From 2b88cb4c60a90db948a3048f823062a57982ecee Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Fri, 10 Jan 2020 17:04:27 +0100
Subject: [PATCH 01/10] Renamed resid methods to resdiuals

---
 nistats/regression.py | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/nistats/regression.py b/nistats/regression.py
index 670e7676..be2e470d 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -18,6 +18,8 @@
 
 __docformat__ = 'restructuredtext en'
 
+import warnings
+
 import numpy as np
 
 from nibabel.onetime import setattr_on_read
@@ -279,6 +281,15 @@ def __init__(self, theta, Y, model, wY, wresid, cov=None, dispersion=1.,
 
     @setattr_on_read
     def resid(self):
+        warnings.warn(FutureWarning,
+                      "'RegressionResults.resid method has been deprecated "
+                      "and will be removed. "
+                      "Please use RegressionResults.residuals()'.")
+        return self.resdiuals()
+
+
+    @setattr_on_read
+    def residuals(self):
         """
         Residuals from the fit.
         """
@@ -354,6 +365,13 @@ def logL(self, Y):
         raise ValueError('can not use this method for simple results')
 
     def resid(self, Y):
+        warnings.warn(FutureWarning,
+                      "'SimpleRegressionResults.resid method has been deprecated "
+                      "and will be removed. "
+                      "Please use SimpleRegressionResults.residuals()'.")
+        return self.residuals(Y)
+
+    def residuals(self, Y):
         """
         Residuals from the fit.
         """

From aa0ca874be356f6851054984a239db355610d3e6 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Mon, 13 Jan 2020 12:57:04 +0100
Subject: [PATCH 02/10] Fixed typo and call

---
 nistats/regression.py | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/nistats/regression.py b/nistats/regression.py
index 939bf6d1..2ab6bf97 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -282,12 +282,12 @@ def __init__(self, theta, Y, model, wY, wresid, cov=None, dispersion=1.,
 
     @setattr_on_read
     def resid(self):
-        warnings.warn(FutureWarning,
-                      "'RegressionResults.resid method has been deprecated "
+        warnings.warn("'RegressionResults.resid()' method has been deprecated "
                       "and will be removed. "
-                      "Please use RegressionResults.residuals()'.")
-        return self.resdiuals()
-
+                      "Please use 'RegressionResults.residuals()'.",
+                      FutureWarning,
+                      )
+        return self.residuals
 
     @setattr_on_read
     def residuals(self):
@@ -373,10 +373,11 @@ def logL(self, Y):
         raise ValueError('can not use this method for simple results')
 
     def resid(self, Y):
-        warnings.warn(FutureWarning,
-                      "'SimpleRegressionResults.resid method has been deprecated "
+        warnings.warn("'SimpleRegressionResults.resid()' method has been deprecated "
                       "and will be removed. "
-                      "Please use SimpleRegressionResults.residuals()'.")
+                      "Please use 'SimpleRegressionResults.residuals()'.",
+                      FutureWarning,
+                      )
         return self.residuals(Y)
 
     def residuals(self, Y):

From 21d5127ca0c949db80340b647bd8570c33456813 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Mon, 13 Jan 2020 14:15:37 +0100
Subject: [PATCH 03/10] Added residuals and resid to tests

---
 nistats/regression.py            |  4 ++--
 nistats/tests/test_regression.py | 13 +++++++++----
 2 files changed, 11 insertions(+), 6 deletions(-)

diff --git a/nistats/regression.py b/nistats/regression.py
index 2ab6bf97..58c9ead3 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -282,9 +282,9 @@ def __init__(self, theta, Y, model, wY, wresid, cov=None, dispersion=1.,
 
     @setattr_on_read
     def resid(self):
-        warnings.warn("'RegressionResults.resid()' method has been deprecated "
+        warnings.warn("'RegressionResults.resid' method has been deprecated "
                       "and will be removed. "
-                      "Please use 'RegressionResults.residuals()'.",
+                      "Please use 'RegressionResults.residuals'.",
                       FutureWarning,
                       )
         return self.residuals
diff --git a/nistats/tests/test_regression.py b/nistats/tests/test_regression.py
index b96bcba1..436d6c0d 100644
--- a/nistats/tests/test_regression.py
+++ b/nistats/tests/test_regression.py
@@ -3,6 +3,7 @@
 """
 
 import numpy as np
+import pytest
 
 from numpy.testing import (assert_array_almost_equal,
                            assert_almost_equal,
@@ -21,16 +22,20 @@ def test_OLS():
     model = OLSModel(design=X)
     results = model.fit(Y)
     assert results.df_resid == 30
-    assert results.resid.shape[0] == 40
+    assert results.residuals.shape[0] == 40
     assert results.predicted.shape[0] == 40
+    with pytest.warns(FutureWarning):
+        assert results.resid.shape[0] == 40
 
 
 def test_AR():
     model = ARModel(design=X, rho=0.4)
     results = model.fit(Y)
     assert results.df_resid == 30
-    assert results.resid.shape[0] == 40
+    assert results.residuals.shape[0] == 40
     assert results.predicted.shape[0] == 40
+    with pytest.warns(FutureWarning):
+        assert results.resid.shape[0] == 40
 
