Skip to main content

It computes the coeficientes of the MMQ for a given set of 2-D points

Project description

MMQ (Least Squares method) Package

Description

The function takes a set of 2-D points (np.array) and returns the coefficients of the function that best fits the points, using the Least Squares method. User needs to provide the function degree (1 for linear, 2 for quadratic, etc.) and the points (x and y) as np.arrays.

Maybe, for high degree functions, the function will face some problems. Be careful.

Installation

pip install mmq

Requirements

  • numpy

Usage

from mmq import metodo_minimos_quadrados
metodo_minimos_quadrados.mmq(x, y, degree)

Example

from mmq import metodo_minimos_quadrados
import numpy as np

x = np.array([1, 2, 3, 4, 5])
y = np.array([1, 3, 5, 7, 9])
degree = 1

metodo_minimos_quadrados.mmq(x, y, degree)

License

MIT

Author

[Igor Matheus Jasenovski]

Version

0.0.1

References

Least Squares Method

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

mmq-0.0.2.tar.gz (2.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mmq-0.0.2-py3-none-any.whl (3.1 kB view details)

Uploaded Python 3

File details

Details for the file mmq-0.0.2.tar.gz.

File metadata

  • Download URL: mmq-0.0.2.tar.gz
  • Upload date:
  • Size: 2.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for mmq-0.0.2.tar.gz
Algorithm Hash digest
SHA256 0fbd3117202e51dda5c8ba2066ad6c8ebba6752b3f648efbe062182bcda9a55a
MD5 3257e081d8489394b306b18913c6c2f6
BLAKE2b-256 9013ed38dcf3f06c23cd3804361592817f60d8e045d3ac490a4628fa2388c4bc

See more details on using hashes here.

File details

Details for the file mmq-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: mmq-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 3.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for mmq-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 db916b148905098a46f74844c7c6d17a6d14c2a23c8e0208430941ea73a76d26
MD5 80f58f25c686a8c15a08ed68d050b1f4
BLAKE2b-256 aac80c43e4e1979a9c2e6e0fd45c7c4d33635d2ba1b99bfb3dd8bd4149c3b017

See more details on using hashes here.

Supported by

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