Mag l1a processing

imap_processing/mag/l0/decom_mag.py

@@ -21,7 +21,7 @@
 logger = logging.getLogger(__name__)
 
 
-def decom_packets(packet_file_path: str | Path) -> list[MagL0]:
+def decom_packets(packet_file_path: str | Path) -> dict[str, list[MagL0]]:
     """Decom MAG data packets using MAG packet definition.
 
     Parameters
@@ -31,9 +31,9 @@ def decom_packets(packet_file_path: str | Path) -> list[MagL0]:
 
     Returns
     -------
-    data : list[MagL0]
-        A list of MAG L0 data classes, including both burst and normal packets. (the
-        packet type is defined in each instance of L0.)
+    data_dict : dict[str, list[MagL0]]
+        A dict with 2 keys pointing to lists of MAG L0 data classes. "norm" corresponds
+        to  normal mode packets, "burst" corresponds to burst mode packets.
     """
     # Define paths
     xtce_document = Path(
@@ -43,7 +43,8 @@ def decom_packets(packet_file_path: str | Path) -> list[MagL0]:
     packet_definition = xtcedef.XtcePacketDefinition(xtce_document)
     mag_parser = parser.PacketParser(packet_definition)
 
-    data_list = []
+    norm_data = []
+    burst_data = []
 
     with open(packet_file_path, "rb") as binary_data:
         mag_packets = mag_parser.generator(binary_data)
@@ -57,59 +58,17 @@ def decom_packets(packet_file_path: str | Path) -> list[MagL0]:
                     else item.raw_value
                     for item in packet.data.values()
                 ]
-                data_list.append(MagL0(CcsdsData(packet.header), *values))
-
-        return data_list
-
-
-def export_to_xarray(l0_data: list[MagL0]):
-    """Generate xarray files for "raw" MAG CDF files from MagL0 data.
-
-    Mag outputs "RAW" CDF files just after decomming. These have the immediately
-    post-decom data, with raw binary data for the vectors instead of vector values.
-
-    Parameters
-    ----------
-    l0_data: list[MagL0]
-        A list of MagL0 datapoints
-
-    Returns
-    -------
-    norm_data : xr.Dataset
-        xarray dataset for generating burst data CDFs
-    burst_data : xr.Dataset
-        xarray dataset for generating burst data CDFs
-    """
-    # TODO split by mago and magi using primary sensor
-    norm_data = []
-    burst_data = []
+                if apid == Mode.NORMAL:
+                    norm_data.append(MagL0(CcsdsData(packet.header), *values))
+                else:
+                    burst_data.append(MagL0(CcsdsData(packet.header), *values))
 
-    for packet in l0_data:
-        if packet.ccsds_header.PKT_APID == Mode.NORMAL:
-            norm_data.append(packet)
-        if packet.ccsds_header.PKT_APID == Mode.BURST:
-            burst_data.append(packet)
-
-    norm_dataset = None
-    burst_dataset = None
-
-    if len(norm_data) > 0:
-        norm_dataset = generate_dataset(
-            norm_data, mag_cdf_attrs.mag_l1a_norm_raw_attrs.output()
-        )
-    if len(burst_data) > 0:
-        burst_dataset = generate_dataset(
-            burst_data, mag_cdf_attrs.mag_l1a_burst_raw_attrs.output()
-        )
-
-    return norm_dataset, burst_dataset
+    return {"norm": norm_data, "burst": burst_data}
 
 
 def generate_dataset(l0_data: list[MagL0], dataset_attrs: dict) -> xr.Dataset:
     """
-    Generate a CDF dataset from the sorted L0 MAG data.
-
-    Used to create 2 similar datasets, for norm and burst data.
+    Generate a CDF dataset from the sorted raw L0 MAG data.
 
     Parameters
     ----------
@@ -124,6 +83,8 @@ def generate_dataset(l0_data: list[MagL0], dataset_attrs: dict) -> xr.Dataset:
     dataset : xr.Dataset
         xarray dataset with proper CDF attributes and shape.
     """
+    # TODO: Correct CDF attributes from email
+
     vector_data = np.zeros((len(l0_data), len(l0_data[0].VECTORS)))
     shcoarse_data = np.zeros(len(l0_data), dtype="datetime64[ns]")
 

imap_processing/mag/l0/mag_l0_data.py

@@ -1,8 +1,12 @@
 """Dataclasses for Level 0 MAG data."""
 
+from __future__ import annotations
+
 from dataclasses import dataclass
 from enum import IntEnum
 
+import numpy as np
+
 from imap_processing.ccsds.ccsds_data import CcsdsData
 
 
@@ -90,19 +94,24 @@ class MagL0:
     PRI_FNTM: int
     SEC_COARSETM: int
     SEC_FNTM: int
-    VECTORS: bytearray
+    VECTORS: np.ndarray | str
 
     def __post_init__(self):
         """Convert Vectors attribute from string to bytearray if needed.
 