 
 def test_residuals():
@@ -42,7 +47,7 @@ def test_residuals():
     Xintercept[:, 0] = 1
     model = OLSModel(design=Xintercept)
     results = model.fit(Y)
-    assert_almost_equal(results.resid.mean(), 0)
+    assert_almost_equal(results.residuals.mean(), 0)
 
 
 def test_predicted_r_square():
@@ -54,7 +59,7 @@ def test_predicted_r_square():
     # rounding errors)
     model = OLSModel(design=Xshort)
     results = model.fit(Yshort)
-    assert_almost_equal(results.resid.sum(), 0)
+    assert_almost_equal(results.residuals.sum(), 0)
     assert_array_almost_equal(results.predicted, Yshort)
     assert_almost_equal(results.r_square, 1.0)
 

From 71313bcfdc4b070847ac21d0e499f8b7f243c57e Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Tue, 14 Jan 2020 17:02:52 +0100
Subject: [PATCH 04/10] Renamed norm_resid to normalized_resuiduals

---
 nistats/first_level_model.py |  2 +-
 nistats/regression.py        | 17 +++++++++++++++++
 2 files changed, 18 insertions(+), 1 deletion(-)

diff --git a/nistats/first_level_model.py b/nistats/first_level_model.py
index ef4e770c..b67c0d53 100644
--- a/nistats/first_level_model.py
+++ b/nistats/first_level_model.py
@@ -596,7 +596,7 @@ def _get_voxelwise_model_attribute(self, attribute, result_as_time_series):
         ----------
         attribute : str
             an attribute of a RegressionResults instance.
-            possible values include: resid, norm_resid, predicted,
+            possible values include: resid, norm_residuals, predicted,
             SSE, r_square, MSE.
         result_as_time_series : bool
             whether the RegressionResult attribute has a value
diff --git a/nistats/regression.py b/nistats/regression.py
index 58c9ead3..bea55744 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -298,6 +298,15 @@ def residuals(self):
 
     @setattr_on_read
     def norm_resid(self):
+        warnings.warn("'RegressionResults.norm_resid' method has been deprecated "
+                      "and will be removed. "
+                      "Please use 'RegressionResults.normalized_residuals'.",
+                      FutureWarning,
+                      )
+        return self.normalized_residuals
+
+    @setattr_on_read
+    def normalized_residuals(self):
         """
         Residuals, normalized to have unit length.
 
@@ -387,6 +396,14 @@ def residuals(self, Y):
         return Y - self.predicted
 
     def norm_resid(self, Y):
+        warnings.warn("'SimpleRegressionResults.norm_resid' method has been deprecated "
+                      "and will be removed. "
+                      "Please use 'SimpleRegressionResults.normalized_residuals'.",
+                      FutureWarning,
+                      )
+        return self.normalized_residuals(Y)
+
+    def normalized_residuals(self, Y):
         """
         Residuals, normalized to have unit length.
 

From 1093cca254208877fe388f6a29ce6b8c64348885 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Tue, 14 Jan 2020 17:04:03 +0100
Subject: [PATCH 05/10] Undid inadvertent option string change

---
 nistats/first_level_model.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nistats/first_level_model.py b/nistats/first_level_model.py
index b67c0d53..ef4e770c 100644
--- a/nistats/first_level_model.py
+++ b/nistats/first_level_model.py
@@ -596,7 +596,7 @@ def _get_voxelwise_model_attribute(self, attribute, result_as_time_series):
         ----------
         attribute : str
             an attribute of a RegressionResults instance.
-            possible values include: resid, norm_residuals, predicted,
+            possible values include: resid, norm_resid, predicted,
             SSE, r_square, MSE.
         result_as_time_series : bool
             whether the RegressionResult attribute has a value

From 867cd49bac8f70adee19511d259426b1039be0b2 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Wed, 15 Jan 2020 16:58:47 +0100
Subject: [PATCH 06/10] Reanmed *_resid to *_residuals and added deprecation
 warning

---
 nistats/contrasts.py             |  2 +-
 nistats/model.py                 | 23 +++++++++++++++--------
 nistats/regression.py            | 20 ++++++++++++++++----
 nistats/tests/test_regression.py |  8 ++++----
 4 files changed, 36 insertions(+), 17 deletions(-)

diff --git a/nistats/contrasts.py b/nistats/contrasts.py
index f7e0ecae..b4339711 100644
--- a/nistats/contrasts.py
+++ b/nistats/contrasts.py
@@ -90,7 +90,7 @@ def compute_contrast(labels, regression_result, con_val, contrast_type=None):
             effect_[:, label_mask] = wcbeta
             var_[label_mask] = rss
 
-    dof_ = regression_result[label_].df_resid
+    dof_ = regression_result[label_].df_residuals
     return Contrast(effect=effect_, variance=var_, dim=dim, dof=dof_,
                     contrast_type=contrast_type)
 
diff --git a/nistats/model.py b/nistats/model.py
index fba86006..e164dfa8 100644
--- a/nistats/model.py
+++ b/nistats/model.py
@@ -3,6 +3,7 @@
 
