From 03b21d091fa4714a557536faf77995ac5af743c7 Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:24:49 -0400
Subject: [PATCH 01/12] ruff __init__

---
 giddy/__init__.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/giddy/__init__.py b/giddy/__init__.py
index 8e89fee..2b9aa05 100644
--- a/giddy/__init__.py
+++ b/giddy/__init__.py
@@ -7,10 +7,10 @@
 
 """
 
-from . import directional
-from . import ergodic
-from . import markov
-from . import mobility
-from . import rank
-from . import util
-from . import sequence
+from . import directional  # noqa F401, E402
+from . import ergodic  # noqa F401, E402
+from . import markov  # noqa F401, E402
+from . import mobility  # noqa F401, E402
+from . import rank  # noqa F401, E402
+from . import util  # noqa F401, E402
+from . import sequence  # noqa F401, E402

From fe4db564c88f9d0e2b5b966b0a648f7938c8f6d9 Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:28:02 -0400
Subject: [PATCH 02/12] ruff directional - check commented out

---
 giddy/directional.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/giddy/directional.py b/giddy/directional.py
index f3999d4..682e9a7 100644
--- a/giddy/directional.py
+++ b/giddy/directional.py
@@ -6,7 +6,7 @@
 
 __all__ = ["Rose"]
 
-import warnings
+
 import numpy as np
 from libpysal import weights
 from libpysal.common import requires as _requires
@@ -27,7 +27,8 @@ class Rose(object):
     Parameters
     ----------
     Y : array (n,2)
-        Columns correspond to end-point time periods to calculate LISA vectors for n object.
+        Columns correspond to end-point time periods to
+        calculate LISA vectors for n object.
     w : PySAL W
         Spatial weights object.
     k : int
@@ -349,10 +350,10 @@ def plot_origin(self):  # TODO add attribute option to color vectors
         Plot vectors of positional transition of LISA values starting
         from the same origin.
         """
-        import matplotlib.cm as cm
+        #import matplotlib.cm as cm
         import matplotlib.pyplot as plt
 
-        ax = plt.subplot(111)
+        #ax = plt.subplot(111)
         xlim = [self._dx.min(), self._dx.max()]
         ylim = [self._dy.min(), self._dy.max()]
         for x, y in zip(self._dx, self._dy):

From a4b3f4e0a3d9678d742eb494d46a87f9e9c5945c Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:32:13 -0400
Subject: [PATCH 03/12] ruff ergodic

---
 giddy/ergodic.py | 13 ++++++++-----
 1 file changed, 8 insertions(+), 5 deletions(-)

diff --git a/giddy/ergodic.py b/giddy/ergodic.py
index 73d91ff..a0a9186 100644
--- a/giddy/ergodic.py
+++ b/giddy/ergodic.py
@@ -124,7 +124,7 @@ def steady_state(P, fill_empty_classes=False):
         ...
     ValueError: Input transition probability matrix has 1 rows full of 0s. Please set fill_empty_classes=True to set diagonal elements for these rows to be 1 to make sure the matrix is stochastic.
 
-    """
+    """  # noqa E501
 
     P = np.asarray(P)
     rows0 = (P.sum(axis=1) == 0).sum()
@@ -204,7 +204,7 @@ def _mfpt_ergodic(P):
     for i in range(k):
         A[:, i] = ss
     A = A.transpose()
-    I = np.identity(k)
+    I = np.identity(k)  # noqa E741
     Z = la.inv(I - P + A)
     E = np.ones_like(Z)
     A_diag = np.diag(A)
@@ -293,7 +293,7 @@ def mfpt(P, fill_empty_classes=False):
     Traceback (most recent call last):
         ...
     ValueError: Input transition probability matrix has 1 rows full of 0s. Please set fill_empty_classes=True to set diagonal elements for these rows to be 1 to make sure the matrix is stochastic.
-    """
+    """  # noqa E501
 
