add port_wifi_indoor_positioning

MANIFEST

@@ -6,14 +6,14 @@ micromlgen/decisiontree.py
 micromlgen/gaussiannb.py
 micromlgen/logisticregression.py
 micromlgen/micromlgen.py
-micromlgen/patches.py
 micromlgen/pca.py
 micromlgen/platforms.py
 micromlgen/randomforest.py
 micromlgen/rvm.py
 micromlgen/sefr.py
 micromlgen/svm.py
 micromlgen/utils.py
+micromlgen/templates/_skeleton.jinja
 micromlgen/templates/classmap.jinja
 micromlgen/templates/dot.jinja
 micromlgen/templates/testset.jinja

micromlgen/__init__.py

@@ -1,3 +1,4 @@
 import micromlgen.platforms as platforms
 from micromlgen.micromlgen import port
 from micromlgen.utils import port_testset, port_trainset
+from micromlgen.wifiindoorpositioning import port_wifi_indoor_positioning

micromlgen/micromlgen.py

@@ -33,4 +33,4 @@ def port(
         return port_gaussiannb(**locals())
     elif is_pca(clf):
         return port_pca(**locals())
-    raise TypeError('clf MUST be one of SVC, LinearSVC, OneClassSVC, RVC, DecisionTree, RandomForest, LogisticRegression, GaussianNB, SEFR, PCA')
+    raise TypeError('clf MUST be one of %s' % ', '.join(platforms.ALLOWED_CLASSIFIERS))

micromlgen/platforms.py

@@ -3,4 +3,17 @@
 ALL = [
     ARDUINO,
     ATTINY
+]
+
+ALLOWED_CLASSIFIERS = [
+    'SVC',
+    'LinearSVC',
+    'OneClassSVC',
+    'RVC',
+    'SEFR',
+    'DecisionTree',
+    'RandomForest',
+    'GaussianNB',
+    'LogisticRegression',
+    'PCA'
 ]

micromlgen/templates/wifiindoorpositioning/wifiindoorpositioning.jinja

@@ -0,0 +1,43 @@
+#pragma once
+
+namespace Eloquent {
+    namespace Projects {
+        class WifiIndoorPositioning {
+            public:
+                /**
+                 * Get feature vector
+                 */
+                float* getFeatures() {
+                    static float features[{{ X[0]|length }}] = {0};
+                    uint8_t numNetworks = WiFi.scanNetworks();
+
+                    for (uint8_t i = 0; i < {{ X[0]|length }}; i++) {
+                        features[i] = 0;
+                    }
+
+                    for (uint8_t i = 0; i < numNetworks; i++) {
+                        int featureIdx = ssidToFeatureIdx(WiFi.SSID(i));
+
+                        if (featureIdx >= 0) {
+                            features[featureIdx] = WiFi.RSSI(i);
+                        }
+                    }
+
+                    return features;
+                }
+
+            protected:
+                /**
+                 * Convert SSID to featureIdx
+                 */
+                int ssidToFeatureIdx(String ssid) {
+                    {% for network, idx in networkmap.items() %}
+                    if (ssid.equals("{{ network }}"))
+                        return {{ idx }};
+                    {% endfor %}
+
+                    return -1;
+                }
+        };
+    }
+}

micromlgen/wifiindoorpositioning.py

@@ -0,0 +1,69 @@
+import json
+import numpy as np
+from micromlgen.utils import jinja
+
+
+def parse_samples(samples, parser):
+    for line in samples.split('\n'):
+        if '{' in line and '}' in line:
+            data = json.loads(line)
+            info = {k: v for k, v in data.items() if k.startswith('__')}
+            networks = {k: v for k, v in data.items() if not k.startswith('__')}
+            yield parser(info, networks)
+
+
+def get_classmap(samples):
+    """Get {location: classIdx} mapping"""
+
+    def parser(info, networks):
+        return info['__location']
+
+    locations = list(parse_samples(samples, parser))
+    return {location: i for i, location in enumerate(sorted(set(locations)))}
+
+
+def get_networkmap(samples):
+    """Get {network: featureIdx} mapping"""
+
+    def parser(info, networks):
+        return networks.keys()
+
+    networks = [list(x) for x in parse_samples(samples, parser)]
+    networks = [network for sub in networks for network in sub]
+    return {network: i for i, network in enumerate(sorted(set(networks)))}
+
+
+def get_x(samples, networkmap):
+    """Get features array"""
+
+    def parser(info, networks):
+        x = [0] * len(networkmap)
+        for network, rssi in networks.items():
+            x[networkmap.get(network)] = rssi
+        return x
+
+    return np.asarray(list(parse_samples(samples, parser)), dtype=np.int8)
+
+
+def get_y(samples, classmap):
+    """Get locationIdx array"""
+
+    def parser(info, networks):
+        location = info['__location']
+        assert location in classmap, 'Unknown location %s' % location
+        return classmap[location]
+
+    return np.asarray(list(parse_samples(samples, parser)))
+
+
+def port_wifi_indoor_positioning(samples):
+    classmap = get_classmap(samples)
+    networkmap = get_networkmap(samples)
+    X = get_x(samples, networkmap)
+    y = get_y(samples, classmap)
+    # classmap is flipped wrt the format `port` expects: flip it
+    classmap = {v: k for k, v in classmap.items()}
+    return X, y, classmap, jinja('wifiindoorpositioning/wifiindoorpositioning.jinja', {
+        'X': X,
+        'networkmap': networkmap
+    })

setup.py

@@ -7,13 +7,13 @@
 setup(
   name = 'micromlgen',
   packages = ['micromlgen'],
-  version = '1.1.7',
+  version = '1.1.8',
   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_117.tar.gz',
+  download_url = 'https://github.com/eloquentarduino/micromlgen/archive/v_118.tar.gz',
   keywords = [
     'ML',
     'microcontrollers',