin_id'] == int(bid)) &
(df['run_name'] == args['run_name'])]
if ((var == cfg.plots_inputs_variables[0])
and (basin == cfg.inputs_basins[0])):
p.append(func)
args['inputs'] = ivalue
args['inputs_methods'] = p
args['var_list'] = cfg.plots_inputs_variables
args['inputs_basins'] = cfg.inputs_basins
inputs(args, cfg._logger)
cfg.fig_names = fig_names
def write_properties(end_date, cnx, plotorder, basins, wy_start, run_name,
figs_path, values, vollbl='TAF', logger=None):
""" Write daily total snowpack properties to csv.
Args
------
end_date {str}: end_date
cnx {str}: database connector
plotorder {list}: basins list
basins {dict}: basins dict
wy_start {str}: YYYY1001
run_name {str}: snowav run_name
figs_path {str}: path to save files
values {list}: list of snowav values
vollbl {str}: volume label
depthlbl {str}: depth label
logger {class}: logger
"""
datestr = end_date.strftime("%Y%m%d")
now_str = datetime.now().date().strftime("%Y-%m-%d")
date_col = 'Date generated: {}'.format(now_str)
unit = vollbl
for value in values:
out = collect(cnx, plotorder, basins, wy_start, end_date, value,
run_name, 'total', 'daily')
out.index = out.index.date
# setting index to date strips the index name
out.index.name = 'date'
if value.lower() == 'swe_vol':
value_line = ('Snow Water Equivalent (SWE) volume in thousands ' +
'of acre-feet (TAF)')
elif value.lower() == 'swi_vol':
value_line = ('Surface Water Input (SWI) volume in thousands ' +
'of acre-feet (TAF)')
else:
if logger is not None:
logger.warning(" Value types other than swe, swi, and "
"their derivates are not supported")
return
headers = ['USDA Agicultural Research Service Snowpack Summary Data',
value_line,
'Data provided are daily model results from the iSnobal model',
'First column is the date of model result',
'Second column is the total basin volume',
'Additional columns are the subbasins in the watershed',
date_col,
'Valid until next reports are generated',
'Contact: Scott Havens <*****@*****.**>'
'\n']
s = ''.join(e for e in unit.lower() if e.isalnum())
filename = '{}_daily_{}_{}.csv'.format(value, datestr, s)
path = os.path.join(os.path.abspath(figs_path), filename)
if os.path.isfile(path):
os.remove(path)
with open(path, mode='w', encoding='utf-8') as f:
f.write('\n'.join(headers))
out.to_csv(path, encoding='utf-8', mode='a')
if logger is not None:
logger.info(' Saved: {}'.format(path))
def report(cfg):
""" Create the pdf report.
The latex formats for figures, tables, and summary paragraphs are created
by templates in snowav/report/. Data is pulled from the snowav database.
To add a figure to the report:
- create the plot (of course)
- add to variables dict in this file, with the same naming convention
variables['PDEP_FIG'] = 'precip_depth%s.png'%(cfg.directory)
- add figure template to snowav_report.tex
\VAR{PDEP_FIG_TPL}
- add to section_dict
- add template to snowav/report/figs/
- add to snowav/config/CoreConfig.py [report] exclude_figs
- if the figure may not exist (such as flt_diff, or those that require
process() to run), address that with some form of exception before
creating the pdf
Args
------
cfg {class}: config class
"""
# bid = cfg.basins[cfg.plotorder[0]]['basin_id']
basins = cfg.basins
wy_start = datetime(cfg.wy-1, 10, 1)
start_date = cfg.start_date
end_date = cfg.end_date
run_name = cfg.run_name
# edges = cfg.edges
plotorder = cfg.plotorder
dpts = int(cfg.dplcs)
ddpts = int(cfg.rep_dplcs)
cnx = cfg.connector
# variables to pass to latex file
variables = {}
dbval = collect(cnx, plotorder[0], basins, wy_start, end_date, 'swi_vol',
run_name, 'total', 'sum')
variables['TOTAL_SWI'] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, plotorder[0], basins, start_date, end_date, 'swi_vol',
run_name, 'total', 'sum')
