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Commit 96cc3945 authored by Giovanni La Mura's avatar Giovanni La Mura
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Update model maker to estimate system requirements and use exception handling+ù

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src/scripts/model_maker.py
+ 199
− 173
View file @ 96cc3945
......@@ -31,6 +31,7 @@ import pdb
import random
import yaml
## \brief 3D software generation capability flag.
allow_3d = True
try:
import pyvista as pv
......@@ -46,7 +47,7 @@ from sys import argv
# `main()` is the function that handles the creation of the code configuration.
# It returns an integer value as exit code, using 0 to signal successful execution.
#
# \returns result: `int` Number of detected error-level inconsistencies.
# \returns result: `int` Exit code (0 = SUCCESS).
def main():
result = 0
config = parse_arguments()
......@@ -68,11 +69,14 @@ def main():
# \return result: `int` An exit code (0 if successful).
def interpolate_constants(sconf):
result = 0
err_arg = ""
try:
for i in range(sconf['configurations']):
for j in range(sconf['nshl'][i]):
file_idx = sconf['dielec_id'][i][j]
dielec_path = Path(sconf['dielec_path'], sconf['dielec_file'][int(file_idx) - 1])
file_name = str(dielec_path)
err_arg = str(dielec_path)
file_name = err_arg
dielec_file = open(file_name, 'r')
wavelengths = []
rpart = []
......@@ -125,6 +129,9 @@ def interpolate_constants(sconf):
else:
print("ERROR: file %s does not cover requested wavelengths!"%file_name)
return 2
except FileNotFoundError as ex:
print("ERROR: file not found %s!"%err_arg)
return 3
return result
## \brief Create tha calculation configuration structure from YAML input.
......@@ -261,12 +268,16 @@ def load_model(model_file):
[0.0 for k in range(sconf['nxi'])] for j in range(sconf['configurations'])
] for i in range(max_layers)
]
interpolate_constants(sconf)
check = interpolate_constants(sconf)
if (check != 0):
return (None, None)
else: # sconf[idfc] != 0 and scaling on wavelength
print("ERROR: for wavelength scaling, optical constants must be tabulated!")
return (None, None)
elif (model['material_settings']['match_mode'] == "GRID"):
match_grid(sconf)
check = match_grid(sconf)
if (check != 0):
return(None, None)
else:
print("ERROR: %s is not a recognized match mode!"%(model['material_settings']['match_mode']))
return (None, None)
......@@ -384,17 +395,25 @@ def load_model(model_file):
rnd_engine = "COMPACT"
if (rnd_engine == "COMPACT"):
check = random_compact(sconf, gconf, rnd_seed, max_rad)
if (check == 1):
if (check == -1):
print("ERROR: compact random generator works only when all sphere types have the same radius.")
return (None, None)
elif (check == -2):
print("ERROR: sub-particle radius larger than particle radius.")
return (None, None)
elif (check == -3):
print("ERROR: requested number of spheres cannot fit in allowed volume.")
return (None, None)
elif (rnd_engine == "LOOSE"):
# random_aggregate() checks internally whether application is INCLUSION
check = random_aggregate(sconf, gconf, rnd_seed, max_rad)
else:
print("ERROR: unrecognized random generator engine.")
return (None, None)
if (check != 0):
print("WARNING: %d sphere(s) could not be placed."%check)
if (check != sconf['nsph']):
print("WARNING: placed only %d out of %d requested spheres."%(check, sconf['nsph']))
sconf['nsph'] = check
gconf['nsph'] = check
else:
if (len(model['geometry_settings']['x_coords']) != gconf['nsph']):
print("ERROR: coordinate vectors do not match the number of spheres!")
......@@ -409,13 +428,16 @@ def load_model(model_file):
write_obj(sconf, gconf, max_rad)
try:
max_gpu_ram = int(model['system_settings']['max_gpu_ram'])
if (max_gpu_ram > 0):
max_gpu_ram_bytes = max_gpu_ram * 1024 * 1024 * 1024
matrix_dim = 2 * gconf['nsph'] * gconf['li'] * (gconf['li'] + 2)
matrix_size_bytes = 16 * matrix_dim * matrix_dim
matrix_size_Gb = float(matrix_size_bytes) / 1024.0 / 1024.0 / 1024.0
print("INFO: estimated matrix size is {0:.3g} Gb.".format(matrix_size_Gb))
if (max_gpu_ram > 0):
max_gpu_ram_bytes = max_gpu_ram * 1024 * 1024 * 1024
if (matrix_size_bytes < max_gpu_ram_bytes):
max_gpu_processes = int(max_gpu_ram_bytes / matrix_size_bytes)
print("INFO: system supports up to %d simultaneous processes on GPU."%max_gpu_processes)
print("INFO: only %d GPU processes allowed, if using refinement."%(max_gpu_processes / 3))
else:
print("WARNING: estimated matrix size is larger than available GPU memory!")
