def process_singlecmds(singlecmds, G):
"""Checks the validity of command parameters and creates instances of classes of parameters.
Args:
singlecmds (dict): Commands that can only occur once in the model.
G (class): Grid class instance - holds essential parameters describing the model.
"""
# Check validity of command parameters in order needed
# messages
cmd = '#messages'
if singlecmds[cmd] is not None:
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if singlecmds[cmd].lower() == 'y':
G.messages = True
elif singlecmds[cmd].lower() == 'n':
G.messages = False
else:
raise CmdInputError(cmd +
' requires input values of either y or n')
# Title
cmd = '#title'
if singlecmds[cmd] is not None:
G.title = singlecmds[cmd]
if G.messages:
print('Model title: {}'.format(G.title))
# Get information about host machine
hostinfo = get_host_info()
# Number of threads (OpenMP) to use
cmd = '#num_threads'
if sys.platform == 'darwin':
os.environ[
'OMP_WAIT_POLICY'] = 'ACTIVE' # Should waiting threads consume CPU power (can drastically effect performance)
os.environ[
'OMP_DYNAMIC'] = 'FALSE' # Number of threads may be adjusted by the run time environment to best utilize system resources
os.environ[
'OMP_PLACES'] = 'cores' # Each place corresponds to a single core (having one or more hardware threads)
os.environ['OMP_PROC_BIND'] = 'TRUE' # Bind threads to physical cores
# os.environ['OMP_DISPLAY_ENV'] = 'TRUE' # Prints OMP version and environment variables (useful for debug)
# Catch bug with Windows Subsystem for Linux (https://github.com/Microsoft/BashOnWindows/issues/785)
if 'Microsoft' in hostinfo['osversion']:
os.environ['KMP_AFFINITY'] = 'disabled'
del os.environ['OMP_PLACES']
del os.environ['OMP_PROC_BIND']
if singlecmds[cmd] is not None:
tmp = tuple(int(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(
cmd +
' requires exactly one parameter to specify the number of threads to use'
)
if tmp[0] < 1:
raise CmdInputError(
cmd + ' requires the value to be an integer not less than one')
G.nthreads = tmp[0]
os.environ['OMP_NUM_THREADS'] = str(G.nthreads)
elif os.environ.get('OMP_NUM_THREADS'):
G.nthreads = int(os.environ.get('OMP_NUM_THREADS'))
else:
# Set number of threads to number of physical CPU cores
G.nthreads = hostinfo['physicalcores']
os.environ['OMP_NUM_THREADS'] = str(G.nthreads)
if G.messages:
print('Number of CPU (OpenMP) threads: {}'.format(G.nthreads))
if G.nthreads > hostinfo['physicalcores']:
print(
Fore.RED +
'WARNING: You have specified more threads ({}) than available physical CPU cores ({}). This may lead to degraded performance.'
.format(G.nthreads, hostinfo['physicalcores']) + Style.RESET_ALL)
# Spatial discretisation
cmd = '#dx_dy_dz'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
if tmp[0] <= 0:
raise CmdInputError(
cmd +
' requires the x-direction spatial step to be greater than zero')
if tmp[1] <= 0:
raise CmdInputError(
cmd +
' requires the y-direction spatial step to be greater than zero')
if tmp[2] <= 0:
raise CmdInputError(
cmd +
' requires the z-direction spatial step to be greater than zero')
G.dx = tmp[0]
G.dy = tmp[1]
G.dz = tmp[2]
if G.messages:
print('Spatial discretisation: {:g} x {:g} x {:g}m'.format(
G.dx, G.dy, G.dz))
# Domain
cmd = '#domain'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.nx = round_value(tmp[0] / G.dx)
G.ny = round_value(tmp[1] / G.dy)
G.nz = round_value(tmp[2] / G.dz)
if G.nx == 0 or G.ny == 0 or G.nz == 0:
raise CmdInputError(cmd +
' requires at least one cell in every dimension')
if G.messages:
print(
'Domain size: {:g} x {:g} x {:g}m ({:d} x {:d} x {:d} = {:g} cells)'
.format(tmp[0], tmp[1], tmp[2], G.nx, G.ny, G.nz,
(G.nx * G.ny * G.nz)))
# Estimate memory (RAM) usage
memestimate = memory_usage(G)
# Check if model can be built and/or run on host
if memestimate > hostinfo['ram']:
raise GeneralError(
'Estimated memory (RAM) required ~{} exceeds {} detected!\n'.
format(human_size(memestimate),
human_size(hostinfo['ram'], a_kilobyte_is_1024_bytes=True)))
if G.messages:
print('Estimated memory (RAM) required: ~{}'.format(
human_size(memestimate)))
# Time step CFL limit (use either 2D or 3D) and default PML thickness
if G.nx == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dy) * (1 / G.dy) + (1 / G.dz) *
(1 / G.dz)))
G.dimension = '2D'
G.pmlthickness['x0'] = 0
G.pmlthickness['xmax'] = 0
elif G.ny == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dz) *
(1 / G.dz)))
G.dimension = '2D'
G.pmlthickness['y0'] = 0
G.pmlthickness['ymax'] = 0
elif G.nz == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) *
(1 / G.dy)))
G.dimension = '2D'
G.pmlthickness['z0'] = 0
G.pmlthickness['zmax'] = 0
else:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) *
(1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
G.dimension = '3D'
# Round down time step to nearest float with precision one less than hardware maximum. Avoids inadvertently exceeding the CFL due to binary representation of floating point number.
