/Users/jeffgostick/Library/CloudStorage/Dropbox/Flash Sync/Code/Git/pnmlib/.venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
from .autonotebook import tqdm as notebook_tqdm# Generate network topology
Nx, Ny, Nz = 2, 2, 1
pn = pnm.generators.cubic(
shape=[Nx, Ny, Nz],
node_prefix='pore',
edge_prefix='throat',
)
# Add labels to each half of the domain
pn['pore.left'] = pn['pore.coords'][:, 0] < 1
pn['pore.right'] = pn['pore.coords'][:, 0] > (Nx - 1)
pnm.core.add_network(prj, pn)onetime_models = {
# We can put an array on network
'network/pore.seed': {
'model': pnm.models.geometry.random_seeds,
'num_range': [0.2, 0.8],
},
# Or an array with the same name at the top level
'pore.seed': {
'model': pnm.models.geometry.random_seeds,
'num_range': [0.2, 0.8],
},
# We can also assign scalar values to one domain
'network/pore.volume@left': {
'model': pnm.models.geometry.constant,
'value': 3.3,
},
# And different values to another
'network/pore.volume@right': {
'model': pnm.models.geometry.constant,
'value': 1.1,
},
}We can have as many different model dicts as we want
geo_models1 = {
# We can write to the top level using values from the network
'pore.size3': {
'model': pnm.models.geometry.product,
'props': ['network/pore.seed', 'network/pore.seed'],
},
# We can use group and domain notation to write vectors.
# Note that network/pore.seed is a full length array, so
# the model also uses the @left when fetching values so we
# don't need to include the @left in the props.
'network/pore.size2@left': {
'model': pnm.models.geometry.product,
'props': ['network/pore.seed', 'network/pore.seed'],
},
'network/pore.size4@left': {
'model': pnm.models.geometry.product,
'props': ['network/pore.seed@left', 'network/pore.seed@left'],
},
}We can “run” the models as follows
This should also work with mixtures. Let’s define a phase with 2 components
Here we have a model which finds the molecular weight of the mixture
def MW_mixture(target, MWs, xs):
xs = [target[xs[i]] for i in range(len(xs))]
MWs = [target[MWs[i]] for i in range(len(MWs))]
MW_mix = np.sum([xs[i]*MWs[i] for i in range(len(xs))], axis=0)
return MW_mix
mixture_models = {
'phase1/pore.MW': {
'model': MW_mixture,
'MWs': ['phase1/O2/param.MW', 'phase1/N2/param.MW'],
'xs': ['phase1/O2/pore.x', 'phase1/N2/pore.x'],
},
}
pnm.models.apply_models(prj, mixture_models)The above works, but is not generalizable. We would like to write the above ‘model dict’ without any reference to ‘phase1’ or ‘O2’ and ‘N2’. We can avoid specifying ‘phase1’ in the model name by using the group name argument when calling apply_models, and rewriting the model to be totally generic.
def MW_mixture2(target, mixture, components=None, MW='param.MW', x='pore.x'):
if components is None:
components = pnm.core.get_components(target, mixture)
MWs = [pnm.core.get_data(target, '/'.join((mixture, c, MW))) for c in components]
xs = [pnm.core.get_data(target, '/'.join((mixture, c, x))) for c in components]
MW_mix = np.sum([xs[i]*MWs[i] for i in range(len(xs))], axis=0)
return MW_mixI’m still not happy that we need to pass ‘mixture’ to the function. It would be truly generic if we could only get rid of that.
def MW_mixture3(target, components=None, MW='param.MW', x='pore.x'):
if components is None:
components = list({c.split('/')[0] for c in target.keys() if '/' in c})
MWs = [pnm.core.get_data(target, '/'.join((c, MW))) for c in components]
xs = [pnm.core.get_data(target, '/'.join((c, x))) for c in components]
MW_mix = np.sum([xs[i]*MWs[i] for i in range(len(xs))], axis=0)
return MW_mixInstead of the mixture arg, which is more literal, we could use group, which is in keeping with the pnmlib terminology. Technically, components are subgroups.
The group argument in the following function means we don’t have to put the group in the model name above. This allows the model to be generic.
{'phase1/pore.temperature': array([1., 1., 1., 1.]),
'phase1/N2/param.MW': 28.0,
'phase1/N2/pore.x': array([0.79, 0.79, 0.79, 0.79]),
'phase1/O2/param.MW': 32.0,
'phase1/O2/pore.x': array([0.21, 0.21, 0.21, 0.21]),
'phase1/pore.MW': array([28.84, 28.84, 28.84, 28.84]),
'phase1/pore.MW2': array([28.84, 28.84, 28.84, 28.84])}├── 'pore.all': 4/4, bool
├── 'pore.coords': (4, 3), float64
├── 'pore.left': 2/4, bool
├── 'pore.right': 2/4, bool
├── 'pore.seed': (4,), float64
├── 'pore.size3': (4,), float64
├── 'throat.all': 4/4, bool
├── 'throat.conns': (4, 2), int64
├── phase1
│ ├── 'pore.MW': (4,), float64
│ ├── 'pore.MW2': (4,), float64
│ ├── 'pore.temperature': (4,), float64
│ ├── O2
│ │ ├── 'param.MW': 32.0
│ │ └── 'pore.x': (4,), float64
│ └── N2
│ ├── 'param.MW': 28.0
│ └── 'pore.x': (4,), float64
└── network
├── 'pore.seed': (4,), float64
├── 'pore.size2': (4,), float64
├── 'pore.size4': (4,), float64
└── 'pore.volume': (4,), float64
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# Properties Valid Values
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
2 network/pore.seed 4 / 4
3 network/pore.size2 2 / 4
4 network/pore.size4 2 / 4
5 network/pore.volume 4 / 4
6 phase1/N2/pore.x 4 / 4
7 phase1/O2/pore.x 4 / 4
8 phase1/pore.MW 4 / 4
9 phase1/pore.MW2 4 / 4
10 phase1/pore.temperature 4 / 4
11 pore.coords 4 / 4
12 pore.seed 4 / 4
13 pore.size3 4 / 4
14 throat.conns 4 / 4
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――
# Labels Assigned Locations
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2 pore.left 2
3 pore.right 2
4 pore.all 4
5 throat.all 4
――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――