else:
......@@ -454,6 +476,8 @@ def match_grid(sconf):
max_layers = 0
nxi = 0
sconf['vec_xi'] = []
err_arg = ""
try:
for i in range(sconf['configurations']):
layers = sconf['nshl'][i]
if (sconf['application'] == "INCLUSION" and i == 0):
......@@ -461,7 +485,8 @@ def match_grid(sconf):
for j in range(layers):
file_idx = sconf['dielec_id'][i][j]
dielec_path = Path(sconf['dielec_path'], sconf['dielec_file'][int(file_idx) - 1])
file_name = str(dielec_path)
err_arg = str(dielec_path)
file_name = err_arg
dielec_file = open(file_name, 'r')
wavelengths = []
rpart = []
......@@ -520,6 +545,9 @@ def match_grid(sconf):
wi += 1
sconf['rdc0'][j][i][dci] = ry
sconf['idc0'][j][i][dci] = iy
except FileNotFoundError as ex:
print("ERROR: file not found %s!"%err_arg)
return 3
return result
## \brief Parse the command line arguments.
......@@ -587,15 +615,19 @@ def random_aggregate(scatterer, geometry, seed, max_rad, max_attempts=100):
vec_thetas = [0.0 for i in range(nsph)]
vec_phis = [0.0 for i in range(nsph)]
vec_rads = [0.0 for i in range(nsph)]
vec_types = []
n_types = scatterer['configurations']
if (0 in scatterer['vec_types']):
tincrement = 1 if scatterer['application'] != "INCLUSION" else 2
for ti in range(nsph):
itype = tincrement + int(n_types * random.random())
scatterer['vec_types'][ti] = itype
if (scatterer['application'] == "INCLUSION"):
scatterer['vec_types'][0] = 1
sph_type_index = scatterer['vec_types'][0] - 1
vec_spheres = [{'itype': sph_type_index + 1, 'x': 0.0, 'y': 0.0, 'z': 0.0}]
vec_rads[0] = scatterer['ros'][sph_type_index]
vec_types.append(sph_type_index + 1)
placed_spheres = 1
attempts = 0
for i in range(1, nsph):
......@@ -669,7 +701,9 @@ def random_aggregate(scatterer, geometry, seed, max_rad, max_attempts=100):
})
is_placed = True
placed_spheres += 1
vec_types.append(sph_type_index + 1)
attempts = 0
scatterer['vec_types'] = vec_types
sph_index = 0
for sphere in sorted(vec_spheres, key=lambda item: item['itype']):
scatterer['vec_types'][sph_index] = sphere['itype']
......@@ -677,6 +711,7 @@ def random_aggregate(scatterer, geometry, seed, max_rad, max_attempts=100):
geometry['vec_sph_y'][sph_index] = sphere['y']
geometry['vec_sph_z'][sph_index] = sphere['z']
sph_index += 1
result = placed_spheres
return result
## \brief Generate a random compact cluster from YAML configuration options.
......@@ -699,45 +734,30 @@ def random_compact(scatterer, geometry, seed, max_rad):
random.seed(seed)
nsph = scatterer['nsph']
n_types = scatterer['configurations']
if (0 in scatterer['vec_types']):
tincrement = 1 if scatterer['application'] != "INCLUSION" else 2
for ti in range(nsph):
itype = tincrement + int(n_types * random.random())
scatterer['vec_types'][ti] = itype
radius = scatterer['ros'][0]
# Return an error code if types have different radii
if (max(scatterer['ros']) != min(scatterer['ros'])):
result = 1
result = -1
elif (radius > max_rad):
