TPPTAnalysisSW/tests/test_non_stationary_reporting_rate.py

"""
Copyright (c) 2019, OptoFidelity OY

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

    1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
    2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
    3. All advertising materials mentioning features or use of this software must display the following acknowledgement: This product includes software developed by the OptoFidelity OY.
    4. Neither the name of the OptoFidelity OY nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""

import cherrypy
from genshi.template import MarkupTemplate
from sqlalchemy.orm import joinedload
import numpy

from TPPTAnalysisSW.testbase import TestBase, testclasscreator
from TPPTAnalysisSW.imagefactory import ImageFactory
from TPPTAnalysisSW.measurementdb import *
from TPPTAnalysisSW.utils import Timer
from TPPTAnalysisSW.settings import settings
from TPPTAnalysisSW.info.version import Version
import TPPTAnalysisSW.plotinfo as plotinfo
import TPPTAnalysisSW.plot_factory as plot_factory
import TPPTAnalysisSW.analyzers as analyzers

class NonStationaryReportingRateTest(TestBase):
    """ A dummy test class for use as a template in creating new test classes """

    # This is the generator function for the class - it must exist in all derived classes
    # Just update the id (dummy=99) and class name
    @staticmethod
    @testclasscreator(12)
    def create_testclass(*args, **kwargs):
        return NonStationaryReportingRateTest(*args, **kwargs)

    # Init function: make necessary initializations.
    # Parent function initializes: self.test_id, self.test_item (dictionary, contains test_type_name) and self.testsession (dictionary)
    def __init__(self, ddtest_row, *args, **kwargs):
        """ Initializes a new NonStationaryReportingRateTest class """
        super(NonStationaryReportingRateTest, self).__init__(ddtest_row, *args, **kwargs)

    # Override to make necessary analysis for test session success
    def runanalysis(self, *args, **kwargs):
        """ Runs the analysis, return a string containing the test result """
        results = self.read_test_results()
        return results['verdict']

    # Override to make necessary operations for clearing test results
    # Clearing the test result from the results table is done elsewhere
    def clearanalysis(self, *args, **kwargs):
        """ Clears analysis results """
        ImageFactory.delete_images(self.test_id)

    # Create the test report. Return the created HTML, or raise cherrypy.HTTPError
    def createreport(self, *args, **kwargs):

        s = Timer(1)

        # clear analysis data
        self.clearanalysis()

        # Create common template parameters (including test_item dictionary, testsession dictionary, test_id, test_type_name etc)
        templateParams = super(NonStationaryReportingRateTest, self).create_common_templateparams(**kwargs)

        s.Time("Init")

        # Read test results
        results = self.read_test_results()

        s.Time("Results")

        templateParams['slowest_reporting_rate'] = results['slowest_reporting_rate']
        templateParams['fastest_reporting_rate'] = results['fastest_reporting_rate']
        templateParams['missing_lines'] = results['missing_lines']
        templateParams['detailed_data'] = zip(results['swipe_ids'], results['max_reporting_rates'],
                                              results['min_reporting_rates'], results['average_reporting_rates'], results['verdicts'], results['images'])

        # Add the image name and parameters to the report
        templateParams['figure'] = ImageFactory.create_image_name(self.test_id, 'nonstrr')
        templateParams['detailed_figure'] = ImageFactory.create_image_name(self.test_id, 'nonstrr', 'detailed')

        # set the content to be used
        templateParams['test_page'] = 'test_non_stationary_reporting_rate.html'
        templateParams['test_script'] = 'test_page_subplots.js'
        templateParams['version'] = Version
        s.Time("Parameters")

        template = MarkupTemplate(open("templates/test_common_body.html"))
        stream = template.generate(**(templateParams))
        s.Time("Generate")
        return stream.render('xhtml'), results['verdict']

    # Create images for the report. If the function returns a value, it is used as the new image name (without image path)
    def createimage(self, imagepath, image_name, *args, **kwargs):

        if image_name == 'nonstrr':
            dbsession = get_database().session()
            dutinfo = plotinfo.TestDUTInfo(testdut_id=self.dut['id'], dbsession=dbsession)
            results = self.read_test_results()
            title = 'Preview: Non-stationary reporting rate ' + self.dut['program']
            plot_factory.plot_swipes_on_target_with_labels(imagepath, results, dutinfo, *args, title=title, **kwargs)
        elif image_name == 'nonstrdtl':
            dbsession = get_database().session()
            dutinfo = plotinfo.TestDUTInfo(testdut_id=self.dut['id'], dbsession=dbsession)
            results = self.read_swipe_info(args[0], dutinfo=dutinfo, dbsession=dbsession)
            title = 'Preview: Non-stationary reporting rate ' + self.dut['program']
            plot_factory.plot_reporting_rate(imagepath, results, title=title, **kwargs)
        else:
            raise cherrypy.HTTPError(message = "No such image in the report")

        return None

    def read_test_results(self, dutinfo = None, dbsession = None):

        s = Timer(2)

        if dbsession is None:
            dbsession = get_database().session()
        if dutinfo is None:
            dutinfo = plotinfo.TestDUTInfo(testdut_id=self.dut['id'], dbsession=dbsession)

        test_results = dbsession.query(OneFingerNonStationaryReportingRateTest).filter(OneFingerNonStationaryReportingRateTest.test_id == self.test_id).\
                                                                                order_by(OneFingerNonStationaryReportingRateTest.id).\
                                                                                options(joinedload('one_finger_non_stationary_reporting_rate_results')).all()

        s.Time("DB")

