Installation¶
ezfit can be installed using pip or uv.
Basic Installation¶
pip install ezfit
Or using uv:
uv pip install ezfit
Dependencies¶
ezfit requires: - Python >= 3.10 - numpy >= 1.26.0 - pandas >= 2.2.2 - scipy >= 1.13.0 - matplotlib >= 3.10.0 - numba >= 0.60.0 - scikit-learn >= 1.3.0
Optional Dependencies¶
For MCMC fitting and advanced diagnostics:
pip install ezfit[mcmc]
This installs: - emcee >= 3.1.0 (MCMC sampler) - corner (corner plots) - arviz >= 0.18.0 (MCMC diagnostics)
For Development¶
To install with development dependencies:
git clone https://github.com/WSU-Carbon-Lab/ezfit.git
cd ezfit
pip install -e ".[dev]"
Verifying Installation¶
Test your installation:
import ezfit
import pandas as pd
import numpy as np
# Create simple test data
x = np.linspace(0, 10, 50)
y = 2 * x + 1 + np.random.normal(0, 0.5, 50)
yerr = np.full_like(y, 0.5)
df = pd.DataFrame({"x": x, "y": y, "yerr": yerr})
def line(x, m, b):
return m * x + b
model, ax, _ = df.fit(line, "x", "y", "yerr")
print("Installation successful!")
print(model)