# Requested spheres are larger than the maximum allowed volume.
# End function with error code -2.
result = -2
else:
radius = scatterer['ros'][0]
x_centers = np.arange(-1.0 * max_rad + radius, max_rad, 2.0 * radius)
y_centers = np.arange(-1.0 * max_rad + radius, max_rad, math.sqrt(3.0) * radius)
z_centers = np.arange(-1.0 * max_rad + radius, max_rad, math.sqrt(3.0) * radius)
x_offset = radius
y_offset = radius
x_layer_offset = radius
y_layer_offset = radius / math.sqrt(3.0)
x_centers = np.arange(-1.0 * max_rad + 2.0 * radius, max_rad, 2.0 * radius)
x_size = len(x_centers)
y_size = int(2.0 * max_rad / ((1.0 + math.sqrt(3.0) / 3.0) * radius))
z_size = int(2.0 * max_rad / ((1.0 + 2.0 * math.sqrt(6.0) / 3.0) * radius))
tmp_spheres = []
n_cells = len(x_centers) * len(y_centers) * len(z_centers)
n_cells = x_size * y_size * z_size
print("INFO: the cubic space would contain %d spheres."%n_cells)
n_max_spheres = int((max_rad / radius) * (max_rad / radius) * (max_rad / radius) * 0.74)
print("INFO: the maximum radius allows for %d spheres."%n_max_spheres)
for zi in range(len(z_centers)):
if (x_layer_offset == 0.0):
x_layer_offset = radius
else:
x_layer_offset = 0.0
if (y_offset == 0.0):
y_offset = radius
else:
y_offset = 0.0
for yi in range(len(y_centers)):
if (x_offset == 0.0):
x_offset = radius
else:
x_offset = 0.0
for xi in range(len(x_centers)):
x = x_centers[xi] + x_offset + x_layer_offset
y = y_centers[yi] + y_offset
z = z_centers[zi]
k = 0
z = -max_rad + radius
while (z < max_rad - radius):
j = 0
y = -max_rad + radius
while (y < max_rad - radius):
for i in range(len(x_centers)):
x = (2 * (i + 1) + (j + k) % 2) * radius - max_rad
extent = radius + math.sqrt(x * x + y * y + z * z)
if (extent < max_rad):
tmp_spheres.append({
......@@ -746,6 +766,11 @@ def random_compact(scatterer, geometry, seed, max_rad):
'y': y,
'z': z
})
#
j += 1
y = math.sqrt(3.0) * (j + (k % 2) / 3.0) * radius - max_rad + radius
k += 1
z = 2.0 / 3.0 * math.sqrt(6.0) * k * radius - max_rad + radius
#tmp_spheres = [{'itype': 1, 'x': 0.0, 'y': 0.0, 'z': 0.0}]
current_n = len(tmp_spheres)
print("INFO: before erosion there are %d spheres in use."%current_n)
......@@ -777,20 +802,20 @@ def random_compact(scatterer, geometry, seed, max_rad):
current_n -= 1
vec_spheres = []
sph_index = 0
# Generate a vector of types if none is given
if (0 in scatterer['vec_types']):
tincrement = 1 if scatterer['application'] != "INCLUSION" else 2
for ti in range(current_n):
itype = tincrement + int(n_types * random.random())
scatterer['vec_types'][ti] = itype
if (scatterer['application'] == "INCLUSION"):
scatterer['vec_types'][0] = 1
for ti in range(len(tmp_spheres)):
sphere = tmp_spheres[ti]
if (sphere['x'] < max_rad):
sphere['itype'] = scatterer['vec_types'][sph_index]
sph_index += 1
vec_spheres.append(sphere)
#pl = pv.Plotter()
#for si in range(len(vec_spheres)):
# x = vec_spheres[si]['x'] / max_rad
# y = vec_spheres[si]['y'] / max_rad
# z = vec_spheres[si]['z'] / max_rad
# mesh = pv.Sphere(radius / max_rad, (x, y, z))
# pl.add_mesh(mesh)
#pl.export_obj("scene.obj")
sph_index = 0
for sphere in sorted(vec_spheres, key=lambda item: item['itype']):
scatterer['vec_types'][sph_index] = sphere['itype']
......@@ -798,7 +823,7 @@ def random_compact(scatterer, geometry, seed, max_rad):
geometry['vec_sph_y'][sph_index] = sphere['y']
geometry['vec_sph_z'][sph_index] = sphere['z']
sph_index += 1
return result
return current_n
## \brief Write the geometry configuration dictionary to legacy format.
#
......@@ -952,9 +977,10 @@ def write_legacy_sconf(conf):
## \brief Export the model to a set of OBJ files for 3D visualization.
#
# This function exports the model as a set of OBJ files (one for every
# spherical unit, plus a single scene file) to allow for model visualization
# with 3D software tools.
# This function exports the model as a single OBJ file, containing the
# information to visualize the particle with 3D software tools. The model
# file is associated with a MTL material libray file, used to assign colors
# to spheres of different type.
#
# \param scatterer: `dict` Scatterer configuration dictionary (gets modified)
# \param geometry: `dict` Geometry configuration dictionary (gets modified)
......
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