        max_reporting_rates = []
        min_reporting_rates = []
        average_reporting_rates = []
        verdicts = []
        swipe_id = 0
        swipe_ids = []
        passed_points = []
        failed_points = []
        images = []
        lines = []
        missing_lines = 0
        if 'minreportingrate' in settings and settings['minreportingrate'] > 0.0:
            accept_delay = (1000.0 / float(settings['minreportingrate']))
        else:
            accept_delay = 0.0

        for test_result in test_results:
            max_reporting_rate = 0.0
            min_reporting_rate = 0.0
            previous_timestamp = 0.0
            max_delay = 0.0
            min_delay = 0.0
            delays = []
            verdict = "N/A" # No points
            for result in test_result.one_finger_non_stationary_reporting_rate_results:
                if previous_timestamp == 0.0:
                    previous_timestamp = result.time
                    passed_points.append((result.panel_x, result.panel_y))
                else:
                    delay = result.time - previous_timestamp
                    delays.append(delay)
                    if delay >= max_delay:
                        max_delay = delay
                    if min_delay == 0.0:
                        min_delay = delay
                    elif delay > 0.0 and delay < min_delay:
                        min_delay = delay
                    previous_timestamp = result.time

                    if delay > accept_delay:
                        failed_points.append((result.panel_x, result.panel_y))
                        verdict = "Fail"
                    else:
                        passed_points.append((result.panel_x, result.panel_y))
                        if verdict == "N/A":
                            verdict = "Pass" # At least one point exists -> Pass (if not later set to fail)

            if len(test_result.one_finger_non_stationary_reporting_rate_results) == 0:
                verdict = "Fail" # If no points in the measurement -> missing line
                missing_lines += 1

            min_reporting_rate = analyzers.round_dec(1.0/(max_delay/1000.0)) if max_delay != 0.0 else None
            max_reporting_rate = analyzers.round_dec(1.0/(min_delay/1000.0)) if min_delay != 0.0 else None
            average_reporting_rate = analyzers.round_dec(1.0/(numpy.average(delays)/1000)) if len(delays) != 0 else None
            min_reporting_rates.append(min_reporting_rate)
            max_reporting_rates.append(max_reporting_rate)
            average_reporting_rates.append(average_reporting_rate)
            lines.append(((test_result.start_x, test_result.start_y), (test_result.end_x, test_result.end_y)))
            verdicts.append(verdict)
            swipe_id += 1
            swipe_ids.append(swipe_id)
            images.append(ImageFactory.create_image_name(self.test_id, 'nonstrdtl', str(test_result.id)))

        s.Time("Analysis")

        results = {}
        results['swipe_ids'] = swipe_ids
        results['max_reporting_rates'] = max_reporting_rates
        results['min_reporting_rates'] = min_reporting_rates
        results['average_reporting_rates'] = average_reporting_rates
        results['verdicts'] = verdicts
        results['images'] = images
        results['passed_points'] = analyzers.panel_to_target(passed_points, dutinfo)
        results['failed_points'] = analyzers.panel_to_target(failed_points, dutinfo)
        results['lines'] = analyzers.robot_to_target(lines, dutinfo)
        results['missing_lines'] = missing_lines

        try:
            results['slowest_reporting_rate'] = numpy.min([f for f in results['min_reporting_rates'] if f is not None])
            results['verdict'] = "Pass" if results['slowest_reporting_rate'] > settings['minreportingrate'] and results['missing_lines'] == 0 else "Fail"
        except ValueError:
            results['slowest_reporting_rate'] = None
            results['verdict'] = "Fail"
        try:
            results['fastest_reporting_rate'] = numpy.max([f for f in results['max_reporting_rates'] if f is not None])
        except ValueError:
            results['fastest_reporting_rate'] = None

        return results

    def read_swipe_info(self, swipe_id, dutinfo = None, dbsession = None):

        s = Timer(2)

        if dbsession is None:
            dbsession = get_database().session()
        if dutinfo is None:
            dutinfo = plotinfo.TestDUTInfo(testdut_id=self.dut['id'], dbsession=dbsession)

        swipe = dbsession.query(OneFingerNonStationaryReportingRateTest).filter(OneFingerNonStationaryReportingRateTest.id == swipe_id).\
                                                                           order_by(OneFingerNonStationaryReportingRateTest.id).\
                                                                           options(joinedload('one_finger_non_stationary_reporting_rate_results')).first()

        points = []
        pindex = 0
        passed = []
        failed = []
        delays = []
        max_delay = None
        previous_timestamp = 0.0
        #start = analyzers.robot_to_target((swipe.start_x, swipe.start_y), dutinfo)
        #end = analyzers.robot_to_target((swipe.end_x, swipe.end_y), dutinfo)
        #transform = analyzers.panel_to_target_transform(dutinfo) + analyzers.target_to_swipe_transform(start, end)

        if 'minreportingrate' in settings and settings['minreportingrate'] > 0.0:
            accept_delay = (1000.0 / float(settings['minreportingrate']))
        else:
            accept_delay = 0.0

        for result in swipe.one_finger_non_stationary_reporting_rate_results:
            #point = transform.transform(((result.panel_x, result.panel_y)))
            #points.append(point)
            if previous_timestamp == 0.0:
                previous_timestamp = result.time
                #passed.append((pindex, 0,0))
                #delays.append(None)
            else:
                delay = result.time - previous_timestamp
                if delay > 0.0:
                    delays.append(delay)
                    previous_timestamp = result.time

                    if max_delay is None or max_delay < delay:
                        max_delay = delay

                    if delay > accept_delay:
                        failed.append((pindex, delay))
                    else:
                        passed.append((pindex, delay))
                    pindex += 1

        results = {'passed': passed,
                   'failed': failed,
                    'max_allowed_delay': analyzers.round_dec(1.0/(float(settings['minreportingrate'])/1000.0)),
                   #'points': points,
                   'delays': delays,
                   'max_delay': max_delay
                   }

        return results