From c48a6555d3ea54051f0a102787460a38b2ed162c Mon Sep 17 00:00:00 2001 From: TeachMeTW Date: Tue, 5 Nov 2024 22:10:44 -0800 Subject: [PATCH] Dist Filter fixed dist name --- .../dwell_segmentation_dist_filter.py | 260 ++++++++++++------ 1 file changed, 178 insertions(+), 82 deletions(-) diff --git a/emission/analysis/intake/segmentation/trip_segmentation_methods/dwell_segmentation_dist_filter.py b/emission/analysis/intake/segmentation/trip_segmentation_methods/dwell_segmentation_dist_filter.py index ea53c9abb..2ffd6f058 100644 --- a/emission/analysis/intake/segmentation/trip_segmentation_methods/dwell_segmentation_dist_filter.py +++ b/emission/analysis/intake/segmentation/trip_segmentation_methods/dwell_segmentation_dist_filter.py @@ -12,6 +12,7 @@ import attrdict as ad import numpy as np import datetime as pydt +import time # Our imports import emission.analysis.point_features as pf @@ -20,6 +21,9 @@ import emission.analysis.intake.segmentation.restart_checking as eaisr import emission.analysis.intake.segmentation.trip_segmentation_methods.trip_end_detection_corner_cases as eaistc +import emission.storage.decorations.stats_queries as esds +import emission.core.timer as ect +import emission.core.wrapper.pipelinestate as ecwp class DwellSegmentationDistFilter(eaist.TripSegmentationMethod): def __init__(self, time_threshold, point_threshold, distance_threshold): @@ -46,9 +50,34 @@ def segment_into_trips(self, timeseries, time_query): data that they want from the sensor streams in order to determine the segmentation points. """ - self.filtered_points_df = timeseries.get_data_df("background/filtered_location", time_query) - self.filtered_points_df.loc[:,"valid"] = True - self.transition_df = timeseries.get_data_df("statemachine/transition", time_query) + with ect.Timer() as t_get_filtered_points: + self.filtered_points_df = timeseries.get_data_df("background/filtered_location", time_query) + user_id = self.filtered_points_df["user_id"].iloc[0] + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/get_filtered_points_df", + time.time(), + t_get_filtered_points.elapsed + ) + + with ect.Timer() as t_mark_valid: + self.filtered_points_df.loc[:, "valid"] = True + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/mark_valid", + time.time(), + t_mark_valid.elapsed + ) + + with ect.Timer() as t_get_transition_df: + self.transition_df = timeseries.get_data_df("statemachine/transition", time_query) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/get_transition_df", + time.time(), + t_get_transition_df.elapsed + ) + if len(self.transition_df) > 0: logging.debug("self.transition_df = %s" % self.transition_df[["fmt_time", "transition"]]) else: @@ -62,86 +91,153 @@ def segment_into_trips(self, timeseries, time_query): last_trip_end_point = None curr_trip_start_point = None just_ended = True - for idx, row in self.filtered_points_df.iterrows(): - currPoint = ad.AttrDict(row) - currPoint.update({"idx": idx}) - logging.debug("-" * 30 + str(currPoint.fmt_time) + "-" * 30) - if curr_trip_start_point is None: - logging.debug("Appending currPoint because the current start point is None") - # segmentation_points.append(currPoint) - - if just_ended: - if self.continue_just_ended(idx, currPoint, self.filtered_points_df): - # We have "processed" the currPoint by deciding to glom it - self.last_ts_processed = currPoint.metadata_write_ts - continue - # else: - # Here's where we deal with the start trip. At this point, the - # distance is greater than the filter. - sel_point = currPoint - logging.debug("Setting new trip start point %s with idx %s" % (sel_point, sel_point.idx)) - curr_trip_start_point = sel_point - just_ended = False - else: - # Using .loc here causes problems if we have filtered out some points and so the index is non-consecutive. - # Using .iloc just ends up including points after this one. - # So we reset_index upstream and use it here. - last10Points_df = self.filtered_points_df.iloc[max(idx-self.point_threshold, curr_trip_start_point.idx):idx+1] - lastPoint = self.find_last_valid_point(idx) - if self.has_trip_ended(lastPoint, currPoint, timeseries): - last_trip_end_point = lastPoint - logging.debug("Appending last_trip_end_point %s with index %s " % - (last_trip_end_point, idx-1)) - segmentation_points.append((curr_trip_start_point, last_trip_end_point)) - logging.info("Found trip end at %s" % last_trip_end_point.fmt_time) - # We have processed everything up to