 Author: Bertrand Thirion, 2011--2015
 """
+import warnings
 
 import numpy as np
 
@@ -72,8 +73,14 @@ def __init__(self, theta, Y, model, cov=None, dispersion=1., nuisance=None,
         self.df_total = Y.shape[0]
         self.df_model = model.df_model
         # put this as a parameter of LikelihoodModel
-        self.df_resid = self.df_total - self.df_model
-        
+        self.df_residuals = self.df_total - self.df_model
+
+    @setattr_on_read
+    def df_resid(self):
+        warnings.warn("The attribute 'df_resid' from LikelihoodModelResults"
+                      "has been deprecated. Please use 'df_residuals'.")
+        return self.df_residuals
+
     @setattr_on_read
     def logL(self):
         """
@@ -200,7 +207,7 @@ def Tcontrast(self, matrix, store=('t', 'effect', 'sd'), dispersion=None):
         if 't' in store:
             st_t = np.squeeze(effect * positive_reciprocal(sd))
         return TContrastResults(effect=st_effect, t=st_t, sd=st_sd,
-                                df_den=self.df_resid)
+                                df_den=self.df_residuals)
 
     def Fcontrast(self, matrix, dispersion=None, invcov=None):
         """ Compute an Fcontrast for a contrast matrix `matrix`.
@@ -262,7 +269,7 @@ def Fcontrast(self, matrix, dispersion=None, invcov=None):
         return FContrastResults(
             effect=ctheta, covariance=self.vcov(
                 matrix=matrix, dispersion=dispersion[np.newaxis]),
-            F=F, df_den=self.df_resid, df_num=invcov.shape[0])
+            F=F, df_den=self.df_residuals, df_num=invcov.shape[0])
 
     def conf_int(self, alpha=.05, cols=None, dispersion=None):
         ''' The confidence interval of the specified theta estimates.
@@ -306,18 +313,18 @@ def conf_int(self, alpha=.05, cols=None, dispersion=None):
 
         '''
         if cols is None:
-            lower = self.theta - inv_t_cdf(1 - alpha / 2, self.df_resid) *\
+            lower = self.theta - inv_t_cdf(1 - alpha / 2, self.df_residuals) * \
                     np.sqrt(np.diag(self.vcov(dispersion=dispersion)))
-            upper = self.theta + inv_t_cdf(1 - alpha / 2, self.df_resid) *\
+            upper = self.theta + inv_t_cdf(1 - alpha / 2, self.df_residuals) * \
                     np.sqrt(np.diag(self.vcov(dispersion=dispersion)))
         else:
             lower, upper = [], []
             for i in cols:
                 lower.append(
-                    self.theta[i] - inv_t_cdf(1 - alpha / 2, self.df_resid) *
+                    self.theta[i] - inv_t_cdf(1 - alpha / 2, self.df_residuals) *
                     np.sqrt(self.vcov(column=i, dispersion=dispersion)))
                 upper.append(
-                    self.theta[i] + inv_t_cdf(1 - alpha / 2, self.df_resid) *
+                    self.theta[i] + inv_t_cdf(1 - alpha / 2, self.df_residuals) *
                     np.sqrt(self.vcov(column=i, dispersion=dispersion)))
         return np.asarray(list(zip(lower, upper)))
 
diff --git a/nistats/regression.py b/nistats/regression.py
index bea55744..691577fe 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -60,7 +60,7 @@ class OLSModel(object):
     normalized_cov_beta : ndarray
         ``np.dot(calc_beta, calc_beta.T)``
 
-    df_resid : scalar
+    df_residuals : scalar
         Degrees of freedom of the residuals.  Number of observations less the
         rank of the design.
 
@@ -92,7 +92,13 @@ def initialize(self, design):
 
         eps = np.abs(self.design).sum() * np.finfo(np.float).eps
         self.df_model = matrix_rank(self.design, eps)
-        self.df_resid = self.df_total - self.df_model
+        self.df_residuals = self.df_total - self.df_model
+
+    @setattr_on_read
+    def df_resid(self):
+        warnings.warn("The attribute 'df_resid' from OLSModel"
+                      "has been deprecated. Please use 'df_residuals'.")
+        return self.df_residuals
 
     def logL(self, beta, Y, nuisance=None):
         r''' Returns the value of the loglikelihood function at beta.
@@ -350,7 +356,7 @@ def r_square(self):
     @setattr_on_read
     def MSE(self):
         """ Mean square (error) """
-        return self.SSE / self.df_resid
+        return self.SSE / self.df_residuals
 
 
 class SimpleRegressionResults(LikelihoodModelResults):
@@ -373,7 +379,7 @@ def __init__(self, results):
         self.df_total = results.Y.shape[0]
         self.df_model = results.model.df_model
         # put this as a parameter of LikelihoodModel
-        self.df_resid = self.df_total - self.df_model
+        self.df_residuals = self.df_total - self.df_model
 
     def logL(self, Y):
         """
@@ -395,6 +401,12 @@ def residuals(self, Y):
         """
         return Y - self.predicted
 