variables['PER_SWI'] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, plotorder[0], basins, start_date, end_date, 'swe_vol',
run_name, 'total', 'end')
variables['TOTAL_SWE'] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, plotorder[0], basins, start_date, end_date, 'swe_avail',
run_name, 'total', 'end')
variables['TOTAL_SAV'] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, plotorder[0], basins, start_date, end_date, 'swe_z',
run_name, 'total', 'end')
variables['TOTAL_PM'] = dbval.sum().values.round(decimals=ddpts)[0]
dbval = collect(cnx, plotorder[0], basins, wy_start, end_date, 'precip_z',
run_name, 'total', 'sum')
variables['TOTALPRE_PM'] = dbval.sum().values.round(decimals=ddpts)[0]
s = collect(cnx, plotorder[0], basins, start_date, start_date, 'swe_vol',
run_name, 'total', 'end')
e = collect(cnx, plotorder[0], basins, start_date, end_date, 'swe_vol',
run_name, 'total', 'end')
start_swe = s.sum().values.round(decimals=dpts)[0]
end_swe = e.sum().values.round(decimals=dpts)[0]
diff = end_swe - start_swe
variables['TOTAL_SDEL'] = diff
variables['TOTAL_PVOL'] = '100'
if float(end_swe) - float(start_swe) > 0:
variables['SIGN'] = r'$+$'
if float(end_swe) - float(start_swe) == 0.0:
variables['SIGN'] = ''
if float(end_swe) - float(start_swe) < 0.0:
variables['SIGN'] = r'-'
dbval = collect(cnx, plotorder[0], basins, wy_start, end_date, 'rain_z',
run_name, 'total', 'sum')
total_rain = dbval.sum().values.round(decimals=ddpts)[0]
if variables['TOTALPRE_PM'] != 0:
variables['TOTAL_RAT'] = str(int((total_rain / variables['TOTALPRE_PM']) * 100))
else:
variables['TOTAL_RAT'] = '-'
variables['TOTALPRE_PM'] = '-'
report_time = datetime.now().strftime("%Y-%-m-%-d %H:%M")
numsubs = range(1, len(cfg.plotorder))
for n, sub in zip(numsubs, cfg.plotorder[1:]):
swiind = 'SUB' + str(n) + '_SWI'
perswiind = 'SUB' + str(n) + '_PERSWI'
sweind = 'SUB' + str(n) + '_SWE'
avsweind = 'SUB' + str(n) + '_SAV'
swedel = 'SUB' + str(n) + '_SDEL'
pm = 'SUB' + str(n) + '_PM'
prepm = 'SUB' + str(n) + 'PRE_PM'
rain = 'SUB' + str(n) + 'RAI'
ratio = 'SUB' + str(n) + '_RAT'
pvol = 'SUB' + str(n) + '_PVOL'
dbval = collect(cnx, sub, basins, wy_start, end_date, 'swi_vol',
run_name, 'total', 'sum')
variables[swiind] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, sub, basins, start_date, end_date, 'swi_vol',
run_name, 'total', 'sum')
variables[perswiind] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, sub, basins, start_date, end_date, 'swe_vol',
run_name, 'total', 'end')
variables[sweind] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, sub, basins, start_date, end_date, 'swe_avail',
run_name, 'total', 'end')
variables[avsweind] = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, sub, basins, start_date, start_date, 'swe_vol',
run_name, 'total', 'end')
start_swe = dbval.sum().values.round(decimals=dpts)[0]
dbval = collect(cnx, sub, basins, start_date, end_date, 'swe_vol',
run_name, 'total', 'end')
end_swe = dbval.sum().values.round(decimals=dpts)[0]
variables[swedel] = end_swe - start_swe
dbval = collect(cnx, sub, basins, start_date, end_date, 'swe_z',
run_name, 'total', 'end')
variables[pm] = dbval.sum().values.round(decimals=ddpts)[0]
dbval = collect(cnx, sub, basins, wy_start, end_date, 'precip_z',
run_name, 'total', 'sum')
variables[prepm] = dbval.sum().values.round(decimals=ddpts)[0]
dbval = collect(cnx, sub, basins, wy_start, end_date, 'rain_z',
run_name, 'total', 'sum')
variables[rain] = dbval.sum().values.round(decimals=ddpts)[0]
if (end_swe > 0) and (variables['TOTAL_SWE'] > 0):
variables[pvol] = end_swe / variables['TOTAL_SWE'] * 100
else:
variables[pvol] = '-'
if variables[prepm] != 0.0:
variables[ratio] = str(int((variables[rain] / variables[prepm]) * 100))
else:
variables[ratio] = '0'
