Skip to main content

Designed to simplify the creation of cost matrices for optimization problems.

Project description

cost-matrix

cost-matrix is a Python package designed to simplify the creation of cost matrices for optimization problems. Whether you're dealing with distance calculations or travel durations, cost-matrix provides a robust set of tools to meet your needs.

This package is invaluable for anyone working on optimization problems, data analysis, or transportation planning. With its diverse range of distance calculation methods and integration with OSRM, it provides a comprehensive solution for generating cost matrices efficiently.

Key Features:

  • Manhattan: Compute distances based on orthogonal paths.
  • Euclidean: Calculate straight-line distances in a Cartesian plane.
  • Spherical: Calculate distances between geographical points considering the Earth's curvature.
  • OSRM: Integrate with the Open Source Routing Machine (OSRM) to obtain travel duration or distance matrices.

Installation

To install the cost-matrix package, you can use pip:

pip install cost-matrix

Example Usage:

import numpy as np
import cost_matrix

# Define source and destination coordinates (latitude, longitude)
sources = np.array([[37.7749, -122.4194], [34.0522, -118.2437]])  # San Francisco, Los Angeles
destinations = np.array([[40.7128, -74.0060], [51.5074, -0.1278]])  # New York, London

# Calculate Manhattan distance matrix
manhattan_matrix = cost_matrix.manhattan(sources, destinations)
print(manhattan_matrix)

# Calculate Euclidean distance matrix
euclidean_matrix = cost_matrix.euclidean(sources, destinations)
print(euclidean_matrix)

# Calculate Spherical distance matrix
spherical_matrix = cost_matrix.spherical(sources, destinations)
print(spherical_matrix)

# Calculate OSRM travel distances matrix
osrm_distance_matrix = cost_matrix.osrm(sources, destinations)
print(osrm_distance_matrix)

# Calculate OSRM travel durations matrix
osrm_duration_matrix = cost_matrix.osrm(
    sources, 
    destinations, 
    cost_type="durations", 
    server_address="http://localhost:5000",
    batch_size=250
)
print(osrm_duration_matrix)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cost_matrix-0.1.1.tar.gz (3.9 kB view details)

Uploaded Source

Built Distribution

cost_matrix-0.1.1-py3-none-any.whl (5.4 kB view details)

Uploaded Python 3

File details

Details for the file cost_matrix-0.1.1.tar.gz.

File metadata

  • Download URL: cost_matrix-0.1.1.tar.gz
  • Upload date:
  • Size: 3.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/6.5.0-35-generic

File hashes

Hashes for cost_matrix-0.1.1.tar.gz
Algorithm Hash digest
SHA256 b6290518812b1cf0887109ef79c1e94e6cbc34061a0f9c008261cc7df173b08d
MD5 64e7cb2e3424a8b0df09721b2da69bd9
BLAKE2b-256 e56d7e300359c4fc575fcd553409f11eceb8d602e405f7d0d4bd205feb22d86b

See more details on using hashes here.

File details

Details for the file cost_matrix-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: cost_matrix-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 5.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/6.5.0-35-generic

File hashes

Hashes for cost_matrix-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6725fe16b0605aa0116f0f0cfb71e8e7ff384beaa65a06b7636c65a46b54cba8
MD5 cc3ca8104cf0ba697fa69a89bb564ca5
BLAKE2b-256 e4b2b4f9941c2b8fdb27e7a4260bbf13f31d670eb834802089300a2b69dbb5f7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page