def preprocessor_pca_modular (data): from modshogun import RealFeatures from modshogun import PCA features = RealFeatures(data) preprocessor = PCA() preprocessor.init(features) preprocessor.apply_to_feature_matrix(features) return features
def RunPCAShogun(q): totalTimer = Timer() # Load input dataset. Log.Info("Loading dataset", self.verbose) try: feat = RealFeatures(self.data.T) with totalTimer: # Get the options for running PCA. if "new_dimensionality" in options: k = int(options.pop("new_dimensionality")) if (k > self.data.shape[1]): Log.Fatal("New dimensionality (" + str(k) + ") cannot be greater than" + "existing dimensionality (" + str(self.data.shape[1]) + ")!") q.put(-1) return -1 else: k = self.data.shape[1] if "whiten" in options: s = True options.pop("whiten") else: s = False if len(options) > 0: Log.Fatal("Unknown parameters: " + str(options)) raise Exception("unknown parameters") # Perform PCA. prep = ShogunPCA(s) prep.set_target_dim(k) prep.init(feat) prep.apply_to_feature_matrix(feat) except Exception as e: q.put(-1) return -1 time = totalTimer.ElapsedTime() q.put(time) return time
def RunPCAShogun(q): totalTimer = Timer() # Load input dataset. Log.Info("Loading dataset", self.verbose) try: feat = RealFeatures(self.data.T) with totalTimer: # Find out what dimension we want. match = re.search('-d (\d+)', options) if not match: k = self.data.shape[1] else: k = int(match.group(1)) if (k > self.data.shape[1]): Log.Fatal("New dimensionality (" + str(k) + ") cannot be greater than" + "existing dimensionality (" + str(self.data.shape[1]) + ")!") q.put(-1) return -1 # Get the options for running PCA. s = True if options.find("-s") > -1 else False # Perform PCA. prep = ShogunPCA(s) prep.set_target_dim(k) prep.init(feat) prep.apply_to_feature_matrix(feat) except Exception as e: q.put(-1) return -1 time = totalTimer.ElapsedTime() q.put(time) return time
def RunPCAShogun(): totalTimer = Timer() # Load input dataset. Log.Info("Loading dataset", self.verbose) try: feat = RealFeatures(self.data.T) with totalTimer: # Get the options for running PCA. if "new_dimensionality" in options: k = int(options.pop("new_dimensionality")) if (k > self.data.shape[1]): Log.Fatal("New dimensionality (" + str(k) + ") cannot be greater than" + "existing dimensionality (" + str(self.data.shape[1]) + ")!") return -1 else: k = self.data.shape[1] if "whiten" in options: s = True options.pop("whiten") else: s = False if len(options) > 0: Log.Fatal("Unknown parameters: " + str(options)) raise Exception("unknown parameters") # Perform PCA. prep = ShogunPCA(s) prep.set_target_dim(k) prep.init(feat) prep.apply_to_feature_matrix(feat) except Exception as e: return -1 return totalTimer.ElapsedTime()