Merge pull request #122 from sdpython/fin

Minor updates to the documentation

Author: sdpython

README.rst

@@ -4,20 +4,9 @@
 
 mlinsights: extensions to scikit-learn
 ======================================
-   qqa
-.. image:: https://travis-ci.com/sdpython/mlinsights.svg?branch=main
-    :target: https://app.travis-ci.com/github/sdpython/mlinsights/
-    :alt: Build status
 
-.. image:: https://ci.appveyor.com/api/projects/status/uj6tq445k3na7hs9?svg=true
-    :target: https://ci.appveyor.com/project/sdpython/mlinsights
-    :alt: Build Status Windows
-
-.. image:: https://circleci.com/gh/sdpython/mlinsights/tree/main.svg?style=svg
-    :target: https://circleci.com/gh/sdpython/mlinsights/tree/main
-
-.. image:: https://dev.azure.com/xavierdupre3/mlinsights/_apis/build/status/sdpython.mlinsights%20(2)
-    :target: https://dev.azure.com/xavierdupre3/mlinsights/
+.. image:: https://dev.azure.com/xavierdupre3/mlinsights/_apis/build/status%2Fsdpython.mlinsights%20(2)?branchName=main
+    :target: https://dev.azure.com/xavierdupre3/mlinsights/_build/latest?definitionId=16&branchName=main
 
 .. image:: https://badge.fury.io/py/mlinsights.svg
     :target: http://badge.fury.io/py/mlinsights
@@ -51,21 +40,16 @@ mlinsights: extensions to scikit-learn
 
 *mlinsights* extends *scikit-learn* with a couple of new models,
 transformers, metrics, plotting. It provides new trainers such as
-*QuantileLinearRegression* which trains a linear regression with *L1* norm
+**QuantileLinearRegression** which trains a linear regression with *L1* norm
 non-linear correlation based on decision trees, or
-*QuantileMLPRegressor* a modification of scikit-learn's MLPRegressor
+**QuantileMLPRegressor** a modification of scikit-learn's MLPRegressor
 which trains a multi-layer perceptron with *L1* norm.
-It also explores *PredictableTSNE* which trains a supervized
-model to replicate *t-SNE* results or a *PiecewiseRegression*
+It also explores **PredictableTSNE** which trains a supervized
+model to replicate *t-SNE* results or a **PiecewiseRegression**
 which partitions the data before fitting a model on each bucket.
+**PiecewiseTreeRegressor** trains a piecewise regressor using
+a linear regression on each piece. **IntervalRegressor** produces
+confidence interval by using bootstrapping. **ApproximateNMFPredictor**
+approximates a NMF to produce prediction without retraining.
 
 `documentation <https://sdpython.github.io/doc/dev/mlinsights/>`_
-
-Function ``pipeline2dot`` converts a pipeline into a graph:
-
-::
-
-    from mlinsights.plotting import pipeline2dot
-    dot = pipeline2dot(clf, df)
-
-.. image:: https://raw.githubusercontent.com/sdpython/mlinsights/main/_doc/sphinxdoc/source/pipeline.png

_doc/index.rst

@@ -2,15 +2,11 @@
 mlinsights: tricky scikit-learn
 ===============================
 
-.. image:: https://github.com/sdpython/mlinsights/blob/main/_doc/_static/project_ico.png?raw=true
+.. image:: https://raw.github.com/sdpython/mlinsights/blob/main/_doc/_static/project_ico.png
     :target: https://github.com/sdpython/mlinsights/
 
-.. image:: https://travis-ci.com/sdpython/mlinsights.svg?branch=main
-    :target: https://app.travis-ci.com/github/sdpython/mlinsights/
-    :alt: Build status
-
-.. image:: https://dev.azure.com/xavierdupre3/mlinsights/_apis/build/status/sdpython.mlinsights%20(2)
-    :target: https://dev.azure.com/xavierdupre3/mlinsights/
+.. image:: https://dev.azure.com/xavierdupre3/mlinsights/_apis/build/status%2Fsdpython.mlinsights%20(2)?branchName=main
+    :target: https://dev.azure.com/xavierdupre3/mlinsights/_build/latest?definitionId=16&branchName=main
 
 .. image:: https://badge.fury.io/py/mlinsights.svg
     :target: http://badge.fury.io/py/mlinsights

mlinsights/mlmodel/direct_blas_lapack.pyx

@@ -68,15 +68,15 @@ def dgelss(double[:, ::1] A, double [:, ::1] B, double prec=-1.):
     return res
 
 
-cdef void copy2array2(const double* pC, double[:, ::1] C) nogil:
+cdef void copy2array2(const double* pC, double[:, ::1] C) noexcept nogil:
     """
     Copies double from a buffer to an array.
     """
     cdef size_t size = C.shape[0] * C.shape[1]
     memcpy(&C[0, 0], pC, size * sizeof(double))
 
 
-cdef void copy2array1(const double* pC, double[::1] C) nogil:
+cdef void copy2array1(const double* pC, double[::1] C) noexcept nogil:
     """
     Copies double from a buffer to an array.
     """
@@ -110,7 +110,7 @@ cdef int _dgelss(double[:, ::1] A, double [:, ::1] B, int* rank,
 
 
 cdef void _dgelss_noalloc(double[:, ::1] A, double [:, ::1] B, int* rank, double* rcond,
-                          double* pS, double *pC, int* work, int* info) nogil:
+                          double* pS, double *pC, int* work, int* info) noexcept nogil:
     """
     Same function as :func:`dgels` but does no check.