+    @setattr_on_read
+    def df_resid(self):
+        warnings.warn("The attribute 'df_resid' from OLSModel"
+                      "has been deprecated. Please use 'df_residuals'.")
+        return self.df_residuals
+
     def norm_resid(self, Y):
         warnings.warn("'SimpleRegressionResults.norm_resid' method has been deprecated "
                       "and will be removed. "
diff --git a/nistats/tests/test_regression.py b/nistats/tests/test_regression.py
index 436d6c0d..6a9fd3b7 100644
--- a/nistats/tests/test_regression.py
+++ b/nistats/tests/test_regression.py
@@ -21,7 +21,7 @@
 def test_OLS():
     model = OLSModel(design=X)
     results = model.fit(Y)
-    assert results.df_resid == 30
+    assert results.df_residuals == 30
     assert results.residuals.shape[0] == 40
     assert results.predicted.shape[0] == 40
     with pytest.warns(FutureWarning):
@@ -31,7 +31,7 @@ def test_OLS():
 def test_AR():
     model = ARModel(design=X, rho=0.4)
     results = model.fit(Y)
-    assert results.df_resid == 30
+    assert results.df_residuals == 30
     assert results.residuals.shape[0] == 40
     assert results.predicted.shape[0] == 40
     with pytest.warns(FutureWarning):
@@ -69,7 +69,7 @@ def test_OLS_degenerate():
     Xd[:, 0] = Xd[:, 1] + Xd[:, 2]
     model = OLSModel(design=Xd)
     results = model.fit(Y)
-    assert results.df_resid == 31
+    assert results.df_residuals == 31
 
 
 def test_AR_degenerate():
@@ -77,4 +77,4 @@ def test_AR_degenerate():
     Xd[:, 0] = Xd[:, 1] + Xd[:, 2]
     model = ARModel(design=Xd, rho=0.9)
     results = model.fit(Y)
-    assert results.df_resid == 31
+    assert results.df_residuals == 31

From 73a8bb2320bdd56f08bb6a1939c1af08571c6fed Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Wed, 15 Jan 2020 18:32:53 +0100
Subject: [PATCH 07/10] Reanmed *_resid to *_residuals and .resid to .residuals

---
 nistats/first_level_model.py            |  4 ++--
 nistats/regression.py                   | 22 ++++++++++++++++------
 nistats/tests/test_first_level_model.py |  6 +++---
 3 files changed, 21 insertions(+), 11 deletions(-)

diff --git a/nistats/first_level_model.py b/nistats/first_level_model.py
index ef4e770c..a75bce83 100644
--- a/nistats/first_level_model.py
+++ b/nistats/first_level_model.py
@@ -133,8 +133,8 @@ def run_glm(Y, X, noise_model='ar1', bins=100, n_jobs=1, verbose=0):
 
     if noise_model == 'ar1':
         # compute and discretize the AR1 coefs
-        ar1 = ((ols_result.resid[1:] * ols_result.resid[:-1]).sum(axis=0) /
-               (ols_result.resid ** 2).sum(axis=0))
+        ar1 = ((ols_result.residuals[1:] * ols_result.residuals[:-1]).sum(axis=0) /
+               (ols_result.residuals ** 2).sum(axis=0))
         del ols_result
         ar1 = (ar1 * bins).astype(np.int) * 1. / bins
         # Fit the AR model acccording to current AR(1) estimates
diff --git a/nistats/regression.py b/nistats/regression.py
index 691577fe..98936bae 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -265,6 +265,7 @@ def whiten(self, X):
             _X[(i + 1):] = _X[(i + 1):] - self.rho[i] * X[0: - (i + 1)]
         return _X
 
+from nistats._utils.helpers import replace_parameters
 
 class RegressionResults(LikelihoodModelResults):
     """
@@ -272,8 +273,8 @@ class RegressionResults(LikelihoodModelResults):
 
     It handles the output of contrasts, estimates of covariance, etc.
     """
-
-    def __init__(self, theta, Y, model, wY, wresid, cov=None, dispersion=1.,
+    @replace_parameters({'wresid': 'wresdiuals'}, lib_name='Nistats')
+    def __init__(self, theta, Y, model, wY, wresiduals, cov=None, dispersion=1.,
                  nuisance=None):
         """See LikelihoodModelResults constructor.
 
@@ -283,9 +284,18 @@ def __init__(self, theta, Y, model, wY, wresid, cov=None, dispersion=1.,
         LikelihoodModelResults.__init__(self, theta, Y, model, cov,
                                         dispersion, nuisance)
         self.wY = wY
-        self.wresid = wresid
+        self.wresiduals = wresiduals
         self.wdesign = model.wdesign
 
+    @setattr_on_read
+    def wresid(self):
+        warnings.warn("'RegressionResults.wresid' method has been deprecated "
+                      "and will be removed. "
+                      "Please use 'RegressionResults.wresiduals'.",
+                      FutureWarning,
+                      )
+        return self.wresiduals
+
     @setattr_on_read
     def resid(self):
         warnings.warn("'RegressionResults.resid' method has been deprecated "
@@ -329,7 +339,7 @@ def normalized_residuals(self):
         See: Montgomery and Peck 3.2.1 p. 68
              Davidson and MacKinnon 15.2 p 662
         """
-        return self.resid * positive_reciprocal(np.sqrt(self.dispersion))
+        return self.residuals * positive_reciprocal(np.sqrt(self.dispersion))
 