# Upper case variables are used in the LaTex file,
# lower case versions are assigned here
# untested - if report title contains comma?
if isinstance(cfg.rep_title, list):
title = cfg.rep_title[0]
for s in cfg.rep_title[1::]:
title = title + ', ' + s
variables['REPORT_TITLE'] = title
else:
if cfg.flt_flag and cfg.flight_figs:
fst = ' Model snow depths were updated with ASO snow depths on '
tst = ''
for i, d in enumerate(cfg.flight_diff_dates):
if d <= cfg.end_date:
dn = d.date().strftime("%m/%d")
if len(cfg.flight_diff_dates) == 1:
fst = fst + dn + '.'
tst += dn
if ((len(cfg.flight_diff_dates) > 1) and
(i < len(cfg.flight_diff_dates) - 1)):
fst = fst + dn + ', '
tst += dn + ', '
if ((len(cfg.flight_diff_dates) > 1) and
(i == len(cfg.flight_diff_dates) - 1)):
fst = fst + 'and ' + dn + '.'
tst += dn
else:
fst = fst.split(dn)[0] + 'and ' + dn + '.'
break
variables['REPORT_TITLE'] = (cfg.rep_title +
r' \\ ASO Updates {}'.format(tst))
variables['FLTSENT'] = fst
else:
variables['REPORT_TITLE'] = cfg.rep_title
variables['FLTSENT'] = ''
variables['REPORT_TIME'] = report_time
variables['WATERYEAR'] = str(cfg.wy)
variables['UNITS'] = cfg.vollbl
variables['VOLLBL'] = cfg.vollbl
variables['DEPLBL'] = cfg.depthlbl
variables['START_DATE'] = cfg.report_start.date().strftime("%B %-d")
variables['END_DATE'] = cfg.report_date.date().strftime("%B %-d")
variables['SWE_IN'] = variables['TOTAL_PM']
variables['SWI_IN'] = variables['TOTAL_SWI']
variables['FIG_PATH'] = cfg.figs_path
variables['SWI_FIG'] = cfg.swi_volume_fig_name
variables['CHANGES_FIG'] = cfg.volume_change_fig_name
variables['TOTALS_FIG'] = cfg.basin_total_fig_name
variables['MULTITOTSWE_FIG'] = 'compare_swe_vol_{}.png'.format(cfg.directory)
variables['PDEP_FIG'] = cfg.precip_fig_name
variables['VALID_FIG'] = cfg.stn_validate_fig_name
variables['COLD_FIG'] = cfg.cold_content_fig_name
variables['SWE_FIG'] = cfg.swe_volume_fig_name
variables['VERSION'] = snowav.__version__
if (cfg.update_file is not None) and cfg.flt_flag and cfg.flight_figs:
for name in cfg.flight_diff_fig_names:
variables['DFLT_FIG'] = name
if cfg.report_diagnostics:
variables['DIAGNOSTICS_FIG'] = 'diagnostics_{}'.format(cfg.directory)
variables['INPUTS_FIG'] = 'inputs_period_{}'.format(cfg.directory)
if cfg.subs_fig is not None:
variables['SUBBASINS_FIG'] = '{}'.format(cfg.subs_fig)
# Logos
variables['ARSLOGO'] = os.path.join(cfg.figs_tpl_path, 'ARS.jpg')
variables['ASOLOGO'] = os.path.join(cfg.figs_tpl_path, 'ASO.jpg')
variables['USDALOGO'] = os.path.join(cfg.figs_tpl_path, 'USDA.png')
variables['JPLLOGO'] = os.path.join(cfg.figs_tpl_path, 'JPL.jpg')
variables['CDWRLOGO'] = os.path.join(cfg.figs_tpl_path, 'CDWR.png')
variables['USBRLOGO'] = os.path.join(cfg.figs_tpl_path, 'USBR.jpg')
variables['NRCSLOGO'] = os.path.join(cfg.figs_tpl_path, 'NRCS.jpg')
variables['KRWALOGO'] = os.path.join(cfg.figs_tpl_path, 'KRWA.jpg')
variables['FRIANTLOGO'] = os.path.join(cfg.figs_tpl_path, 'FRIANT.jpg')
