aequilibrae.distribution.gravity_application#
Classes
|
Applies a synthetic gravity model. |
- class aequilibrae.distribution.gravity_application.GravityApplication(project=None, **kwargs)[source]#
Applies a synthetic gravity model.
Model is an instance of SyntheticGravityModel class.
Impedance is an instance of AequilibraEMatrix.
Vectors are a pandas DataFrame.
>>> import pandas as pd >>> from aequilibrae.distribution import SyntheticGravityModel, GravityApplication >>> project = create_example(project_path) # We define the model we will use >>> model = SyntheticGravityModel() # Before adding a parameter to the model, you need to define the model functional form # You can select one of GAMMA, EXPO or POWER. >>> model.function = "GAMMA" # Only the parameter(s) applicable to the chosen functional form will have any effect >>> model.alpha = 0.1 >>> model.beta = 0.0001 # We load the impedance matrix >>> matrix = project.matrices.get_matrix("skims") >>> matrix.computational_view(["distance_blended"]) # We create the vectors we will use >>> query = "SELECT zone_id, population, employment FROM zones;" >>> with project.db_connection as conn: ... df = pd.read_sql(query, conn) >>> df.sort_values(by="zone_id", inplace=True) >>> df.set_index("zone_id", inplace=True) # You create the vectors you would have >>> df = df.assign(productions=df.population * 3.0) >>> df = df.assign(attractions=df.employment * 4.0) >>> vectors = df[["productions", "attractions"]] # Balance the vectors >>> vectors.loc[:, "attractions"] *= vectors["productions"].sum() / vectors["attractions"].sum() # Create the problem object >>> args = {"impedance": matrix, ... "vectors": vectors, ... "row_field": "productions", ... "model": model, ... "column_field": "attractions", ... "nan_as_zero":True ... } >>> gravity = GravityApplication(**args) # Solve and save the outputs >>> gravity.apply() >>> gravity.output.export(project_path / 'matrices' / 'gravity_omx.omx') >>> project.close()
- apply()[source]#
Runs the Gravity Application instance as instantiated
Resulting matrix is the output class member
- save_to_project(name: str, file_name: str, project=None) None [source]#
Saves the matrix output to the project file
- Arguments:
name (
str
): Name of the desired matrix recordfile_name (
str
): Name for the matrix file name. AEM and OMX supportedproject (
Project
, Optional): Project we want to save the results to. Defaults to the active project