def test_plot_km():
if pdf_output:
from matplotlib.backends.backend_pdf import PdfPages
pdf = PdfPages("test_survfunc.pdf")
else:
pdf = None
sr1 = SurvfuncRight(ti1, st1)
sr2 = SurvfuncRight(ti2, st2)
fig = plot_survfunc(sr1)
close_or_save(pdf, fig)
fig = plot_survfunc(sr2)
close_or_save(pdf, fig)
fig = plot_survfunc([sr1, sr2])
close_or_save(pdf, fig)
# Plot the SAS BMT data
gb = bmt.groupby("Group")
sv = []
for g in gb:
s0 = SurvfuncRight(g[1]["T"], g[1]["Status"], title=g[0])
sv.append(s0)
fig = plot_survfunc(sv)
ax = fig.get_axes()[0]
ax.set_position([0.1, 0.1, 0.64, 0.8])
ha, lb = ax.get_legend_handles_labels()
fig.legend([ha[k] for k in (0, 2, 4)],
[lb[k] for k in (0, 2, 4)],
'center right')
close_or_save(pdf, fig)
# Simultaneous CB for BMT data
ii = bmt.Group == "ALL"
sf = SurvfuncRight(bmt.loc[ii, "T"], bmt.loc[ii, "Status"])
fig = sf.plot()
ax = fig.get_axes()[0]
ax.set_position([0.1, 0.1, 0.64, 0.8])
ha, lb = ax.get_legend_handles_labels()
lcb, ucb = sf.simultaneous_cb(transform="log")
plt.fill_between(sf.surv_times, lcb, ucb, color="lightgrey")
lcb, ucb = sf.simultaneous_cb(transform="arcsin")
plt.plot(sf.surv_times, lcb, color="darkgrey")
plt.plot(sf.surv_times, ucb, color="darkgrey")
plt.plot(sf.surv_times, sf.surv_prob - 2*sf.surv_prob_se, color="red")
plt.plot(sf.surv_times, sf.surv_prob + 2*sf.surv_prob_se, color="red")
plt.xlim(100, 600)
close_or_save(pdf, fig)
if pdf_output:
pdf.close()
def test_simultaneous_cb():
# The exact numbers here are regression tests, but they are close
# to page 103 of Klein and Moeschberger.
df = bmt.loc[bmt["Group"] == "ALL", :]
sf = SurvfuncRight(df["T"], df["Status"])
lcb1, ucb1 = sf.simultaneous_cb(transform="log")
lcb2, ucb2 = sf.simultaneous_cb(transform="arcsin")
ti = sf.surv_times.tolist()
ix = [ti.index(x) for x in (110, 122, 129, 172)]
assert_allclose(lcb1[ix], np.r_[0.43590582, 0.42115592, 0.4035897, 0.38785927])
assert_allclose(ucb1[ix], np.r_[0.93491636, 0.89776803, 0.87922239, 0.85894181])
assert_allclose(lcb2[ix], np.r_[0.52115708, 0.48079378, 0.45595321, 0.43341115])
assert_allclose(ucb2[ix], np.r_[0.96465636, 0.92745068, 0.90885428, 0.88796708])
def test_simultaneous_cb():
# The exact numbers here are regression tests, but they are close
# to page 103 of Klein and Moeschberger.
df = bmt.loc[bmt["Group"] == "ALL", :]
sf = SurvfuncRight(df["T"], df["Status"])
lcb1, ucb1 = sf.simultaneous_cb(transform="log")
lcb2, ucb2 = sf.simultaneous_cb(transform="arcsin")
ti = sf.surv_times.tolist()
ix = [ti.index(x) for x in (110, 122, 129, 172)]
assert_allclose(lcb1[ix], np.r_[0.43590582, 0.42115592, 0.4035897,
0.38785927])
assert_allclose(ucb1[ix], np.r_[0.93491636, 0.89776803, 0.87922239,
0.85894181])
assert_allclose(lcb2[ix], np.r_[0.52115708, 0.48079378, 0.45595321,
0.43341115])
assert_allclose(ucb2[ix], np.r_[0.96465636, 0.92745068, 0.90885428,
0.88796708])