variables['AWSMLOGO'] = os.path.join(cfg.figs_tpl_path, 'logo.png')
dfind = [str(i) for i in cfg.edges]
dfindt = [str(i) for i in cfg.edges] + ['total']
colstr = 'l' + 'r' * len(cfg.plotorder)
if len(cfg.plotorder) > 5:
spacecmd = r'\resizebox{\textwidth}{!}{'
else:
spacecmd = r'{'
# ntables = len(cfg.tables)
mtables = 2
ptables = 0
if 'swe_depth' in cfg.tables:
dbval = collect(cnx, plotorder, basins, start_date, end_date, 'swe_z', run_name, dfindt, 'end')
dbval = dbval.rename(columns=cfg.labels)
swe_byelev = dbval.round(decimals=dpts)
swe_byelev.rename(index={'total': 'mean'}, inplace=True)
swe_byelev.index.name = 'Elevation'
variables['SWE_BYELEV'] = (r' \normalsize \textbf{SWE [%s], %s}\\ \vspace{0.1cm} \\'
% (cfg.depthlbl, cfg.report_date.date().strftime("%Y-%-m-%-d")) +
spacecmd + swe_byelev.to_latex(na_rep='-', column_format=colstr) +
r'} \\ \footnotesize{\textbf{Table %s:} SWE depth.}' % (str(mtables)))
mtables += 1
ptables += 1
else:
variables['SWE_BYELEV'] = ''
if 'swe_vol' in cfg.tables:
ptables += 1
if ptables == 2:
clrpage = r'\clearpage'
else:
clrpage = ''
dbval = collect(cnx, plotorder, basins, start_date, end_date, 'swe_vol', run_name, dfindt, 'end')
dbval = dbval.rename(columns=cfg.labels)
swe_byelev = dbval.round(decimals=dpts)
swe_byelev.index.name = 'Elevation'
variables['SWEVOL_BYELEV'] = (r' \normalsize \textbf{SWE [%s], %s}\\ \vspace{0.1cm} \\'
% (cfg.vollbl, cfg.report_date.date().strftime("%Y-%-m-%-d")) +
spacecmd + swe_byelev.to_latex(na_rep='-', column_format=colstr) +
r'} \\ \footnotesize{\textbf{Table %s:} SWE volume.}%s' % (str(mtables), clrpage))
mtables += 1
else:
variables['SWEVOL_BYELEV'] = ''
if 'swe_change' in cfg.tables:
ptables += 1
if ptables == 2:
clrpage = r'\clearpage'
else:
clrpage = ''
dbval = collect(cnx, plotorder, basins, start_date, start_date, 'swe_z', run_name, dfindt, 'end')
dbval = dbval.rename(columns=cfg.labels)
start_swe = dbval.round(decimals=dpts)
dbval = collect(cnx, plotorder, basins, start_date, end_date, 'swe_z', run_name, dfindt, 'end')
dbval = dbval.rename(columns=cfg.labels)
end_swe = dbval.round(decimals=dpts)
dswe_byelev = end_swe - start_swe
dswe_byelev.rename(index={'total': 'mean'}, inplace=True)
dswe_byelev.index.name = 'Elevation'
variables['DSWE_BYELEV'] = (r' \normalsize \textbf{Change in SWE [%s], %s to %s}\\ \vspace{0.1cm} \\'
% (cfg.depthlbl, cfg.report_start.date().strftime("%Y-%-m-%-d"),
cfg.report_date.date().strftime("%Y-%-m-%-d")) + spacecmd +
dswe_byelev.to_latex(na_rep='-', column_format=colstr) +
r'} \\ \footnotesize{\textbf{Table %s:} Change in SWE.} %s' % (
str(mtables), clrpage))
mtables += 1
else:
variables['DSWE_BYELEV'] = ''
if 'swe_percent' in cfg.tables:
ptables += 1
if (ptables % 2) == 0 and ptables != 0:
clrpage = r'\clearpage'
else:
clrpage = ''
dbval = collect(cnx, plotorder, basins, start_date, end_date, 'swe_vol', run_name, dfind, 'end')
dbval = dbval.rename(columns=cfg.labels)
swe_byelev = dbval.round(decimals=dpts)
value = swe_byelev.iloc[:-1].sum()
