import numpy as np
from matplotlib import pyplot as plt
from fpu_test_gen import reverse_endian, dtype_size


def generate(fname, samples, dtype=np.float32):
    dsize = dtype_size(dtype)
    numbers = np.linspace(-4, 4, samples, dtype=dtype)
    data = numbers.tobytes()
    with open(fname, 'w') as f:
        for i in range(samples):
            f.write(f"{reverse_endian(data[i*dsize:i*dsize+dsize]).hex()}  // {numbers[i]:0.6f}\n")


def view_result(fname, dtype=np.float32):
    x_bytes = b''
    y_bytes = b''
    timing = []
    with open(fname, 'r') as f:
        for line in f.readlines():
            parts = line.split()
            x_bytes += reverse_endian(bytes.fromhex(parts[0]))
            y_bytes += reverse_endian(bytes.fromhex(parts[1]))
            timing.append(int(parts[2]))
    x = np.frombuffer(x_bytes, dtype=dtype)
    y = np.frombuffer(y_bytes, dtype=dtype)
    t = np.array(timing) / 10

    fig, ax = plt.subplots()
    plt.title('Digital circuit sigmoid function test')
    ax2 = ax.twinx()
    ax.plot(x, y, '.', markersize=0.95)
    ax2.plot(x, t, '.', markersize=0.95, color='m')
    ax.set_xlabel('Function input')
    ax.set_ylabel('Function output')
    ax2.set_ylabel('Timing in cycles', color='m')
    plt.grid()
    plt.show()


if __name__ == '__main__':
    # generate('sigmoid_test.hex', 5001)
    view_result('sigmoid_result.hex')