linpredict 0.1.0

Simple linear prediction - fit y = mx + c and predict values

LinPredict

Simple linear prediction library. Pass x and y values, get the next predicted value.

Installation

pip install linpredict

Quick Start

from linpredict import quick_predict, fit, predict_next

# Simplest usage - just pass y values
predictions = quick_predict([2, 4, 6, 8])
print(predictions)  # [10.0]

# Predict multiple steps ahead
predictions = quick_predict([2, 4, 6, 8], steps=3)
print(predictions)  # [10.0, 12.0, 14.0]

Full Usage

from linpredict import fit, predict_next

# Fit a line to your data
x = [1, 2, 3, 4, 5]
y = [2.1, 3.9, 6.2, 7.8, 10.1]

# Get the line equation
eq = fit(x, y)
print(eq)  # y = 1.9900x + 0.0600

# Access slope and intercept
print(f"Slope: {eq.slope}")      # ~2.0
print(f"Intercept: {eq.intercept}")  # ~0.0

# Predict specific x values
print(eq.predict(6))      # Single prediction
print(eq.predict([6, 7, 8]))  # Multiple predictions

# Or use predict_next for automatic next value
next_x, next_y = predict_next(x, y, steps=2)
print(f"Next x: {next_x}, Next y: {next_y}")

API Reference

fit(x, y) -> LineEquation

Fit a line (y = mx + c) to data points. Returns a LineEquation object.

predict_next(x, y, steps=1) -> (list, list)

Predict the next value(s) in sequence. Returns tuple of (next_x_values, predicted_y_values).

quick_predict(y, steps=1) -> list

Quick prediction when you only have y values (assumes x is 0, 1, 2, ...).

LineEquation

• .slope - The m in y = mx + c
• .intercept - The c in y = mx + c
• .predict(x) - Predict y for given x value(s)

License

MIT

Author

PRAVIN MR

GitHub: https://github.com/mr-pravin

Email: [e-mail]