G.dt = round_value(G.dt, decimalplaces=d.getcontext().prec - 1)
if G.messages:
print('Time step (at {} CFL limit): {:g} secs'.format(
G.dimension, G.dt))
# Time step stability factor
cmd = '#time_step_stability_factor'
if singlecmds[cmd] is not None:
tmp = tuple(float(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if tmp[0] <= 0 or tmp[0] > 1:
raise CmdInputError(
cmd +
' requires the value of the time step stability factor to be between zero and one'
)
G.dt = G.dt * tmp[0]
if G.messages:
print('Time step (modified): {:g} secs'.format(G.dt))
# Time window
cmd = '#time_window'
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(
cmd +
' requires exactly one parameter to specify the time window. Either in seconds or number of iterations.'
)
tmp = tmp[0].lower()
# If number of iterations given
try:
tmp = int(tmp)
G.timewindow = (tmp - 1) * G.dt
G.iterations = tmp
# If real floating point value given
except:
tmp = float(tmp)
if tmp > 0:
G.timewindow = tmp
G.iterations = round_value((tmp / G.dt)) + 1
else:
raise CmdInputError(cmd + ' must have a value greater than zero')
if G.messages:
print('Time window: {:g} secs ({} iterations)'.format(
G.timewindow, G.iterations))
# PML
cmd = '#pml_cells'
if singlecmds[cmd] is not None:
tmp = singlecmds[cmd].split()
if len(tmp) != 1 and len(tmp) != 6:
raise CmdInputError(cmd + ' requires either one or six parameters')
if len(tmp) == 1:
for key in G.pmlthickness.keys():
G.pmlthickness[key] = int(tmp[0])
else:
G.pmlthickness['x0'] = int(tmp[0])
G.pmlthickness['y0'] = int(tmp[1])
G.pmlthickness['z0'] = int(tmp[2])
G.pmlthickness['xmax'] = int(tmp[3])
G.pmlthickness['ymax'] = int(tmp[4])
G.pmlthickness['zmax'] = int(tmp[5])
if 2 * G.pmlthickness['x0'] >= G.nx or 2 * G.pmlthickness[
'y0'] >= G.ny or 2 * G.pmlthickness[
'z0'] >= G.nz or 2 * G.pmlthickness[
'xmax'] >= G.nx or 2 * G.pmlthickness[
'ymax'] >= G.ny or 2 * G.pmlthickness['zmax'] >= G.nz:
raise CmdInputError(cmd + ' has too many cells for the domain size')
# src_steps
cmd = '#src_steps'
if singlecmds[cmd] is not None:
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.srcsteps[0] = round_value(float(tmp[0]) / G.dx)
G.srcsteps[1] = round_value(float(tmp[1]) / G.dy)
G.srcsteps[2] = round_value(float(tmp[2]) / G.dz)
if G.messages:
print(
'Simple sources will step {:g}m, {:g}m, {:g}m for each model run.'
.format(G.srcsteps[0] * G.dx, G.srcsteps[1] * G.dy,
G.srcsteps[2] * G.dz))
# rx_steps
cmd = '#rx_steps'
if singlecmds[cmd] is not None:
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.rxsteps[0] = round_value(float(tmp[0]) / G.dx)
G.rxsteps[1] = round_value(float(tmp[1]) / G.dy)
G.rxsteps[2] = round_value(float(tmp[2]) / G.dz)
if G.messages:
print(
'All receivers will step {:g}m, {:g}m, {:g}m for each model run.'
.format(G.rxsteps[0] * G.dx, G.rxsteps[1] * G.dy,
G.rxsteps[2] * G.dz))
# Excitation file for user-defined source waveforms
cmd = '#excitation_file'
if singlecmds[cmd] is not None:
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
excitationfile = tmp[0]
# See if file exists at specified path and if not try input file directory
if not os.path.isfile(excitationfile):
excitationfile = os.path.abspath(
os.path.join(G.inputdirectory, excitationfile))
# Get waveform names
with open(excitationfile, 'r') as f:
waveformIDs = f.readline().split()
# Read all waveform values into an array
waveformvalues = np.loadtxt(excitationfile,
skiprows=1,
dtype=floattype)
for waveform in range(len(waveformIDs)):
if any(x.ID == waveformIDs[waveform] for x in G.waveforms):
raise CmdInputError(
'Waveform with ID {} already exists'.format(
waveformIDs[waveform]))
w = Waveform()
w.ID = waveformIDs[waveform]
w.type = 'user'
if len(waveformvalues.shape) == 1:
w.uservalues = waveformvalues[:]
else:
w.uservalues = waveformvalues[:, waveform]
if G.messages:
print('User waveform {} created.'.format(w.ID))
G.waveforms.append(w)
def process_singlecmds(singlecmds, G):
"""Checks the validity of command parameters and creates instances of classes of parameters.
Args:
singlecmds (dict): Commands that can only occur once in the model.
G (class): Grid class instance - holds essential parameters describing the model.