sweper_byelev = (swe_byelev / value * 100).round(decimals=dpts)
sweper_byelev.index.name = 'Elevation'
variables['SWEPER_BYELEV'] = (
r' \normalsize \textbf{SWE volume, percent of basin total, %s}\\ \vspace{0.1cm} \\'
% (cfg.report_date.date().strftime("%Y-%-m-%-d")) +
spacecmd + sweper_byelev.round(1).to_latex(na_rep='-', column_format=colstr) +
r'} \\ \footnotesize{\textbf{Table %s:} Percent of total SWE volume.}%s' % (str(mtables), clrpage))
variables['SWEPER_BYELEV'] = variables['SWEPER_BYELEV'].replace('inf', '-')
mtables += 1
else:
variables['SWEPER_BYELEV'] = ''
if 'swi_vol' in cfg.tables:
dbval = collect(cnx, plotorder, basins, start_date, end_date, 'swi_vol', run_name, dfindt, 'sum')
dbval = dbval.rename(columns=cfg.labels)
swi_byelev = dbval.round(decimals=dpts)
variables['ACCUM_BYELEV'] = (r' \normalsize \textbf{SWI [%s] by elevation, %s to %s}\\ \vspace{0.1cm} \\'
% (cfg.vollbl, cfg.report_start.date().strftime("%Y-%-m-%-d"),
cfg.report_date.date().strftime("%Y-%-m-%-d")) + spacecmd +
swi_byelev.to_latex(na_rep='-', column_format=colstr) +
r'} \\ \footnotesize{\textbf{Table %s:} SWI volume. }' % (str(mtables)))
mtables += 1
else:
variables['ACCUM_BYELEV'] = ''
variables['TOT_LBL'] = cfg.plotorder[0]
# for n in range(1,len(cfg.plotorder)):
for n in range(1, len(cfg.labels)):
s = 'SUB' + str(n) + '_LBL'
variables[s] = cfg.labels[cfg.plotorder[n]]
# Convert floats to strings
for name in variables:
if isinstance(variables[name], float):
if cfg.dplcs == 0:
tmp = str(int(variables[name]))
else:
tmp = str(round(variables[name], cfg.dplcs))
variables[name] = tmp
# Summary sections and fig template have variable strings
# (e.g. CHANGES_FIG) that need to be replaced
section_dict = {'SUMMARY': cfg.summary_file,
'CHANGES_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'changes_fig_tpl.txt'),
'SWI_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'swi_fig_tpl.txt'),
'TOTALS_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'totals_fig_tpl.txt'),
'MULTITOTSWE_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'multitotswe_fig_tpl.txt'),
'VALID_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'valid_fig_tpl.txt'),
'FLTCHANGES_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'flt_fig_tpl.txt'),
'PDEP_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'pdep_fig_tpl.txt'),
'COLD_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'cold_fig_tpl.txt'),
'SWE_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'swe_fig_tpl.txt'),
'SUBBASINS_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'subbasins_fig_tpl.txt'),
'DIAGNOSTICS_FIG_TPL': os.path.join(cfg.figs_tpl_path, 'diagnostics_fig_tpl.txt'),
'SWE_SUMMARY_TPL': os.path.join(cfg.figs_tpl_path,
'swe_summary_{}sub.txt'.format(str(len(cfg.plotorder))))}
# Define and load summary tables depending on number of subbasins
# Remove if no flight
if not cfg.flt_flag or not cfg.flight_figs:
del section_dict['FLTCHANGES_FIG_TPL']