the trip end by marking it as a completed trip - self.last_ts_processed = currPoint.metadata_write_ts - just_ended = True - # Now, we have finished processing the previous point as a trip - # end or not. But we still need to process this point by seeing - # whether it should represent a new trip start, or a glom to the - # previous trip - if not self.continue_just_ended(idx, currPoint, self.filtered_points_df): - sel_point = currPoint - logging.debug("Setting new trip start point %s with idx %s" % (sel_point, sel_point.idx)) + + with ect.Timer() as t_loop: + for idx, row in self.filtered_points_df.iterrows(): + currPoint = ad.AttrDict(row) + currPoint.update({"idx": idx}) + logging.debug("-" * 30 + str(currPoint.fmt_time) + "-" * 30) + + if curr_trip_start_point is None: + logging.debug("Appending currPoint because the current start point is None") + # segmentation_points.append(currPoint) + + if just_ended: + with ect.Timer() as t_continue_just_ended: + continue_flag = self.continue_just_ended(idx, currPoint, self.filtered_points_df) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/continue_just_ended", + time.time(), + t_continue_just_ended.elapsed + ) + + if continue_flag: + # We have "processed" the currPoint by deciding to glom it + self.last_ts_processed = currPoint.metadata_write_ts + continue + # else: + sel_point = currPoint + logging.debug("Setting new trip start point %s with idx %s" % (sel_point, sel_point.idx)) + with ect.Timer() as t_set_start_point: curr_trip_start_point = sel_point - just_ended = False - - # Since we only end a trip when we start a new trip, this means that - # the last trip that was pushed is ignored. Consider the example of - # 2016-02-22 when I took kids to karate. We arrived shortly after 4pm, - # so during that remote push, a trip end was not detected. And we got - # back home shortly after 5pm, so the trip end was only detected on the - # phone at 6pm. At that time, the following points were pushed: - # ..., 2016-02-22T16:04:02, 2016-02-22T16:49:34, 2016-02-22T16:49:50, - # ..., 2016-02-22T16:57:04 - # Then, on the server, while iterating through the points, we detected - # a trip end at 16:04, and a new trip start at 16:49. But we did not - # detect the trip end at 16:57, because we didn't start a new point. - # This has two issues: - # - we won't see this trip until the next trip start, which may be on the next day - # - we won't see this trip at all, because when we run the pipeline the - # next time, we will only look at points from that time onwards. These - # points have been marked as "processed", so they won't even be considered. - - # There are multiple potential fixes: - # - we can mark only the completed trips as processed. This will solve (2) above, but not (1) - # - we can mark a trip end based on the fact that we only push data - # when a trip ends, so if we have data, it means that the trip has been - # detected as ended on the phone. - # This seems a bit fragile - what if we start pushing incomplete trip - # data for efficiency reasons? Therefore, we also check to see if there - # is a trip_end_detected in this timeframe after the last point. If so, - # then we end the trip at the last point that we have. - if not just_ended and len(self.transition_df) > 0: - stopped_moving_after_last = self.transition_df[(self.transition_df.ts > currPoint.ts) & (self.transition_df.transition == 2)] - logging.debug("stopped_moving_after_last = %s" % stopped_moving_after_last[["fmt_time", "transition"]]) - if len(stopped_moving_after_last) > 0: - logging.debug("Found %d transitions after last point, ending trip..." % len(stopped_moving_after_last)) - segmentation_points.append((curr_trip_start_point, currPoint)) - self.last_ts_processed = currPoint.metadata_write_ts - else: - logging.debug("Found %d transitions after last point, not ending trip..." % len(stopped_moving_after_last)) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/set_new_trip_start_point", + time.time(), + t_set_start_point.elapsed + ) + just_ended = False + else: + with ect.Timer() as t_process_trip: + # Using .loc here causes problems if we have filtered out some points and so the index is non-consecutive. + # Using .iloc just ends up including points after this one. + # So we reset_index upstream and use it here. + last10Points_df = self.filtered_points_df.iloc[ + max(idx - self.point_threshold, curr_trip_start_point.idx):idx + 1 + ] + lastPoint = self.find_last_valid_point(idx) + with ect.Timer() as t_has_trip_ended: + trip_ended = self.has_trip_ended(lastPoint, currPoint, timeseries) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/has_trip_ended", + time.time(), + t_has_trip_ended.elapsed + ) + + if trip_ended: + with ect.Timer() as t_get_last_trip_end_point: + last_trip_end_point = lastPoint + logging.debug("Appending last_trip_end_point %s with index %s " % + (last_trip_end_point, idx - 1)) + segmentation_points.append((curr_trip_start_point, last_trip_end_point)) + logging.info("Found trip end at %s" % last_trip_end_point.fmt_time) + # We have processed everything up to the trip end by marking it as a completed trip + self.last_ts_processed = currPoint.metadata_write_ts + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/get_last_trip_end_point", + time.time(), + t_get_last_trip_end_point.elapsed + ) + + with ect.Timer() as t_handle_trip_end: + just_ended = True + # Now, we have finished processing the previous point as a trip + # end or not. But we still need to process this point by seeing + # whether it should represent a new trip start, or a glom to the + # previous trip + if not self.continue_just_ended(idx, currPoint, self.filtered_points_df): + sel_point = currPoint + logging.debug("Setting new trip start point %s with idx %s" % (sel_point, sel_point.idx)) + curr_trip_start_point = sel_point + just_ended = False + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/handle_trip_end", + time.time(), + t_handle_trip_end.elapsed + ) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/loop", + time.time(), + t_loop.elapsed + ) + + with ect.Timer() as t_post_loop: + # Since we only end a trip when we start a new trip, this means that + # the last trip that was pushed is ignored. Consider the example of + # 2016-02-22 when I took kids to karate. We arrived shortly after 4pm, + # so during that remote push, a trip end was not detected. And we got + # back home shortly after 5pm, so the trip end was only detected on the + # phone at 6pm. At that time, the following points were pushed: + # ..., 2016-02-22T16:04:02, 2016-02-22T16:49:34, 2016-02-22T16:49:50, + # ..., 2016-02-22T16:57:04 + # Then, on the server, while iterating through the points, we detected + # a trip end at 16:04, and a new trip start at 16:49. But we did not + # detect the trip end at 16:57, because we didn't start a new point. + # This has two issues: + # - we won't see this trip until the next trip start, which may be on the next day + # - we won't see this trip at all, because when we run the pipeline the + # next time, we will only look at points from that time onwards. These + # points have been marked as "processed", so they won't even be considered. + + # There are multiple potential fixes: + # - we can mark only the completed trips as processed. This will solve (2) above, but not (1) + # - we can mark a trip end based on the fact that we only push data + # when a trip ends, so if we have data, it means that the trip has been + # detected as ended on the phone. + # This seems a bit fragile - what if we start pushing incomplete trip + # data for efficiency reasons? Therefore, we also check to see if there + # is a trip_end_detected in this timeframe after the last point. If so, + # then we end the trip at the last point that we have. + if not just_ended and len(self.transition_df) > 0: + with ect.Timer() as t_check_transitions: + stopped_moving_after_last = self.transition_df[ + (self.transition_df.ts > currPoint.ts) & (self.transition_df.transition == 2) + ] + logging.debug("stopped_moving_after_last = %s" % stopped_moving_after_last[["fmt_time", "transition"]]) + if len(stopped_moving_after_last) > 0: + logging.debug("Found %d transitions after last point, ending trip..." % len(stopped_moving_after_last)) + segmentation_points.append((curr_trip_start_point, currPoint)) + self.last_ts_processed = currPoint.metadata_write_ts + else: + logging.debug("Found %d transitions after last point, not ending trip..." % len(stopped_moving_after_last)) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/check_transitions_post_loop", + time.time(), + t_check_transitions.elapsed + ) + esds.store_pipeline_time( + user_id, + ecwp.PipelineStages.TRIP_SEGMENTATION.name + "/segment_into_trips_dist/post_loop", + time.time(), + t_post_loop.elapsed + ) + return segmentation_points def has_trip_ended(self, lastPoint, currPoint, timeseries):