"""
# Check validity of command parameters in order needed
# messages
cmd = '#messages'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if singlecmds[cmd].lower() == 'y':
G.messages = True
elif singlecmds[cmd].lower() == 'n':
G.messages = False
else:
raise CmdInputError(cmd + ' requires input values of either y or n')
# Title
cmd = '#title'
if singlecmds[cmd] != 'None':
G.title = singlecmds[cmd]
if G.messages:
print('Model title: {}'.format(G.title))
# Number of processors to run on (OpenMP)
cmd = '#num_threads'
os.environ['OMP_WAIT_POLICY'] = 'active'
os.environ['OMP_DYNAMIC'] = 'false'
os.environ['OMP_PROC_BIND'] = 'true'
if singlecmds[cmd] != 'None':
tmp = tuple(int(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter to specify the number of threads to use')
if tmp[0] < 1:
raise CmdInputError(cmd + ' requires the value to be an integer not less than one')
G.nthreads = tmp[0]
os.environ['OMP_NUM_THREADS'] = str(G.nthreads)
elif os.environ.get('OMP_NUM_THREADS'):
G.nthreads = int(os.environ.get('OMP_NUM_THREADS'))
else:
# Set number of threads to number of physical CPU cores, i.e. avoid hyperthreading with OpenMP
G.nthreads = psutil.cpu_count(logical=False)
os.environ['OMP_NUM_THREADS'] = str(G.nthreads)
if G.messages:
print('Number of threads: {}'.format(G.nthreads))
if G.nthreads > psutil.cpu_count(logical=False):
print('\nWARNING: You have specified more threads ({}) than available physical CPU cores ({}). This may lead to degraded performance.'.format(G.nthreads, psutil.cpu_count(logical=False)))
# Spatial discretisation
cmd = '#dx_dy_dz'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
if tmp[0] <= 0:
raise CmdInputError(cmd + ' requires the x-direction spatial step to be greater than zero')
if tmp[1] <= 0:
raise CmdInputError(cmd + ' requires the y-direction spatial step to be greater than zero')
if tmp[2] <= 0:
raise CmdInputError(cmd + ' requires the z-direction spatial step to be greater than zero')
G.dx = tmp[0]
G.dy = tmp[1]
G.dz = tmp[2]
if G.messages:
print('Spatial discretisation: {:g} x {:g} x {:g}m'.format(G.dx, G.dy, G.dz))
# Domain
cmd = '#domain'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.nx = round_value(tmp[0]/G.dx)
G.ny = round_value(tmp[1]/G.dy)
G.nz = round_value(tmp[2]/G.dz)
if G.nx == 0 or G.ny == 0 or G.nz == 0:
raise CmdInputError(cmd + ' requires at least one cell in every dimension')
if G.messages:
print('Domain size: {:g} x {:g} x {:g}m ({:d} x {:d} x {:d} = {:g} cells)'.format(tmp[0], tmp[1], tmp[2], G.nx, G.ny, G.nz, (G.nx * G.ny * G.nz)))
# Guesstimate at memory usage
mem = (((G.nx + 1) * (G.ny + 1) * (G.nz + 1) * 13 * np.dtype(floattype).itemsize + (G.nx + 1) * (G.ny + 1) * (G.nz + 1) * 18) * 1.1) + 30e6
print('Memory (RAM) usage: ~{} required, {} available'.format(human_size(mem), human_size(psutil.virtual_memory().total)))
# Time step CFL limit (use either 2D or 3D) and default PML thickness
if G.nx == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
G.dtlimit = '2D'
G.pmlthickness = (0, G.pmlthickness, G.pmlthickness, 0, G.pmlthickness, G.pmlthickness)
elif G.ny == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dz) * (1 / G.dz)))
G.dtlimit = '2D'
G.pmlthickness = (G.pmlthickness, 0, G.pmlthickness, G.pmlthickness, 0, G.pmlthickness)
elif G.nz == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy)))
G.dtlimit = '2D'
G.pmlthickness = (G.pmlthickness, G.pmlthickness, 0, G.pmlthickness, G.pmlthickness, 0)
else:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
G.dtlimit = '3D'
G.pmlthickness = (G.pmlthickness, G.pmlthickness, G.pmlthickness, G.pmlthickness, G.pmlthickness, G.pmlthickness)
# Round down time step to nearest float with precision one less than hardware maximum. Avoids inadvertently exceeding the CFL due to binary representation of floating point number.
G.dt = round_value(G.dt, decimalplaces=d.getcontext().prec - 1)
if G.messages:
print('Time step (at {} CFL limit): {:g} secs'.format(G.dtlimit, G.dt))
# Time step stability factor
cmd = '#time_step_stability_factor'
if singlecmds[cmd] != 'None':
tmp = tuple(float(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if tmp[0] <= 0 or tmp[0] > 1:
raise CmdInputError(cmd + ' requires the value of the time step stability factor to be between zero and one')
G.dt = G.dt * tmp[0]
if G.messages:
print('Time step (modified): {:g} secs'.format(G.dt))
# Time window
cmd = '#time_window'
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter to specify the time window. Either in seconds or number of iterations.')