if not cfg.report_diagnostics:
del section_dict['DIAGNOSTICS_FIG_TPL']
variables['DIAGNOSTICS_FIG'] = ''
for rep in section_dict.keys():
# for variable numbers of fligth figures
if rep == 'FLTCHANGES_FIG_TPL':
fid = open(section_dict[rep], 'r')
var = fid.read()
fid.close()
for name in sorted(variables):
if name == 'DFLT_FIG':
for i, fltname in enumerate(cfg.flight_diff_fig_names):
flt_date = cfg.flight_outputs['dates'][i].date().strftime("%Y%m%d")
flt_num = cfg.flight_delta_vol_df[flt_date].round(1).to_latex(na_rep='-', column_format=colstr)
table = (r'{ \vspace{0.5cm} \textbf{Change in SWE [%s] by elevation, ' % (cfg.vollbl) +
r'from %s update} \\ \vspace{0.1cm} \\' % (flt_date) +
r' %s %s }' % (spacecmd, flt_num))
if i == 0:
tmp = var.replace(name, fltname)
else:
tmp += var.replace(name, fltname)
tmp += table
var = tmp.replace(name, variables[name])
else:
var = var.replace(name, variables[name])
variables[rep] = var
else:
fid = open(section_dict[rep], 'r')
var = fid.read()
fid.close()
for name in sorted(variables):
var = var.replace(name, variables[name])
variables[rep] = var
if not cfg.subs_fig:
variables['SUBBASINS_FIG_TPL'] = ''
if not cfg.rep_compare_runs_flag:
variables['MULTITOTSWE_FIG_TPL'] = ''
if not cfg.rep_swi_flag:
variables['SWI_FIG_TPL'] = ''
if not cfg.rep_image_change_flag:
variables['CHANGES_FIG_TPL'] = ''
if not cfg.rep_cold_content_flag:
variables['COLD_FIG_TPL'] = ''
if not cfg.rep_swe_volume_flag:
variables['SWE_FIG_TPL'] = ''
if not cfg.rep_basin_total_flag:
variables['TOTALS_FIG_TPL'] = ''
if not cfg.rep_stn_validate_flag:
variables['VALID_FIG_TPL'] = ''
if not cfg.rep_compare_runs_flag:
variables['MULTITOTSWE_FIG_TPL'] = ''
if not cfg.rep_precip_depth_flag:
variables['PDEP_FIG_TPL'] = ''
# Make the report
env = make_env(loader=FileSystemLoader(cfg.templ_path))
tpl = env.get_template(cfg.tex_file)
# print VAR-replaced latex file for debugging if desired
if cfg.print_latex:
print(tpl.render(variables))
pdf = build_pdf(tpl.render(variables))
# Save in reports and with figs
rpath = os.path.join(cfg.figs_path, '' + cfg.report_name)
pdf.save_to(rpath)
cfg._logger.info(' Saved {}'.format(rpath))
if cfg.rep_path is not None:
rpath = os.path.join(cfg.rep_path, '' + cfg.report_name)
pdf.save_to(rpath)
cfg._logger.info(' Saved {}'.format(rpath))
def flt_image_change(file, update_numbers, end_date, flight_outputs,
pre_flight_outputs, masks, lims, barcolors, edges,
connector, plotorder, wy, depth_factor, basins,
run_name, figsize, depthlbl, elevlbl, vollbl, dplcs,
figspath, dpi=200, logger=None):
""" Difference in SWE from one day prior to flight updates to the day of
flight updates.
The file specified in [plots] update_file is used to get dates of flight
updates and the masks for which portions of the basin were updated. The
actual SWE differences are between the snow.nc files on the dates of the
flights and the day immediately prior. [plots] update_numbers is a 1-based
list of subsetting flights that can be applied.
