From fdf378f5c8116c9a7ff7b03c7c32b7e1e0231ca8 Mon Sep 17 00:00:00 2001
From: Marc-Antoine Schmidt <marc-antoine.schmidt@quantco.com>
Date: Tue, 15 Jun 2021 17:31:01 -0400
Subject: [PATCH] fix issue #381 (#382)

* fixed method and added test

* added changelog entry

* Prepared changelog for release
---
 CHANGELOG.rst                 | 14 +++++++++++++-
 src/quantcore/glm/_solvers.py |  2 +-
 tests/glm/test_glm.py         |  8 ++++++++
 3 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 9adbe964..c32ea3a6 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -8,13 +8,25 @@ Changelog
 =========
 
 Unreleased
+----------
+
+
+1.4.2 - 2021-06-15
 ------------------
-**Tutorials and documenation improvements**:
+
+**Tutorials and documenation improvements:**
+
 - Adding tutorials to the documentation
 - Additional documentation improvements
 
+**Bug fix:**
+
+- Verbose progress bar now working again.
+
 **Other:**
+
 - Small improvement in documentation for the ``alpha_index`` argument to :func:`quantcore.glm.GeneralizedLinearRegressor.predict`.
+- Pinned pre-commit hooks versions.
 
 1.4.1 - 2021-05-01
 ------------------
diff --git a/src/quantcore/glm/_solvers.py b/src/quantcore/glm/_solvers.py
index fc59dd42..49edf54c 100644
--- a/src/quantcore/glm/_solvers.py
+++ b/src/quantcore/glm/_solvers.py
@@ -407,7 +407,7 @@ def _update(self, n_iter, iteration_runtime, cur_grad_norm):
         step = max(self.n_bar_steps - (np.log10(cur_grad_norm) - np.log10(self.tol)), 0)
         # round to two digits for beauty
         self.t.n = np.round(step, 2)
-        self.t._update(0)
+        self.t.update(0)
 
 
 class IRLSData:
diff --git a/tests/glm/test_glm.py b/tests/glm/test_glm.py
index 82118b50..cf237007 100644
--- a/tests/glm/test_glm.py
+++ b/tests/glm/test_glm.py
@@ -1810,3 +1810,11 @@ def test_alpha_parametrization_fail(kwargs, regression_data):
     with pytest.raises((ValueError, TypeError)):
         model = GeneralizedLinearRegressor(**kwargs)
         model.fit(X=X, y=y)
+
+
+def test_verbose(regression_data, capsys):
+    X, y = regression_data
+    mdl = GeneralizedLinearRegressor(verbose=1)
+    mdl.fit(X=X, y=y)
+    captured = capsys.readouterr()
+    assert "Iteration" in captured.err