tmp = tmp[0].lower()
# If number of iterations given
try:
tmp = int(tmp)
G.timewindow = (tmp - 1) * G.dt
G.iterations = tmp
# If real floating point value given
except:
tmp = float(tmp)
if tmp > 0:
G.timewindow = tmp
G.iterations = round_value((tmp / G.dt)) + 1
else:
raise CmdInputError(cmd + ' must have a value greater than zero')
if G.messages:
print('Time window: {:g} secs ({} iterations)'.format(G.timewindow, G.iterations))
# PML
cmd = '#pml_cells'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1 and len(tmp) != 6:
raise CmdInputError(cmd + ' requires either one or six parameters')
if len(tmp) == 1:
G.pmlthickness = (int(tmp[0]), int(tmp[0]), int(tmp[0]), int(tmp[0]), int(tmp[0]), int(tmp[0]))
else:
G.pmlthickness = (int(tmp[0]), int(tmp[1]), int(tmp[2]), int(tmp[3]), int(tmp[4]), int(tmp[5]))
if 2*G.pmlthickness[0] >= G.nx or 2*G.pmlthickness[1] >= G.ny or 2*G.pmlthickness[2] >= G.nz or 2*G.pmlthickness[3] >= G.nx or 2*G.pmlthickness[4] >= G.ny or 2*G.pmlthickness[5] >= G.nz:
raise CmdInputError(cmd + ' has too many cells for the domain size')
# src_steps
cmd = '#src_steps'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.srcstepx = round_value(float(tmp[0])/G.dx)
G.srcstepy = round_value(float(tmp[1])/G.dy)
G.srcstepz = round_value(float(tmp[2])/G.dz)
if G.messages:
print('Simple sources will step {:g}m, {:g}m, {:g}m for each model run.'.format(G.srcstepx * G.dx, G.srcstepy * G.dy, G.srcstepz * G.dz))
# rx_steps
cmd = '#rx_steps'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.rxstepx = round_value(float(tmp[0])/G.dx)
G.rxstepy = round_value(float(tmp[1])/G.dy)
G.rxstepz = round_value(float(tmp[2])/G.dz)
if G.messages:
print('All receivers will step {:g}m, {:g}m, {:g}m for each model run.'.format(G.rxstepx * G.dx, G.rxstepy * G.dy, G.rxstepz * G.dz))
# Excitation file for user-defined source waveforms
cmd = '#excitation_file'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
excitationfile = tmp[0]
# See if file exists at specified path and if not try input file directory
if not os.path.isfile(excitationfile):
excitationfile = os.path.abspath(os.path.join(G.inputdirectory, excitationfile))
# Get waveform names
with open(excitationfile, 'r') as f:
waveformIDs = f.readline().split()
# Read all waveform values into an array
waveformvalues = np.loadtxt(excitationfile, skiprows=1, dtype=floattype)
for waveform in range(len(waveformIDs)):
if any(x.ID == waveformIDs[waveform] for x in G.waveforms):
raise CmdInputError('Waveform with ID {} already exists'.format(waveformIDs[waveform]))
w = Waveform()
w.ID = waveformIDs[waveform]
w.type = 'user'
if len(waveformvalues.shape) == 1:
w.uservalues = waveformvalues[:]
else:
w.uservalues = waveformvalues[:,waveform]
if G.messages:
print('User waveform {} created.'.format(w.ID))
G.waveforms.append(w)
def process_singlecmds(singlecmds, multicmds, G):
"""Checks the validity of command parameters and creates instances of classes of parameters.
Args:
singlecmds (dict): Commands that can only occur once in the model.
multicmds (dict): Commands that can have multiple instances in the model (required to pass to process_materials_file function).
G (class): Grid class instance - holds essential parameters describing the model.
"""
# Check validity of command parameters in order needed
# messages
cmd = "#messages"
if singlecmds[cmd] != "None":
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + " requires exactly one parameter")
if singlecmds[cmd].lower() == "y":
G.messages = True
elif singlecmds[cmd].lower() == "n":
G.messages = False
else:
raise CmdInputError(cmd + " requires input values of either y or n")
# Title
cmd = "#title"
if singlecmds[cmd] != "None":
G.title = singlecmds[cmd]
if G.messages:
print("Model title: {}".format(G.title))
# Number of processors to run on (OpenMP)
cmd = "#num_threads"
ompthreads = os.environ.get("OMP_NUM_THREADS")
if singlecmds[cmd] != "None":
tmp = tuple(int(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + " requires exactly one parameter to specify the number of threads to use")
if tmp[0] < 1:
raise CmdInputError(cmd + " requires the value to be an integer not less than one")
G.nthreads = tmp[0]
elif ompthreads:
G.nthreads = int(ompthreads)
else:
# Set number of threads to number of physical CPU cores, i.e. avoid hyperthreading with OpenMP
G.nthreads = psutil.cpu_count(logical=False)
if G.messages:
print("Number of threads: {}".format(G.nthreads))
# Spatial discretisation
cmd = "#dx_dy_dz"
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + " requires exactly three parameters")
if tmp[0] <= 0:
raise CmdInputError(cmd + " requires the x-direction spatial step to be greater than zero")
if tmp[1] <= 0:
raise CmdInputError(cmd + " requires the y-direction spatial step to be greater than zero")
if tmp[2] <= 0:
raise CmdInputError(cmd + " requires the z-direction spatial step to be greater than zero")
G.dx = tmp[0]
G.dy = tmp[1]
G.dz = tmp[2]
if G.messages:
print("Spatial discretisation: {:g} x {:g} x {:g}m".format(G.dx, G.dy, G.dz))
# Domain
cmd = "#domain"
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + " requires exactly three parameters")
G.nx = round_value(tmp[0] / G.dx)
G.ny = round_value(tmp[1] / G.dy)
G.nz = round_value(tmp[2] / G.dz)
if G.messages:
print(
"Model domain: {:g} x {:g} x {:g}m ({:d} x {:d} x {:d} = {:g} cells)".format(
tmp[0], tmp[1], tmp[2], G.nx, G.ny, G.nz, (G.nx * G.ny * G.nz)
)
)
mem = (
(
(G.nx + 1) * (G.ny + 1) * (G.nz + 1) * 13 * np.dtype(floattype).itemsize
+ (G.nx + 1) * (G.ny + 1) * (G.nz + 1) * 18
)
* 1.1
) + 30e6
print(
"Memory (RAM) usage: ~{} required, {} available".format(
human_size(mem), human_size(psutil.virtual_memory().total)
)
)
# Time step CFL limit - use either 2D or 3D (default)
cmd = "#time_step_limit_type"
if singlecmds[cmd] != "None":
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + " requires exactly one parameter")
if singlecmds[cmd].lower() == "2d":
if G.nx == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
elif G.ny == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dz) * (1 / G.dz)))
elif G.nz == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy)))
else:
raise CmdInputError(cmd + " 2D CFL limit can only be used when one dimension of the domain is one cell")
elif singlecmds[cmd].lower() == "3d":
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
else:
raise CmdInputError(cmd + " requires input values of either 2D or 3D")
else:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
# Round down time step to nearest float with precision one less than hardware maximum. Avoids inadvertently exceeding the CFL due to binary representation of floating point number.
