Modular modeling framework for nonlinear scientific models
Project description
MModel is a lightweight and modular model building framework for small-scale and nonlinear models. The package aims to solve scientific program prototyping and distribution difficulties, making it easier to create modular, fast, and user-friendly packages. The package is fully tested.
Quickstart
To create a nonlinear model that has the result of (x + y)log(x + y, base):
from mmodel import ModelGraph, Model, MemHandler
import math
def func_a(x, y):
return x + y
def func_b(sum_xy, base):
return math.log(sum_xy, base)
def func_c(sum_xy, log_xy):
return sum_xy * log_xy
# create graph links
grouped_edges = [
("func a", ["func b", "func c"]),
("func b", "func c"),
]
node_objects = [
("func a", func_a, ["sum_xy"]),
("func b", func_b, ["log_xy"]),
("func c", func_c, ["result"]),
]
graph = ModelGraph(name="example_graph")
graph.add_grouped_edges_from(grouped_edges)
graph.set_node_objects_from(node_objects)
example_model = Model("example_model", graph, handler=(MemHandler, {}))
>>> print(example_model)
example_model(base, x, y)
signature:
returns: result
handler: MemHandler, {}
modifiers: none
>>> example_model(2, 5, 3) # (5 + 3)log(5 + 3, 2)
24.0
The resulting example_func is callable.
One key feature of mmodel is modifiers, which modify callables post definition. To loop the “base” parameter.
from mmodel import subgraph_by_parameters, modify_subgraph, loop_modifier
subgraph = subgraph_by_parameters(graph, ["base"])
loop_node = Model(
"loop_node",
subgraph,
(MemHandler, {}),
modifiers=[(loop_modifier, {"parameter": "base"})],
)
looped_graph = modify_subgraph(graph, subgraph, "loop node", loop_node)
looped_model = Model("loop_model", looped_graph, loop_node.handler)
>>> print(looped_model)
loop_model(base, x, y)
returns: result
handler: MemHandler, {}
modifiers: []
>>> looped_model([2, 4], 5, 3) # (5 + 3)log(5 + 3, 2)
[24.0, 12.0]
Modifiers can also be added to the whole model or a single node.
To draw the graph or the underlying graph of the model:
from mmodel import draw_plain_graph
graph.draw(method=draw_plain_graph)
example_model.draw(method=draw_plain_graph)
Installation
Graphviz installation
To view the graph, Graphviz needs to be installed: Graphviz Installation For windows installation, please choose “add Graphviz to the system PATH for all users/current users” during the setup.
MModel installation
pip install mmodel
Development installation
MModel uses poetry as the build system. The package works with both pip and poetry installation.
To install test and docs, despondencies run:
pip install .[test] .[docs]
To run the tests in different python environments and cases (py38, py39, py310, coverage and docs):
tox
To create the documentation, run under the “/docs” directory:
make html
Project details
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