我试图写一个fitter一些大米分布式数据，我有，但它是不工作的一些，可能是愚蠢的，原因。
分布创建得很好，拟合路由似乎与我习惯的高斯分布一样。然而，当我拟合曲线时，我只是胡说八道。似乎看不出我哪里出错了。

import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import rice
from scipy.optimize import curve_fit

# Custom Rice PDF function
def rice_pdf(x, nu, amplitude, b, scale):
    return (x / b) * np.exp(-(x**2 + scale**2) / (2 * b**2)) * amplitude

# Function to fit a Rice distribution to a histogram using curve_fit
def fit_rice_distribution_to_histogram(hist_data, bins):
    # Calculate bin centers
    bin_centers = (bins[:-1] + bins[1:]) / 2

    # Initial guesses for the parameters (nu, amplitude, b, scale)
    initial_guess = [8.4, 1.0, 1.0, np.mean(bin_centers)]

    # Fit the Rice distribution to the histogram data using curve_fit
    params, covariance = curve_fit(rice_pdf, bin_centers, hist_data, p0=initial_guess)
    nu, amplitude, b, scale = params

    # Create the fitted Rice distribution
    fitted_distribution = rice(nu, loc=scale, scale=np.sqrt(b**2 + scale**2))

    return fitted_distribution, nu, amplitude, b, scale

# Example usage:
if __name__ == "__main__":
    # Parameters for the Rice distribution
    nu = 8.5
    sigma = 10.5
    sample_size = 100

    # Calculate b from nu and sigma
    b = nu / sigma

    # Generate random data points from the Rice distribution
    data = rice.rvs(b=b, scale=sigma, size=sample_size)

    # Create a histogram of the generated data
    hist_data, bins, _ = plt.hist(data, bins=20, density=True, alpha=0.5, label="Generated Data")
    plt.xlabel("Value")
    plt.ylabel("Probability Density")

    # Fit a Rice distribution to the histogram using curve_fit
    fitted_distribution, fitted_nu, amplitude, fitted_b, fitted_scale = fit_rice_distribution_to_histogram(hist_data, bins)

    # Plot the original histogram and the fitted distribution
    x = np.linspace(min(bins), max(bins), 1000)
    pdf_values = fitted_distribution.pdf(x)
    plt.plot(x, pdf_values, 'r', label="Fitted Rice Distribution")
    plt.legend()
    plt.show()

    # Print fitted parameters
    print("Fitted Nu:", fitted_nu)
    print("Fitted Amplitude:", amplitude)
    print("Fitted b:", fitted_b)
    print("Fitted Scale:", fitted_scale)

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