G.dt = round_value(G.dt, decimalplaces=d.getcontext().prec - 1)
if G.messages:
print("Time step: {:g} secs".format(G.dt))
# Time step stability factor
cmd = "#time_step_stability_factor"
if singlecmds[cmd] != "None":
tmp = tuple(float(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + " requires exactly one parameter")
if tmp[0] <= 0 or tmp[0] > 1:
raise CmdInputError(
cmd + " requires the value of the time step stability factor to be between zero and one"
)
G.dt = G.dt * tmp[0]
if G.messages:
print("Time step (modified): {:g} secs".format(G.dt))
# Time window
cmd = "#time_window"
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(
cmd
+ " requires exactly one parameter to specify the time window. Either in seconds or number of iterations."
)
tmp = tmp[0].lower()
# If real floating point value given
if "." in tmp or "e" in tmp:
if float(tmp) > 0:
G.timewindow = float(tmp)
G.iterations = round_value((float(tmp) / G.dt)) + 1
else:
raise CmdInputError(cmd + " must have a value greater than zero")
# If number of iterations given
else:
G.timewindow = (int(tmp) - 1) * G.dt
G.iterations = int(tmp)
if G.messages:
print("Time window: {:g} secs ({} iterations)".format(G.timewindow, G.iterations))
# PML
cmd = "#pml_cells"
if singlecmds[cmd] != "None":
tmp = singlecmds[cmd].split()
if len(tmp) != 1 and len(tmp) != 6:
raise CmdInputError(cmd + " requires either one or six parameters")
if len(tmp) == 1:
G.pmlthickness = (int(tmp[0]), int(tmp[0]), int(tmp[0]), int(tmp[0]), int(tmp[0]), int(tmp[0]))
else:
G.pmlthickness = (int(tmp[0]), int(tmp[1]), int(tmp[2]), int(tmp[3]), int(tmp[4]), int(tmp[5]))
if (
2 * G.pmlthickness[0] >= G.nx
or 2 * G.pmlthickness[1] >= G.ny
or 2 * G.pmlthickness[2] >= G.nz
or 2 * G.pmlthickness[3] >= G.nx
or 2 * G.pmlthickness[4] >= G.ny
or 2 * G.pmlthickness[5] >= G.nz
):
raise CmdInputError(cmd + " has too many cells for the domain size")
# src_steps
cmd = "#src_steps"
if singlecmds[cmd] != "None":
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + " requires exactly three parameters")
G.srcstepx = round_value(float(tmp[0]) / G.dx)
G.srcstepy = round_value(float(tmp[1]) / G.dy)
G.srcstepz = round_value(float(tmp[2]) / G.dz)
if G.messages:
print(
"All sources will step {:g}m, {:g}m, {:g}m for each model run.".format(
G.srcstepx * G.dx, G.srcstepy * G.dy, G.srcstepz * G.dz
)
)
# rx_steps
cmd = "#rx_steps"
if singlecmds[cmd] != "None":
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + " requires exactly three parameters")
G.rxstepx = round_value(float(tmp[0]) / G.dx)
G.rxstepy = round_value(float(tmp[1]) / G.dy)
G.rxstepz = round_value(float(tmp[2]) / G.dz)
if G.messages:
print(
"All receivers will step {:g}m, {:g}m, {:g}m for each model run.".format(
G.rxstepx * G.dx, G.rxstepy * G.dy, G.rxstepz * G.dz
)
)
# Excitation file for user-defined source waveforms
cmd = "#excitation_file"
if singlecmds[cmd] != "None":
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + " requires exactly one parameter")
excitationfile = tmp[0]
# Open file and get waveform names
with open(excitationfile, "r") as f:
waveformIDs = f.readline().split()
# Read all waveform values into an array
waveformvalues = np.loadtxt(excitationfile, skiprows=1, dtype=floattype)
for waveform in range(len(waveformIDs)):
if any(x.ID == waveformIDs[waveform] for x in G.waveforms):
raise CmdInputError("Waveform with ID {} already exists".format(waveformIDs[waveform]))
w = Waveform()
w.ID = waveformIDs[waveform]
w.type = "user"
if len(waveformvalues.shape) == 1:
w.uservalues = waveformvalues[:]
else:
w.uservalues = waveformvalues[:, waveform]
if G.messages:
print("User waveform {} created.".format(w.ID))
G.waveforms.append(w)
def process_singlecmds(singlecmds, G):
"""Checks the validity of command parameters and creates instances of classes of parameters.
Args:
singlecmds (dict): Commands that can only occur once in the model.
G (class): Grid class instance - holds essential parameters describing the model.
