1058 filtro por incerteza na predicao

backend/tno/migrations/0007_occultation_closest_approach_uncertainty_km.py

@@ -0,0 +1,24 @@
+# Generated by Django 3.2.18 on 2024-08-28 13:56
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ("tno", "0006_auto_20240822_1847"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="occultation",
+            name="closest_approach_uncertainty_km",
+            field=models.FloatField(
+                blank=True,
+                default=None,
+                help_text="Uncertainty in geocentric closest approach (km)",
+                null=True,
+                verbose_name="Closest approach uncertainty in km",
+            ),
+        ),
+    ]

backend/tno/models/occultation.py

@@ -414,6 +414,14 @@ class Occultation(models.Model):
         default=None,
         help_text="Indicates the probability that the event will happen at the indicated path",
     )
+
+    closest_approach_uncertainty_km = models.FloatField(
+        verbose_name="Closest approach uncertainty in km",
+        null=True,
+        blank=True,
+        default=None,
+        help_text="Uncertainty in geocentric closest approach (km)",
+    )
     # ------------------------------------------------------
     # Colunas que aparentemente não esto sendo preenchidas
     # ------------------------------------------------------

backend/tno/views/occultation.py

@@ -58,6 +58,10 @@ class OccultationFilter(django_filters.FilterSet):
 
     magnitude_drop = django_filters.RangeFilter(field_name="magnitude_drop")
 
+    closest_approach_uncertainty_km = django_filters.RangeFilter(
+        field_name="closest_approach_uncertainty_km"
+    )
+
     longitude = django_filters.NumberFilter(
         method="longitude_filter", label="Longitude"
     )
@@ -137,6 +141,7 @@ class Meta:
             "magnitude_drop",
             "diameter",
             "event_duration",
+            "closest_approach_uncertainty_km",
             "local_solar_time",
             "nightside",
             "jobid",

frontend/src/components/ClosestApproachUncertaintyField/index.js

@@ -0,0 +1,36 @@
+import PropTypes from 'prop-types'
+import TextField from '@mui/material/TextField'
+
+function ClosestApproachUncertaintyField({ value, onChange }) {
+  const handleChange = (e) => {
+    let newValue = e.target.value
+
+    if (newValue === '') {
+      onChange(undefined)
+    }
+    if (newValue !== '') {
+      onChange(parseFloat(newValue))
+    }
+  }
+
+  return (
+    <TextField
+      type='number'
+      label='Uncertainty (km)'
+      variant='outlined'
+      value={value !== undefined ? parseFloat(value) : ''}
+      onChange={handleChange}
+      fullWidth
+    />
+  )
+}
+
+ClosestApproachUncertaintyField.defaultProps = {
+  value: undefined
+}
+ClosestApproachUncertaintyField.propTypes = {
+  value: PropTypes.number,
+  onChange: PropTypes.func.isRequired
+}
+
+export default ClosestApproachUncertaintyField

frontend/src/components/PredictionEventsFilter/index.js

@@ -17,6 +17,7 @@ import { PredictionEventsContext } from '../../contexts/PredictionContext'
 import SolarTimeFilter from '../SolarTimeFilter'
 import Divider from '@mui/material/Divider'
 import Button from '@mui/material/Button'
+import ClosestApproachUncertaintyField from '../ClosestApproachUncertaintyField/index'
 
 function PredictionEventsFilter() {
   const { queryOptions, setQueryOptions, clearFilter } = useContext(PredictionEventsContext)
@@ -156,7 +157,7 @@ function PredictionEventsFilter() {
           <Grid item xs={12}>
             <Divider />
           </Grid>
-          <Grid item xs={3} container>
+          <Grid item xs={12} md={6} lg={4}>
             <MaginitudeDropSelect
               value={queryOptions.filters.maginitudeDropMin}
               onChange={(newValue) => {
@@ -172,7 +173,7 @@ function PredictionEventsFilter() {
               }}
             />
           </Grid>
-          <Grid item xs={3} container>
+          <Grid item xs={12} md={6} lg={4}>
             <EventDurationField
               value={queryOptions.filters.eventDurationMin}
               onChange={(e) => {
@@ -188,7 +189,23 @@ function PredictionEventsFilter() {
               }}
             />
           </Grid>
-          <Grid item xs={6} container>
+          <Grid item xs={12} md={6} lg={4}>
+            <ClosestApproachUncertaintyField
+              value={queryOptions.filters.closestApproachUncertainty}
+              onChange={(value) => {
+                setQueryOptions((prev) => {
+                  return {
+                    ...prev,
+                    filters: {
+                      ...prev.filters,
+                      closestApproachUncertainty: value
+                    }
+                  }
+                })
+              }}
+            />
+          </Grid>
+          <Grid item xs={12} md={6} lg={8}>
             <ObjectDiameterFilter
               value={{
                 diameterMin: queryOptions.filters.diameterMin,