     P = np.asarray(P)
     rows0 = (P.sum(axis=1) == 0).sum()
@@ -353,7 +353,10 @@ def mfpt(P, fill_empty_classes=False):
 
 def var_fmpt_ergodic(p):
     warn(
-        "var_fmpt_ergodic is deprecated. It will be replaced in giddy 2.5 with var_fmpt_ergodic",
+        (
+            "var_fmpt_ergodic is deprecated. It will be "
+            "replaced in giddy 2.5 with var_fmpt_ergodic"
+        ),
         DeprecationWarning,
         stacklevel=2,
     )
@@ -398,7 +401,7 @@ def var_mfpt_ergodic(p):
     k = P.shape[0]
     A = _steady_state_ergodic(P)
     A = np.tile(A, (k, 1))
-    I = np.identity(k)
+    I = np.identity(k)  # noqa E741
     Z = la.inv(I - P + A)
     E = np.ones_like(Z)
     D = np.diag(1.0 / np.diag(A))

From 891b425a50fa1619a03a00f22929b2c93676f012 Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:48:52 -0400
Subject: [PATCH 04/12] ruff markov - check commented out

---
 giddy/markov.py | 29 ++++++++++++++++-------------
 1 file changed, 16 insertions(+), 13 deletions(-)

diff --git a/giddy/markov.py b/giddy/markov.py
index 6876613..84bce93 100644
--- a/giddy/markov.py
+++ b/giddy/markov.py
@@ -19,7 +19,6 @@
 from .ergodic import steady_state, mfpt
 from .util import fill_empty_diagonals
 from .components import Graph
-from warnings import warn
 from scipy import stats
 from scipy.stats import rankdata
 from operator import gt
@@ -282,12 +281,12 @@ def __init__(self, class_ids, classes=None, fill_empty_classes=False, summary=Tr
                     )
                 print(*self.astates_indices, sep=", ")
 
-    @property
-    def mfpt(self):
-        warn("self._mfpt is deprecated. Please use self._mfpt")
-        if not hasattr(self, "_mfpt"):
-            self._mfpt = mfpt(self.p, fill_empty_classes=True)
-        return self._mfpt
+    #@property
+    #def mfpt(self):
+    #    warn("self._mfpt is deprecated. Please use self._mfpt")
+    #    if not hasattr(self, "_mfpt"):
+    #        self._mfpt = mfpt(self.p, fill_empty_classes=True)
+    #    return self._mfpt
 
     @property
     def mfpt(self):
@@ -708,7 +707,9 @@ class Spatial_Markov(object):
     We can easily adjust this assigning `fill_empty_classes = True` when initializing
     `Spatial_Markov`.
 
-    >>> sm = Spatial_Markov(rpci, w, cutoffs=cc, lag_cutoffs=cc, fill_empty_classes=True)
+    >>> sm = Spatial_Markov(
+    ...     rpci, w, cutoffs=cc, lag_cutoffs=cc, fill_empty_classes=True
+    ... )
     >>> for p in sm.P:
     ...     print(p)
     [[0.96703297 0.03296703 0.         0.         0.        ]
@@ -1127,7 +1128,7 @@ def chi2(T1, T2):
 
     .. math::
 
-            E_{i,j} = \sum_j T1_{i,j} * T2_{i,j}/\sum_j T2_{i,j}
+            E_{i,j} = \\sum_j T1_{i,j} * T2_{i,j}/\\sum_j T2_{i,j}
 