"""
# Check validity of command parameters in order needed
# messages
cmd = '#messages'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if singlecmds[cmd].lower() == 'y':
G.messages = True
elif singlecmds[cmd].lower() == 'n':
G.messages = False
else:
raise CmdInputError(cmd + ' requires input values of either y or n')
# Title
cmd = '#title'
if singlecmds[cmd] != 'None':
G.title = singlecmds[cmd]
if G.messages:
print('Model title: {}'.format(G.title))
# Number of threads (OpenMP) to use
cmd = '#num_threads'
if sys.platform == 'darwin':
os.environ['OMP_WAIT_POLICY'] = 'ACTIVE' # What to do with threads when they are waiting; can drastically effect performance
os.environ['OMP_DYNAMIC'] = 'FALSE'
os.environ['OMP_PROC_BIND'] = 'TRUE' # Bind threads to physical cores
if singlecmds[cmd] != 'None':
tmp = tuple(int(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter to specify the number of threads to use')
if tmp[0] < 1:
raise CmdInputError(cmd + ' requires the value to be an integer not less than one')
G.nthreads = tmp[0]
os.environ['OMP_NUM_THREADS'] = str(G.nthreads)
elif os.environ.get('OMP_NUM_THREADS'):
G.nthreads = int(os.environ.get('OMP_NUM_THREADS'))
else:
# Set number of threads to number of physical CPU cores, i.e. avoid hyperthreading with OpenMP
G.nthreads = psutil.cpu_count(logical=False)
os.environ['OMP_NUM_THREADS'] = str(G.nthreads)
if G.messages:
machineID, cpuID, osversion = get_machine_cpu_os()
print('Number of threads: {} ({})'.format(G.nthreads, cpuID))
if G.nthreads > psutil.cpu_count(logical=False):
print(Fore.RED + 'WARNING: You have specified more threads ({}) than available physical CPU cores ({}). This may lead to degraded performance.'.format(G.nthreads, psutil.cpu_count(logical=False)) + Style.RESET_ALL)
# Spatial discretisation
cmd = '#dx_dy_dz'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
if tmp[0] <= 0:
raise CmdInputError(cmd + ' requires the x-direction spatial step to be greater than zero')
if tmp[1] <= 0:
raise CmdInputError(cmd + ' requires the y-direction spatial step to be greater than zero')
if tmp[2] <= 0:
raise CmdInputError(cmd + ' requires the z-direction spatial step to be greater than zero')
G.dx = tmp[0]
G.dy = tmp[1]
G.dz = tmp[2]
if G.messages:
print('Spatial discretisation: {:g} x {:g} x {:g}m'.format(G.dx, G.dy, G.dz))
# Domain
cmd = '#domain'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.nx = round_value(tmp[0] / G.dx)
G.ny = round_value(tmp[1] / G.dy)
G.nz = round_value(tmp[2] / G.dz)
if G.nx == 0 or G.ny == 0 or G.nz == 0:
raise CmdInputError(cmd + ' requires at least one cell in every dimension')
if G.messages:
print('Domain size: {:g} x {:g} x {:g}m ({:d} x {:d} x {:d} = {:g} cells)'.format(tmp[0], tmp[1], tmp[2], G.nx, G.ny, G.nz, (G.nx * G.ny * G.nz)))
# Estimate memory (RAM) usage
stdoverhead = 70e6
floatarrays = (6 + 6 + 1) * (G.nx + 1) * (G.ny + 1) * (G.nz + 1) * np.dtype(floattype).itemsize # 6 x field arrays + 6 x ID arrays + 1 x solid array
rigidarray = (12 + 6) * (G.nx + 1) * (G.ny + 1) * (G.nz + 1) * np.dtype(np.int8).itemsize
memestimate = stdoverhead + floatarrays + rigidarray
if memestimate > psutil.virtual_memory().total:
print(Fore.RED + 'WARNING: Estimated memory (RAM) required ~{} exceeds {} detected!\n'.format(human_size(memestimate), human_size(psutil.virtual_memory().total, a_kilobyte_is_1024_bytes=True)) + Style.RESET_ALL)
if G.messages:
print('Estimated memory (RAM) required: ~{} ({} detected)'.format(human_size(memestimate), human_size(psutil.virtual_memory().total, a_kilobyte_is_1024_bytes=True)))
# Time step CFL limit (use either 2D or 3D) and default PML thickness
if G.nx == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
G.dimension = '2D'
G.pmlthickness['xminus'] = 0
G.pmlthickness['xplus'] = 0
elif G.ny == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dz) * (1 / G.dz)))
G.dimension = '2D'
G.pmlthickness['yminus'] = 0
G.pmlthickness['yplus'] = 0
elif G.nz == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy)))
G.dimension = '2D'
G.pmlthickness['zminus'] = 0
G.pmlthickness['zplus'] = 0
else:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) * (1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
G.dimension = '3D'
# Round down time step to nearest float with precision one less than hardware maximum. Avoids inadvertently exceeding the CFL due to binary representation of floating point number.
G.dt = round_value(G.dt, decimalplaces=d.getcontext().prec - 1)
if G.messages:
print('Time step (at {} CFL limit): {:g} secs'.format(G.dimension, G.dt))
# Time step stability factor
cmd = '#time_step_stability_factor'
if singlecmds[cmd] != 'None':
tmp = tuple(float(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if tmp[0] <= 0 or tmp[0] > 1:
raise CmdInputError(cmd + ' requires the value of the time step stability factor to be between zero and one')
G.dt = G.dt * tmp[0]
if G.messages:
print('Time step (modified): {:g} secs'.format(G.dt))
# Time window
cmd = '#time_window'
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter to specify the time window. Either in seconds or number of iterations.')
