<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def plot_day(fignum, BcrBc, S, sym, **kwargs):
 """ function to plot Day plots Parameters _________ fignum : matplotlib figure number BcrBc : list or array ratio of coercivity of remenance to coercivity S : list or array ratio of saturation remanence to saturation magnetization (squareness) sym : matplotlib symbol (e.g., 'rs' for red squares) **kwargs : dictionary with {'names':[list of names for symbols]} """

    plt.figure(num=fignum)
    plt.plot(BcrBc, S, sym)
    plt.axhline(0, color='k')
    plt.axhline(.05, color='k')
    plt.axhline(.5, color='k')
    plt.axvline(1, color='k')
    plt.axvline(4, color='k')
    plt.xlabel('Bcr/Bc')
    plt.ylabel('Mr/Ms')
    plt.title('Day Plot')
    plt.xlim(0, 6)
    #bounds= plt.axis()
    #plt.axis([0, bounds[1],0, 1])
    mu_o = 4. * np.pi * 1e-7
    Bc_sd = 46e-3  # (MV1H) dunlop and carter-stiglitz 2006 (in T)
    Bc_md = 5.56e-3  # (041183) dunlop and carter-stiglitz 2006 (in T)
    chi_sd = 5.20e6 * mu_o  # now in T
    chi_md = 4.14e6 * mu_o  # now in T
    chi_r_sd = 4.55e6 * mu_o  # now in T
    chi_r_md = 0.88e6 * mu_o  # now in T
    Bcr_sd, Bcr_md = 52.5e-3, 26.1e-3  # (MV1H and 041183 in DC06 in tesla)
    Ms = 480e3  # A/m
    p = .1  # from Dunlop 2002
    N = old_div(1., 3.)  # demagnetizing factor
    f_sd = np.arange(1., 0., -.01)  # fraction of sd
    f_md = 1. - f_sd  # fraction of md
    f_sp = 1. - f_sd  # fraction of sp
    # Mr/Ms ratios for USD,MD and Jax shaped
    sdrat, mdrat, cbrat = 0.498, 0.048, 0.6
    Mrat = f_sd * sdrat + f_md * mdrat  # linear mixing - eq. 9 in Dunlop 2002
    Bc = old_div((f_sd * chi_sd * Bc_sd + f_md * chi_md * Bc_md),
                 (f_sd * chi_sd + f_md * chi_md))  # eq. 10 in Dunlop 2002
    Bcr = old_div((f_sd * chi_r_sd * Bcr_sd + f_md * chi_r_md * Bcr_md),
                  (f_sd * chi_r_sd + f_md * chi_r_md))  # eq. 11 in Dunlop 2002
    chi_sps = np.arange(1, 5) * chi_sd
    plt.plot(old_div(Bcr, Bc), Mrat, 'r-')
    if 'names' in list(kwargs.keys()):
        names = kwargs['names']
        for k in range(len(names)):
            plt.text(BcrBc[k], S[k], names[k])