pivdata_loc = glob.glob(parentdir + '/PIVlab*') resultdir = os.path.join(parentdir, resultdirname) for pivdatum_loc in pivdata_loc: # Extract desired displacement if args.mode == 'constant': mag = fs.get_float_from_str(pivdatum_loc, 'mag', '.h5') # velocity magnitude mag_str = fs.convert_float_to_decimalstr(mag) mag_str_2 = fs.convert_float_to_decimalstr(mag, zpad=4) # for naming scheme # Plotting settings Part 2 vmin, vmax = mag * 0, mag * 1.2 # Load pivlab output pivdata = rw.read_hdf5(pivdatum_loc) xx, yy = pivdata['x'], pivdata['y'] ux, uy = pivdata['ux'][..., 0], pivdata['uy'][..., 0] # Find an original velocity field data for fakedatum in fakedata: if mag_str in fakedatum: print 'Fake data found!' # update iws and disps for heatmap iws.append(iw) disps.append(mag) # Load fake data fdata = rw.read_hdf5(fakedatum) xx0, yy0 = fdata['x'], fdata['y'] ux0, uy0 = fdata['ux'], fdata['uy']
resultdir = os.path.join(parentdir, resultdirname) for pivdatum_loc in pivdata_loc: # Extract desired displacement if args.mode == 'constant': mag = fs.get_float_from_str(pivdatum_loc, 'mag', '.h5') # velocity magnitude mag_str = fs.convert_float_to_decimalstr(mag) mag_str_2 = fs.convert_float_to_decimalstr( mag, zpad=4) # for naming scheme # Plotting settings Part 2 vmin, vmax = mag * 0, mag * 1.2 # Load pivlab output pivdata = rw.read_hdf5(pivdatum_loc) xx, yy = pivdata['x'], pivdata['y'] ux, uy = pivdata['ux'][..., 0], pivdata['uy'][..., 0] fig1, ax11, cc11 = graph.color_plot(xx, yy, ux, vmin=vmin, vmax=vmax, cmap=cmap2, fignum=1, subplot=231) fig1, ax14, cc14 = graph.color_plot(xx, yy, uy, vmin=-1,
) parser.add_argument('-fps', '--fps', help='frame rate of recorded video. default: 2000.', type=float, default=2000. ) parser.add_argument('-cutoff', '--cutoff', help='Energy cutoff in mm2/s2. default: 3x10^4', type=float, default=1.*10**4 ) args = parser.parse_args() dir = os.path.split(args.filepath)[0] filepath = args.filepath data = rw.read_hdf5(filepath) e_raw = np.asarray(data['energy']) print e_raw.shape # (z, x, y) is easy to work with dragonfly # e_raw2 = np.swapaxes(e_raw, 0, 1) # e = np.swapaxes(e_raw2, 1, 2) e = e_raw e = e * (args.fps*args.scale)**2 cutoffe = args.cutoff print e.shape print 'energy maximum, mean:', np.nanmax(e), np.nanmean(e) # Make sure data does not contain np.nan or np.inf. if so replace with zero.
# Plotting settings cmap = 'RdBu' # cmap = 'magma' params = {'figure.figsize': (18, 14), 'xtick.labelsize': 14, # tick 'ytick.labelsize': 14 } graph.update_figure_params(params) # Load fake data fkp = args.fakedatapath data = rw.read_hdf5(fkp) xx, yy = data['x'], data['y'] ux0, uy0 = data['ux'], data['uy'] # Coarse-grain data nrows_sub, ncolumns_sub = args.iw, args.iw # number of pixels to average over xx_coarse = fa.coarse_grain_2darr_overwrap(xx, nrows_sub, ncolumns_sub, overwrap=0.5) yy_coarse = fa.coarse_grain_2darr_overwrap(yy, nrows_sub, ncolumns_sub, overwrap=0.5) ux0_coarse = fa.coarse_grain_2darr_overwrap(ux0, nrows_sub, ncolumns_sub, overwrap=0.5) uy0_coarse = fa.coarse_grain_2darr_overwrap(uy0, nrows_sub, ncolumns_sub, overwrap=0.5) fig1, ax11, cc11 = graph.color_plot(xx, yy, ux0, cmap=cmap, vmin=-2, vmax=2, fignum=1, subplot=221) fig1, ax12, cc12 = graph.color_plot(xx_coarse, yy_coarse, ux0_coarse, cmap=cmap, vmin=-2, vmax=2, fignum=1, subplot=222)