     Degrees of freedom corrected for any rows in either T1 or T2 that have
     zero total transitions.
@@ -1849,7 +1850,7 @@ def summary(self, file_name=None, title="Markov Homogeneity Test"):
         lead = "-" * width
         head = title.center(width)
         contents = [lead, head, lead]
-        l = "Number of regimes: %d" % int(self.m)
+        l = "Number of regimes: %d" % int(self.m)  # noqa E741
         k = "Number of classes: %d" % int(self.k)
         r = "Regime names: "
         r += ", ".join(regime_names)
@@ -2085,13 +2086,13 @@ def sojourn_time(p, summary=True):
     >>> sojourn_time(p)
     Sojourn times are infinite for absorbing states! In this Markov Chain, states [2] are absorbing states.
     array([ 2.,  1., inf])
-    """
+    """  # noqa E501
 
     p = np.asarray(p)
     if (p.sum(axis=1) == 0).sum() > 0:
         p = fill_empty_diagonals(p)
 
-    markovchain = qe.MarkovChain(p)
+    #markovchain = qe.MarkovChain(p)
     pii = p.diagonal()
 
     if not (1 - pii).all():
@@ -2212,8 +2213,10 @@ class GeoRank_Markov(Markov):
     """
 
     def __init__(self, y, fill_empty_classes=False, summary=True):
+
         y = np.asarray(y)
-        n = y.shape[0]
+        #n = y.shape[0]
+
         # resolve ties: All values are given a distinct rank, corresponding
         # to the order that the values occur in each cross section.
         ranks = np.array([rankdata(col, method="ordinal") for col in y.T]).T

From 5a00d05dc40443013ec5e19d9484d67344a8f170 Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:51:11 -0400
Subject: [PATCH 05/12] ruff rank - check commented out

---
 giddy/rank.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/giddy/rank.py b/giddy/rank.py
index d89fff9..f1be977 100644
--- a/giddy/rank.py
+++ b/giddy/rank.py
@@ -16,7 +16,6 @@
 from scipy.stats.mstats import rankdata
 from scipy.special import erfc
 import numpy as np
-import scipy as sp
 from libpysal import weights
 
 
@@ -184,7 +183,7 @@ def _calc(self, x, y):
         n = len(y)
         perm = list(range(n))
         perm.sort(key=lambda a: (x[a], y[a]))
-        vals = y[perm]
+        #vals = y[perm]
         ExtraY = 0
         ExtraX = 0
         ACount = 0
@@ -315,8 +314,9 @@ class SpatialTau(object):
     taus               : float
                          spatial tau values for permuted samples (if permutations>0).
     tau_spatial_psim   : float
-                         one-sided pseudo p-value for observed tau_spatial under the null
-                         of spatial randomness of rank exchanges (if permutations>0).
+                         one-sided pseudo p-value for observed tau_spatial
+                         under the null of spatial randomness of rank exchanges
+                         (if permutations>0).
 
     Notes
     -----

From 9007cd458fd310bedbf470850886cee62436dd5e Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:56:46 -0400
Subject: [PATCH 06/12] ruff sequence

---
 giddy/sequence.py | 29 +++++++++++++++++++++++++----
 1 file changed, 25 insertions(+), 4 deletions(-)

diff --git a/giddy/sequence.py b/giddy/sequence.py
index 4eb3ccd..6ecd2c6 100644
--- a/giddy/sequence.py
+++ b/giddy/sequence.py
@@ -84,7 +84,14 @@ class Sequence(object):
 
     1.2 User-defined substitution cost matrix and indel cost
 
-    >>> subs_mat = np.array([[0, 0.76, 0.29, 0.05],[0.30, 0, 0.40, 0.60],[0.16, 0.61, 0, 0.26],[0.38, 0.20, 0.12, 0]])
+    >>> subs_mat = np.array(
+    ...     [
+    ...         [0, 0.76, 0.29, 0.05],
+    ...         [0.30, 0, 0.40, 0.60],
+    ...         [0.16, 0.61, 0, 0.26],
+    ...         [0.38, 0.20, 0.12, 0]
+    ...     ]
+    ... )
     >>> indel = subs_mat.max()
     >>> seqAna = Sequence([seq1,seq2,seq3], subs_mat=subs_mat, indel=indel)
     >>> seqAna.seq_dis_mat
@@ -117,7 +124,14 @@ class Sequence(object):
     between different types is always 1 and indel cost is 2) - give the same
     sequence distance matrix as "hamming" distance
 
