Examples with BgReading com.eveningoutpost.dexdrip.Models.BgReading used on opensource projects

Example 41 with BgReading

use of com.eveningoutpost.dexdrip.Models.BgReading in project xDrip by NightscoutFoundation.

the class WatchUpdaterService method resendData.

private void resendData() {
    Log.d(TAG, "resendData ENTER");
    forceGoogleApiConnect();
    Log.d(TAG, "resendData googleApiClient connected ENTER");
    long startTime = new Date().getTime() - (60000 * 60 * 24);
    BgReading last_bg = BgReading.last();
    if (last_bg != null) {
        List<BgReading> graph_bgs = BgReading.latestForGraph(60, startTime);
        BgGraphBuilder bgGraphBuilder = new BgGraphBuilder(getApplicationContext());
        if (!graph_bgs.isEmpty()) {
            final int battery = PowerStateReceiver.getBatteryLevel(getApplicationContext());
            DataMap entries = dataMap(last_bg, mPrefs, bgGraphBuilder, battery);
            final ArrayList<DataMap> dataMaps = new ArrayList<>(graph_bgs.size());
            for (BgReading bg : graph_bgs) {
                dataMaps.add(dataMap(bg, mPrefs, bgGraphBuilder, battery));
            }
            // MOST IMPORTANT LINE FOR TIMESTAMP
            entries.putLong("time", new Date().getTime());
            entries.putDataMapArrayList("entries", dataMaps);
            if (mPrefs.getBoolean("extra_status_line", false)) {
                entries.putString("extra_status_line", Home.extraStatusLine());
            }
            new SendToDataLayerThread(WEARABLE_DATA_PATH, googleApiClient).executeOnExecutor(xdrip.executor, entries);
        }
    }
}

Example 42 with BgReading

use of com.eveningoutpost.dexdrip.Models.BgReading in project xDrip by NightscoutFoundation.

the class WatchUpdaterService method sendData.

private void sendData() {
    BgReading bg = BgReading.last();
    if (bg != null) {
        forceGoogleApiConnect();
        if (wear_integration) {
            final int battery = PowerStateReceiver.getBatteryLevel(getApplicationContext());
            new SendToDataLayerThread(WEARABLE_DATA_PATH, googleApiClient).executeOnExecutor(xdrip.executor, dataMap(bg, mPrefs, new BgGraphBuilder(getApplicationContext()), battery));
        }
    }
}

Example 43 with BgReading

use of com.eveningoutpost.dexdrip.Models.BgReading in project xDrip by NightscoutFoundation.

the class WebServiceSgv method request.

// process the request and produce a response object
public WebResponse request(String query) {
    // result code for any steps cgi parameters, 200 = good
    int steps_result_code = 0;
    // result code for any heart cgi parameters, 200 = good
    int heart_result_code = 0;
    // result code for any heart cgi parameters, 200 = good
    int tasker_result_code = 0;
    // show the units we are using
    int units_indicator = 1;
    // whether to cut out portions of the data
    boolean brief = false;
    final Map<String, String> cgi = getQueryParameters(query);
    int count = 24;
    if (cgi.containsKey("count")) {
        try {
            count = Integer.valueOf(cgi.get("count"));
            count = Math.min(count, 100);
            count = Math.max(count, 1);
            UserError.Log.d(TAG, "SGV count request for: " + count + " entries");
        } catch (Exception e) {
        // meh
        }
    }
    if (cgi.containsKey("steps")) {
        UserError.Log.d(TAG, "Received steps request: " + cgi.get("steps"));
        // forward steps request to steps route
        final WebResponse steps_reply_wr = ((RouteFinder) Singleton.get("RouteFinder")).handleRoute("steps/set/" + cgi.get("steps"));
        steps_result_code = steps_reply_wr.resultCode;
    }
    if (cgi.containsKey("heart")) {
        UserError.Log.d(TAG, "Received heart request: " + cgi.get("heart"));
        // forward steps request to heart route
        // accuracy currently ignored (always 1) - TODO review
        final WebResponse heart_reply_wr = ((RouteFinder) Singleton.get("RouteFinder")).handleRoute("heart/set/" + cgi.get("heart") + "/1");
        heart_result_code = heart_reply_wr.resultCode;
    }
    if (cgi.containsKey("tasker")) {
        UserError.Log.d(TAG, "Received tasker request: " + cgi.get("tasker"));
        // forward steps request to heart route
        // send single word command to tasker, eg snooze or osnooze
        final WebResponse tasker_reply_wr = ((RouteFinder) Singleton.get("RouteFinder")).handleRoute("tasker/" + cgi.get("tasker"));
        tasker_result_code = tasker_reply_wr.resultCode;
    }
    if (cgi.containsKey("brief_mode")) {
        brief = true;
    }
    final JSONArray reply = new JSONArray();
    final List<BgReading> readings = BgReading.latest(count);
    if (readings != null) {
        // populate json structures
        try {
            final String collector_device = DexCollectionType.getBestCollectorHardwareName();
            String external_status_line = getLastStatusLine();
            // for each reading produce a json record
            for (BgReading reading : readings) {
                final JSONObject item = new JSONObject();
                if (!brief) {
                    item.put("_id", reading.uuid);
                    item.put("device", collector_device);
                    item.put("dateString", DateUtil.toNightscoutFormat(reading.timestamp));
                    item.put("sysTime", DateUtil.toNightscoutFormat(reading.timestamp));
                }
                item.put("date", reading.timestamp);
                item.put("sgv", (int) reading.getDg_mgdl());
                item.put("delta", new BigDecimal(reading.getDg_slope() * 5 * 60 * 1000).setScale(3, BigDecimal.ROUND_HALF_UP));
                item.put("direction", reading.getDg_deltaName());
                item.put("noise", reading.noiseValue());
                if (!brief) {
                    item.put("filtered", (long) (reading.filtered_data * 1000));
                    item.put("unfiltered", (long) (reading.raw_data * 1000));
                    item.put("rssi", 100);
                    item.put("type", "sgv");
                }
                if (units_indicator > 0) {
                    item.put("units_hint", Pref.getString("units", "mgdl").equals("mgdl") ? "mgdl" : "mmol");
                    units_indicator = 0;
                }
                // emit the external status line once if present
                if (external_status_line.length() > 0) {
                    item.put("aaps", external_status_line);
                    item.put("aaps-ts", getLastStatusLineTime());
                    external_status_line = "";
                }
                // emit result code from steps if present
                if (steps_result_code > 0) {
                    item.put("steps_result", steps_result_code);
                    steps_result_code = 0;
                }
                // emit result code from heart if present
                if (heart_result_code > 0) {
                    item.put("heart_result", heart_result_code);
                    heart_result_code = 0;
                }
                // emit result code from tasker if present
                if (tasker_result_code > 0) {
                    item.put("tasker_result", tasker_result_code);
                    tasker_result_code = 0;
                }
                reply.put(item);
            }
            Log.d(TAG, "Output: " + reply.toString());
        } catch (JSONException e) {
            UserError.Log.wtf(TAG, "Got json exception: " + e);
        }
    }
    return new WebResponse(reply.toString());
}

Example 44 with BgReading

use of com.eveningoutpost.dexdrip.Models.BgReading in project xDrip by NightscoutFoundation.

the class BgGraphBuilder method addBgReadingValues.

private synchronized void addBgReadingValues(final boolean simple) {
    if (readings_lock.isLocked()) {
        Log.d(TAG, "BgReadings lock is currently held");
    }
    readings_lock.lock();
    try {
        if (plugin_adjusted) {
            Log.i(TAG, "Reloading as Plugin modified data: " + JoH.backTrace(1) + " size:" + bgReadings.size());
            bgReadings.clear();
            bgReadings.addAll(BgReading.latestForGraph(loaded_numValues, loaded_start, loaded_end));
        } else {
        // Log.d(TAG, "not adjusted");
        }
        filteredValues.clear();
        rawInterpretedValues.clear();
        iobValues.clear();
        activityValues.clear();
        cobValues.clear();
        predictedBgValues.clear();
        polyBgValues.clear();
        noisePolyBgValues.clear();
        annotationValues.clear();
        treatmentValues.clear();
        highValues.clear();
        lowValues.clear();
        inRangeValues.clear();
        calibrationValues.clear();
        bloodTestValues.clear();
        pluginValues.clear();
        final double bgScale = bgScale();
        final double now = JoH.ts();
        // most recent bgreading timestamp we have
        long highest_bgreading_timestamp = -1;
        // 10 minutes // TODO MAKE PREFERENCE?
        double trend_start_working = now - (1000 * 60 * 12);
        if (bgReadings.size() > 0) {
            highest_bgreading_timestamp = bgReadings.get(0).timestamp;
            final double ms_since_last_reading = now - highest_bgreading_timestamp;
            if (ms_since_last_reading < 500000) {
                // push back start of trend calc window
                trend_start_working -= ms_since_last_reading;
                Log.d(TAG, "Pushed back trend start by: " + JoH.qs(ms_since_last_reading / 1000) + " secs - last reading: " + JoH.dateTimeText(highest_bgreading_timestamp));
            }
        }
        final double trendstart = trend_start_working;
        // 20 minutes // TODO MAKE PREFERENCE
        final double noise_trendstart = now - (1000 * 60 * 20);
        double oldest_noise_timestamp = now;
        double newest_noise_timestamp = 0;
        TrendLine[] polys = new TrendLine[5];
        polys[0] = new PolyTrendLine(1);
        // polys[1] = new PolyTrendLine(2);
        polys[1] = new Forecast.LogTrendLine();
        polys[2] = new Forecast.ExpTrendLine();
        polys[3] = new Forecast.PowerTrendLine();
        TrendLine poly = null;
        final List<Double> polyxList = new ArrayList<>();
        final List<Double> polyyList = new ArrayList<>();
        final List<Double> noise_polyxList = new ArrayList<>();
        final List<Double> noise_polyyList = new ArrayList<>();
        // 8 hours
        final double avg1start = now - (1000 * 60 * 60 * 8);
        // 8 hours
        final double momentum_illustration_start = now - (1000 * 60 * 60 * 2);
        avg1startfuzzed = avg1start / FUZZER;
        avg1value = 0;
        avg1counter = 0;
        avg2value = 0;
        avg2counter = 0;
        double last_calibration = 0;
        double last_bloodtest = 0;
        if (doMgdl) {
            Profile.scale_factor = Constants.MMOLL_TO_MGDL;
        } else {
            Profile.scale_factor = 1;
        }
        final long close_to_side_time = (long) (end_time * FUZZER) - (Constants.MINUTE_IN_MS * 10);
        // enumerate calibrations
        try {
            for (Calibration calibration : calibrations) {
                if (calibration.timestamp < (start_time * FUZZER))
                    break;
                if (calibration.slope_confidence != 0) {
                    final long adjusted_timestamp = (calibration.timestamp + (AddCalibration.estimatedInterstitialLagSeconds * 1000));
                    final PointValueExtended this_point = new PointValueExtended((float) (adjusted_timestamp / FUZZER), (float) unitized(calibration.bg));
                    if (adjusted_timestamp >= close_to_side_time) {
                        predictivehours = Math.max(predictivehours, 1);
                    }
                    this_point.real_timestamp = calibration.timestamp;
                    calibrationValues.add(this_point);
                    if (calibration.timestamp > last_calibration) {
                        last_calibration = calibration.timestamp;
                    }
                }
            }
        } catch (Exception e) {
            Log.e(TAG, "Exception doing calibration values in bggraphbuilder: " + e.toString());
        }
        // enumerate blood tests
        try {
            for (BloodTest bloodtest : bloodtests) {
                final long adjusted_timestamp = (bloodtest.timestamp + (AddCalibration.estimatedInterstitialLagSeconds * 1000));
                final PointValueExtended this_point = new PointValueExtended((float) (adjusted_timestamp / FUZZER), (float) unitized(bloodtest.mgdl));
                this_point.type = PointValueExtended.BloodTest;
                this_point.uuid = bloodtest.uuid;
                this_point.real_timestamp = bloodtest.timestamp;
                // exclude any which have been used for calibration
                boolean matches = false;
                for (PointValue calibration_point : calibrationValues) {
                    if ((Math.abs(calibration_point.getX() - this_point.getX())) <= ((AddCalibration.estimatedInterstitialLagSeconds * 1000) / FUZZER) && (calibration_point.getY() == calibration_point.getY())) {
                        matches = true;
                        break;
                    }
                }
                if (!matches)
                    bloodTestValues.add(this_point);
                if (bloodtest.timestamp > last_bloodtest) {
                    last_bloodtest = bloodtest.timestamp;
                }
                if (adjusted_timestamp >= close_to_side_time) {
                    predictivehours = Math.max(predictivehours, 1);
                }
            }
        } catch (Exception e) {
            Log.e(TAG, "Exception doing calibration values in bggraphbuilder: " + e.toString());
        }
        final boolean has_filtered = DexCollectionType.hasFiltered();
        final boolean predict_use_momentum = prefs.getBoolean("predict_use_momentum", true);
        final boolean show_moment_working_line = prefs.getBoolean("show_momentum_working_line", false);
        final boolean interpret_raw = prefs.getBoolean("interpret_raw", false);
        final boolean show_filtered = prefs.getBoolean("show_filtered_curve", false) && has_filtered;
        final boolean predict_lows = prefs.getBoolean("predict_lows", true);
        final boolean show_plugin = prefs.getBoolean("plugin_plot_on_graph", false);
        final boolean glucose_from_plugin = prefs.getBoolean("display_glucose_from_plugin", false);
        if ((Home.get_follower()) && (bgReadings.size() < 3)) {
            GcmActivity.requestBGsync();
        }
        final CalibrationAbstract plugin = (show_plugin) ? PluggableCalibration.getCalibrationPluginFromPreferences() : null;
        CalibrationAbstract.CalibrationData cd = (plugin != null) ? plugin.getCalibrationData() : null;
        int cdposition = 0;
        if ((glucose_from_plugin) && (cd != null)) {
            // plugin will be adjusting data
            plugin_adjusted = true;
        }
        for (final BgReading bgReading : bgReadings) {
            if ((cd != null) && (calibrations.size() > 0)) {
                while ((bgReading.timestamp < calibrations.get(cdposition).timestamp) || (calibrations.get(cdposition).slope == 0)) {
                    Log.d(TAG, "BG reading earlier than calibration at index: " + cdposition + "  " + JoH.dateTimeText(bgReading.timestamp) + " cal: " + JoH.dateTimeText(calibrations.get(cdposition).timestamp));
                    if (cdposition < calibrations.size() - 1) {
                        cdposition++;
                        // cd = (plugin != null) ? plugin.getCalibrationData(calibrations.get(cdposition).timestamp) : null;
                        final CalibrationAbstract.CalibrationData oldcd = cd;
                        cd = plugin.getCalibrationData(calibrations.get(cdposition).timestamp);
                        if (cd == null) {
                            Log.d(TAG, "cd went to null during adjustment - likely graph spans multiple sensors");
                            cd = oldcd;
                        }
                        Log.d(TAG, "Now using calibration from: " + JoH.dateTimeText(calibrations.get(cdposition).timestamp) + " slope: " + cd.slope + " intercept: " + cd.intercept);
                    } else {
                        Log.d(TAG, "No more calibrations to choose from");
                        break;
                    }
                }
            }
            // swap main and plugin plot if display glucose is from plugin
            if ((glucose_from_plugin) && (cd != null)) {
                pluginValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(bgReading.calculated_value)));
                // recalculate from plugin - beware floating / cached references!
                bgReading.calculated_value = plugin.getGlucoseFromBgReading(bgReading, cd);
                bgReading.filtered_calculated_value = plugin.getGlucoseFromFilteredBgReading(bgReading, cd);
            }
            if ((show_filtered) && (bgReading.filtered_calculated_value > 0) && (bgReading.filtered_calculated_value != bgReading.calculated_value)) {
                filteredValues.add(new PointValue((float) ((bgReading.timestamp - timeshift) / FUZZER), (float) unitized(bgReading.filtered_calculated_value)));
            }
            if ((interpret_raw && (bgReading.raw_calculated > 0))) {
                rawInterpretedValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(bgReading.raw_calculated)));
            }
            if ((!glucose_from_plugin) && (plugin != null) && (cd != null)) {
                pluginValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(plugin.getGlucoseFromBgReading(bgReading, cd))));
            }
            if (bgReading.calculated_value >= 400) {
                highValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(400)));
            } else if (unitized(bgReading.calculated_value) >= highMark) {
                highValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(bgReading.calculated_value)));
            } else if (unitized(bgReading.calculated_value) >= lowMark) {
                inRangeValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(bgReading.calculated_value)));
            } else if (bgReading.calculated_value >= 40) {
                lowValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(bgReading.calculated_value)));
            } else if (bgReading.calculated_value > 13) {
                lowValues.add(new PointValue((float) (bgReading.timestamp / FUZZER), (float) unitized(40)));
            }
            avg2counter++;
            avg2value += bgReading.calculated_value;
            if (bgReading.timestamp > avg1start) {
                avg1counter++;
                avg1value += bgReading.calculated_value;
            }
            // noise calculator
            if ((!simple || (noise_processed_till_timestamp < highest_bgreading_timestamp)) && (bgReading.timestamp > noise_trendstart) && (bgReading.timestamp > last_calibration)) {
                if (has_filtered && (bgReading.filtered_calculated_value > 0) && (bgReading.filtered_calculated_value != bgReading.calculated_value)) {
                    final double shifted_timestamp = bgReading.timestamp - timeshift;
                    if (shifted_timestamp > last_calibration) {
                        if (shifted_timestamp < oldest_noise_timestamp)
                            oldest_noise_timestamp = shifted_timestamp;
                        noise_polyxList.add(shifted_timestamp);
                        noise_polyyList.add((bgReading.filtered_calculated_value));
                        if (d)
                            Log.d(TAG, "flt noise poly Added: " + noise_polyxList.size() + " " + JoH.qs(noise_polyxList.get(noise_polyxList.size() - 1)) + " / " + JoH.qs(noise_polyyList.get(noise_polyyList.size() - 1), 2));
                    }
                }
                if (bgReading.calculated_value > 0) {
                    if (bgReading.timestamp < oldest_noise_timestamp)
                        oldest_noise_timestamp = bgReading.timestamp;
                    if (bgReading.timestamp > newest_noise_timestamp) {
                        newest_noise_timestamp = bgReading.timestamp;
                        original_value = bgReading.calculated_value;
                    }
                    noise_polyxList.add((double) bgReading.timestamp);
                    noise_polyyList.add((bgReading.calculated_value));
                    if (d)
                        Log.d(TAG, "raw noise poly Added: " + noise_polyxList.size() + " " + JoH.qs(noise_polyxList.get(noise_polyxList.size() - 1)) + " / " + JoH.qs(noise_polyyList.get(noise_polyyList.size() - 1), 2));
                }
            }
            // momentum trend
            if (!simple && (bgReading.timestamp > trendstart) && (bgReading.timestamp > last_calibration)) {
                if (has_filtered && (bgReading.filtered_calculated_value > 0) && (bgReading.filtered_calculated_value != bgReading.calculated_value)) {
                    polyxList.add((double) bgReading.timestamp - timeshift);
                    polyyList.add(unitized(bgReading.filtered_calculated_value));
                }
                if (bgReading.calculated_value > 0) {
                    polyxList.add((double) bgReading.timestamp);
                    polyyList.add(unitized(bgReading.calculated_value));
                }
                if (d)
                    Log.d(TAG, "poly Added: " + JoH.qs(polyxList.get(polyxList.size() - 1)) + " / " + JoH.qs(polyyList.get(polyyList.size() - 1), 2));
            }
        }
        if (avg1counter > 0) {
            avg1value = avg1value / avg1counter;
        }
        if (avg2counter > 0) {
            avg2value = avg2value / avg2counter;
        }
        // always calculate noise if needed
        if (noise_processed_till_timestamp < highest_bgreading_timestamp) {
            // noise evaluate
            Log.d(TAG, "Noise: Processing new data for noise: " + JoH.dateTimeText(noise_processed_till_timestamp) + " vs now: " + JoH.dateTimeText(highest_bgreading_timestamp));
            try {
                if (d)
                    Log.d(TAG, "noise Poly list size: " + noise_polyxList.size());
                // TODO Impossible to satisfy noise evaluation size with only raw data do we want it with raw only??
                if (noise_polyxList.size() > 5) {
                    noisePoly = new PolyTrendLine(2);
                    final double[] noise_polyys = PolyTrendLine.toPrimitiveFromList(noise_polyyList);
                    final double[] noise_polyxs = PolyTrendLine.toPrimitiveFromList(noise_polyxList);
                    noisePoly.setValues(noise_polyys, noise_polyxs);
                    last_noise = noisePoly.errorVarience();
                    if (newest_noise_timestamp > oldest_noise_timestamp) {
                        best_bg_estimate = noisePoly.predict(newest_noise_timestamp);
                        last_bg_estimate = noisePoly.predict(newest_noise_timestamp - DEXCOM_PERIOD);
                    } else {
                        best_bg_estimate = -99;
                        last_bg_estimate = -99;
                    }
                    Log.i(TAG, "Noise: Poly Error Varience: " + JoH.qs(last_noise, 5));
                } else {
                    Log.i(TAG, "Noise: Not enough data to get sensible noise value");
                    noisePoly = null;
                    last_noise = -9999;
                    best_bg_estimate = -9999;
                    last_bg_estimate = -9999;
                }
                // store that we have processed up to this timestamp
                noise_processed_till_timestamp = highest_bgreading_timestamp;
            } catch (Exception e) {
                Log.e(TAG, " Error with noise poly trend: " + e.toString());
            }
        } else {
            Log.d(TAG, "Noise Cached noise timestamp: " + JoH.dateTimeText(noise_processed_till_timestamp));
        }
        if (!simple) {
            // momentum
            try {
                if (d)
                    Log.d(TAG, "moment Poly list size: " + polyxList.size());
                if (polyxList.size() > 1) {
                    final double[] polyys = PolyTrendLine.toPrimitiveFromList(polyyList);
                    final double[] polyxs = PolyTrendLine.toPrimitiveFromList(polyxList);
                    // set and evaluate poly curve models and select first best
                    double min_errors = 9999999;
                    for (TrendLine this_poly : polys) {
                        if (this_poly != null) {
                            if (poly == null)
                                poly = this_poly;
                            this_poly.setValues(polyys, polyxs);
                            if (this_poly.errorVarience() < min_errors) {
                                min_errors = this_poly.errorVarience();
                                poly = this_poly;
                            // if (d) Log.d(TAG, "set forecast best model to: " + poly.getClass().getSimpleName() + " with varience of: " + JoH.qs(poly.errorVarience(),14));
                            }
                        }
                    }
                    if (d)
                        Log.i(TAG, "set forecast best model to: " + poly.getClass().getSimpleName() + " with varience of: " + JoH.qs(poly.errorVarience(), 4));
                } else {
                    if (d)
                        Log.i(TAG, "Not enough data for forecast model");
                }
            } catch (Exception e) {
                Log.e(TAG, " Error with poly trend: " + e.toString());
            }
            try {
                // show trend for whole bg reading area
                if ((show_moment_working_line) && (poly != null)) {
                    for (BgReading bgReading : bgReadings) {
                        // only show working curve for last x hours to a
                        if (bgReading.timestamp > momentum_illustration_start) {
                            double polyPredicty = poly.predict(bgReading.timestamp);
                            // if (d) Log.d(TAG, "Poly predict: "+JoH.qs(polyPredict)+" @ "+JoH.qs(iob.timestamp));
                            if ((polyPredicty < highMark) && (polyPredicty > 0)) {
                                PointValue zv = new PointValue((float) (bgReading.timestamp / FUZZER), (float) polyPredicty);
                                polyBgValues.add(zv);
                            }
                        }
                    }
                }
            } catch (Exception e) {
                Log.e(TAG, "Error creating back trend: " + e.toString());
            }
            // low estimator
            // work backwards to see whether we think a low is estimated
            low_occurs_at = -1;
            try {
                if ((predict_lows) && (prediction_enabled) && (poly != null)) {
                    final double offset = ActivityRecognizedService.raise_limit_due_to_vehicle_mode() ? unitized(ActivityRecognizedService.getVehicle_mode_adjust_mgdl()) : 0;
                    final double plow_now = JoH.ts();
                    // max look-ahead
                    double plow_timestamp = plow_now + (1000 * 60 * 99);
                    double polyPredicty = poly.predict(plow_timestamp);
                    Log.d(TAG, "Low predictor at max lookahead is: " + JoH.qs(polyPredicty));
                    // store that we have processed up to this timestamp
                    low_occurs_at_processed_till_timestamp = highest_bgreading_timestamp;
                    if (polyPredicty <= (lowMark + offset)) {
                        low_occurs_at = plow_timestamp;
                        final double lowMarkIndicator = (lowMark - (lowMark / 4));
                        // if (d) Log.d(TAG, "Poly predict: "+JoH.qs(polyPredict)+" @ "+JoH.qsz(iob.timestamp));
                        while (plow_timestamp > plow_now) {
                            plow_timestamp = plow_timestamp - FUZZER;
                            polyPredicty = poly.predict(plow_timestamp);
                            if (polyPredicty > (lowMark + offset)) {
                                PointValue zv = new PointValue((float) (plow_timestamp / FUZZER), (float) polyPredicty);
                                polyBgValues.add(zv);
                            } else {
                                low_occurs_at = plow_timestamp;
                                if (polyPredicty > lowMarkIndicator) {
                                    polyBgValues.add(new PointValue((float) (plow_timestamp / FUZZER), (float) polyPredicty));
                                }
                            }
                        }
                        Log.i(TAG, "LOW PREDICTED AT: " + JoH.dateTimeText((long) low_occurs_at));
                        predictivehours = Math.max(predictivehours, (int) ((low_occurs_at - plow_now) / (60 * 60 * 1000)) + 1);
                    }
                }
            } catch (NullPointerException e) {
            // Log.d(TAG,"Error with low prediction trend: "+e.toString());
            }
            final boolean show_noise_working_line;
            if (last_noise > NOISE_TRIGGER || (last_noise > BgGraphBuilder.NOISE_TRIGGER_ULTRASENSITIVE && Pref.getBooleanDefaultFalse("engineering_mode") && Pref.getBooleanDefaultFalse("bg_compensate_noise_ultrasensitive"))) {
                show_noise_working_line = true;
            } else {
                show_noise_working_line = prefs.getBoolean("show_noise_workings", false);
            }
            // noise debug
            try {
                // overlay noise curve
                if ((show_noise_working_line) && (prediction_enabled) && (noisePoly != null)) {
                    for (BgReading bgReading : bgReadings) {
                        // only show working curve for last x hours to a
                        if ((bgReading.timestamp > oldest_noise_timestamp) && (bgReading.timestamp > last_calibration)) {
                            double polyPredicty = unitized(noisePoly.predict(bgReading.timestamp));
                            if (d)
                                Log.d(TAG, "noise Poly predict: " + JoH.qs(polyPredicty) + " @ " + JoH.qs(bgReading.timestamp));
                            if ((polyPredicty < highMark) && (polyPredicty > 0)) {
                                PointValue zv = new PointValue((float) (bgReading.timestamp / FUZZER), (float) polyPredicty);
                                noisePolyBgValues.add(zv);
                            }
                        }
                    }
                }
            } catch (Exception e) {
                Log.e(TAG, "Error creating noise working trend: " + e.toString());
            }
            try {
                // display treatment blobs and annotations
                for (Treatments treatment : treatments) {
                    double height = 6 * bgScale;
                    if (treatment.insulin > 0)
                        // some scaling needed I think
                        height = treatment.insulin;
                    if (height > highMark)
                        height = highMark;
                    if (height < lowMark)
                        height = lowMark;
                    final PointValueExtended pv = new PointValueExtended((float) (treatment.timestamp / FUZZER), (float) height);
                    String mylabel = "";
                    if (treatment.insulin > 0) {
                        if (mylabel.length() > 0)
                            mylabel = mylabel + System.getProperty("line.separator");
                        mylabel = mylabel + (JoH.qs(treatment.insulin, 2) + "u").replace(".0u", "u");
                    }
                    if (treatment.carbs > 0) {
                        if (mylabel.length() > 0)
                            mylabel = mylabel + System.getProperty("line.separator");
                        mylabel = mylabel + (JoH.qs(treatment.carbs, 1) + "g").replace(".0g", "g");
                    }
                    // standard label
                    pv.setLabel(mylabel);
                    // Log.d(TAG, "watchkeypad pv.mylabel: " + mylabel);
                    if ((treatment.notes != null) && (treatment.notes.length() > 0)) {
                        pv.note = treatment.notes;
                        // Log.d(TAG, "watchkeypad pv.note: " + pv.note + " mylabel: " + mylabel);
                        try {
                            final Pattern p = Pattern.compile(".*?pos:([0-9.]+).*");
                            final Matcher m = p.matcher(treatment.enteredBy);
                            if (m.matches()) {
                                pv.set(pv.getX(), (float) JoH.tolerantParseDouble(m.group(1)));
                            }
                        } catch (Exception e) {
                            Log.d(TAG, "Exception matching position: " + e);
                        }
                    } else {
                        pv.note = treatment.getBestShortText();
                    }
                    if (treatmentValues.size() > 0) {
                        // not sure if this >1 is right really - needs a review
                        PointValue lastpv = treatmentValues.get(treatmentValues.size() - 1);
                        if (Math.abs(lastpv.getX() - pv.getX()) < ((10 * 60 * 1000) / FUZZER)) {
                            // merge label with previous - Intelligent parsing and additions go here
                            if (d)
                                Log.d(TAG, "Merge treatment difference: " + Float.toString(lastpv.getX() - pv.getX()));
                            String lastlabel = String.valueOf(lastpv.getLabelAsChars());
                            if (lastlabel.length() > 0) {
                                lastpv.setLabel(lastlabel + "+" + mylabel);
                                pv.setLabel("");
                            }
                        }
                    }
                    // hover
                    treatmentValues.add(pv);
                    if (d)
                        Log.d(TAG, "Treatment total record: " + Double.toString(height) + " " + " timestamp: " + Long.toString(treatment.timestamp));
                }
            } catch (Exception e) {
                Log.e(TAG, "Exception doing treatment values in bggraphbuilder: " + e.toString());
            }
            try {
                // we need to check we actually have sufficient data for this
                double predictedbg = -1000;
                BgReading mylastbg = bgReadings.get(0);
                double lasttimestamp = 0;
                // this can be optimised to oncreate and onchange
                // TODO handle this better now we use profile time blocks
                Profile.reloadPreferencesIfNeeded(prefs);
                try {
                    if (mylastbg != null) {
                        if (doMgdl) {
                            predictedbg = mylastbg.calculated_value;
                        } else {
                            predictedbg = mylastbg.calculated_value_mmol();
                        }
                        // if (d) Log.d(TAG, "Starting prediction with bg of: " + JoH.qs(predictedbg));
                        lasttimestamp = mylastbg.timestamp / FUZZER;
                        if (d)
                            Log.d(TAG, "Starting prediction with bg of: " + JoH.qs(predictedbg) + " secs ago: " + (JoH.ts() - mylastbg.timestamp) / 1000);
                    } else {
                        Log.i(TAG, "COULD NOT GET LAST BG READING FOR PREDICTION!!!");
                    }
                } catch (Exception e) {
                // could not get a bg reading
                }
                final double iobscale = 1 * bgScale;
                final double cobscale = 0.2 * bgScale;
                final double initial_predicted_bg = predictedbg;
                final double relaxed_predicted_bg_limit = initial_predicted_bg * 1.20;
                final double cob_insulin_max_draw_value = highMark * 1.20;
                // final List<Iob> iobinfo_old = Treatments.ioBForGraph(numValues, (start_time * FUZZER));
                // for test
                final List<Iob> iobinfo = (simulation_enabled) ? Treatments.ioBForGraph_new(NUM_VALUES, (start_time * FUZZER)) : null;
                // initial value in case there are no iob records
                long fuzzed_timestamp = (long) end_time;
                if (d)
                    Log.d(TAG, "Internal date timestamp: " + android.text.format.DateFormat.format("yyyy-MM-dd HH:mm:ss", new java.util.Date()));
                if (d)
                    Log.d(TAG, "initial Fuzzed end timestamp: " + android.text.format.DateFormat.format("yyyy-MM-dd HH:mm:ss", fuzzed_timestamp * FUZZER));
                if (d)
                    Log.d(TAG, "initial Fuzzed start timestamp: " + android.text.format.DateFormat.format("yyyy-MM-dd HH:mm:ss", (long) start_time * FUZZER));
                if ((iobinfo != null) && (prediction_enabled) && (simulation_enabled)) {
                    double predict_weight = 0.1;
                    boolean iob_shown_already = false;
                    for (Iob iob : iobinfo) {
                        // double activity = iob.activity;
                        if ((iob.iob > 0) || (iob.cob > 0) || (iob.jActivity > 0) || (iob.jCarbImpact > 0)) {
                            fuzzed_timestamp = iob.timestamp / FUZZER;
                            if (d)
                                Log.d(TAG, "iob timestamp: " + iob.timestamp);
                            if (iob.iob > Profile.minimum_shown_iob) {
                                double height = iob.iob * iobscale;
                                if (height > cob_insulin_max_draw_value)
                                    height = cob_insulin_max_draw_value;
                                PointValue pv = new PointValue((float) fuzzed_timestamp, (float) height);
                                iobValues.add(pv);
                                // currently scaled by profile
                                double activityheight = iob.jActivity * 3;
                                if (activityheight > cob_insulin_max_draw_value)
                                    activityheight = cob_insulin_max_draw_value;
                                PointValue av = new PointValue((float) fuzzed_timestamp, (float) activityheight);
                                activityValues.add(av);
                            }
                            if (iob.cob > 0) {
                                double height = iob.cob * cobscale;
                                if (height > cob_insulin_max_draw_value)
                                    height = cob_insulin_max_draw_value;
                                PointValue pv = new PointValue((float) fuzzed_timestamp, (float) height);
                                if (d)
                                    Log.d(TAG, "Cob total record: " + JoH.qs(height) + " " + JoH.qs(iob.cob) + " " + Float.toString(pv.getY()) + " @ timestamp: " + Long.toString(iob.timestamp));
                                // warning should not be hardcoded
                                cobValues.add(pv);
                            }
                            // do we actually need to calculate this within the loop - can we use only the last datum?
                            if (fuzzed_timestamp > (lasttimestamp)) {
                                double polyPredict = 0;
                                if (poly != null) {
                                    try {
                                        polyPredict = poly.predict(iob.timestamp);
                                        if (d)
                                            Log.d(TAG, "Poly predict: " + JoH.qs(polyPredict) + " @ " + JoH.dateTimeText(iob.timestamp));
                                        if (show_moment_working_line) {
                                            if (((polyPredict < highMark) || (polyPredict < initial_predicted_bg)) && (polyPredict > 0)) {
                                                PointValue zv = new PointValue((float) fuzzed_timestamp, (float) polyPredict);
                                                polyBgValues.add(zv);
                                            }
                                        }
                                    } catch (Exception e) {
                                        Log.e(TAG, "Got exception with poly predict: " + e.toString());
                                    }
                                }
                                if (d)
                                    Log.d(TAG, "Processing prediction: before: " + JoH.qs(predictedbg) + " activity: " + JoH.qs(iob.jActivity) + " jcarbimpact: " + JoH.qs(iob.jCarbImpact));
                                // lower bg by current insulin activity
                                predictedbg -= iob.jActivity;
                                predictedbg += iob.jCarbImpact;
                                double predictedbg_final = predictedbg;
                                // add momentum characteristics if we have them
                                final boolean momentum_smoothing = true;
                                if ((predict_use_momentum) && (polyPredict > 0)) {
                                    predictedbg_final = ((predictedbg * predict_weight) + polyPredict) / (predict_weight + 1);
                                    if (momentum_smoothing)
                                        predictedbg = predictedbg_final;
                                    if (d)
                                        Log.d(TAG, "forecast predict_weight: " + JoH.qs(predict_weight));
                                }
                                // from 0-infinity - // TODO account for step!!!
                                predict_weight = predict_weight * 2.5;
                                // we should pull in actual graph upper and lower limits here
                                if (((predictedbg_final < cob_insulin_max_draw_value) || (predictedbg_final < relaxed_predicted_bg_limit)) && (predictedbg_final > 0)) {
                                    PointValue zv = new PointValue((float) fuzzed_timestamp, (float) predictedbg_final);
                                    predictedBgValues.add(zv);
                                }
                            }
                            if (fuzzed_timestamp > end_time) {
                                // round up to nearest future hour - timestamps in minutes here
                                predictivehours = (int) (((fuzzed_timestamp - end_time) * FUZZER) / (1000 * 60 * 60)) + 1;
                                if (d)
                                    Log.d(TAG, "Predictive hours updated to: " + predictivehours);
                            } else {
                                // KS Log.d(TAG, "IOB DEBUG: " + (fuzzed_timestamp - end_time) + " " + iob.iob);
                                if (!iob_shown_already && (Math.abs(fuzzed_timestamp - end_time) < 5) && (iob.iob > 0)) {
                                    iob_shown_already = true;
                                    // show current iob
                                    // double position = 12.4 * bgScale; // this is for mmol - needs generic for mg/dl
                                    // if (Math.abs(predictedbg - position) < (2 * bgScale)) {
                                    // position = 7.0 * bgScale;
                                    // }
                                    // PointValue iv = new PointValue((float) fuzzed_timestamp, (float) position);
                                    DecimalFormat df = new DecimalFormat("#");
                                    df.setMaximumFractionDigits(2);
                                    df.setMinimumIntegerDigits(1);
                                    // iv.setLabel("IoB: " + df.format(iob.iob));
                                    Home.updateStatusLine("iob", df.format(iob.iob));
                                // annotationValues.add(iv); // needs to be different value list so we can make annotation nicer
                                }
                            }
                        }
                    }
                    if (d)
                        Log.i(TAG, "Size of iob: " + Integer.toString(iobinfo.size()) + " Predictive hours: " + Integer.toString(predictivehours) + " Predicted end game change: " + JoH.qs(predictedbg - mylastbg.calculated_value_mmol()) + " Start bg: " + JoH.qs(mylastbg.calculated_value_mmol()) + " Predicted: " + JoH.qs(predictedbg));
                // calculate bolus or carb adjustment - these should have granularity for injection / pump and thresholds
                } else {
                    if (d)
                        Log.i(TAG, "iobinfo was null");
                }
                double[] evaluation;
                if (prediction_enabled && simulation_enabled) {
                    // if (doMgdl) {
                    // These routines need to understand how the profile is defined to use native instead of scaled
                    evaluation = Profile.evaluateEndGameMmol(predictedbg, lasttimestamp * FUZZER, end_time * FUZZER);
                    // } else {
                    // evaluation = Profile.evaluateEndGameMmol(predictedbg, lasttimestamp * FUZZER, end_time * FUZZER);
                    // }
                    String bwp_update = "";
                    keyStore.putL("bwp_last_insulin_timestamp", -1);
                    if (d)
                        Log.i(TAG, "Predictive BWP: Current prediction: " + JoH.qs(predictedbg) + " / carbs: " + JoH.qs(evaluation[0]) + " insulin: " + JoH.qs(evaluation[1]));
                    if (!BgReading.isDataStale()) {
                        if (((low_occurs_at < 1) || Pref.getBooleanDefaultFalse("always_show_bwp")) && (Pref.getBooleanDefaultFalse("show_bwp"))) {
                            if (evaluation[0] > Profile.minimum_carb_recommendation) {
                                // PointValue iv = new PointValue((float) fuzzed_timestamp, (float) (10 * bgScale));
                                // iv.setLabel("+Carbs: " + JoH.qs(evaluation[0], 0));
                                bwp_update = "\u224F" + " Carbs: " + JoH.qs(evaluation[0], 0);
                            // annotationValues.add(iv); // needs to be different value list so we can make annotation nicer
                            } else if (evaluation[1] > Profile.minimum_insulin_recommendation) {
                                // PointValue iv = new PointValue((float) fuzzed_timestamp, (float) (11 * bgScale));
                                // iv.setLabel("+Insulin: " + JoH.qs(evaluation[1], 1));
                                keyStore.putS("bwp_last_insulin", JoH.qs(evaluation[1], 1) + ((low_occurs_at > 0) ? ("!") : ""));
                                keyStore.putL("bwp_last_insulin_timestamp", JoH.tsl());
                                // warning symbol
                                bwp_update = "\u224F" + " Insulin: " + JoH.qs(evaluation[1], 1) + ((low_occurs_at > 0) ? (" " + "\u26A0") : "");
                            // annotationValues.add(iv); // needs to be different value list so we can make annotation nicer
                            }
                        }
                    }
                    // always send so we can blank if needed
                    Home.updateStatusLine("bwp", bwp_update);
                }
            } catch (Exception e) {
                Log.e(TAG, "Exception doing iob values in bggraphbuilder: " + e.toString());
            }
        }
    // if !simple
    } finally {
        readings_lock.unlock();
    }
}

Example 45 with BgReading

use of com.eveningoutpost.dexdrip.Models.BgReading in project xDrip by NightscoutFoundation.

the class NightscoutUploader method doRESTUploadTo.

private void doRESTUploadTo(NightscoutService nightscoutService, String secret, List<BgReading> glucoseDataSets, List<BloodTest> meterRecords, List<Calibration> calRecords) throws Exception {
    final JSONArray array = new JSONArray();
    for (BgReading record : glucoseDataSets) {
        populateV1APIBGEntry(array, record);
    }
    for (BloodTest record : meterRecords) {
        populateV1APIMeterReadingEntry(array, record);
    }
    for (Calibration record : calRecords) {
        final BloodTest dupe = BloodTest.getForPreciseTimestamp(record.timestamp, 60000);
        if (dupe == null) {
            // also add calibrations as meter records
            populateV1APIMeterReadingEntry(array, record);
        } else {
            Log.d(TAG, "Found duplicate blood test entry for this calibration record: " + record.bg + " vs " + dupe.mgdl + " mg/dl");
        }
        populateV1APICalibrationEntry(array, record);
    }
    if (array.length() > 0) {
        // KS
        final RequestBody body = RequestBody.create(MediaType.parse("application/json"), array.toString());
        final Response<ResponseBody> r = nightscoutService.upload(secret, body).execute();
        if (!r.isSuccess())
            throw new UploaderException(r.message(), r.code());
        checkGzipSupport(r);
        try {
            postDeviceStatus(nightscoutService, secret);
        } catch (Exception e) {
            Log.e(TAG, "Ignoring devicestatus post exception: " + e);
        }
    }
    try {
        if (Pref.getBooleanDefaultFalse("send_treatments_to_nightscout")) {
            postTreatments(nightscoutService, secret);
        } else {
            Log.d(TAG, "Skipping treatment upload due to preference disabled");
        }
    } catch (Exception e) {
        Log.e(TAG, "Exception uploading REST API treatments: " + e.getMessage());
        if (e.getMessage().equals("Not Found")) {
            final String msg = "Please ensure careportal plugin is enabled on nightscout for treatment upload!";
            Log.wtf(TAG, msg);
            Home.toaststaticnext(msg);
            handleRestFailure(msg);
        }
    }
    // TODO in the future we may want to merge these in to a single post
    if (Pref.getBooleanDefaultFalse("use_pebble_health") && (Home.get_engineering_mode())) {
        try {
            postHeartRate(nightscoutService, secret);
            postStepsCount(nightscoutService, secret);
            postMotionTracking(nightscoutService, secret);
        } catch (Exception e) {
            if (JoH.ratelimit("heartrate-upload-exception", 3600)) {
                Log.e(TAG, "Exception uploading REST API heartrate: " + e.getMessage());
            }
        }
    }
}