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)