diff --git a/configuration/scripts/tests/QC/cice.t-test.py b/configuration/scripts/tests/QC/cice.t-test.py index 19cb0926f..86938d8e8 100755 --- a/configuration/scripts/tests/QC/cice.t-test.py +++ b/configuration/scripts/tests/QC/cice.t-test.py @@ -358,48 +358,102 @@ def skill_test(path_a, fname, data_a, data_b, num_files, hemisphere): logger.info('Quadratic Skill Test Failed for %s Hemisphere', hemisphere) return False -def plot_data(data, lat, lon, units): - '''This function plots CICE data and creates a .png file (ice_thickness_map.png).''' +def plot_data(data, lat, lon, units, case, plot_type): + '''This function plots CICE data and creates a .png file.''' try: - logger.info('Creating map of the data (ice_thickness_map.png)') # Load the necessary plotting libraries import matplotlib.pyplot as plt from mpl_toolkits.basemap import Basemap from mpl_toolkits.axes_grid1 import make_axes_locatable except ImportError: logger.warning('Error loading necessary Python modules in plot_data function') + return # Suppress Matplotlib deprecation warnings import warnings warnings.filterwarnings("ignore", category=UserWarning) # Create the figure and axis - fig = plt.figure(figsize=(12, 8)) - ax = fig.add_axes([0.05, 0.08, 0.9, 0.9]) + fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(14, 8)) + # Plot the northern hemisphere data as a scatter plot # Create the basemap, and draw boundaries - m = Basemap(projection='kav7', lon_0=180., resolution='l') - m.drawmapboundary(fill_color='white') + plt.sca(axes[0]) + m = Basemap(projection='npstere', boundinglat=35,lon_0=270, resolution='l') m.drawcoastlines() + m.fillcontinents() m.drawcountries() - # Plot the data as a scatter plot - x, y = m(lon, lat) - sc = m.scatter(x, y, c=data, cmap='jet', lw=0) + if plot_type == 'scatter': + x, y = m(lon,lat) + sc = m.scatter(x, y, c=data, cmap='jet', lw=0, s=4) + else: + # Create new arrays to add 1 additional longitude value to prevent a + # small amount of whitespace around longitude of 0/360 degrees. + lon_cyc = np.zeros((lon.shape[0],lon.shape[1]+1)) + mask = np.zeros((data.shape[0],data.shape[1]+1)) + lat_cyc = np.zeros((lat.shape[0],lat.shape[1]+1)) + + mask[:,0:-1] = data.mask[:,:] + mask[:,-1] = data.mask[:,0] + lon_cyc[:,0:-1] = lon[:,:]; lon_cyc[:,-1] = lon[:,0] + lat_cyc[:,0:-1] = lat[:,:]; lat_cyc[:,-1] = lat[:,0] + + lon1 = np.ma.masked_array(lon_cyc, mask=mask) + lat1 = np.ma.masked_array(lat_cyc, mask=mask) + + d = np.zeros((data.shape[0],data.shape[1]+1)) + d[:,0:-1] = data[:,:] + d[:,-1] = data[:,0] + d1 = np.ma.masked_array(d,mask=mask) + + x, y = m(lon1.data, lat1.data) + + if plot_type == 'contour': + sc = m.contourf(x, y, d1, cmap='jet') + else: # pcolor + sc = m.pcolor(x, y, d1, cmap='jet') + + m.drawparallels(np.arange(-90.,120.,15.),labels=[1,0,0,0]) # draw parallels + m.drawmeridians(np.arange(0.,420.,30.),labels=[1,1,1,1]) # draw meridians + + # Plot the southern hemisphere data as a scatter plot + plt.sca(axes[1]) + m = Basemap(projection='spstere', boundinglat=-45,lon_0=270, resolution='l') + m.drawcoastlines() + m.fillcontinents() + m.drawcountries() + + if plot_type == 'scatter': + x, y = m(lon,lat) + sc = m.scatter(x, y, c=data, cmap='jet', lw=0, s=4) + else: + x, y = m(lon1.data, lat1.data) - m.drawmeridians(np.arange(0, 360, 60), labels=[0, 0, 0, 1], fontsize=10) - m.drawparallels(np.arange(-90, 90, 30), labels=[1, 0, 0, 0], fontsize=10) + # Bandaid for a bug in the version of Basemap used during development + outside = (x <= m.xmin) | (x >= m.xmax) | (y <= m.ymin) | (y >= m.ymax) + tmp = np.ma.masked_where(outside,d1) - plt.title('CICE Ice Thickness') + if plot_type == 'contour': + sc = m.contourf(x, y, tmp, cmap='jet') + else: # pcolor + sc = m.pcolor(x, y, tmp, cmap='jet') - # Create the colorbar and add Pass / Fail labels - divider = make_axes_locatable(ax) - cax = divider.append_axes("bottom", size="5%", pad=0.5) - cb = plt.colorbar(sc, cax=cax, orientation="horizontal", format="%.2f") + m.drawparallels(np.arange(-90.,120.,15.),labels=[1,0,0,0]) # draw parallels + m.drawmeridians(np.arange(0.,420.,30.),labels=[1,1,1,1]) # draw meridians + + plt.suptitle('CICE Mean Ice Thickness\n{}'.format(case), y=0.95) + + # Make some room at the bottom of the figure, and create a colorbar + fig.subplots_adjust(bottom=0.2) + cbar_ax = fig.add_axes([0.11,0.1,0.8,0.05]) + cb = plt.colorbar(sc, cax=cbar_ax, orientation="horizontal", format="%.2f") cb.set_label(units, x=1.0) - plt.savefig('ice_thickness_map.png', dpi=300) + outfile = 'ice_thickness_{}.png'.format(case.replace('\n- ','_minus_')) + logger.info('Creating map of the data ({})'.format(outfile)) + plt.savefig(outfile, dpi=300, bbox_inches='tight') def plot_two_stage_failures(data, lat, lon): '''This function plots each grid cell and whether or not it Passed or Failed @@ -428,7 +482,7 @@ def plot_two_stage_failures(data, lat, lon): ax = fig.add_axes([0.05, 0.08, 0.9, 0.9]) # Create the basemap, and draw boundaries - m = Basemap(projection='kav7', lon_0=180., resolution='l') + m = Basemap(projection='moll', lon_0=0., resolution='l') m.drawmapboundary(fill_color='white') m.drawcoastlines() m.drawcountries() @@ -440,7 +494,7 @@ def plot_two_stage_failures(data, lat, lon): # Plot the data as a scatter plot x, y = m(lon, lat) - sc = m.scatter(x, y, c=int_data, cmap=cm, lw=0, vmin=0, vmax=1) + sc = m.scatter(x, y, c=int_data, cmap=cm, lw=0, vmin=0, vmax=1, s=4) m.drawmeridians(np.arange(0, 360, 60), labels=[0, 0, 0, 1], fontsize=10) m.drawparallels(np.arange(-90, 90, 30), labels=[1, 0, 0, 0], fontsize=10) @@ -482,8 +536,11 @@ def main(): help='Path to the test history (iceh_inst*) files. REQUIRED') parser.add_argument('-v', '--verbose', dest='verbose', help='Print debug output?', \ action='store_true') + parser.add_argument('-pt','--plot_type', dest='plot_type', help='Specify type of plot \ + to create', choices=['scatter','contour','pcolor']) parser.set_defaults(verbose=False) + parser.set_defaults(plot_type='pcolor') # If no arguments are provided, print the help message if len(sys.argv) == 1: @@ -528,6 +585,17 @@ def main(): # If test failed, attempt to create a plot of the failure locations if not PASSED: plot_two_stage_failures(H1_array, t_lat, t_lon) + + # Create plots of mean ice thickness + baseDir = os.path.abspath(args.base_dir).rstrip('history/').rstrip(\ + 'history').split('/')[-1] + testDir = os.path.abspath(args.test_dir).rstrip('history/').rstrip( \ + 'history').split('/')[-1] + plot_data(np.mean(data_base,axis=0), t_lat, t_lon, 'm', baseDir, args.plot_type) + plot_data(np.mean(data_test,axis=0), t_lat, t_lon, 'm', testDir, args.plot_type) + plot_data(np.mean(data_base-data_test,axis=0), t_lat, t_lon, 'm', '{}\n- {}'.\ + format(baseDir,testDir), args.plot_type) + logger.error('Quality Control Test FAILED') sys.exit(-1) @@ -559,6 +627,16 @@ def main(): PASSED_SKILL = PASSED_NH and PASSED_SH + # Plot the ice thickness data for the base and test cases + baseDir = os.path.abspath(args.base_dir).rstrip('history/').rstrip( \ + 'history').split('/')[-1] + testDir = os.path.abspath(args.test_dir).rstrip('history/').rstrip( \ + 'history').split('/')[-1] + plot_data(np.mean(data_base,axis=0), t_lat, t_lon, 'm', baseDir, args.plot_type) + plot_data(np.mean(data_test,axis=0), t_lat, t_lon, 'm', testDir, args.plot_type) + plot_data(np.mean(data_base-data_test,axis=0), t_lat, t_lon, 'm', '{}\n- {}'.\ + format(baseDir,testDir), args.plot_type) + logger.info('') if not PASSED_SKILL: logger.error('Quality Control Test FAILED') diff --git a/doc/source/user_guide/ug_testing.rst b/doc/source/user_guide/ug_testing.rst index 27393e3de..fd21c86f7 100644 --- a/doc/source/user_guide/ug_testing.rst +++ b/doc/source/user_guide/ug_testing.rst @@ -846,7 +846,7 @@ To install the necessary Python packages, the ``pip`` Python utility can be used pip install --user matplotlib To run the compliance test, setup a baseline run with the original baseline model and then -a perturbation run based on recent model changes. Use ``--sets qc`` in both runs in addition +a perturbation run based on recent model changes. Use ``--set qc`` in both runs in addition to other settings needed. Then use the QC script to compare history output, .. code-block:: bash @@ -870,11 +870,17 @@ Implementation notes: 1) Provide a pass/fail on each of the confidence intervals, 2) Facilitate output of a bitmap for each test so that locations of failures can be identified. -The cice.t-test.py requires memory to store multiple two-dimensional fields spanning +The ``cice.t-test.py`` requires memory to store multiple two-dimensional fields spanning 1825 unique timesteps, a total of several GB. An appropriate resource is needed to run the script. If the script runs out of memory on an interactive resource, try logging into a batch resource or finding a large memory node. +The ``cice.t-test.py`` script will also attempt to generate plots of the mean ice thickness +for both the baseline and test cases. Additionally, if the 2-stage test fails then the +script will attempt to plot a map showing the grid cells that failed the test. For a +full list of options, run ``python cice.t-test.py -h``. + + End-To-End Testing Procedure ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~