'pick labels for output figures')
label_args.add_argument('--xlabel', default='Time (ps)')
label_args.add_argument('--ylabel', default='Maximum shear (1/ps)')
label_args.add_argument('--title', default='Maximum found shear of system per time')
# Parse and control for action
args = parser.parse_args()
# Plot options
colours = get_colours(args.colour, 2)
linestyles = get_linestyles(args.linestyle, 2)
labels, draw_legend = get_labels(args.label, 2)
# Define system and add data maps
system = System()
system.files(base=args.datamap, start=args.begin, end=args.end)
# Collect shear data in list
frames = []
max_shear = []
floor = args.floor
ceil = floor + args.num_shear
if ceil <= floor:
parser.error('number of cell rows to calculate shear over (--number) must be positive')
rows = [floor, ceil]
for i, _file in enumerate(system.datamaps):
print("Reading %s (%d of %d) ... " % (_file, i+1, len(system.datamaps)), end='')
sys.stdout.flush()
label_args.add_argument('--xlabel', default='Time (ps)')
label_args.add_argument('--ylabel', default='Dissipated energy (kJ/mol)')
label_args.add_argument('--title', default='')
args = parser.parse_args()
xlims = [args.xmin, args.xmax]
ylims = [args.ymin, args.ymax]
times = []
d_visc_energy = []
d_slip_energy = []
# Create system
system = System(base = args.base)
system.files(start = args.start, end = args.end)
for frame, _file in enumerate(system.datamaps):
datamap = DataMap(_file, min_mass = args.min_mass)
times.append(frame*args.delta_t)
d_visc_energy.append(datamap._sum_viscous_dissipation(args.width,
args.delta_t, args.num_cells, args.viscosity, args.mass_flow))
if args.slip:
d_slip_energy.append(calc_slip_dissipation(datamap, args.floor))
times = list(np.array(times) + args.time_start)
if args.print:
for i, (time, energy) in enumerate(zip(times, d_visc_energy)):
parser.add_argument('-vadj', '--adjust_velocity', action='store_true',
help="remove averaged contact line velocity from flow velocity")
parser.add_argument('-dt', '--delta_t', type=float, default=10.,
help="time between frames in ps (default: 10)")
parser.add_argument('--noheaders', action='store_false', dest='header',
help="do not output position and height headers")
parser.add_argument('--nooutput', action='store_false', dest='do_output',
help="do not output cells")
# Parse and control for action
args = parser.parse_args()
# If base given, create system
if args.base != None:
system = System(base = args.base)
system.files(start = args.begin, end = args.end)
else:
system = System()
system.datamaps = [args.file]
if args.average:
args.do_output = False
var = []
if args.type == 'temp':
var.append('T')
elif args.type == 'flow':
var.append('U')
var.append('V')
else:
# Decorations
label_args = parser.add_argument_group('label options',
'pick labels for output figures')
label_args.add_argument('--xlabel', default='Mass flow along x (nm/ps)')
label_args.add_argument('--ylabel', default='Height (nm)')
label_args.add_argument('--title', default='')
# Parse and control for action
args = parser.parse_args()
# Define system and add data maps
system = System()
if args.num_combine == 0:
system.datamaps.append(args.datamap)
elif args.num_combine >= 1:
system.files(base=args.datamap, start=args.start, end=args.start+args.num_combine-1)
else:
parser.error('negative -n supplied')
# Collect profile data into 2D arrays
profile = {'data': [], 'count': [], 'std': [], 'error': []}
for i, _file in enumerate(system.datamaps):
datamap = DataMap(_file, min_mass=args.min_mass)
height = {'data': []}
for _type in profile.keys():
profile[_type].append([])
for row in datamap.cells:
count = 0
i += 1
else:
combined.update({"U": 0.0, "V": 0.0})
# Append to container
output.cells.append(combined)
# Convert by hand to good format and save
output.cells = np.array(output.cells)
output._info = output.info
output._grid()
return output
# Create containers
dens = System(base=args.dens)
dens.files(start=args.start, end=args.end, numdigits=args.numdigits, ext=args.extension)
flow = System(base=args.flow)
flow.files(start=args.start, end=args.end, numdigits=args.numdigits, ext=args.extension)
# Combine and output one by one
for i, _list in enumerate(zip(dens.datamaps, flow.datamaps)):
print("\rCombining maps %d ..." % (i + 1), end=" ")
output = combine(dict(zip(["dens", "flow"], _list)))
num = ("%%0%dd" % args.numdigits) % (i + args.start)
save = "%s%s%s" % (args.output, num, args.extension)
output.save(save)