     @setattr_on_read
     def predicted(self):
@@ -344,7 +354,7 @@ def predicted(self):
     def SSE(self):
         """Error sum of squares. If not from an OLS model this is "pseudo"-SSE.
         """
-        return (self.wresid ** 2).sum(0)
+        return (self.wresiduals ** 2).sum(0)
 
     @setattr_on_read
     def r_square(self):
@@ -432,7 +442,7 @@ def normalized_residuals(self, Y):
         See: Montgomery and Peck 3.2.1 p. 68
              Davidson and MacKinnon 15.2 p 662
         """
-        return self.resid(Y) * positive_reciprocal(np.sqrt(self.dispersion))
+        return self.residuals(Y) * positive_reciprocal(np.sqrt(self.dispersion))
 
     def predicted(self):
         """ Return linear predictor values from a design matrix.
diff --git a/nistats/tests/test_first_level_model.py b/nistats/tests/test_first_level_model.py
index 09165151..2b5c7262 100644
--- a/nistats/tests/test_first_level_model.py
+++ b/nistats/tests/test_first_level_model.py
@@ -606,9 +606,9 @@ def test_first_level_model_residuals():
                             noise_model='ols')
     model.fit(fmri_data, design_matrices=design_matrices)
 
-    resid = model.residuals[0]
-    mean_resids = model.masker_.transform(resid).mean(0)
-    assert_array_almost_equal(mean_resids, 0)
+    residuals = model.residuals[0]
+    mean_residuals = model.masker_.transform(residuals).mean(0)
+    assert_array_almost_equal(mean_residuals, 0)
 
 
 def test_first_level_model_predictions_r_square():

From cfcebed64aea332463d9ce09ade9c765dbc3d9a2 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Tue, 21 Jan 2020 17:02:05 +0100
Subject: [PATCH 08/10] Added tests for renamed attributes and associated
 warnings

 - Reduced verbosity in warning message.
 - Renamed wresiduals to whitened_residuals.
---
 nistats/model.py                 |  5 +++--
 nistats/regression.py            | 36 ++++++++++++++++----------------
 nistats/tests/test_regression.py | 23 ++++++++++++++++----
 3 files changed, 40 insertions(+), 24 deletions(-)

diff --git a/nistats/model.py b/nistats/model.py
index e164dfa8..098d9aa5 100644
--- a/nistats/model.py
+++ b/nistats/model.py
@@ -77,8 +77,9 @@ def __init__(self, theta, Y, model, cov=None, dispersion=1., nuisance=None,
 
     @setattr_on_read
     def df_resid(self):
-        warnings.warn("The attribute 'df_resid' from LikelihoodModelResults"
-                      "has been deprecated. Please use 'df_residuals'.")
+        warnings.warn("'df_resid' from LikelihoodModelResults "
+                      "has been deprecated. Please use 'df_residuals'.",
+                      FutureWarning)
         return self.df_residuals
 
     @setattr_on_read
diff --git a/nistats/regression.py b/nistats/regression.py
index 98936bae..95f2b8e4 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -27,6 +27,7 @@
 import scipy.linalg as spl
 
 from .model import LikelihoodModelResults
+from nistats._utils.helpers import replace_parameters
 from .utils import positive_reciprocal
 
 
@@ -265,7 +266,6 @@ def whiten(self, X):
             _X[(i + 1):] = _X[(i + 1):] - self.rho[i] * X[0: - (i + 1)]
         return _X
 
-from nistats._utils.helpers import replace_parameters
 
 class RegressionResults(LikelihoodModelResults):
     """
@@ -273,8 +273,8 @@ class RegressionResults(LikelihoodModelResults):
 
     It handles the output of contrasts, estimates of covariance, etc.
     """
-    @replace_parameters({'wresid': 'wresdiuals'}, lib_name='Nistats')
-    def __init__(self, theta, Y, model, wY, wresiduals, cov=None, dispersion=1.,
+    @replace_parameters({'wresid': 'whitened_residuals'}, lib_name='Nistats')
+    def __init__(self, theta, Y, model, wY, whitened_residuals, cov=None, dispersion=1.,
                  nuisance=None):
         """See LikelihoodModelResults constructor.
 
@@ -284,23 +284,23 @@ def __init__(self, theta, Y, model, wY, wresiduals, cov=None, dispersion=1.,
         LikelihoodModelResults.__init__(self, theta, Y, model, cov,
                                         dispersion, nuisance)
         self.wY = wY
-        self.wresiduals = wresiduals
+        self.whitened_residuals = whitened_residuals
         self.wdesign = model.wdesign
 
     @setattr_on_read
     def wresid(self):
-        warnings.warn("'RegressionResults.wresid' method has been deprecated "
-                      "and will be removed. "
-                      "Please use 'RegressionResults.wresiduals'.",
+        warnings.warn("'wresid' from RegressionResults "
+                      "has been deprecated and will be removed. "
+                      "Please use 'whitened_residuals' instead.",
                       FutureWarning,
                       )
-        return self.wresiduals
+        return self.whitened_residuals
 