Args
------
file {str}: path to lidar_depths.nc
update_numbers {list}: flight numbers to generate
end_date {datetime}: end date
flight_outputs {dict}: from config.py
pre_flight_outputs {dict}: from config.py
masks {dict}: from config.py
lims {list}: percent of min/max for color limits
barcolors {list}: colors
edges {list}: elevation bands
connector {str}: database connector
plotorder {list}: basins
wy {int}: water year
depth_factor {float}: depth factor
basins {dict}: from config.py
run_name {str}: snowav run_name
figsize {list}: figure dimensions
depthlbl {str}: depth label
elevlbl {str}: elevation label
vollbl {str}: volume label
dplcs {int}: decimal places
figspath {str}: base path for figures
dpi {int}: figure dpi
"""
e = False
basin_name = plotorder[0].lower().split(" ")[0]
flight_diff_fig_names = []
flight_delta_vol_df = {}
p = nc.Dataset(file, 'r')
if update_numbers is None:
times = p.variables['time'][:]
else:
if max(update_numbers) > len(p.variables['time']) - 1:
raise Exception('Max flight update_numbers greater than available '
'flights')
else:
times = p.variables['time'][update_numbers]
# remove flight indices that might be after the report period
idx = []
for i, n in enumerate(times):
date = calculate_date_from_wyhr(int(n), wy)
if date > end_date:
idx = np.append(idx, i)
times = np.delete(times, idx)
ix = np.argsort(times)
times = times[ix]
if update_numbers is not None:
update_numbers = [int(x) for x in update_numbers]
for i, time in enumerate(times):
if update_numbers is not None:
depth = p.variables['depth'][update_numbers[ix[i]], :, :]
else:
depth = p.variables['depth'][ix[i], :, :]
delta_swe = flight_outputs['swe_z'][i][:] - pre_flight_outputs['swe_z'][i][:]
delta_swe = delta_swe * depth_factor
# We will always make the difference between the previous day
start_date = flight_outputs['dates'][i] - timedelta(hours=24)
end_date = flight_outputs['dates'][i]
try:
delta_swe_byelev = collect(connector, plotorder, basins, start_date,
end_date, 'swe_vol', run_name, edges,
'difference')
except:
e = True
try:
end_swe_byelev = collect(connector, plotorder, basins, start_date,
end_date, 'swe_vol', run_name, edges,
'end')
except:
e = True
if e:
if logger is not None:
logger.info(' Failed requesting database records ending on {} '
'for flight difference figure. This may mean that '
'[run] directory has not been processed with '
'[snowav] run_name: {} for the periods in '
'[plots] update_file. Try subsetting with [plots] '
'update_numbers or processing the full [run] '
'directory.'.format(end_date, run_name))
logger.info(' Flight figures being set to False...')
return [], []
# Make copy so that we can add nans for the plots
delta_state = copy.deepcopy(delta_swe)
v_min, v_max = np.nanpercentile(delta_state, [lims[0], lims[1]])
colorsbad = plt.cm.Set1_r(np.linspace(0., 1, 1))
colors1 = cmocean.cm.matter_r(np.linspace(0., 1, 127))
colors2 = plt.cm.Blues(np.linspace(0, 1, 128))
colors = np.vstack((colorsbad, colors1, colors2))
mymap = mcolors.LinearSegmentedColormap.from_list('my_colormap', colors)
ixf = delta_state == 0
delta_state[ixf] = -100000
pmask = masks[plotorder[0]]['mask']
ixo = pmask == 0
delta_state[ixo] = np.nan
cmap = copy.copy(mymap)
cmap.set_bad('white', 1.)
