Пример #1
0
def plot_tauH_heatmap(fig, axs, cbaxes):
    # setup grid
    n0 = (-9, -1)
    mig = (-9, -1)
    n0Fine = np.logspace(*n0, 1000)
    migFine = np.logspace(*mig, 1000)
    n0Gr, migGr = np.meshgrid(n0Fine, migFine)

    # calc tau_Her
    tauHMat = mlsg.calc_tauHer_numeric(n0Gr, migGr)

    # plot Heatmap
    viridisBig = mpl.cm.get_cmap('coolwarm', 512)
    indexVec = np.hstack((np.linspace(0, 0.5,
                                      100), np.linspace(0.5, 1 - 1E-12, 150)))
    cmap = mpl.colors.ListedColormap(viridisBig(indexVec))

    colors = sns.color_palette("RdBu_r", 1024)
    idx = np.floor(indexVec * 1024).astype(int)
    cmap = [colors[i] for i in idx]
    cmap = colr.ListedColormap(cmap)

    currData = np.log10(tauHMat)

    axl = axs.imshow(currData,
                     cmap=cmap,
                     interpolation='nearest',
                     extent=[*n0, *mig],
                     origin='lower',
                     vmin=-6,
                     vmax=9)

    axs.set_xticks([-9, -6, -3, -1])
    axs.set_yticks([-9, -6, -3, -1])

    axs.set_xlabel('$\\log_{10} \\frac{n_0}{k}$')
    axs.set_ylabel('$\\log_{10} \\frac{\\theta}{\\beta}$')
    axs.set_aspect('equal')

    cbaxes.set_axis_off()
    cb = fig.colorbar(axl,
                      ax=cbaxes,
                      orientation='horizontal',
                      label="$\\log_{10}\\tau_{her}$",
                      ticks=[-6, -3, 0, 3, 6, 9],
                      anchor=(0.5, 0),
                      aspect=30,
                      shrink=0.5)

    cb.ax.xaxis.set_ticks_position('top')
    cb.ax.xaxis.set_label_position('top')
Пример #2
0
def process_data(statData):
    # calculate heritability time
    tauHer = mlsg.calc_tauHer_numeric(
        statData['n0'], statData['mig'])
    tauVar = mlsg.calc_tauV(statData['cost'])
    tauHer_Rel = tauHer/statData['TAU_H']
    tauVar_rel = tauVar/statData['TAU_H']
    dataToStore = (tauHer, tauVar, tauHer_Rel, tauVar_rel)
    nameToStore = ('tauHer', 'tauVar', 'tauHer_rel',
                   'tauVar_rel')
    statData = rf.append_fields(
        statData, nameToStore, dataToStore, usemask=False)

    return statData
Пример #3
0
def process_data(statData):
    # calculate heritability time
    tauHer = mlsg.calc_tauHer_numeric(
        statData['n0'], statData['mig'])
    tauVar = mlsg.calc_tauV(statData['cost'])
    tauHerRel = tauHer/statData['TAU_H']
    tauVar_rel = tauVar/statData['TAU_H']
    sigma_cat = mlsg.make_categorial(statData['sigmaBirth'])
    BH_cat = mlsg.make_categorial(statData['B_H'])
    dataToStore = (tauHer, tauVar, tauHerRel, tauVar_rel, sigma_cat, BH_cat)
    nameToStore = ('tauHer', 'tauVar', 'tauHer_rel',
                   'tauVar_rel', 'sigma_cat', 'BH_cat')

    statData = rf.append_fields(
        statData, nameToStore, dataToStore, usemask=False)

    return statData