     @setattr_on_read
     def resid(self):
-        warnings.warn("'RegressionResults.resid' method has been deprecated "
-                      "and will be removed. "
-                      "Please use 'RegressionResults.residuals'.",
+        warnings.warn("'resid' from RegressionResults "
+                      "has been deprecated and will be removed. "
+                      "Please use 'residuals' instead.",
                       FutureWarning,
                       )
         return self.residuals
@@ -314,9 +314,9 @@ def residuals(self):
 
     @setattr_on_read
     def norm_resid(self):
-        warnings.warn("'RegressionResults.norm_resid' method has been deprecated "
-                      "and will be removed. "
-                      "Please use 'RegressionResults.normalized_residuals'.",
+        warnings.warn("'norm_resid' from RegressionResults "
+                      "has been deprecated and will be removed. "
+                      "Please use 'normalized_residuals' instead.",
                       FutureWarning,
                       )
         return self.normalized_residuals
@@ -354,7 +354,7 @@ def predicted(self):
     def SSE(self):
         """Error sum of squares. If not from an OLS model this is "pseudo"-SSE.
         """
-        return (self.wresiduals ** 2).sum(0)
+        return (self.whitened_residuals ** 2).sum(0)
 
     @setattr_on_read
     def r_square(self):
@@ -398,9 +398,9 @@ def logL(self, Y):
         raise ValueError('can not use this method for simple results')
 
     def resid(self, Y):
-        warnings.warn("'SimpleRegressionResults.resid()' method has been deprecated "
-                      "and will be removed. "
-                      "Please use 'SimpleRegressionResults.residuals()'.",
+        warnings.warn("'resid()' from SimpleRegressionResults"
+                      " has been deprecated and will be removed. "
+                      "Please use 'residuals()'.",
                       FutureWarning,
                       )
         return self.residuals(Y)
diff --git a/nistats/tests/test_regression.py b/nistats/tests/test_regression.py
index 6a9fd3b7..8a03bb78 100644
--- a/nistats/tests/test_regression.py
+++ b/nistats/tests/test_regression.py
@@ -24,8 +24,6 @@ def test_OLS():
     assert results.df_residuals == 30
     assert results.residuals.shape[0] == 40
     assert results.predicted.shape[0] == 40
-    with pytest.warns(FutureWarning):
-        assert results.resid.shape[0] == 40
 
 
 def test_AR():
@@ -34,8 +32,6 @@ def test_AR():
     assert results.df_residuals == 30
     assert results.residuals.shape[0] == 40
     assert results.predicted.shape[0] == 40
-    with pytest.warns(FutureWarning):
-        assert results.resid.shape[0] == 40
 
 
 def test_residuals():
@@ -48,6 +44,7 @@ def test_residuals():
     model = OLSModel(design=Xintercept)
     results = model.fit(Y)
     assert_almost_equal(results.residuals.mean(), 0)
+    assert len(results.whitened_residuals) == 40
 
 
 def test_predicted_r_square():
@@ -78,3 +75,21 @@ def test_AR_degenerate():
     model = ARModel(design=Xd, rho=0.9)
     results = model.fit(Y)
     assert results.df_residuals == 31
+
+
+def test_resid_rename_warnings_ols():
+    model = OLSModel(design=X)
+    results_ols = model.fit(Y)
+    with pytest.warns(FutureWarning, match="'df_resid'"):
+        assert results_ols.df_resid == 30
+    with pytest.warns(FutureWarning, match="'resid'"):
+        assert results_ols.resid.shape[0] == 40
+
+
+def test_resid_rename_warnings_ar():
+    model = ARModel(design=X, rho=0.4)
+    results_ar = model.fit(Y)
+    with pytest.warns(FutureWarning, match="'resid'"):
+        assert results_ar.resid.shape[0] == 40
+    with pytest.warns(FutureWarning, match="'wresid"):
+        assert len(results_ar.wresid) == 40

From 53514d6db3d3758f62e7711db3618d96b8d7d8a2 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Wed, 22 Jan 2020 14:34:27 +0100
Subject: [PATCH 09/10] Renamed wX and wY to whitened_X, whitened_Y

---
 nistats/regression.py | 27 ++++++++++++++++++---------
 1 file changed, 18 insertions(+), 9 deletions(-)

diff --git a/nistats/regression.py b/nistats/regression.py
index 95f2b8e4..dc74ef6f 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -176,7 +176,7 @@ def whiten(self, X):
 
         Returns
         -------
-        wX : array
+        whitened_X : array
             This matrix is the matrix whose pseudoinverse is ultimately
             used in estimating the coefficients. For OLSModel, it is
             does nothing. For WLSmodel, ARmodel, it pre-applies
@@ -257,14 +257,14 @@ def whiten(self, X):
 
