def test_weibull_aft_plot_partial_effects_on_outcome_with_multiple_columns(self, block):
df = load_rossi()
aft = WeibullAFTFitter()
aft.fit(df, "week", "arrest")
aft.plot_partial_effects_on_outcome(["age", "prio"], [[10, 0], [50, 10], [80, 50]])
self.plt.tight_layout()
self.plt.title("test_weibull_aft_plot_partial_effects_on_outcome_with_multiple_columns")
self.plt.show(block=block)
def test_weibull_aft_plot_partial_effects_on_outcome(self, block):
df = load_rossi()
aft = WeibullAFTFitter()
aft.fit(df, "week", "arrest")
aft.plot_partial_effects_on_outcome("age", [10, 50, 80])
self.plt.tight_layout()
self.plt.title("test_weibull_aft_plot_partial_effects_on_outcome")
self.plt.show(block=block)
def test_aft_plot_partial_effects_on_outcome_with_categorical(self, block):
df = load_rossi()
df["cat"] = np.random.choice(["a", "b", "c"], size=df.shape[0])
aft = WeibullAFTFitter()
aft.fit(df, "week", "arrest", formula="cat + age + fin")
aft.plot_partial_effects_on_outcome("cat", values=["a", "b", "c"])
self.plt.title("test_aft_plot_partial_effects_on_outcome_with_categorical")
self.plt.show(block=block)
def home_vary_survival(df, DURATION, EVENT, option):
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(10, 7))
#plt.ylim(0, 1.01)
#plt.xlim(0, 60)
times = np.arange(0, 120)
if option == "Baseline":
kmf = KaplanMeierFitter().fit(df[DURATION], df[EVENT])
kmf.survival_function_.plot(ax=ax)
else:
min_value = min(df[option].values)
max_value = max(df[option].values) + 1
interval = math.ceil((max_value - min_value) / 4)
value_range = range(min_value, max_value, interval)
wft = WeibullAFTFitter().fit(df,
DURATION,
EVENT,
ancillary=True,
timeline=times)
wft.plot_partial_effects_on_outcome(option,
value_range,
cmap='coolwarm',
ax=ax)
st.pyplot(plt)
duration_col="mainline_vol",
event_col="failure",
formula=
"ramp_metering+length_of_acceleration_lane+ffs_cap_df+number_of_mainline_lane_downstream+simple_merge",
)
aft.print_summary()
aft.plot()
aft.median_survival_time_
aft.mean_survival_time_
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(5, 4))
aft.plot_partial_effects_on_outcome(
"ramp_metering",
[0, 1],
cmap="coolwarm",
ax=ax,
plot_baseline=False,
times=range(1000, 3200, 50),
)
fig2, ax1 = plt.subplots(nrows=1, ncols=1, figsize=(5, 4))
aft.plot_partial_effects_on_outcome(
"length_of_acceleration_lane",
[500, 1000, 1500],
plot_baseline=False,
cmap="coolwarm",
ax=ax1,
times=range(1000, 3200, 50),
)
fig2, ax1 = plt.subplots(nrows=1, ncols=1, figsize=(5, 4))