frontend/src/contexts/PredictionContext.js

@@ -28,6 +28,7 @@ export function PredictionEventsProvider({ children }) {
         maginitudeDropMin: undefined,
         diameterMin: undefined,
         diameterMax: undefined,
+        closestApproachUncertainty: undefined,
         eventDurationMin: undefined,
         geo: false,
         latitude: undefined,

frontend/src/pages/PredictionEvents/Detail.js

@@ -110,12 +110,10 @@ function PredictionEventDetail() {
       {
         title: 'Uncertainty in closest approach (1σ)',
         value: `${
-          occultation.closest_approach_uncertainty
-            ? (() => {
-                const ca_uncert =
-                  Math.tan((occultation.closest_approach_uncertainty * Math.PI) / (180 * 60 * 60)) * (occultation.delta * 149597870.7)
-                return ca_uncert < 1 ? `${(ca_uncert * 1000).toFixed(0)} (m)` : `${ca_uncert.toFixed(0)} (km)`
-              })()
+          occultation.closest_approach_uncertainty_km
+            ? occultation.closest_approach_uncertainty_km < 1
+              ? `${(occultation.closest_approach_uncertainty_km * 1000).toFixed(0)} (m)`
+              : `${occultation.closest_approach_uncertainty_km.toFixed(0)} (Km)`
             : null
         }`
       },

frontend/src/services/api/Occultation.js

@@ -160,6 +160,10 @@ const parsePredictEventsFilters = (params) => {
       newFilters.event_duration_min = filters.eventDurationMin
     }
 
+    if (filters.closestApproachUncertainty !== undefined && filters.closestApproachUncertainty !== '') {
+      newFilters.closest_approach_uncertainty_km_max = filters.closestApproachUncertainty
+    }
+
     // Filtro por Object Diameter Range min, max
     if (filters.diameterMin !== undefined && filters.diameterMin !== '') {
       newFilters.diameter_min = filters.diameterMin

predict_occultation/src/asteroid/asteroid.py

@@ -978,6 +978,7 @@ def register_occultations(self, start_period: str, end_period: str, jobid: int):
                     "moon_illuminated_fraction",
                     "probability_of_centrality",
                     "hash_id",
+                    "closest_approach_uncertainty_km",
                 ]
             )
 

predict_occultation/src/dao/occultation.py

@@ -68,7 +68,7 @@ def import_occultations(self, data):
         # )
 
         sql = (
-            f"COPY {self.tbl} (name, number, date_time, gaia_source_id, ra_star_candidate, dec_star_candidate, ra_target, dec_target, closest_approach, position_angle, velocity, delta, g, j_star, h, k_star, long, loc_t, off_ra, off_dec, proper_motion, ct, multiplicity_flag, e_ra, e_dec, pmra, pmdec, ra_star_deg, dec_star_deg, ra_target_deg, dec_target_deg, created_at, apparent_diameter, aphelion, apparent_magnitude, dec_star_to_date, dec_star_with_pm, dec_target_apparent, diameter, e_dec_target, e_ra_target, eccentricity, ephemeris_version, g_mag_vel_corrected, h_mag_vel_corrected, inclination, instant_uncertainty, magnitude_drop, perihelion, ra_star_to_date, ra_star_with_pm, ra_target_apparent, rp_mag_vel_corrected, semimajor_axis, have_path_coeff, occ_path_max_longitude, occ_path_min_longitude, occ_path_coeff, occ_path_is_nightside, occ_path_max_latitude, occ_path_min_latitude, base_dynclass, bsp_planetary, bsp_source, catalog, dynclass, job_id, leap_seconds, nima, obs_source, orb_ele_source, predict_step, albedo, albedo_err_max, albedo_err_min, alias, arg_perihelion, astorb_dynbaseclass, astorb_dynsubclass, density, density_err_max, density_err_min, diameter_err_max, diameter_err_min, epoch, last_obs_included, long_asc_node, mass, mass_err_max, mass_err_min, mean_anomaly, mean_daily_motion, mpc_critical_list, pha_flag, principal_designation, rms, g_star, h_star, event_duration, moon_separation, sun_elongation, closest_approach_uncertainty, moon_illuminated_fraction, probability_of_centrality, hash_id) "
+            f"COPY {self.tbl} (name, number, date_time, gaia_source_id, ra_star_candidate, dec_star_candidate, ra_target, dec_target, closest_approach, position_angle, velocity, delta, g, j_star, h, k_star, long, loc_t, off_ra, off_dec, proper_motion, ct, multiplicity_flag, e_ra, e_dec, pmra, pmdec, ra_star_deg, dec_star_deg, ra_target_deg, dec_target_deg, created_at, apparent_diameter, aphelion, apparent_magnitude, dec_star_to_date, dec_star_with_pm, dec_target_apparent, diameter, e_dec_target, e_ra_target, eccentricity, ephemeris_version, g_mag_vel_corrected, h_mag_vel_corrected, inclination, instant_uncertainty, magnitude_drop, perihelion, ra_star_to_date, ra_star_with_pm, ra_target_apparent, rp_mag_vel_corrected, semimajor_axis, have_path_coeff, occ_path_max_longitude, occ_path_min_longitude, occ_path_coeff, occ_path_is_nightside, occ_path_max_latitude, occ_path_min_latitude, base_dynclass, bsp_planetary, bsp_source, catalog, dynclass, job_id, leap_seconds, nima, obs_source, orb_ele_source, predict_step, albedo, albedo_err_max, albedo_err_min, alias, arg_perihelion, astorb_dynbaseclass, astorb_dynsubclass, density, density_err_max, density_err_min, diameter_err_max, diameter_err_min, epoch, last_obs_included, long_asc_node, mass, mass_err_max, mass_err_min, mean_anomaly, mean_daily_motion, mpc_critical_list, pha_flag, principal_designation, rms, g_star, h_star, event_duration, moon_separation, sun_elongation, closest_approach_uncertainty, moon_illuminated_fraction, probability_of_centrality, hash_id, closest_approach_uncertainty_km) "
             "FROM STDIN with (FORMAT CSV, DELIMITER '|', HEADER);"
         )
 

