def model_diff(parameter_set_nr, data_kind='WOA', path='/tmp', normalize_with_deviation=False, y_max=(None, None)):
from simulation.model.constants import DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME, DATABASE_TIME_STEP_DIRNAME, DATABASE_PARAMETERS_SET_DIRNAME, DATABASE_PARAMETERS_FILENAME
from simulation.model.constants import (METOS_X_DIM as X_DIM, METOS_Y_DIM as Y_DIM, METOS_Z_LEFT as Z_VALUES_LEFT)
logger.debug('Plotting model output for parameter set {}'.format(parameter_set_nr))
## load parameters
parameter_set_dirname = DATABASE_PARAMETERS_SET_DIRNAME.format(parameter_set_nr)
p_file = os.path.join(DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME.format('dop_po4'), DATABASE_TIME_STEP_DIRNAME.format(1), parameter_set_dirname, DATABASE_PARAMETERS_FILENAME)
p = np.loadtxt(p_file)
## init data base
data_base = simulation.util.data_base.init_data_base(data_kind)
if not normalize_with_deviation:
file = os.path.join(path, 'model_diff_-_{}_-_' + parameter_set_dirname + '_-_{}.png')
else:
file = os.path.join(path, 'model_diff_normalized_with_deviation_-_{}_-_' + parameter_set_dirname + '_-_{}.png')
## print for WOA
if data_kind.upper() == 'WOA':
diff_boxes = np.abs(data_base.diff_boxes(p, normalize_with_deviation=normalize_with_deviation))
## print for WOD
elif data_kind.upper() == 'WOD':
diff = np.abs(data_base.diff(p, normalize_with_deviation=normalize_with_deviation))
diff_boxes = data_base.convert_to_boxes(diff, no_data_value=np.inf)
else:
raise ValueError('Data_kind {} unknown. Must be "WOA" or "WOD".'.format(data_kind))
def plot_tracer_diff(diff, file, y_max=None):
util.plot.data(np.abs(diff), file, land_value=np.nan, no_data_value=np.inf, v_min=0, v_max=y_max)
plot_tracer_diff(diff_boxes[0], file.format(data_kind, 'dop'), y_max=y_max[0])
plot_tracer_diff(diff_boxes[1], file.format(data_kind, 'po4'), y_max=y_max[1])
def model_diff(parameter_set_nr, data_kind='WOA', path='/tmp', normalize_with_deviation=False, y_max=(None, None)):
from simulation.model.constants import DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME, DATABASE_TIME_STEP_DIRNAME, DATABASE_PARAMETERS_DIRNAME, DATABASE_PARAMETERS_FILENAME
from simulation.model.constants import (METOS_X_DIM as X_DIM, METOS_Y_DIM as Y_DIM, METOS_Z_LEFT as Z_VALUES_LEFT)
logger.debug('Plotting model output for parameter set {}'.format(parameter_set_nr))
## load parameters
parameter_set_dirname = DATABASE_PARAMETERS_DIRNAME.format(parameter_set_nr)
p_file = os.path.join(DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME.format('dop_po4'), DATABASE_TIME_STEP_DIRNAME.format(1), parameter_set_dirname, DATABASE_PARAMETERS_FILENAME)
p = np.loadtxt(p_file)
## init data base
data_base = simulation.util.data_base.init_data_base(data_kind)
if not normalize_with_deviation:
file = os.path.join(path, 'model_diff_-_{}_-_' + parameter_set_dirname + '_-_{}.png')
else:
file = os.path.join(path, 'model_diff_normalized_with_deviation_-_{}_-_' + parameter_set_dirname + '_-_{}.png')
## print for WOA
if data_kind.upper() == 'WOA':
diff_boxes = np.abs(data_base.diff_boxes(p, normalize_with_deviation=normalize_with_deviation))
## print for WOD
elif data_kind.upper() == 'WOD':
diff = np.abs(data_base.diff(p, normalize_with_deviation=normalize_with_deviation))