         Also convert encoded "VECSEC" (vectors per second) into proper vectors per
         second values
         """
-        if isinstance(self.VECTORS, str):
-            # Convert string output from space_packet_parser to bytearray
-            self.VECTORS = bytearray(
-                int(self.VECTORS, 2).to_bytes(len(self.VECTORS) // 8, "big")
-            )
+        # Convert string output from space_packet_parser to numpy array of
+        # big-endian bytes
+        self.VECTORS = np.frombuffer(
+            int(self.VECTORS, 2).to_bytes(len(self.VECTORS) // 8, "big"),
+            dtype=np.dtype(">b"),
+        )
+
+        # Remove buffer from end of vectors
+        if len(self.VECTORS) % 2:
+            self.VECTORS = self.VECTORS[:-1]
 
         self.PRI_VECSEC = 2**self.PRI_VECSEC
         self.SEC_VECSEC = 2**self.SEC_VECSEC

imap_processing/mag/l1a/mag_l1a.py

@@ -3,7 +3,10 @@
 import logging
 
 from imap_processing.cdf.utils import write_cdf
+from imap_processing.mag import mag_cdf_attrs
 from imap_processing.mag.l0 import decom_mag
+from imap_processing.mag.l0.mag_l0_data import MagL0
+from imap_processing.mag.l1a.mag_l1a_data import MagL1a, TimeTuple
 
 logger = logging.getLogger(__name__)
 
@@ -17,14 +20,115 @@ def mag_l1a(packet_filepath):
     packet_filepath :
         Packet files for processing
     """
-    mag_l0 = decom_mag.decom_packets(packet_filepath)
+    packets = decom_mag.decom_packets(packet_filepath)
 
-    mag_norm, mag_burst = decom_mag.export_to_xarray(mag_l0)
+    norm_data = packets["norm"]
+    burst_data = packets["burst"]
 
-    if mag_norm is not None:
-        file = write_cdf(mag_norm)
-        logger.info(f"Created CDF file at {file}")
+    if norm_data is not None:
+        mag_norm_raw = decom_mag.generate_dataset(
+            norm_data, mag_cdf_attrs.mag_l1a_norm_raw_attrs.output()
+        )
+        file = write_cdf(mag_norm_raw)
+        logger.info(f"Created RAW CDF file at {file}")
 
-    if mag_burst is not None:
-        file = write_cdf(mag_burst)
-        logger.info(f"Created CDF file at {file}")
+    if burst_data is not None:
+        mag_burst_raw = decom_mag.generate_dataset(
+            burst_data, mag_cdf_attrs.mag_l1a_burst_raw_attrs.output()
+        )
+        file = write_cdf(mag_burst_raw)
+        logger.info(f"Created RAW CDF file at {file}")
+
+
+def process_packets(mag_l0_list: list[MagL0]) -> dict[str, list[MagL1a]]:
+    """
+    Given a list of MagL0 packets, process them into MagO and MagI L1A data classes.
+
+    Parameters
+    ----------
+    mag_l0_list : list[MagL0]
+        List of Mag L0 packets to process
+
+    Returns
+    -------
+    packet_dict: dict[str, list[MagL1a]]
+        Dictionary containing two keys: "mago" which points to a list of mago MagL1A
+        objects, and "magi" which points to a list of magi MagL1A objects.
+
+    """
+    magi = []
+    mago = []
+
+    for mag_l0 in mag_l0_list:
+        if mag_l0.COMPRESSION:
+            raise NotImplementedError("Unable to process compressed data")
+
+        primary_start_time = TimeTuple(mag_l0.PRI_COARSETM, mag_l0.PRI_FNTM)
+        secondary_start_time = TimeTuple(mag_l0.SEC_COARSETM, mag_l0.SEC_FNTM)
+
+        # seconds of data in this packet is the SUBTYPE plus 1
+        seconds_per_packet = mag_l0.PUS_SSUBTYPE + 1
+
+        # now we know the number of secs of data in the packet, and the data rates of
+        # each sensor, we can calculate how much data is in this packet and where the
+        # byte boundaries are.
+
+        # VECSEC is already decoded in mag_l0
+        total_primary_vectors = seconds_per_packet * mag_l0.PRI_VECSEC
+        total_secondary_vectors = seconds_per_packet * mag_l0.SEC_VECSEC
+
+        primary_vectors, secondary_vectors = MagL1a.process_vector_data(
+            mag_l0.VECTORS, total_primary_vectors, total_secondary_vectors
+        )
+
+        # Primary sensor is MAGO (most common expected case)
+        if mag_l0.PRI_SENS == 0:
+            mago_l1a = MagL1a(
+                True,
+                bool(mag_l0.MAGO_ACT),
+                primary_start_time,
+                mag_l0.PRI_VECSEC,
+                total_primary_vectors,
+                seconds_per_packet,
+                mag_l0.SHCOARSE,
+                primary_vectors,
+            )
+
+            magi_l1a = MagL1a(
+                False,
+                bool(mag_l0.MAGI_ACT),
+                secondary_start_time,
+                mag_l0.SEC_VECSEC,
+                total_secondary_vectors,
+                seconds_per_packet,
+                mag_l0.SHCOARSE,
+                secondary_vectors,
+            )
+        # Primary sensor is MAGI
+        else:
+            magi_l1a = MagL1a(
+                False,
+                bool(mag_l0.MAGI_ACT),
+                primary_start_time,
+                mag_l0.PRI_VECSEC,
+                total_primary_vectors,
+                seconds_per_packet,
+                mag_l0.SHCOARSE,
+                primary_vectors,
+            )
+
+            mago_l1a = MagL1a(
+                True,
+                bool(mag_l0.MAGO_ACT),
+                secondary_start_time,
+                mag_l0.SEC_VECSEC,
+                total_secondary_vectors,
+                seconds_per_packet,
+                mag_l0.SHCOARSE,
+                secondary_vectors,
+            )
+
+        mago.append(mago_l1a)
+        magi.append(magi_l1a)
+
+    return {"mago": mago, "magi": magi}