+ Нет данных. Выберите спутник и диапазон дат, затем нажмите 'Загрузить данные'.
+
+
-
-
+
+
-
-
Все точки, участвующие в усреднении 0
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Детали группы
-
-
-
-
-
-
- Усреднённый результат
-
-
-
-
- Усреднённые координаты:
-
-
-
- Всего точек:
-
-
-
- Валидных:
-
-
-
- Выбросов:
-
-
-
-
-
-
-
-
+
Сводная таблица усреднённых групп 0
+
@@ -265,105 +235,427 @@
{% endblock %}
diff --git a/dbapp/mainapp/views/points_averaging.py b/dbapp/mainapp/views/points_averaging.py
index bfea7a3..9363251 100644
--- a/dbapp/mainapp/views/points_averaging.py
+++ b/dbapp/mainapp/views/points_averaging.py
@@ -1,5 +1,6 @@
"""
Points averaging view for satellite data grouping by day/night intervals.
+Groups points by Source, then by time intervals within each Source.
"""
from datetime import datetime, timedelta
from django.contrib.auth.mixins import LoginRequiredMixin
@@ -8,7 +9,7 @@ from django.shortcuts import render
from django.views import View
from django.utils import timezone
-from ..models import ObjItem, Satellite
+from ..models import ObjItem, Satellite, Source
from ..utils import (
calculate_mean_coords,
calculate_distance_wgs84,
@@ -29,8 +30,9 @@ class PointsAveragingView(LoginRequiredMixin, View):
"""
def get(self, request):
- # Get satellites that have points with geo data
+ # Get satellites that have sources with points with geo data
satellites = Satellite.objects.filter(
+ parameters__objitem__source__isnull=False,
parameters__objitem__geo_obj__coords__isnull=False
).distinct().order_by('name')
@@ -44,13 +46,14 @@ class PointsAveragingView(LoginRequiredMixin, View):
class PointsAveragingAPIView(LoginRequiredMixin, View):
"""
- API endpoint for grouping and averaging points by day/night intervals.
+ API endpoint for grouping and averaging points by Source and day/night intervals.
Groups points into:
- Day: 08:00 - 19:00
- Night: 19:00 - 08:00 (next day)
+ - Weekend: Friday 19:00 - Monday 08:00
- For each group, calculates average coordinates and checks for outliers (>56 km).
+ For each group within each Source, calculates average coordinates and checks for outliers (>56 km).
"""
def get(self, request):
@@ -76,9 +79,50 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
except ValueError:
return JsonResponse({'error': 'Неверный формат даты'}, status=400)
- # Get all points for the satellite in the date range
- objitems = ObjItem.objects.filter(
- parameter_obj__id_satellite=satellite,
+ # Get all Sources for the satellite that have points in the date range
+ sources = Source.objects.filter(
+ source_objitems__parameter_obj__id_satellite=satellite,
+ source_objitems__geo_obj__coords__isnull=False,
+ source_objitems__geo_obj__timestamp__gte=date_from_obj,
+ source_objitems__geo_obj__timestamp__lt=date_to_obj,
+ ).distinct().prefetch_related(
+ 'source_objitems',
+ 'source_objitems__geo_obj',
+ 'source_objitems__geo_obj__mirrors',
+ 'source_objitems__parameter_obj',
+ 'source_objitems__parameter_obj__polarization',
+ 'source_objitems__parameter_obj__modulation',
+ 'source_objitems__parameter_obj__standard',
+ )
+
+ if not sources.exists():
+ return JsonResponse({'error': 'Источники не найдены в указанном диапазоне'}, status=404)
+
+ # Process each source
+ result_sources = []
+ for source in sources:
+ source_data = self._process_source(source, date_from_obj, date_to_obj)
+ if source_data['groups']: # Only add if has groups with points
+ result_sources.append(source_data)
+
+ if not result_sources:
+ return JsonResponse({'error': 'Точки не найдены в указанном диапазоне'}, status=404)
+
+ return JsonResponse({
+ 'success': True,
+ 'satellite': satellite.name,
+ 'date_from': date_from,
+ 'date_to': date_to,
+ 'sources': result_sources,
+ 'total_sources': len(result_sources),
+ })
+
+ def _process_source(self, source, date_from_obj, date_to_obj):
+ """
+ Process a single Source: get its points and group them by time intervals.
