import matplotlib.pyplot as plt
import math
import statistics
def func1(sps):
    variation_series = sorted(list(sps))
    mean_val = statistics.mean(variation_series)
    median_val = statistics.median(variation_series)
    if len(variation_series) > 1:
        std_val = statistics.stdev(variation_series)
    else:
        std_val = 0
    params = [mean_val, median_val, std_val]
    return variation_series, params

def func2(sps, nint):
    data = list(sps)
    min_val = min(data)
    max_val = max(data)
    interval_width = (max_val - min_val) / nint
    bins = [min_val + i * interval_width for i in range(nint + 1)]
    hist = []
    bin_edges = []
    for i in range(nint):
        bin_start = bins[i]
        bin_end = bins[i + 1]
        if i == nint - 1:
            count = sum(1 for x in data if bin_start <= x <= bin_end)
        else:
            count = sum(1 for x in data if bin_start <= x < bin_end)
        hist.append(count)
        bin_edges.append((bin_start, bin_end))
    plt.figure(figsize=(10, 6))
    plt.hist(data, bins=nint, edgecolor='black', alpha=0.7)
    plt.title(f'Гистограмма выборки ({nint} интервалов)')
    plt.xlabel('Значения')
    plt.ylabel('Частота')
    plt.grid(True, alpha=0.3)
    plt.text(0.02, 0.98, f'Интервалов: {nint}', transform=plt.gca().transAxes,
             verticalalignment='top', bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))   
    plt.show()
    histogram_result = [bin_edges, hist]
    return histogram_result