port_trainset

Author: agrimagsrl

MANIFEST

@@ -8,6 +8,7 @@ micromlgen/platforms.py
 micromlgen/utils.py
 micromlgen/templates/classmap.jinja
 micromlgen/templates/testset.jinja
+micromlgen/templates/trainset.jinja
 micromlgen/templates/pca/pca.jinja
 micromlgen/templates/rvm/rvm.jinja
 micromlgen/templates/svm/svm.jinja

micromlgen/__init__.py

@@ -1,3 +1,3 @@
 import micromlgen.platforms as platforms
 from micromlgen.micromlgen import port
-from micromlgen.utils import port_testset
+from micromlgen.utils import port_testset, port_trainset

micromlgen/templates/trainset.jinja

@@ -0,0 +1,31 @@
+#pragma once
+
+namespace Eloquent {
+    namespace ML {
+        namespace Train {
+
+            /**
+             * A tailor made training set
+             */
+            class {{ classname }} {
+                public:
+                    {{ classname }}() :
+                        _x{  {% for x in X %}
+                                { {% for xi in x %} {% if loop.index > 1 %}, {% endif %} {{ f.round(xi) }} {% endfor %} },
+                            {% endfor %}
+                        },
+                        _y{  {% for yi in y %} {% if loop.index > 1 %}, {% endif %} {{ f.round(yi) }} {% endfor %}  }
+                    {}
+
+                    template<class Classifier>
+                    void fit(Classifier clf) {
+                        clf.fit(_x, _y, {{ X|length }});
+                    }
+
+                protected:
+                    float _x[{{ X|length }}][{{ X[0]|length }}];
+                    int _y[{{ X|length }}];
+            };
+        }
+    }
+}

micromlgen/utils.py

@@ -46,5 +46,9 @@ def jinja(template_file, data):
     return prettify(code)
 
 
+def port_trainset(X, y, classname='TrainSet'):
+    return jinja('trainset.jinja', locals())
+
+
 def port_testset(X, y, classname='TestSet'):
-    return jinja('testset.jinja', locals())
+    return jinja('testset.jinja', locals())

setup.py

@@ -7,13 +7,13 @@
 setup(
   name = 'micromlgen',
   packages = ['micromlgen'],
-  version = '1.1.1',
+  version = '1.1.3',
   license='MIT',
   description = 'Generate C code for microcontrollers from Python\'s sklearn classifiers',
   author = 'Simone Salerno',
   author_email = 'eloquentarduino@gmail.com',
   url = 'https://github.com/eloquentarduino/micromlgen',
-  download_url = 'https://github.com/eloquentarduino/micromlgen/archive/v_111.tar.gz',
+  download_url = 'https://github.com/eloquentarduino/micromlgen/archive/v_113.tar.gz',
   keywords = [
     'ML',
     'microcontrollers',