Skip to main content

xarray-lmfit

Supported Python Versions PyPi Conda Version Workflow Status Documentation Status pre-commit.ci status codecov Ruff

xarray-lmfit is a Python package that bridges the power of xarray for handling multi-dimensional labeled arrays with the flexible fitting capabilities of lmfit.

With xarray-lmfit, lmfit models can be fit to xarray Datasets and DataArrays, automatically propagating across multiple dimensions. The fit results are stored as xarray Datasets, retaining the original coordinates and dimensions of the input data.

Disclaimer: Please note that this package is independent and not affiliated with the xarray or lmfit projects. If you encounter any issues, please report them on the xarray-lmfit issue tracker.

Installation

Install via pip:

pip install xarray-lmfit

Install via conda:

conda install -c conda-forge xarray-lmfit

Usage

Below is a basic example to demonstrate how to use xarray-lmfit:

import xarray as xr
import numpy as np
from lmfit.models import GaussianModel

import xarray_lmfit as xlm

# Create an example dataset
x = np.linspace(0, 10, 100)
y = 3.0 * np.exp(-((x - 5) ** 2) / (2 * 1.0**2)) + np.random.normal(0, 0.1, x.size)
data = xr.DataArray(y, dims="x", coords={"x": x})

# Define the model to be used
model = GaussianModel()

# Perform the fit
result = data.xlm.modelfit("x", model=model)

Documentation

For more detailed documentation and examples, please visit the documentation.

License

This project is licensed under the GPL-3.0 License.

Metadata

Release files for xarray-lmfit 0.6.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for xarray-lmfit 0.6.1
File Size Uploaded
xarray_lmfit-0.6.1.tar.gz 43.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for xarray-lmfit 0.6.1
File Interpreter ABI Platform
xarray_lmfit-0.6.1-py3-none-any.whl Python 3 none any Details

Total release size: 72.5 kB

Release files / xarray_lmfit-0.6.1.tar.gz

Download URL xarray_lmfit-0.6.1.tar.gz
Size 43.1 kB
Tags Source
SHA-256 checksum
How to use checksums
8040561d927c239ba264145eecbd7bb9951379b3a430cd3d80530522b48495fe
BLAKE2b-256 checksum
How to use checksums
70b1c8722c878dd043ca871206aaf0330ada24a7735d90f9de2d0646d9a4fe37
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.13.1 {"installer":{"name":"uv","version":"0.13.1","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release files / xarray_lmfit-0.6.1-py3-none-any.whl

Download URL xarray_lmfit-0.6.1-py3-none-any.whl
Size 29.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
fe6606e059bc5bbecc098c3e14189beca000e654ab5c46d7018295aaf85f6397
BLAKE2b-256 checksum
How to use checksums
db1e50efc30378f5c7c3e5fab466d1906f4938fc8ec6897f4fff348494184793
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.13.1 {"installer":{"name":"uv","version":"0.13.1","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release history Release notifications | RSS feed

This release

0.6.1 This release

2 release files

0.6.0

2 release files

0.5.6

2 release files

0.5.5

2 release files

0.5.4

2 release files

0.5.3

2 release files

0.5.2

2 release files

0.5.1

2 release files

0.5.0

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.3

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page