plot_quadratics.md

import numpy as np
import matplotlib.pyplot as plt

def plot_quadratic_coefficients(coefficients):
    """
    Plots y = ax^2 + bx + c for each set of coefficients within specified x and y ranges.

    Parameters:
    - coefficients: dict, a dictionary of coefficient sets with 'a', 'b', and 'c' for each key.
    """
    x_values = np.linspace(0, 25, 400)  # Generate 400 points from 0 to 15 for smooth curves.
    
    plt.figure(figsize=(10, 6))
    for label, coef in coefficients.items():
        a, b, c = coef['a'], coef['b'], coef['c']
        y_values = a * x_values**2 + b * x_values + c
        plt.plot(x_values, y_values, label=label)
    
    plt.ylim(0, 1.5)  # Set the y-axis range from 0 to 1.5.
    plt.xlim(0, 25)  # Set the x-axis range from 0 to 15 for clarity.
    plt.xlabel('X Axis')
    plt.ylabel('Y Axis')
    plt.title('Quadratic Coefficients Graph')
    plt.legend()
    plt.grid(True)
    plt.show()

coefficients = {
    "clip_aesthetic": {"a": -0.01028806584362138, "b": 0.21913580246913555, "c": 0.08518518518518595},
    "log_pixels": {"a": -0.0005806010928961671, "b": 0.024132513661202018, "c": 0.7775409836065581},
    "twitter_aesthetic_v2": {"a": -0.003809523809523807, "b": 0.08952380952380948, "c": 0.6228571428571431},
    "year_since_2000": {"a": 0.0012500000000000011, "b": -0.03000000000000003, "c": 1.1},
    "transformed_views_per_react": {"a": 0.0031488978857400285, "b": -0.12474134053081526, "c": 2.0626180836707224},
    "log_norm_pseudo_engagement_ratio": {"a": -0.00023088023088022288, "b": 0.03763347763347757, "c": 0.8}
}

plot_quadratic_coefficients(coefficients)