import numpy as np
from scipy.optimize import leastsq


def hfitoff(data, xdeg):
    """
    Harmonic fit with offset
    """
    start, end = min(xdeg), max(xdeg)
    guess_amplitude = 2 ** 0.5 * np.std(data)
    guess_phase = 0
    guess_offset = np.mean(data)
    xrad = xdeg / 180 * np.pi
    optimize_func = lambda x: x[0] * np.sin(xrad + x[1]) + x[2] - data
    fit_amplitude, fit_phase, fit_offset = leastsq(optimize_func, [guess_amplitude, guess_phase, guess_offset])[0]
    fit_xdeg = np.linspace(start, end, 100)
    fit_data = fit_amplitude * np.sin(fit_xdeg / 180 * np.pi + fit_phase) + fit_offset
    ph_crest = 90 - fit_phase / np.pi * 180
    xdeg_max = xdeg[np.argmax(data)]
    if start <= ph_crest <= end:
        return (fit_amplitude, fit_phase, fit_offset, True, ph_crest, fit_xdeg, fit_data)
    else:
        return (fit_amplitude, fit_phase, fit_offset, False, xdeg_max, fit_xdeg, fit_data)