Added wave processing from RBSP data

el_paso/processing/__init__.py

@@ -3,15 +3,24 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-from el_paso.processing import magnetic_field_utils
 from el_paso.processing.bin_by_time import TimeBinMethod, bin_by_time
-from el_paso.processing.compute_equatorial_plasmaspheric_density import compute_equatorial_plasmaspheric_density
+from el_paso.processing.compute_equatorial_plasmaspheric_density import (
+    compute_equatorial_plasmaspheric_density,
+)
 from el_paso.processing.compute_invariant_K import compute_invariant_K
 from el_paso.processing.compute_invariant_mu import compute_invariant_mu
-from el_paso.processing.compute_magnetic_field_variables import VariableRequest, compute_magnetic_field_variables
+from el_paso.processing.compute_magnetic_field_variables import (
+    VariableRequest,
+    compute_magnetic_field_variables,
+)
 from el_paso.processing.compute_phase_space_density import compute_phase_space_density
-from el_paso.processing.construct_pitch_angle_distribution import construct_pitch_angle_distribution
+from el_paso.processing.construct_pitch_angle_distribution import (
+    construct_pitch_angle_distribution,
+)
 from el_paso.processing.convert_string_to_datetime import convert_string_to_datetime
+from el_paso.processing.create_quality_flag_from_magnetometer import (
+    magnetometer_quality_flags,
+)
 from el_paso.processing.fold_pitch_angles_and_flux import fold_pitch_angles_and_flux
 from el_paso.processing.get_real_time_tipsod import get_real_time_tipsod
 from el_paso.processing.magnetic_field_utils import MagFieldVarTypes
@@ -32,5 +41,5 @@
     "convert_string_to_datetime",
     "fold_pitch_angles_and_flux",
     "get_real_time_tipsod",
-    "magnetic_field_utils",
+    "magnetometer_quality_flags",
 ]

el_paso/processing/create_quality_flag_from_magnetometer.py

@@ -0,0 +1,44 @@
+# SPDX-FileCopyrightText: 2026 GFZ Helmholtz Centre for Geosciences
+# SPDX-FileContributor: Alwin Roy
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+from astropy import units as u
+
+import el_paso as ep
+
+
+def magnetometer_quality_flags(variables: dict, threshold: int = 500) -> np.ndarray:
+    """Compute a quality mask for magnetometer data using Bt.
+
+    The mask flags samples that are considered valid based on two criteria:
+    1. Magnetic field magnitude (Bt) must be positive.
+    2. Consecutive differences |ΔBt| must be below the spike threshold.
+
+    Args:
+        variables (dict): Dictionary containing variable objects. Must include
+            the key "Bt". Each variable must implement ``get_data()``.
+        threshold(int, optional): Spike detection threshold in nT.
+            Defaults to 500.
+
+    Returns:
+        np.ndarray: Boolean array where ``True`` indicates valid data and
+        ``False`` indicates flagged samples.
+    """
+    bt_var = variables["Bt"]
+    bt = bt_var.get_data(u.nT)
+
+    mask_positive = bt > 0
+
+    delta_b = np.diff(bt, prepend=bt[0])
+    mask_spike = np.abs(delta_b) < threshold
+
+    mask = mask_positive & mask_spike
+
+    mask = ep.Variable(
+        data=mask_positive & mask_spike,
+        original_unit=u.dimensionless_unscaled,
+    )
+
+    return mask

scripts/inspect_cdf_file.py

@@ -34,6 +34,9 @@ def inspect_cdf_file(file_path: str) -> None:
     for var in variable_names:
         var_attrs_full = cdf_file.varattsget(var)
         vdr_info = cdf_file.varinq(var)
+        if vdr_info.Last_Rec < 0:
+            print(f"{var}: no records")
+            continue
         var_data = cdf_file.varget(var)
 
         var_shape = var_data.shape  # type: ignore[reportAttributeAccessIssue]