         Returns
         -------
-        wX : ndarray
+        whitened_X : ndarray
             X whitened with order self.order AR
         """
         X = np.asarray(X, np.float64)
-        _X = X.copy()
+        whitened_X = X.copy()
         for i in range(self.order):
-            _X[(i + 1):] = _X[(i + 1):] - self.rho[i] * X[0: - (i + 1)]
-        return _X
+            whitened_X[(i + 1):] = whitened_X[(i + 1):] - self.rho[i] * X[0: - (i + 1)]
+        return whitened_X
 
 
 class RegressionResults(LikelihoodModelResults):
@@ -273,8 +273,8 @@ class RegressionResults(LikelihoodModelResults):
 
     It handles the output of contrasts, estimates of covariance, etc.
     """
-    @replace_parameters({'wresid': 'whitened_residuals'}, lib_name='Nistats')
-    def __init__(self, theta, Y, model, wY, whitened_residuals, cov=None, dispersion=1.,
+    @replace_parameters({'wresid': 'whitened_residuals', 'wY': 'whitened_Y'}, lib_name='Nistats')
+    def __init__(self, theta, Y, model, whitened_Y, whitened_residuals, cov=None, dispersion=1.,
                  nuisance=None):
         """See LikelihoodModelResults constructor.
 
@@ -283,10 +283,19 @@ def __init__(self, theta, Y, model, wY, whitened_residuals, cov=None, dispersion
         """
         LikelihoodModelResults.__init__(self, theta, Y, model, cov,
                                         dispersion, nuisance)
-        self.wY = wY
+        self.whitened_Y = whitened_Y
         self.whitened_residuals = whitened_residuals
         self.wdesign = model.wdesign
 
+    @setattr_on_read
+    def wY(self):
+        warnings.warn("'wY' from RegressionResults "
+                      "has been deprecated and will be removed. "
+                      "Please use 'whitened_Y' instead.",
+                      FutureWarning,
+                      )
+        return self.whitened_Y
+
     @setattr_on_read
     def wresid(self):
         warnings.warn("'wresid' from RegressionResults "
@@ -361,7 +370,7 @@ def r_square(self):
         """Proportion of explained variance.
         If not from an OLS model this is "pseudo"-R2.
         """
-        return np.var(self.predicted, 0) / np.var(self.wY, 0)
+        return np.var(self.predicted, 0) / np.var(self.whitened_Y, 0)
 
     @setattr_on_read
     def MSE(self):

From 59a9730be9763628e6950f12af8d502de66d6561 Mon Sep 17 00:00:00 2001
From: "Kshitij Chawla (kchawla-pi)" <kc.insight.pi@gmail.com>
Date: Wed, 22 Jan 2020 20:08:04 +0100
Subject: [PATCH 10/10] Replaced wdesign with whitened_design, improved tests

---
 nistats/model.py                 |  3 +-
 nistats/regression.py            | 55 ++++++++++++++++++++++----------
 nistats/tests/test_regression.py | 15 ++++++---
 3 files changed, 51 insertions(+), 22 deletions(-)

diff --git a/nistats/model.py b/nistats/model.py
index 098d9aa5..63b14a84 100644
--- a/nistats/model.py
+++ b/nistats/model.py
@@ -78,7 +78,8 @@ def __init__(self, theta, Y, model, cov=None, dispersion=1., nuisance=None,
     @setattr_on_read
     def df_resid(self):
         warnings.warn("'df_resid' from LikelihoodModelResults "
-                      "has been deprecated. Please use 'df_residuals'.",
+                      "has been deprecated and will be removed. "
+                      "Please use 'df_residuals'.",
                       FutureWarning)
         return self.df_residuals
 
diff --git a/nistats/regression.py b/nistats/regression.py
index dc74ef6f..8f772691 100644
--- a/nistats/regression.py
+++ b/nistats/regression.py
@@ -50,8 +50,8 @@ class OLSModel(object):
     design : ndarray
         This is the design, or X, matrix.
 
-    wdesign : ndarray
-        This is the whitened design matrix.  `design` == `wdesign` by default
+    whitened_design : ndarray
+        This is the whitened design matrix.  `design` == `whitened_design` by default
         for the OLSModel, though models that inherit from the OLSModel will
         whiten the design.
 
@@ -85,11 +85,11 @@ def initialize(self, design):
         # PLEASE don't assume we have a constant...
         # TODO: handle case for noconstant regression
         self.design = design
-        self.wdesign = self.whiten(self.design)
-        self.calc_beta = spl.pinv(self.wdesign)
+        self.whitened_design = self.whiten(self.design)
+        self.calc_beta = spl.pinv(self.whitened_design)
         self.normalized_cov_beta = np.dot(self.calc_beta,
                                           np.transpose(self.calc_beta))
-        self.df_total = self.wdesign.shape[0]
+        self.df_total = self.whitened_design.shape[0]
 
         eps = np.abs(self.design).sum() * np.finfo(np.float).eps
         self.df_model = matrix_rank(self.design, eps)
@@ -97,10 +97,20 @@ def initialize(self, design):
 
     @setattr_on_read
     def df_resid(self):
-        warnings.warn("The attribute 'df_resid' from OLSModel"
-                      "has been deprecated. Please use 'df_residuals'.")
+        warnings.warn("'df_resid' from OLSModel"
+                      "has been deprecated and will be removed. "
+                      "Please use 'df_residuals'.",
+                      FutureWarning)
         return self.df_residuals
 
+    @setattr_on_read
+    def wdesign(self):
+        warnings.warn("'wdesign' from OLSModel"
+                      "has been deprecated and will be removed. "
+                      "Please use 'whitened_design'.",
+                      FutureWarning)
+        return self.whitened_design
+
     def logL(self, beta, Y, nuisance=None):
         r''' Returns the value of the loglikelihood function at beta.
 