-    >>> subs_mat = np.array([[0., 1., 1., 1.],[1., 0., 1., 1.],[1., 1., 0., 1.],[1., 1., 1., 0.]])
+    >>> subs_mat = np.array(
+    ...     [
+    ...         [0., 1., 1., 1.],
+    ...         [1., 0., 1., 1.],
+    ...         [1., 1., 0., 1.],
+    ...         [1., 1., 1., 0.]
+    ...     ]
+    ... )
     >>> indel = 2
     >>> seqAna = Sequence([seq1,seq2,seq3], subs_mat=subs_mat, indel=indel)
     >>> seqAna.seq_dis_mat
@@ -130,7 +144,14 @@ class Sequence(object):
     slightly different sequence distance matrix from "hamming" distance since
     insertion and deletion is happening
 
-    >>> subs_mat = np.array([[0., 1., 1., 1.],[1., 0., 1., 1.],[1., 1., 0.,1.],[1., 1., 1., 0.]])
+    >>> subs_mat = np.array(
+    ...     [
+    ...         [0., 1., 1., 1.],
+    ...         [1., 0., 1., 1.],
+    ...         [1., 1., 0., 1.],
+    ...         [1., 1., 1., 0.]
+    ...     ]
+    ... )
     >>> indel = 1
     >>> seqAna = Sequence([seq1,seq2,seq3], subs_mat=subs_mat, indel=indel)
     >>> seqAna.seq_dis_mat
@@ -151,7 +172,7 @@ class Sequence(object):
     >>> seqAna = Sequence([seq1,seq2,seq3], indel=indel)
     Traceback (most recent call last):
     ValueError: Please specify a proper `dist_type` or `subs_mat` and `indel` to proceed!
-    """
+    """  # noqa E501
 
     def __init__(self, y, subs_mat=None, dist_type=None, indel=None, cluster_type=None):
         y = np.asarray(y)

From 147140f4844b2ee321f2ce8efc677364f53c0239 Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:56:59 -0400
Subject: [PATCH 07/12] ruff test_sequence

---
 giddy/tests/test_sequence.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/giddy/tests/test_sequence.py b/giddy/tests/test_sequence.py
index 8c2ae05..02426f5 100644
--- a/giddy/tests/test_sequence.py
+++ b/giddy/tests/test_sequence.py
@@ -1,4 +1,3 @@
-import unittest
 import numpy as np
 import pytest
 from ..sequence import Sequence

From f689cea08226d71de30165a828cb7d2e580e8d6e Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:57:32 -0400
Subject: [PATCH 08/12] re-blacken

---
 giddy/directional.py | 4 ++--
 giddy/markov.py      | 9 ++++-----
 giddy/rank.py        | 2 +-
 3 files changed, 7 insertions(+), 8 deletions(-)

diff --git a/giddy/directional.py b/giddy/directional.py
index 682e9a7..13c5188 100644
--- a/giddy/directional.py
+++ b/giddy/directional.py
@@ -350,10 +350,10 @@ def plot_origin(self):  # TODO add attribute option to color vectors
         Plot vectors of positional transition of LISA values starting
         from the same origin.
         """
-        #import matplotlib.cm as cm
+        # import matplotlib.cm as cm
         import matplotlib.pyplot as plt
 
-        #ax = plt.subplot(111)
+        # ax = plt.subplot(111)
         xlim = [self._dx.min(), self._dx.max()]
         ylim = [self._dy.min(), self._dy.max()]
         for x, y in zip(self._dx, self._dy):
diff --git a/giddy/markov.py b/giddy/markov.py
index 84bce93..1ccd529 100644
--- a/giddy/markov.py
+++ b/giddy/markov.py
@@ -281,8 +281,8 @@ def __init__(self, class_ids, classes=None, fill_empty_classes=False, summary=Tr
                     )
                 print(*self.astates_indices, sep=", ")
 
