import numpy
import netCDF4
import matplotlib.pyplot as plt
from compass.step import Step
[docs]class Visualize(Step):
"""
A step for visualizing the output from a dome test case
Attributes
----------
mesh_type : str
The resolution or mesh type of the test case
"""
[docs] def __init__(self, test_case, mesh_type, name='visualize', subdir=None,
input_dir='run_model'):
"""
Create the step
Parameters
----------
test_case : compass.TestCase
The test case this step belongs to
mesh_type : str
The resolution or mesh type of the test case
name : str, optional
the name of the test case
subdir : str, optional
the subdirectory for the step. The default is ``name``
input_dir : str, optional
The input directory within the test case with a file ``output.nc``
to visualize
"""
super().__init__(test_case=test_case, name=name, subdir=subdir)
self.mesh_type = mesh_type
self.add_input_file(filename='output.nc',
target='../{}/output.nc'.format(input_dir))
# depending on settings, this may produce no outputs, so we won't add
# any
# no setup method is needed
[docs] def run(self):
"""
Run this step of the test case
"""
visualize_dome(self.config, self.logger, filename='output.nc')
[docs]def visualize_dome(config, logger, filename):
"""
Plot the output from a dome test case
Parameters
----------
config : configparser.ConfigParser
Configuration options for this test case, a combination of the defaults
for the machine, core and configuration
logger : logging.Logger
A logger for output from the step
filename : str
file to visualize
"""
section = config['dome_viz']
time_slice = section.getint('time_slice')
save_images = section.getboolean('save_images')
hide_figs = section.getboolean('hide_figs')
# Note: this may be slightly wrong for some calendar types!
secInYr = 3600.0 * 24.0 * 365.0
f = netCDF4.Dataset(filename, 'r')
times = f.variables['xtime']
thickness = f.variables['thickness']
# dcEdge = f.variables['dcEdge']
# bedTopography = f.variables['bedTopography'] # not needed
xCell = f.variables['xCell']
yCell = f.variables['yCell']
xEdge = f.variables['xEdge']
yEdge = f.variables['yEdge']
angleEdge = f.variables['angleEdge']
temperature = f.variables['temperature']
lowerSurface = f.variables['lowerSurface']
upperSurface = f.variables['upperSurface']
normalVelocity = f.variables['normalVelocity']
# uReconstructX = f.variables['uReconstructX']
uReconstructX = f.variables['uReconstructX']
uReconstructY = f.variables['uReconstructY']
vert_levs = len(f.dimensions['nVertLevels'])
time_length = times.shape[0]
logger.info("vert_levs = {}; time_length = {}".format(vert_levs,
time_length))
var_slice = thickness[time_slice, :]
fig = plt.figure(1, facecolor='w')
fig.add_subplot(111, aspect='equal')
# C = plt.contourf(xCell, yCell, var_slice )
plt.scatter(xCell[:], yCell[:], 80, var_slice, marker='h',
edgecolors='none')
plt.colorbar()
plt.title('thickness at time {}'.format(time_slice))
plt.draw()
if save_images:
logger.info("Saving figures to files.")
plt.savefig('dome_thickness.png')
fig = plt.figure(2)
fig.add_subplot(121, aspect='equal')
plt.scatter(xCell[:], yCell[:], 80, lowerSurface[time_slice, :],
marker='h', edgecolors='none')
plt.colorbar()
plt.title('lower surface at time {}'.format(time_slice))
plt.draw()
fig.add_subplot(122, aspect='equal')
plt.scatter(xCell[:], yCell[:], 80, upperSurface[time_slice, :],
marker='h', edgecolors='none')
plt.colorbar()
plt.title('upper surface at time {}'.format(time_slice))
plt.draw()
if save_images:
plt.savefig('dome_surfaces.png')
fig = plt.figure(3)
for templevel in range(0, vert_levs):
fig.add_subplot(3, 4, templevel+1, aspect='equal')
var_slice = temperature[time_slice, :, templevel]
# C = plt.contourf(xCell, yCell, var_slice )
plt.scatter(xCell[:], yCell[:], 40, var_slice, marker='h',
edgecolors='none')
plt.colorbar()
plt.title('temperature at level {} at time {}'.format(templevel,
time_slice))
plt.draw()
if save_images:
plt.savefig('dome_temperature.png')
fig = plt.figure(4)
fig.add_subplot(121, aspect='equal')
plt.scatter(xEdge[:], yEdge[:], 80,
normalVelocity[time_slice, :, vert_levs-1] * secInYr,
marker='h', edgecolors='none')
plt.colorbar()
normalVel = normalVelocity[time_slice, :, vert_levs-1]
plt.quiver(xEdge[:], yEdge[:],
numpy.cos(angleEdge[:]) * normalVel * secInYr,
numpy.sin(angleEdge[:]) * normalVel * secInYr)
plt.title('normalVelocity of bottom layer at time {}'.format(time_slice))
plt.draw()
fig.add_subplot(122, aspect='equal')
plt.scatter(xEdge[:], yEdge[:], 80,
normalVelocity[time_slice, :, 0] * secInYr, marker='h',
edgecolors='none')
plt.colorbar()
normalVel = normalVelocity[time_slice, :, 0]
plt.quiver(xEdge[:], yEdge[:],
numpy.cos(angleEdge[:]) * normalVel * secInYr,
numpy.sin(angleEdge[:]) * normalVel * secInYr)
plt.title('normalVelocity of top layer at time {}'.format(time_slice))
plt.draw()
if save_images:
plt.savefig('dome_normalVelocity.png')
fig = plt.figure(5, facecolor='w')
fig.add_subplot(121, aspect='equal')
plt.scatter(xCell[:], yCell[:], 80,
uReconstructX[time_slice, :, 0] * secInYr, marker='h',
edgecolors='none')
plt.colorbar()
plt.quiver(xCell[:], yCell[:], uReconstructX[time_slice, :, 0] * secInYr,
uReconstructY[time_slice, :, 0] * secInYr)
plt.title('uReconstructX of top layer at time {}'.format(time_slice))
plt.draw()
fig.add_subplot(122, aspect='equal')
plt.scatter(xCell[:], yCell[:], 80,
uReconstructY[time_slice, :, 0] * secInYr, marker='h',
edgecolors='none')
plt.colorbar()
plt.quiver(xCell[:], yCell[:], uReconstructX[time_slice, :, 0] * secInYr,
uReconstructY[time_slice, :, 0] * secInYr)
plt.title('uReconstructY of top layer at time {}'.format(time_slice))
plt.draw()
if save_images:
plt.savefig('dome_uReconstruct.png')
if hide_figs:
logger.info("Plot display disabled with hide_plot config option.")
else:
plt.show()
f.close()