fix some tests and use initial conditions

lifelines/fitters/piecewise_exponential_fitter.py

@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 import autograd.numpy as np
 from lifelines.fitters import KnownModelParametricUnivariateFitter
+from lifelines import utils
 
 
 class PiecewiseExponentialFitter(KnownModelParametricUnivariateFitter):
@@ -81,6 +82,7 @@ def __init__(self, breakpoints, *args, **kwargs):
         super(PiecewiseExponentialFitter, self).__init__(*args, **kwargs)
 
     def _cumulative_hazard(self, params, times):
+        times = np.atleast_1d(times)
         n = times.shape[0]
         times = times.reshape((n, 1))
         bp = self.breakpoints

lifelines/fitters/spline_fitter.py

@@ -90,6 +90,9 @@ def __init__(self, knot_locations: np.ndarray, *args, **kwargs):
         self._bounds = [(None, None)] * (self.n_knots)
         super(SplineFitter, self).__init__(*args, **kwargs)
 
+    def _create_initial_point(self, Ts, E, entry, weights):
+        return 0.1 * np.ones(self.n_knots)
+
     def _cumulative_hazard(self, params, t):
         phis = params
         lT = np.log(t)

lifelines/tests/test_estimation.py

@@ -118,7 +118,7 @@ def __init__(self, *args, **kwargs):
 
 class SplineFitterTesting(SplineFitter):
     def __init__(self, *args, **kwargs):
-        super(SplineFitterTesting, self).__init__([0.0, 50.0], *args, **kwargs)
+        super(SplineFitterTesting, self).__init__([0.0, 40.0], *args, **kwargs)
 
 
 class CustomRegressionModelTesting(ParametricRegressionFitter):