-    #@property
-    #def mfpt(self):
+    # @property
+    # def mfpt(self):
     #    warn("self._mfpt is deprecated. Please use self._mfpt")
     #    if not hasattr(self, "_mfpt"):
     #        self._mfpt = mfpt(self.p, fill_empty_classes=True)
@@ -2092,7 +2092,7 @@ def sojourn_time(p, summary=True):
     if (p.sum(axis=1) == 0).sum() > 0:
         p = fill_empty_diagonals(p)
 
-    #markovchain = qe.MarkovChain(p)
+    # markovchain = qe.MarkovChain(p)
     pii = p.diagonal()
 
     if not (1 - pii).all():
@@ -2213,9 +2213,8 @@ class GeoRank_Markov(Markov):
     """
 
     def __init__(self, y, fill_empty_classes=False, summary=True):
-
         y = np.asarray(y)
-        #n = y.shape[0]
+        # n = y.shape[0]
 
         # resolve ties: All values are given a distinct rank, corresponding
         # to the order that the values occur in each cross section.
diff --git a/giddy/rank.py b/giddy/rank.py
index f1be977..8ef936b 100644
--- a/giddy/rank.py
+++ b/giddy/rank.py
@@ -183,7 +183,7 @@ def _calc(self, x, y):
         n = len(y)
         perm = list(range(n))
         perm.sort(key=lambda a: (x[a], y[a]))
-        #vals = y[perm]
+        # vals = y[perm]
         ExtraY = 0
         ExtraX = 0
         ACount = 0

From 9972017c6617dd0e081f7ab177f6e3a94a2a9515 Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Tue, 3 Oct 2023 20:59:10 -0400
Subject: [PATCH 09/12] adding pre-commit

---
 .pre-commit-config.yaml | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 .pre-commit-config.yaml

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..78f73a7
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,15 @@
+files: "giddy\/"
+repos:
+  - repo: https://github.com/psf/black
+    rev: "23.9.1"
+    hooks:
+      - id: black
+        language_version: python3
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: "v0.0.292"
+    hooks:
+      - id: ruff
+
+ci:
+  autofix_prs: false
+  autoupdate_schedule: quarterly

From 0ca8a5312b9a7bcd2627bbf021e2cba420389abd Mon Sep 17 00:00:00 2001
From: James Gaboardi <jgaboardi@gmail.com>
Date: Thu, 5 Oct 2023 13:19:48 -0400
Subject: [PATCH 10/12] update raw string input

---
 giddy/markov.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/giddy/markov.py b/giddy/markov.py
index 1ccd529..3a1507c 100644
--- a/giddy/markov.py
+++ b/giddy/markov.py
@@ -1076,7 +1076,7 @@ def _maybe_classify(self, y, k, cutoffs):
 
 
 def chi2(T1, T2):
-    """
+    r"""
     chi-squared test of difference between two transition matrices.
 
     Parameters
@@ -1128,7 +1128,7 @@ def chi2(T1, T2):
 
     .. math::
 
-            E_{i,j} = \\sum_j T1_{i,j} * T2_{i,j}/\\sum_j T2_{i,j}
+            E_{i,j} = \sum_j T1_{i,j} * T2_{i,j}/\sum_j T2_{i,j}
 
     Degrees of freedom corrected for any rows in either T1 or T2 that have
     zero total transitions.