tmp = tmp[0].lower()
# If number of iterations given
try:
tmp = int(tmp)
G.timewindow = (tmp - 1) * G.dt
G.iterations = tmp
# If real floating point value given
except:
tmp = float(tmp)
if tmp > 0:
G.timewindow = tmp
G.iterations = round_value((tmp / G.dt)) + 1
else:
raise CmdInputError(cmd + ' must have a value greater than zero')
if G.messages:
print('Time window: {:g} secs ({} iterations)'.format(G.timewindow, G.iterations))
# PML
cmd = '#pml_cells'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1 and len(tmp) != 6:
raise CmdInputError(cmd + ' requires either one or six parameters')
if len(tmp) == 1:
for key in G.pmlthickness.keys():
G.pmlthickness[key] = int(tmp[0])
else:
G.pmlthickness['xminus'] = int(tmp[0])
G.pmlthickness['yminus'] = int(tmp[1])
G.pmlthickness['zminus'] = int(tmp[2])
G.pmlthickness['xplus'] = int(tmp[3])
G.pmlthickness['yplus'] = int(tmp[4])
G.pmlthickness['zplus'] = int(tmp[5])
if 2 * G.pmlthickness['xminus'] >= G.nx or 2 * G.pmlthickness['yminus'] >= G.ny or 2 * G.pmlthickness['zminus'] >= G.nz or 2 * G.pmlthickness['xplus'] >= G.nx or 2 * G.pmlthickness['yplus'] >= G.ny or 2 * G.pmlthickness['zplus'] >= G.nz:
raise CmdInputError(cmd + ' has too many cells for the domain size')
# src_steps
cmd = '#src_steps'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.srcsteps[0] = round_value(float(tmp[0]) / G.dx)
G.srcsteps[1] = round_value(float(tmp[1]) / G.dy)
G.srcsteps[2] = round_value(float(tmp[2]) / G.dz)
if G.messages:
print('Simple sources will step {:g}m, {:g}m, {:g}m for each model run.'.format(G.srcsteps[0] * G.dx, G.srcsteps[1] * G.dy, G.srcsteps[2] * G.dz))
# rx_steps
cmd = '#rx_steps'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.rxsteps[0] = round_value(float(tmp[0]) / G.dx)
G.rxsteps[1] = round_value(float(tmp[1]) / G.dy)
G.rxsteps[2] = round_value(float(tmp[2]) / G.dz)
if G.messages:
print('All receivers will step {:g}m, {:g}m, {:g}m for each model run.'.format(G.rxsteps[0] * G.dx, G.rxsteps[1] * G.dy, G.rxsteps[2] * G.dz))
# Excitation file for user-defined source waveforms
cmd = '#excitation_file'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
excitationfile = tmp[0]
# See if file exists at specified path and if not try input file directory
if not os.path.isfile(excitationfile):
excitationfile = os.path.abspath(os.path.join(G.inputdirectory, excitationfile))
# Get waveform names
with open(excitationfile, 'r') as f:
waveformIDs = f.readline().split()
# Read all waveform values into an array
waveformvalues = np.loadtxt(excitationfile, skiprows=1, dtype=floattype)
for waveform in range(len(waveformIDs)):
if any(x.ID == waveformIDs[waveform] for x in G.waveforms):
raise CmdInputError('Waveform with ID {} already exists'.format(waveformIDs[waveform]))
w = Waveform()
w.ID = waveformIDs[waveform]
w.type = 'user'
if len(waveformvalues.shape) == 1:
w.uservalues = waveformvalues[:]
else:
w.uservalues = waveformvalues[:, waveform]
if G.messages:
print('User waveform {} created.'.format(w.ID))
G.waveforms.append(w)
def process_singlecmds(singlecmds, multicmds, G):
"""Checks the validity of command parameters and creates instances of classes of parameters.
Args:
singlecmds (dict): Commands that can only occur once in the model.
multicmds (dict): Commands that can have multiple instances in the model (required to pass to process_materials_file function).
G (class): Grid class instance - holds essential parameters describing the model.
"""
# Check validity of command parameters in order needed
# messages
cmd = '#messages'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if singlecmds[cmd].lower() == 'y':
G.messages = True
elif singlecmds[cmd].lower() == 'n':
G.messages = False
else:
raise CmdInputError(cmd +
' requires input values of either y or n')
# Title
cmd = '#title'
if singlecmds[cmd] != 'None':
G.title = singlecmds[cmd]
if G.messages:
print('Model title: {}'.format(G.title))
# Number of processors to run on (OpenMP)
cmd = '#num_threads'
ompthreads = os.environ.get('OMP_NUM_THREADS')
if singlecmds[cmd] != 'None':
tmp = tuple(int(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(
cmd +
' requires exactly one parameter to specify the number of threads to use'
)
if tmp[0] < 1:
raise CmdInputError(
cmd + ' requires the value to be an integer not less than one')
G.nthreads = tmp[0]
elif ompthreads:
G.nthreads = int(ompthreads)
else:
# Set number of threads to number of physical CPU cores, i.e. avoid hyperthreading with OpenMP
G.nthreads = psutil.cpu_count(logical=False)
if G.messages:
print('Number of threads: {}'.format(G.nthreads))
# Spatial discretisation
cmd = '#dx_dy_dz'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
if tmp[0] <= 0:
raise CmdInputError(
cmd +
' requires the x-direction spatial step to be greater than zero')
if tmp[1] <= 0:
raise CmdInputError(
cmd +
' requires the y-direction spatial step to be greater than zero')
if tmp[2] <= 0:
raise CmdInputError(
cmd +
' requires the z-direction spatial step to be greater than zero')
G.dx = tmp[0]
G.dy = tmp[1]
G.dz = tmp[2]
if G.messages:
print('Spatial discretisation: {:g} x {:g} x {:g}m'.format(
G.dx, G.dy, G.dz))
# Domain
cmd = '#domain'
tmp = [float(x) for x in singlecmds[cmd].split()]
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.nx = round_value(tmp[0] / G.dx)
G.ny = round_value(tmp[1] / G.dy)
G.nz = round_value(tmp[2] / G.dz)
if G.nx == 0 or G.ny == 0 or G.nz == 0:
raise CmdInputError(cmd +
' requires at least one cell in every dimension')
if G.messages:
print(
'Domain size: {:g} x {:g} x {:g}m ({:d} x {:d} x {:d} = {:g} cells)'
.format(tmp[0], tmp[1], tmp[2], G.nx, G.ny, G.nz,
(G.nx * G.ny * G.nz)))
# Guesstimate at memory usage
mem = (((G.nx + 1) * (G.ny + 1) *
(G.nz + 1) * 13 * np.dtype(floattype).itemsize + (G.nx + 1) *
(G.ny + 1) * (G.nz + 1) * 18) * 1.1) + 30e6
print('Memory (RAM) usage: ~{} required, {} available'.format(
human_size(mem), human_size(psutil.virtual_memory().total)))
# Time step CFL limit - use either 2D or 3D (default)
cmd = '#time_step_limit_type'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if singlecmds[cmd].lower() == '2d':
if G.nx == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dy) * (1 / G.dy) + (1 / G.dz) *
(1 / G.dz)))
elif G.ny == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dz) *
(1 / G.dz)))
elif G.nz == 1:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) *
(1 / G.dy)))
else:
raise CmdInputError(
cmd +
' 2D CFL limit can only be used when one dimension of the domain is one cell'
)
elif singlecmds[cmd].lower() == '3d':
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) *
(1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
else:
raise CmdInputError(cmd +
' requires input values of either 2D or 3D')
else:
G.dt = 1 / (c * np.sqrt((1 / G.dx) * (1 / G.dx) + (1 / G.dy) *
(1 / G.dy) + (1 / G.dz) * (1 / G.dz)))
# Round down time step to nearest float with precision one less than hardware maximum. Avoids inadvertently exceeding the CFL due to binary representation of floating point number.