diff_boxes = data_base.convert_to_boxes(diff, no_data_value=np.inf)
else:
raise ValueError('Data_kind {} unknown. Must be "WOA" or "WOD".'.format(data_kind))
def plot_tracer_diff(diff, file, y_max=None):
util.plot.data(np.abs(diff), file, land_value=np.nan, no_data_value=np.inf, v_min=0, v_max=y_max)
plot_tracer_diff(diff_boxes[0], file.format(data_kind, 'dop'), y_max=y_max[0])
plot_tracer_diff(diff_boxes[1], file.format(data_kind, 'po4'), y_max=y_max[1])
def model_output(parameter_set_nr, kind='BOXES', path='/tmp', y_max=(None, None), average_in_time=False):
from simulation.model.constants import DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME, DATABASE_TIME_STEP_DIRNAME, DATABASE_PARAMETERS_SET_DIRNAME, DATABASE_PARAMETERS_FILENAME
from simulation.util.constants import CACHE_DIRNAME, BOXES_F_FILENAME, WOD_F_FILENAME
logger.debug('Plotting model output for parameter set {}'.format(parameter_set_nr))
## load parameters
parameter_set_dirname = DATABASE_PARAMETERS_SET_DIRNAME.format(parameter_set_nr)
p_file = os.path.join(DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME.format('dop_po4'), DATABASE_TIME_STEP_DIRNAME.format(1), parameter_set_dirname, DATABASE_PARAMETERS_FILENAME)
p = np.loadtxt(p_file)
## init data base
if kind.upper() == 'BOXES':
data_base = simulation.util.data_base.init_data_base('WOA')
f = data_base.f_boxes(p)
f[f < 0] = 0
if average_in_time:
f = f.mean(axis=1)
else:
data_base = simulation.util.data_base.init_data_base('WOD')
f = data_base.f(p)
f = data_base.convert_to_boxes(f, no_data_value=np.inf)
file = os.path.join(path, 'model_output_-_' + kind + '_-_' + parameter_set_dirname + '_-_{tracer}.png')
tracers = ('dop', 'po4')
for i in range(len(tracers)):
util.plot.data(f[i], file.format(tracer=tracers[i]), land_value=np.nan, no_data_value=np.inf, v_min=0, v_max=y_max[i], contours=True, colorbar=False)
def model_output(parameter_set_nr, kind='BOXES', path='/tmp', y_max=(None, None), average_in_time=False):
from simulation.model.constants import DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME, DATABASE_TIME_STEP_DIRNAME, DATABASE_PARAMETERS_DIRNAME, DATABASE_PARAMETERS_FILENAME
from simulation.util.constants import CACHE_DIRNAME, BOXES_F_FILENAME, WOD_F_FILENAME
logger.debug('Plotting model output for parameter set {}'.format(parameter_set_nr))
## load parameters
parameter_set_dirname = DATABASE_PARAMETERS_DIRNAME.format(parameter_set_nr)
p_file = os.path.join(DATABASE_OUTPUT_DIR, DATABASE_MODEL_DIRNAME.format('dop_po4'), DATABASE_TIME_STEP_DIRNAME.format(1), parameter_set_dirname, DATABASE_PARAMETERS_FILENAME)
p = np.loadtxt(p_file)
## init data base
if kind.upper() == 'BOXES':
data_base = simulation.util.data_base.init_data_base('WOA')
f = data_base.f_boxes(p)
f[f < 0] = 0
if average_in_time:
f = f.mean(axis=1)
else:
data_base = simulation.util.data_base.init_data_base('WOD')
f = data_base.f(p)
f = data_base.convert_to_boxes(f, no_data_value=np.inf)
file = os.path.join(path, 'model_output_-_' + kind + '_-_' + parameter_set_dirname + '_-_{tracer}.png')
tracers = ('dop', 'po4')
for i in range(len(tracers)):
util.plot.data(f[i], file.format(tracer=tracers[i]), land_value=np.nan, no_data_value=np.inf, v_min=0, v_max=y_max[i], contours=True, colorbar=False)