@@ -154,7 +164,7 @@ def logL(self, beta, Y, nuisance=None):
         .. [1] W. Green.  "Econometric Analysis," 5th ed., Pearson, 2003.
         '''
         # This is overwriting an abstract method of LikelihoodModel
-        X = self.wdesign
+        X = self.whitened_design
         wY = self.whiten(Y)
         r = wY - np.dot(X, beta)
         n = self.df_total
@@ -204,9 +214,9 @@ def fit(self, Y):
         # squares models assume covariance is diagonal, i.e. heteroscedastic).
         wY = self.whiten(Y)
         beta = np.dot(self.calc_beta, wY)
-        wresid = wY - np.dot(self.wdesign, beta)
-        dispersion = np.sum(wresid ** 2, 0) / (self.wdesign.shape[0] -
-                                               self.wdesign.shape[1])
+        wresid = wY - np.dot(self.whitened_design, beta)
+        dispersion = np.sum(wresid ** 2, 0) / (self.whitened_design.shape[0] -
+                                               self.whitened_design.shape[1])
         lfit = RegressionResults(beta, Y, self,
                                  wY, wresid, dispersion=dispersion,
                                  cov=self.normalized_cov_beta)
@@ -285,7 +295,16 @@ def __init__(self, theta, Y, model, whitened_Y, whitened_residuals, cov=None, di
                                         dispersion, nuisance)
         self.whitened_Y = whitened_Y
         self.whitened_residuals = whitened_residuals
-        self.wdesign = model.wdesign
+        self.whitened_design = model.whitened_design
+
+    @setattr_on_read
+    def wdesign(self):
+        warnings.warn("'wdesign' from RegressionResults"
+                      "has been deprecated and will be removed. "
+                      "Please use 'whitened_design'.",
+                      FutureWarning)
+        return self.whitened_design
+
 
     @setattr_on_read
     def wY(self):
@@ -356,7 +375,7 @@ def predicted(self):
         """
         beta = self.theta
         # the LikelihoodModelResults has parameters named 'theta'
-        X = self.wdesign
+        X = self.whitened_design
         return np.dot(X, beta)
 
     @setattr_on_read
@@ -423,13 +442,15 @@ def residuals(self, Y):
     @setattr_on_read
     def df_resid(self):
         warnings.warn("The attribute 'df_resid' from OLSModel"
-                      "has been deprecated. Please use 'df_residuals'.")
+                      "has been deprecated and will be removed. "
+                      "Please use 'df_residuals'.",
+                      FutureWarning)
         return self.df_residuals
 
     def norm_resid(self, Y):
-        warnings.warn("'SimpleRegressionResults.norm_resid' method has been deprecated "
-                      "and will be removed. "
-                      "Please use 'SimpleRegressionResults.normalized_residuals'.",
+        warnings.warn("'SimpleRegressionResults.norm_resid' method "
+                      "has been deprecated and will be removed. "
+                      "Please use 'normalized_residuals'.",
                       FutureWarning,
                       )
         return self.normalized_residuals(Y)
diff --git a/nistats/tests/test_regression.py b/nistats/tests/test_regression.py
index 8a03bb78..f1d27f48 100644
--- a/nistats/tests/test_regression.py
+++ b/nistats/tests/test_regression.py
@@ -81,15 +81,22 @@ def test_resid_rename_warnings_ols():
     model = OLSModel(design=X)
     results_ols = model.fit(Y)
     with pytest.warns(FutureWarning, match="'df_resid'"):
-        assert results_ols.df_resid == 30
+        assert_array_equal(results_ols.df_resid, results_ols.df_residuals)
     with pytest.warns(FutureWarning, match="'resid'"):
-        assert results_ols.resid.shape[0] == 40
+        assert_array_equal(results_ols.resid, results_ols.residuals)
+    with pytest.warns(FutureWarning, match="'wY'"):
+        assert_array_equal(results_ols.wY, results_ols.whitened_Y)
+    with pytest.warns(FutureWarning, match="'wdesign'"):
+        assert_array_equal(results_ols.wdesign, results_ols.whitened_design)
+    with pytest.warns(FutureWarning, match="'wdesign'"):
+        assert_array_equal(model.wdesign, model.whitened_design)
+
 
 
 def test_resid_rename_warnings_ar():
     model = ARModel(design=X, rho=0.4)
     results_ar = model.fit(Y)
     with pytest.warns(FutureWarning, match="'resid'"):
-        assert results_ar.resid.shape[0] == 40
+        assert_array_equal(results_ar.resid, results_ar.residuals)
     with pytest.warns(FutureWarning, match="'wresid"):
-        assert len(results_ar.wresid) == 40
+        assert_array_equal(results_ar.wresid, results_ar.whitened_residuals)