tutorials/2_variable_class.ipynb

@@ -16,32 +16,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "941c7d1f",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[91mLogger not instantiated.\u001b[0m\n",
-      "\u001b[91mBasic logger can be instantiated using `logging.basicConfig(level=logging.INFO)`\u001b[0m\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "{'Epoch': Variable holding (1000,) data points with metadata: VariableMetadata(unit=Unit(dimensionless), original_cadence_seconds=0, source_files=['example_orbit.csv'], description='', processing_notes='', standard_name=''),\n",
-       " 'alt': Variable holding (1000,) data points with metadata: VariableMetadata(unit=Unit(\"km\"), original_cadence_seconds=0, source_files=['example_orbit.csv'], description='', processing_notes='', standard_name=''),\n",
-       " 'lon': Variable holding (1000,) data points with metadata: VariableMetadata(unit=Unit(\"km\"), original_cadence_seconds=0, source_files=['example_orbit.csv'], description='', processing_notes='', standard_name=''),\n",
-       " 'lat': Variable holding (1000,) data points with metadata: VariableMetadata(unit=Unit(\"km\"), original_cadence_seconds=0, source_files=['example_orbit.csv'], description='', processing_notes='', standard_name='')}"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from datetime import datetime, timezone\n",
     "\n",
@@ -97,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "5ba56b19",
    "metadata": {},
    "outputs": [],
@@ -115,7 +93,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "fdef5a25",
    "metadata": {},
    "outputs": [],
@@ -136,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "a762b8f5",
    "metadata": {},
    "outputs": [],
@@ -166,7 +144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "929bab50",
    "metadata": {},
    "outputs": [],
@@ -222,18 +200,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "fb2b1708",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[datetime.datetime(2017, 7, 30, 0, 0, 11, 507000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 0, 34, 203000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 0, 56, 899000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 1, 19, 596000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 1, 30, 945000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 1, 42, 293000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 2, 4, 990000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 2, 27, 685000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 2, 39, 34000, tzinfo=datetime.timezone.utc), datetime.datetime(2017, 7, 30, 0, 2, 50, 382000, tzinfo=datetime.timezone.utc)]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "variables[\"Epoch\"].convert_to_unit(ep.units.posixtime)\n",
     "times = [datetime.fromtimestamp(timestamp, timezone.utc) for timestamp in variables[\"Epoch\"].get_data()]\n",
@@ -250,23 +220,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "25916994",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Energies in eV: [14.98455  16.81365  18.8538   21.17535  23.707949 26.592299 29.828398\n",
-      " 33.486603 37.566902 42.13965 ]\n",
-      "Energies in MeV using get_data: [1.4984550e-05 1.6813650e-05 1.8853800e-05 2.1175350e-05 2.3707949e-05\n",
-      " 2.6592299e-05 2.9828398e-05 3.3486602e-05 3.7566901e-05 4.2139647e-05]\n",
-      "Energies in MeV after converting: [1.4984550e-05 1.6813650e-05 1.8853800e-05 2.1175350e-05 2.3707949e-05\n",
-      " 2.6592299e-05 2.9828398e-05 3.3486602e-05 3.7566901e-05 4.2139647e-05]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"Energies in eV:\", variables[\"Energy_FEDU\"].get_data()[0, 0:10])\n",
     "print(\"Energies in MeV using get_data:\", variables[\"Energy_FEDU\"].get_data(\"MeV\")[0, 0:10])\n",
@@ -285,22 +242,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "1ec55e23",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[2.99691001e-05 3.36273006e-05 3.77075994e-05 4.23507008e-05\n",
-      " 4.74158987e-05 5.31845981e-05 5.96567952e-05 6.69732035e-05\n",
-      " 7.51338011e-05 8.42792942e-05]\n",
-      "[0.01498455 0.01681365 0.0188538  0.02117535 0.02370795 0.0265923\n",
-      " 0.0298284  0.0334866  0.0375669  0.04213965]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "old_data = variables[\"Energy_FEDU\"].get_data().astype(np.float64)\n",
     "\n",
@@ -316,7 +261,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "verb4d",
+   "display_name": "venv",
    "language": "python",
    "name": "python3"
   },
@@ -330,7 +275,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.13"
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,