G.dt = round_value(G.dt, decimalplaces=d.getcontext().prec - 1)
if G.messages:
print('Time step: {:g} secs'.format(G.dt))
# Time step stability factor
cmd = '#time_step_stability_factor'
if singlecmds[cmd] != 'None':
tmp = tuple(float(x) for x in singlecmds[cmd].split())
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
if tmp[0] <= 0 or tmp[0] > 1:
raise CmdInputError(
cmd +
' requires the value of the time step stability factor to be between zero and one'
)
G.dt = G.dt * tmp[0]
if G.messages:
print('Time step (modified): {:g} secs'.format(G.dt))
# Time window
cmd = '#time_window'
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(
cmd +
' requires exactly one parameter to specify the time window. Either in seconds or number of iterations.'
)
tmp = tmp[0].lower()
# If real floating point value given
if '.' in tmp or 'e' in tmp:
if float(tmp) > 0:
G.timewindow = float(tmp)
G.iterations = round_value((float(tmp) / G.dt)) + 1
else:
raise CmdInputError(cmd + ' must have a value greater than zero')
# If number of iterations given
else:
G.timewindow = (int(tmp) - 1) * G.dt
G.iterations = int(tmp)
if G.messages:
print('Time window: {:g} secs ({} iterations)'.format(
G.timewindow, G.iterations))
# PML
cmd = '#pml_cells'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1 and len(tmp) != 6:
raise CmdInputError(cmd + ' requires either one or six parameters')
if len(tmp) == 1:
G.pmlthickness = (int(tmp[0]), int(tmp[0]), int(tmp[0]),
int(tmp[0]), int(tmp[0]), int(tmp[0]))
else:
G.pmlthickness = (int(tmp[0]), int(tmp[1]), int(tmp[2]),
int(tmp[3]), int(tmp[4]), int(tmp[5]))
if 2 * G.pmlthickness[0] >= G.nx or 2 * G.pmlthickness[
1] >= G.ny or 2 * G.pmlthickness[2] >= G.nz or 2 * G.pmlthickness[
3] >= G.nx or 2 * G.pmlthickness[
4] >= G.ny or 2 * G.pmlthickness[5] >= G.nz:
raise CmdInputError(cmd + ' has too many cells for the domain size')
# src_steps
cmd = '#src_steps'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.srcstepx = round_value(float(tmp[0]) / G.dx)
G.srcstepy = round_value(float(tmp[1]) / G.dy)
G.srcstepz = round_value(float(tmp[2]) / G.dz)
if G.messages:
print(
'All sources will step {:g}m, {:g}m, {:g}m for each model run.'
.format(G.srcstepx * G.dx, G.srcstepy * G.dy,
G.srcstepz * G.dz))
# rx_steps
cmd = '#rx_steps'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 3:
raise CmdInputError(cmd + ' requires exactly three parameters')
G.rxstepx = round_value(float(tmp[0]) / G.dx)
G.rxstepy = round_value(float(tmp[1]) / G.dy)
G.rxstepz = round_value(float(tmp[2]) / G.dz)
if G.messages:
print(
'All receivers will step {:g}m, {:g}m, {:g}m for each model run.'
.format(G.rxstepx * G.dx, G.rxstepy * G.dy, G.rxstepz * G.dz))
# Excitation file for user-defined source waveforms
cmd = '#excitation_file'
if singlecmds[cmd] != 'None':
tmp = singlecmds[cmd].split()
if len(tmp) != 1:
raise CmdInputError(cmd + ' requires exactly one parameter')
excitationfile = tmp[0]
# See if file exists at specified path and if not try input file directory
if not os.path.isfile(excitationfile):
excitationfile = os.path.join(G.inputdirectory, excitationfile)
# Get waveform names
with open(excitationfile, 'r') as f:
waveformIDs = f.readline().split()
# Read all waveform values into an array
waveformvalues = np.loadtxt(excitationfile,
skiprows=1,
dtype=floattype)
for waveform in range(len(waveformIDs)):
if any(x.ID == waveformIDs[waveform] for x in G.waveforms):
raise CmdInputError(
'Waveform with ID {} already exists'.format(
waveformIDs[waveform]))
w = Waveform()
w.ID = waveformIDs[waveform]
w.type = 'user'
if len(waveformvalues.shape) == 1:
w.uservalues = waveformvalues[:]
else:
w.uservalues = waveformvalues[:, waveform]
if G.messages:
print('User waveform {} created.'.format(w.ID))
G.waveforms.append(w)