From 8a7e6f97f530ea59d3ba1755e72bd9ab5d24a209 Mon Sep 17 00:00:00 2001
From: Wei Kang <weikang9009@gmail.com>
Date: Tue, 17 Oct 2023 09:51:01 -0500
Subject: [PATCH 11/12] remove noqa comments and resolve issues in
 https://github.com/pysal/giddy/pull/202

---
 giddy/__init__.py | 14 +++++++-------
 giddy/ergodic.py  | 22 +++++++++++-----------
 giddy/markov.py   | 13 +++----------
 giddy/sequence.py |  2 +-
 4 files changed, 22 insertions(+), 29 deletions(-)

diff --git a/giddy/__init__.py b/giddy/__init__.py
index 2b9aa05..8e89fee 100644
--- a/giddy/__init__.py
+++ b/giddy/__init__.py
@@ -7,10 +7,10 @@
 
 """
 
-from . import directional  # noqa F401, E402
-from . import ergodic  # noqa F401, E402
-from . import markov  # noqa F401, E402
-from . import mobility  # noqa F401, E402
-from . import rank  # noqa F401, E402
-from . import util  # noqa F401, E402
-from . import sequence  # noqa F401, E402
+from . import directional
+from . import ergodic
+from . import markov
+from . import mobility
+from . import rank
+from . import util
+from . import sequence
diff --git a/giddy/ergodic.py b/giddy/ergodic.py
index a0a9186..12497ae 100644
--- a/giddy/ergodic.py
+++ b/giddy/ergodic.py
@@ -124,7 +124,7 @@ def steady_state(P, fill_empty_classes=False):
         ...
     ValueError: Input transition probability matrix has 1 rows full of 0s. Please set fill_empty_classes=True to set diagonal elements for these rows to be 1 to make sure the matrix is stochastic.
 
-    """  # noqa E501
+    """
 
     P = np.asarray(P)
     rows0 = (P.sum(axis=1) == 0).sum()
@@ -201,17 +201,17 @@ def _mfpt_ergodic(P):
     k = P.shape[0]
     A = np.zeros_like(P)
     ss = _steady_state_ergodic(P)
-    for i in range(k):
-        A[:, i] = ss
+    for j in range(k):
+        A[:, j] = ss
     A = A.transpose()
-    I = np.identity(k)  # noqa E741
-    Z = la.inv(I - P + A)
+    i = np.identity(k)
+    Z = la.inv(i - P + A)
     E = np.ones_like(Z)
     A_diag = np.diag(A)
     A_diag = A_diag + (A_diag == 0)
     D = np.diag(1.0 / A_diag)
     Zdg = np.diag(np.diag(Z))
-    M = (I - Z + E.dot(Zdg)).dot(D)
+    M = (i - Z + E.dot(Zdg)).dot(D)
     return M
 
 
@@ -293,7 +293,7 @@ def mfpt(P, fill_empty_classes=False):
     Traceback (most recent call last):
         ...
     ValueError: Input transition probability matrix has 1 rows full of 0s. Please set fill_empty_classes=True to set diagonal elements for these rows to be 1 to make sure the matrix is stochastic.
-    """  # noqa E501
+    """
 
     P = np.asarray(P)
     rows0 = (P.sum(axis=1) == 0).sum()
@@ -401,13 +401,13 @@ def var_mfpt_ergodic(p):
     k = P.shape[0]
     A = _steady_state_ergodic(P)
     A = np.tile(A, (k, 1))
-    I = np.identity(k)  # noqa E741
-    Z = la.inv(I - P + A)
+    i = np.identity(k)
+    Z = la.inv(i - P + A)
     E = np.ones_like(Z)
     D = np.diag(1.0 / np.diag(A))
     Zdg = np.diag(np.diag(Z))
-    M = (I - Z + E.dot(Zdg)).dot(D)
+    M = (i - Z + E.dot(Zdg)).dot(D)
     ZM = Z.dot(M)
     ZMdg = np.diag(np.diag(ZM))
-    W = M.dot(2 * Zdg.dot(D) - I) + 2 * (ZM - E.dot(ZMdg))
+    W = M.dot(2 * Zdg.dot(D) - i) + 2 * (ZM - E.dot(ZMdg))
     return np.array(W - np.multiply(M, M))
diff --git a/giddy/markov.py b/giddy/markov.py
index 3a1507c..6166d9f 100644
--- a/giddy/markov.py
+++ b/giddy/markov.py
@@ -281,13 +281,6 @@ def __init__(self, class_ids, classes=None, fill_empty_classes=False, summary=Tr
                     )
                 print(*self.astates_indices, sep=", ")
 