+ """
+ # Get all points for this source in the date range
+ objitems = source.source_objitems.filter(
geo_obj__coords__isnull=False,
geo_obj__timestamp__gte=date_from_obj,
geo_obj__timestamp__lt=date_to_obj,
@@ -89,16 +133,12 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
'parameter_obj__modulation',
'parameter_obj__standard',
'geo_obj',
- 'source',
).prefetch_related(
'geo_obj__mirrors'
).order_by('geo_obj__timestamp')
- if not objitems.exists():
- return JsonResponse({'error': 'Точки не найдены в указанном диапазоне'}, status=404)
-
- # Group points by source name and day/night intervals
- groups = self._group_points_by_intervals(objitems)
+ # Group points by day/night intervals
+ groups = self._group_points_by_intervals(list(objitems))
# Process each group: calculate average and check for outliers
result_groups = []
@@ -106,21 +146,27 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
group_result = self._process_group(group_key, points)
result_groups.append(group_result)
- return JsonResponse({
- 'success': True,
- 'satellite': satellite.name,
- 'date_from': date_from,
- 'date_to': date_to,
+ # Get source name from first point or use ID
+ source_name = f"Источник #{source.id}"
+ if objitems.exists():
+ first_point = objitems.first()
+ if first_point.name:
+ source_name = first_point.name
+
+ return {
+ 'source_id': source.id,
+ 'source_name': source_name,
+ 'total_points': sum(len(g['points']) for g in result_groups),
'groups': result_groups,
- 'total_groups': len(result_groups),
- })
+ }
def _group_points_by_intervals(self, objitems):
"""
- Group points by source name and day/night intervals.
+ Group points by day/night intervals.
Day: 08:00 - 19:00
Night: 19:00 - 08:00 (next day)
+ Weekend: Friday 19:00 - Monday 08:00
"""
groups = {}
@@ -129,19 +175,14 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
continue
timestamp = timezone.localtime(objitem.geo_obj.timestamp)
- # timestamp = objitem.geo_obj.timestamp
- source_name = objitem.name or f"Объект #{objitem.id}"
# Determine interval
interval_key = self._get_interval_key(timestamp)
- # Create group key: (source_name, interval_key)
- group_key = (source_name, interval_key)
+ if interval_key not in groups:
+ groups[interval_key] = []
- if group_key not in groups:
- groups[group_key] = []
-
- groups[group_key].append(objitem)
+ groups[interval_key].append(objitem)
return groups
@@ -208,7 +249,7 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
return date - timedelta(days=3)
return date
- def _process_group(self, group_key, points):
+ def _process_group(self, interval_key, points):
"""
Process a group of points: calculate average and check for outliers.
@@ -218,8 +259,6 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
3. Iteratively add points within 56 km of current average
4. Points not within 56 km of final average are outliers
"""
- source_name, interval_key = group_key
-
# Parse interval info
date_str, interval_type = interval_key.rsplit('_', 1)
interval_date = datetime.strptime(date_str, '%Y-%m-%d').date()
@@ -322,7 +361,7 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
# Calculate median time from valid points using timestamp_objects array
valid_timestamps = []
for i in valid_indices:
- if timestamp_objects[i]:
+ if i < len(timestamp_objects) and timestamp_objects[i]:
valid_timestamps.append(timestamp_objects[i])
median_time_str = '-'
@@ -344,7 +383,6 @@ class PointsAveragingAPIView(LoginRequiredMixin, View):
median_time_str = timezone.localtime(median_datetime).strftime("%d.%m.%Y %H:%M")
return {
- 'source_name': source_name,
'interval_key': interval_key,
'interval_label': interval_label,
'total_points': len(points_data),