remove skbayes.RVC dependency

MANIFEST

@@ -3,10 +3,12 @@ setup.cfg
 setup.py
 micromlgen/__init__.py
 micromlgen/micromlgen.py
+micromlgen/patches.py
 micromlgen/platforms.py
 micromlgen/utils.py
 micromlgen/templates/classmap.jinja
 micromlgen/templates/testset.jinja
+micromlgen/templates/pca/pca.jinja
 micromlgen/templates/rvm/rvm.jinja
 micromlgen/templates/svm/svm.jinja
 micromlgen/templates/svm/computations/class.jinja

micromlgen/micromlgen.py

@@ -1,6 +1,9 @@
-from skbayes.rvm_ard_models import RVC
 from sklearn.svm import SVC, LinearSVC, OneClassSVM
 from sklearn.decomposition import PCA
+try:
+    from skbayes.rvm_ard_models import RVC
+except ImportError:
+    from micromlgen.patches import RVC
 
 from micromlgen import platforms
 from micromlgen.utils import jinja

micromlgen/patches.py

@@ -0,0 +1,3 @@
+class RVC:
+    """Patch un-installed skbayes RVC classifier"""
+    pass

micromlgen/templates/classmap.jinja

@@ -3,8 +3,8 @@
 /**
  * Convert class idx to readable name
  */
-const char* classIdxToName(uint8_t classIdx) {
-    switch (classIdx) {
+const char* predictLabel(float *x) {
+    switch (predict(x)) {
         {% for idx, name in classmap.items() %}
             case {{ idx }}:
                 return "{{ name }}";

micromlgen/templates/svm/kernel/arduino.jinja

@@ -2,7 +2,7 @@
  * Compute kernel between feature vector and support vector.
  * Kernel type: {{ kernel['type'] }}
  */
-float compute_kernel(float x[{{ sizes.features }}], ...) {
+float compute_kernel(float *x, ...) {
     va_list w;
     va_start(w, {{ sizes.features }});
 

micromlgen/templates/svm/kernel/attiny.jinja

@@ -2,7 +2,7 @@
  * Compute kernel between feature vector and support vector.
  * Kernel type: {{ kernel['type'] }}
  */
-float compute_kernel(float x[{{ sizes.features }}], float w[{{ sizes.features }}]) {
+float compute_kernel(float *x, float w[{{ sizes.features }}]) {
     va_list w;
     va_start(w, {{ sizes.features }});
 

setup.py

@@ -7,13 +7,13 @@
 setup(
   name = 'micromlgen',
   packages = ['micromlgen'],
-  version = '1.1.0',
+  version = '1.1.1',
   license='MIT',
   description = 'Generate C code for microcontrollers from Python\'s sklearn classifiers',
   author = 'Simone Salerno',
   author_email = '[email protected]',
   url = 'https://github.com/eloquentarduino/micromlgen',
-  download_url = 'https://github.com/eloquentarduino/micromlgen/archive/v_11.tar.gz',
+  download_url = 'https://github.com/eloquentarduino/micromlgen/archive/v_111.tar.gz',
   keywords = [
     'ML',
     'microcontrollers',