Tiago de Freitas Pereira
--- a/bob/learn/linear/whitening.py 0 → 100644
+++ b/bob/learn/linear/whitening.py 0 → 100644
+    .. math::
+        W = cholesky([Cov(X)]^{-1})
+
+
+    References:
+        - 1. https://rtmath.net/help/html/e9c12dc0-e813-4ca9-aaa3-82340f1c5d24.htm
+        - 2. http://en.wikipedia.org/wiki/Cholesky_decomposition
+
+    """
+
+    def __init__(self, pinv: bool = False):
+        self.pinv = pinv
+
+    def fit(self, X: da.Array, y=None):
+        # 1. Computes the mean vector and the covariance matrix of the training set
+        mu = da.mean(X, axis=0)
--- a/conda/meta.yaml
+++ b/conda/meta.yaml
    - {{ compiler('c') }}
    - {{ compiler('cxx') }}
    - pkg-config {{ pkg_config }}
--- a/conda/meta.yaml
+++ b/conda/meta.yaml
    - {{ pin_compatible('scipy') }}
+    - {{ pin_compatible('dask') }}
+    - {{ pin_compatible('scikit-learn') }}

 test:
  imports:
    - {{ name }}
  commands:
-    - nosetests --with-coverage --cover-package={{ name }} -sv {{ name }}
+    - pytest --capture=no --verbose --cov {{ name }} --cov-config {{ project_dir }}/pyproject.toml --cov-report term-missing --cov-report html:{{ project_dir }}/sphinx/coverage --cov-report xml:{{ project_dir }}/coverage.xml --pyargs {{ name }}
    - sphinx-build -aEW {{ project_dir }}/doc {{ project_dir }}/sphinx
    - sphinx-build -aEb doctest {{ project_dir }}/doc sphinx
    - conda inspect linkages -p $PREFIX {{ name }}  # [not win]
    - conda inspect objects -p $PREFIX {{ name }}  # [osx]
  requires:
    - nose {{ nose }}
--- a/doc/index.rst
+++ b/doc/index.rst

 .. todolist::

-This package includes the definition of a linear machine, which is capable of
-either projecting the input data into maximally spread representations,
-linearly, or providing linear separation planes for multi-class data samples.
 The package includes the machine definition *per se* and a selection of
 different trainers for specialized purposes: