Added fast autofocus

                    self.stream,

                    format='mjpeg',

                    quality=self.config['jpeg_quality'],

                    bitrate=-1, # RWB: disable bitrate control

                    splitter_port=splitter_port)

            except picamera.exc.PiCameraAlreadyRecording:

                logging.info("Error while starting preview: Recording already running.")

import time

import numpy as np

import threading

from openflexure_microscope.plugins import MicroscopePlugin

from openflexure_microscope.utilities import set_properties

from openflexure_microscope.api.v1.views import MicroscopeViewPlugin

from openflexure_microscope.api.utilities import JsonPayload

from flask import request, jsonify, abort, current_app

import logging

from contextlib import contextmanager

class JPEGSharpnessMonitor():

    def __init__(self, microscope, timeout=60):

        self.microscope = microscope

        self.camera = microscope.camera

        self.stage = microscope.stage

        self.jpeg_sizes = []

        self.jpeg_times = []

        self.stage_positions = []

        self.stage_times = []

        self.stop_event = threading.Event()

        self.timeout = timeout

        self.keep_alive()

        self.background_thread = None

    def is_alive(self):

        if self.background_thread is None:

            return False

        else:

            return self.background_thread.is_alive()

    def should_stop(self):

        import time

        return time.time() - self.kept_alive > self.timeout

    def keep_alive(self):

        import time

        self.kept_alive = time.time()

    def start(self):

        "Start monitoring sharpness by looking at JPEG size"

        self.background_thread = threading.Thread(target=self._measure_jpegs)

        self.background_thread.start()

        return self

    def stop(self):

        "Stop the background thread"

        self.stop_event.set()

        self.background_thread.join()

    def _measure_jpegs(self):

        "Function that runs in a background thread to record sharpness"

        logging.info("Starting sharpness measurement in background thread")

        self.keep_alive()

        while not self.stop_event.is_set() and not self.should_stop():

            self.jpeg_sizes.append(self.jpeg_size())

            self.jpeg_times.append(time.time())

        if self.stop_event.is_set():

            logging.info("Cleanly stopped sharpness measurement in background thread")

        if self.should_stop():

            logging.info("Sharpness measurement timed out and has stopped")

    def jpeg_size(self):

        """Return the size of a frame from the MJPEG stream"""

        return len(self.camera.get_frame())

    def focus_rel(self, dz, backlash=False, **kwargs):

        self.keep_alive()

        self.stage_times.append(time.time())

        self.stage_positions.append(self.stage.position)

        self.stage.move_rel([0, 0, dz], backlash=backlash, **kwargs)

        self.stage_times.append(time.time())

        self.stage_positions.append(self.stage.position)

        i = len(self.stage_positions) - 2

        return i, self.stage_positions[-1][2]

    def move_data(self, istart, istop=None):

        "Extract sharpness as a function of (interpolated) z"

        global np, logging

        if istop is None:

            istop = istart + 2

        jpeg_times = np.array(self.jpeg_times)

        jpeg_sizes = np.array(self.jpeg_sizes)

        stage_times = np.array(self.stage_times)[istart:istop]

        stage_zs = np.array(self.stage_positions)[istart:istop, 2]

        start = np.argmax(jpeg_times > stage_times[0])

        stop = np.argmax(jpeg_times > stage_times[1])

        if stop < 1:

            stop = len(jpeg_times)

            logging.debug("changing stop to {}".format(stop))

        jpeg_times = jpeg_times[start:stop]

        jpeg_zs = np.interp(jpeg_times, stage_times, stage_zs)

        return jpeg_times, jpeg_zs, jpeg_sizes[start:stop]

    def sharpest_z_on_move(self, index):

        """Return the z position of the sharpest image on a given move"""

        jt, jz, js = self.move_data(index)

        return jz[np.argmax(js)]

    def data_dict(self):

        """Return the gathered data as a single convenient dictionary"""

        data = {}

        for k in ['jpeg_times', 'jpeg_sizes', 'stage_times', 'stage_positions']:

            data[k] = getattr(self, k)

        return data

class FastAutofocusAPI(MicroscopeViewPlugin):

    def post(self):

        payload = JsonPayload(request)

        # Figure out the parameters to use

        dz = payload.param("dz", default=2000, convert=int)

        backlash = payload.param("backlash", default=None, convert=int)

        if backlash < 0:

            backlash = None

        print("Running autofocus...")

        task = self.microscope.task.start(self.plugin.fast_autofocus, dz, backlash=backlash)

        # return a handle on the autofocus task

        return jsonify(task.state), 202

class Plugin(MicroscopePlugin):

    """

    Plugin to provide fast autofocus

    """

    JPEGSharpnessMonitor = JPEGSharpnessMonitor # make the class available

    def sharpness_monitor(self):

        return JPEGSharpnessMonitor(self.microscope)

    @contextmanager

    def monitor_sharpness(self):

        m = self.sharpness_monitor()

        m.start()

        try:

            yield m

        finally:

            m.stop()

    def move_and_find_focus(self, dz):

        """Make a relative Z move and return the peak sharpness position"""

        with self.monitor_sharpness() as m:

            m.focus_rel(dz)

            return m.sharpest_z_on_move(0)

    def fast_autofocus(self, dz=2000, backlash=None):

        """Perform a down-up-down-up autofocus"""

        with self.monitor_sharpness() as m:

            i, z = m.focus_rel(-dz/2)

            i, z = m.focus_rel(dz)

            fz = m.sharpest_z_on_move(i)

            if backlash is None:

                i, z = m.focus_rel(-dz) # move all the way to the start so it's consistent

            else:

                i, z = m.focus_rel(fz - z - backlash)

            m.focus_rel(fz - z)

            return m.data_dict()

    api_views = {

            '/fast_autofocus': FastAutofocusAPI,

    }