.. _program_listing_file_processors_runningstats_runningstats.cpp:

Program Listing for File runningstats.cpp
=========================================

|exhale_lsh| :ref:`Return to documentation for file <file_processors_runningstats_runningstats.cpp>` (``processors/runningstats/runningstats.cpp``)

.. |exhale_lsh| unicode:: U+021B0 .. UPWARDS ARROW WITH TIP LEFTWARDS

.. code-block:: cpp

   // ---------------------------------------------------------------------
   // This file is part of falcon-core.
   //
   // Copyright (C) 2015, 2016, 2017 Neuro-Electronics Research Flanders
   //
   // Falcon-server is free software: you can redistribute it and/or modify
   // it under the terms of the GNU General Public License as published by
   // the Free Software Foundation, either version 3 of the License, or
   // (at your option) any later version.
   //
   // Falcon-server is distributed in the hope that it will be useful,
   // but WITHOUT ANY WARRANTY; without even the implied warranty of
   // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   // GNU General Public License for more details.
   //
   // You should have received a copy of the GNU General Public License
   // along with falcon-core. If not, see <http://www.gnu.org/licenses/>.
   // ---------------------------------------------------------------------
   
   #include "runningstats.hpp"
   
   RunningStats::RunningStats() : IProcessor() {
     add_option("integration time", integration_time_,
                "Time window for exponential smoothing.");
   
     add_option("outlier/protection", outlier_protection_,
                "enable outlier protection. "
                "Outliers are values larger than a predefined z-score. "
                "The contribution of an outlier is reduced by an amount "
                "that depends on the magnitude of the outlier.");
   
     add_option("outlier/zscore", outlier_zscore_,
                "z-score that defines an outlier.");
   
     add_option("outlier/half life", outlier_half_life_,
                "The number of standard deviations above the outlier "
                "z-score at which the influence of the outlier is halved.");
   }
   
   void RunningStats::CreatePorts() {
     data_in_port_ = create_input_port<TimeSeriesType<double>>(
         "data", TimeSeriesType<double>::Capabilities(ChannelRange(1, 256)),
         PortInPolicy(SlotRange(1)));
   
     data_out_port_ = create_output_port<TimeSeriesType<double>>(
         "data", TimeSeriesType<double>::Parameters(), PortOutPolicy(SlotRange(1)));
   
   }
   
   void RunningStats::CompleteStreamInfo() {
     for (int k = 0; k < data_in_port_->number_of_slots(); ++k) {
       data_out_port_->streaminfo(k).set_parameters(
           data_in_port_->streaminfo(k).parameters<const typename TimeSeriesType<double>::Parameters &>());
       data_out_port_->streaminfo(k).set_stream_parameters(data_in_port_->streaminfo(k));
     }
   }
   
   void RunningStats::Preprocess(ProcessingContext &context) {
     double sample_rate =
         data_in_port_->prototype(0).sample_rate();
     double alpha = 1.0 / (integration_time_() * sample_rate);
   
     stats_.reset(new dsp::algorithms::RunningMeanMAD(
         alpha, integration_time_() * sample_rate, outlier_protection_(),
         outlier_zscore_(), outlier_half_life_()));
   }
   
   void RunningStats::Process(ProcessingContext &context) {
     TimeSeriesType<double>::Data *data_in;
     TimeSeriesType<double>::Data *data_out;
     unsigned N = 100;
   
     while (!context.terminated()) {
       // retrieve new data
       if (!data_in_port_->slot(0)->RetrieveData(data_in)) {
         break;
       }
   
       data_out = data_out_port_->slot(0)->ClaimData(false);
       // loop through each sample
       for (unsigned int sample = 0; sample < data_in->nsamples(); ++sample) {
         stats_->add_sample(data_in->data_sample(sample, 0));
         data_out->set_data_sample(sample, 0, stats_->center());
         data_out->set_data_sample(sample, 1, stats_->dispersion());
         data_out->set_sample_timestamp(sample, data_in->sample_timestamp(sample));
       }
   
       data_out->CloneTimestamps(*data_in);
       data_out_port_->slot(0)->PublishData();
       data_in_port_->slot(0)->ReleaseData();
   
       N--;
       if (N == 0) {
         LOG(UPDATE) << "center = " << stats_->center()
                     << ", dispersion = " << stats_->dispersion();
         N = 100;
       }
     }
   }
   
   REGISTERPROCESSOR(RunningStats)