From 5297391b10ff626c92b60038930a86f7fc26ab32 Mon Sep 17 00:00:00 2001 From: Wei Kang Date: Sat, 29 Jun 2024 18:14:21 -0500 Subject: [PATCH] change doctests output --- giddy/markov.py | 16 ++++++++-------- giddy/rank.py | 8 ++++---- 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/giddy/markov.py b/giddy/markov.py index e10c79c..367f252 100644 --- a/giddy/markov.py +++ b/giddy/markov.py @@ -1119,7 +1119,7 @@ def chi2(T1, T2): [ 1., 92., 815., 51.], [ 1., 0., 60., 903.]]) >>> chi2(T1,T2) - (23.39728441473295, 0.005363116704861337, 9) + (np.float64(23.39728441473295), np.float64(0.005363116704861337), np.int64(9)) Notes ----- @@ -1468,20 +1468,20 @@ def spillover(self, quadrant=1, neighbors_on=False): >>> lm_random = LISA_Markov(pci, w, permutations=99) >>> r = lm_random.spillover() >>> (r['components'][:, 12] > 0).sum() - 17 + np.int64(17) >>> (r['components'][:, 13]>0).sum() - 23 + np.int64(23) >>> (r['spill_over'][:,12]>0).sum() - 6 + np.int64(6) Including neighbors of core neighbors >>> rn = lm_random.spillover(neighbors_on=True) >>> (rn['components'][:, 12] > 0).sum() - 26 + np.int64(26) >>> (rn["components"][:, 13] > 0).sum() - 34 + np.int64(34) >>> (rn["spill_over"][:, 12] > 0).sum() - 8 + np.int64(8) """ n, k = self.q.shape @@ -2081,7 +2081,7 @@ def sojourn_time(p, summary=True): >>> p = np.array([[.5, .25, .25], [.5, 0, .5],[ 0, 0, 0]]) >>> sojourn_time(p) - Sojourn times are infinite for absorbing states! In this Markov Chain, states [2] are absorbing states. + Sojourn times are infinite for absorbing states! In this Markov Chain, states [np.int64(2)] are absorbing states. array([ 2., 1., inf]) """ # noqa E501 diff --git a/giddy/rank.py b/giddy/rank.py index 4f71f4e..2141baf 100644 --- a/giddy/rank.py +++ b/giddy/rank.py @@ -469,10 +469,10 @@ class Tau_Local: 0.48387097, 0.93548387, 0.61290323, 0.74193548, 0.41935484, 0.61290323, 0.61290323]) >>> tau_local.tau - 0.6612903225806451 + np.float64(0.6612903225806451) >>> tau_classic = Tau(r[:,0],r[:,1]) >>> tau_classic.tau - 0.6612903225806451 + np.float64(0.6612903225806451) """ @@ -586,10 +586,10 @@ class Tau_Local_Neighbor: array([-1, 1, 1, 1, 1, 1, 1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1]) >>> (res.tau_ln * res.tau_ln_weights).sum() #global spatial tau - 0.39682539682539675 + np.float64(0.39682539682539675) >>> res1 = SpatialTau(r[:,0],r[:,1],w,permutations=999) >>> res1.tau_spatial - 0.3968253968253968 + np.float64(0.3968253968253968) """