sns.set_style('darkgrid')
sns.set_context("notebook")
plt.close(i)
fig, (ax, ax1) = plt.subplots(num=i, figsize=figsize, dpi=dpi, nrows=1,
ncols=2)
norm = MidpointNormalize(midpoint=0, vmin=v_min, vmax=v_max)
# this is primarily for awsm_test_cases, in which the flight update
# nc file doesn't contain mask information. wy2019-forward flight nc
# files *should* have a mask
if hasattr(depth, 'mask'):
mask = np.ma.masked_array(depth.mask, ~depth.mask)
if mask.shape != delta_state.shape:
raise Exception('Dimensions {}: {} do not match snow.nc: '
'{}'.format(file, mask.shape, delta_state.shape))
delta_state[mask] = np.nan
h = ax.imshow(delta_state * mask, cmap=cmap, clim=(v_min, v_max),
norm=norm)
else:
h = ax.imshow(delta_state, cmap=cmap, clim=(v_min, v_max),
norm=norm)
for name in masks:
ax.contour(masks[name]['mask'], cmap="Greys", linewidths=1)
h.axes.get_xaxis().set_ticks([])
h.axes.get_yaxis().set_ticks([])
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.2)
cbar = plt.colorbar(h, cax=cax)
cbar.set_label(r'$\Delta$ SWE [{}]'.format(depthlbl))
end_date = start_date + timedelta(hours=1)
d = end_date + timedelta(hours=1)
h.axes.set_title('Change in SWE Depth\n{} to {}'
.format(start_date.date().strftime("%Y-%-m-%-d"),
end_date.date().strftime("%Y-%-m-%-d")))
if len(plotorder) == 1:
porder = plotorder
else:
porder = plotorder[1::]
for iters, name in enumerate(porder):
if dplcs == 0:
lbl = '{}: {} {}'.format(name,
str(int(delta_swe_byelev[name].sum())),
vollbl)
else:
lbl = '{}: {} {}'.format(name,
str(np.round(delta_swe_byelev[name].sum(),
dplcs)), vollbl)
if iters == 0:
ax1.bar(range(0, len(edges)), delta_swe_byelev[name],
color=barcolors[iters],
edgecolor='k', label=lbl)
else:
ax1.bar(range(0, len(edges)), delta_swe_byelev[name],
color=barcolors[iters],
edgecolor='k',
label=lbl,
alpha=0.5)
end_swe_byelev = end_swe_byelev.fillna(0)
datestr = flight_outputs['dates'][i].date().strftime("%Y%m%d")
percent_delta_byelev = (delta_swe_byelev.sum(skipna=True) / end_swe_byelev.sum()) * 100
flight_delta_vol_df[flight_outputs['dates'][i].date().strftime("%Y%m%d")] = delta_swe_byelev
fp = os.path.join(figspath,
'{}_flight_{}_delta_taf.csv'.format(basin_name, datestr))
delta_swe_byelev.to_csv(fp)
fp = os.path.join(figspath,
'{}_flight_{}_percent_change.csv'.format(basin_name, datestr))
percent_delta_byelev.to_csv(fp)
plt.tight_layout()
xts = ax1.get_xticks()
edges_lbl = []
for x in xts[0:len(xts) - 1]:
edges_lbl.append(str(int(edges[int(x)])))
ax1.set_xticklabels(str(x) for x in edges_lbl)
for tick in ax1.get_xticklabels():
tick.set_rotation(30)
ylims = ax1.get_ylim()
ymax = ylims[1] + abs(ylims[1] - ylims[0])
ymin = ylims[0] - abs(ylims[1] - ylims[0]) * 0.1
ax1.set_ylim((ymin, ymax))
ax1.set_ylabel(r'$\Delta$ SWE [{}]'.format(vollbl))
ax1.set_xlabel('elevation [{}]'.format(elevlbl))
ax1.yaxis.set_label_position("right")
ax1.tick_params(axis='x')
ax1.tick_params(axis='y')
ax1.yaxis.tick_right()
if len(plotorder) > 1:
ax1.legend(loc=2, fontsize=10)
plt.tight_layout()
fig.subplots_adjust(top=0.88)
fstr = '{}_flight_difference_{}.png'.format(basin_name, datestr)
flight_diff_fig_names += [fstr]
fig_path = os.path.join(figspath, fstr)
snowav.framework.figures.save_fig(fig, fig_path)
if logger is not None:
logger.info(' Saved: {}'.format(fig_path))
p.close()
return flight_diff_fig_names, flight_delta_vol_df