-    # @property
-    # def mfpt(self):
-    #    warn("self._mfpt is deprecated. Please use self._mfpt")
-    #    if not hasattr(self, "_mfpt"):
-    #        self._mfpt = mfpt(self.p, fill_empty_classes=True)
-    #    return self._mfpt
-
     @property
     def mfpt(self):
         if not hasattr(self, "_mfpt"):
@@ -1850,14 +1843,14 @@ def summary(self, file_name=None, title="Markov Homogeneity Test"):
         lead = "-" * width
         head = title.center(width)
         contents = [lead, head, lead]
-        l = "Number of regimes: %d" % int(self.m)  # noqa E741
+        L = "Number of regimes: %d" % int(self.m)
         k = "Number of classes: %d" % int(self.k)
         r = "Regime names: "
         r += ", ".join(regime_names)
         t = "Number of transitions: %d" % int(self.t_total)
         contents.append(k)
         contents.append(t)
-        contents.append(l)
+        contents.append(L)
         contents.append(r)
         contents.append(lead)
         h = "%7s %20s %20s" % ("Test", "LR", "Chi-2")
@@ -2086,7 +2079,7 @@ def sojourn_time(p, summary=True):
     >>> sojourn_time(p)
     Sojourn times are infinite for absorbing states! In this Markov Chain, states [2] are absorbing states.
     array([ 2.,  1., inf])
-    """  # noqa E501
+    """
 
     p = np.asarray(p)
     if (p.sum(axis=1) == 0).sum() > 0:
diff --git a/giddy/sequence.py b/giddy/sequence.py
index 6ecd2c6..8d9d481 100644
--- a/giddy/sequence.py
+++ b/giddy/sequence.py
@@ -172,7 +172,7 @@ class Sequence(object):
     >>> seqAna = Sequence([seq1,seq2,seq3], indel=indel)
     Traceback (most recent call last):
     ValueError: Please specify a proper `dist_type` or `subs_mat` and `indel` to proceed!
-    """  # noqa E501
+    """
 
     def __init__(self, y, subs_mat=None, dist_type=None, indel=None, cluster_type=None):
         y = np.asarray(y)

From fc9993fdf8309b53dc7fbf9a2e7e749fe00e5e9d Mon Sep 17 00:00:00 2001
From: Wei Kang <weikang9009@gmail.com>
Date: Tue, 17 Oct 2023 09:53:53 -0500
Subject: [PATCH 12/12] remove lines that are redundant

---
 giddy/directional.py | 2 --
 giddy/rank.py        | 1 -
 2 files changed, 3 deletions(-)

diff --git a/giddy/directional.py b/giddy/directional.py
index 13c5188..6136881 100644
--- a/giddy/directional.py
+++ b/giddy/directional.py
@@ -350,10 +350,8 @@ def plot_origin(self):  # TODO add attribute option to color vectors
         Plot vectors of positional transition of LISA values starting
         from the same origin.
         """
-        # import matplotlib.cm as cm
         import matplotlib.pyplot as plt
 
-        # ax = plt.subplot(111)
         xlim = [self._dx.min(), self._dx.max()]
         ylim = [self._dy.min(), self._dy.max()]
         for x, y in zip(self._dx, self._dy):
diff --git a/giddy/rank.py b/giddy/rank.py
index 8ef936b..efb6cf2 100644
--- a/giddy/rank.py
+++ b/giddy/rank.py
@@ -183,7 +183,6 @@ def _calc(self, x, y):
         n = len(y)
         perm = list(range(n))
         perm.sort(key=lambda a: (x[a], y[a]))
-        # vals = y[perm]
         ExtraY = 0
         ExtraX = 0
         ACount = 0