predict_occultation/src/predict_occultation/pipeline/occ_path_coeff.py

@@ -148,6 +148,7 @@ def run_occultation_path_coeff(
         df["event_duration"] = None
         df["instant_uncertainty"] = None
         df["closest_approach_uncertainty"] = None
+        df["closest_approach_uncertainty_km"] = None
         df["moon_separation"] = None
         df["sun_elongation"] = None
         df["moon_illuminated_fraction"] = None
@@ -177,6 +178,7 @@ def run_occultation_path_coeff(
                 "event_duration": None,
                 "instant_uncertainty": None,
                 "closest_approach_uncertainty": None,
+                "closest_approach_uncertainty_km": None,
                 "moon_separation": None,
                 "sun_elongation": None,
                 "moon_illuminated_fraction": None,
@@ -264,6 +266,7 @@ def run_occultation_path_coeff(
             # e calcula a incerteza no instante central
             e_ra_target, e_dec_target = None, None
             closest_approach_uncertainty = None
+            closest_approach_uncertainty_km = None
             instant_uncertainty = None
             if has_uncertainties:
                 datetime_object = dt.fromisoformat(row["date_time"])
@@ -292,6 +295,9 @@ def run_occultation_path_coeff(
                     e_dec_star=df_gaia_csv["dec_error"][star_index] / 1000,
                 )
 
+                closest_approach_uncertainty_km = np.tan(
+                    (closest_approach_uncertainty * np.pi) / (180 * 60 * 60)
+                ) * (row["delta"] * 149597870.7)
                 # instant_uncertainty = get_instant_uncertainty(row["position_angle"], row["delta"], row["velocity"],
                 #     e_ra_target, e_dec_target, e_ra_star=df_gaia_csv["ra_error"][star_index]/1000, e_dec_star=df_gaia_csv["dec_error"][star_index]/1000)
 
@@ -303,6 +309,7 @@ def run_occultation_path_coeff(
                     "event_duration": event_duration,
                     "instant_uncertainty": instant_uncertainty,
                     "closest_approach_uncertainty": closest_approach_uncertainty,
+                    "closest_approach_uncertainty_km": closest_approach_uncertainty_km,
                     "moon_separation": moon_separation,
                     "sun_elongation": sun_elongation,
                     "moon_illuminated_fraction": moon_illuminated_fraction,
@@ -373,6 +380,9 @@ def run_occultation_path_coeff(
             df["closest_approach_uncertainty"] = df_coeff[
                 "closest_approach_uncertainty"
             ]
+            df["closest_approach_uncertainty_km"] = df_coeff[
+                "closest_approach_uncertainty_km"
+            ]
             df["moon_separation"] = df_coeff["moon_separation"]
             df["sun_elongation"] = df_coeff["sun_elongation"]
             df["moon_illuminated_fraction"] = df_coeff["moon_illuminated_fraction"]
@@ -594,6 +604,7 @@ def run_occultation_path_coeff(
                 "moon_illuminated_fraction",
                 "probability_of_centrality",
                 "hash_id",
+                "closest_approach_uncertainty_km",
             ]
         )