utils.py

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#general imports
import sys
 
#dunedaq imports
import daqdataformats
import detdataformats
import fddetdataformats
import trgdataformats
import detchannelmaps
 
#unpacker imports
from rawdatautils.unpack.dataclasses import *
import rawdatautils.unpack.wibeth
import rawdatautils.unpack.daphne
import h5py
 
#analysis imports
import numpy as np
import numpy.fft
 
class NullChannelMap:
 
    def get_offline_channel_from_det_crate_slot_stream_chan(det, crate, slot, stream, ch):
        return (ch + (stream << 10 ) + (slot << 18 ) + (crate << 22))
    def get_plane_from_offline_channel(ch):
        return -1
    def get_element_id_from_offline_channel(ch):
        return 0xffff
    def get_element_name_from_offline_channel(ch):
        return "Null"
 
class Unpacker:
 
    is_fragment_unpacker = False
 
    is_detector_unpacker = False
    is_trigger_unpacker = False
    
    def __init__(self, index=None):
        self.index = index
 
    def get_all_data(self,in_data=None):
        return None
 
class SourceIDUnpacker(Unpacker):
 
    is_fragment_unpacker = False
 
    is_detector_unpacker = False
    is_trigger_unpacker = False
 
    def get_srcid_data(self,sid):
        return [ SourceIDData(run=self.index.run,
                              trigger=self.index.trigger,
                              sequence=self.index.sequence,
                              src_id=sid.id,
                              subsystem=sid.subsystem,
                              subsystem_str=daqdataformats.SourceID.subsystem_to_string(sid.subsystem),
                              version=sid.version) ]
 
    def get_all_data(self,in_data):
        #in_data = sid
        return { "sid": self.get_srcid_data(in_data) }
 
class TriggerRecordHeaderUnpacker(Unpacker):
 
    is_fragment_unpacker = False
    
    def get_trh_data(self,trh,n_fragments):
        return [ TriggerRecordData(run=trh.get_run_number(),
                                         trigger=trh.get_trigger_number(),
                                         sequence=trh.get_sequence_number(),
                                         trigger_timestamp_dts=trh.get_trigger_timestamp(),
                                         n_fragments=n_fragments,
                                         n_requested_components=trh.get_num_requested_components(),
                                         error_bits=trh.get_header().error_bits,
                                         trigger_type=trh.get_trigger_type(),
                                         max_sequence_number=trh.get_max_sequence_number(),
                                         total_size_bytes=trh.get_total_size_bytes()) ]
 
    def get_all_data(self,in_data):
        #in_data[0]=trh
        #in_data[1]=n_fragments
        return { "trh": self.get_trh_data(in_data[0],in_data[1]) }
    
class FragmentUnpacker(Unpacker):
 
    is_fragment_unpacker = True
    
    is_detector_unpacker = False
    is_trigger_unpacker = False
 
    def get_n_obj(self,frag):
        return None
 
    def get_trg_data(self,in_data):
        return None, None
 
    def get_det_data(self,in_data):
        return None, None, None, None
 
    def get_frh_data(self,frag):
        frh = frag.get_header()
        return [ FragmentHeaderData(run=frh.run_number,
                                    trigger=frh.trigger_number,
                                    sequence=frh.sequence_number,
                                    src_id=frh.element_id.id,
                                    trigger_timestamp_dts=frh.trigger_timestamp,
                                    window_begin_dts=frh.window_begin,
                                    window_end_dts=frh.window_end,
                                    det_id=frh.detector_id,
                                    error_bits=frh.error_bits,
                                    fragment_type=frh.fragment_type,
                                    total_size_bytes=frh.size,
                                    data_size_bytes=frag.get_data_size()) ]
 
    def get_all_data(self,in_data):
        #in_data = fragment
        
        data_dict = { "frh": self.get_frh_data(in_data) }
 
        #if no data, nothing to unpack further
        if in_data.get_data_size()==0:
            return data_dict
        
        type_string = f'{detdataformats.DetID.Subdetector(in_data.get_detector_id()).name}_{in_data.get_fragment_type().name}'
 
        if(self.is_trigger_unpackeris_trigger_unpacker):
            trgh, trgd = self.get_trg_data(in_data)
            if trgh is not None: data_dict[f"trgh_{type_string}"] = trgh
            if trgd[0] is not None: data_dict[f"trgd_{type_string}"] = trgd[0]
            if trgd[1] is not None: data_dict[f"trgd_{type_string}_inputs"] = trgd[1]
 
        if(self.is_detector_unpackeris_detector_unpacker):
            daqh, deth, detd, detw = self.get_det_data(in_data)
            if daqh is not None: data_dict["daqh"] = daqh
            if deth is not None: data_dict[f"deth_{type_string}"] = deth
            if detd is not None: data_dict[f"detd_{type_string}"] = detd
            if detw is not None: data_dict[f"detw_{type_string}"] = detw
 
        return data_dict
 
class TriggerDataUnpacker(FragmentUnpacker):
    
    is_trigger_unpacker = True
 
    def get_trg_data(self,frag):
        return self.get_trg_header_data(frag),self.get_trg_obj_data(frag)
 
    def get_trg_header_data(self,frag):
        frh = frag.get_header()
        return [ TriggerHeaderData(run=frh.run_number,
                                   trigger=frh.trigger_number,
                                   sequence=frh.sequence_number,
                                   src_id=frh.element_id.id,
                                   n_obj=self.get_n_obj(frag),
                                   version=self.get_trg_data_version(frag)) ]
 
 
class TriggerPrimitiveUnpacker(TriggerDataUnpacker):
 
    trg_obj = trgdataformats.TriggerPrimitive
 
    def __init__(self,channel_map=None):
        super().__init__()
        if 'TPC' in channel_map:
            self.channel_map = detchannelmaps.make_tpc_map(channel_map)
        elif 'PDS' in channel_map:
            self.channel_map = detchannelmaps.make_pds_map(channel_map)
        else:
            self.channel_map = NullChannelMap
 
    def get_n_obj(self,frag):
        return int(frag.get_data_size()/self.trg_obj.sizeof())
 
    def get_trg_data_version(self,frag):
        if self.get_n_objget_n_obj(frag)==0:
            return None
        trig_obj = self.trg_obj(frag.get_data())
        return trig_obj.version
 
    def get_trg_obj_data(self,frag):
        frh = frag.get_header()
        tpd_list = []
        for i_tp in range(self.get_n_objget_n_obj(frag)):
            tp = self.trg_obj(frag.get_data(i_tp*self.trg_obj.sizeof()))
            ch_info = self.channel_map.get_channel_info_from_offline_channel(tp.channel)
            tpd_list.append( TriggerPrimitiveData(run=frh.run_number,
                                                  trigger=frh.trigger_number,
                                                  sequence=frh.sequence_number,
                                                  src_id=frh.element_id.id,
                                                  time_start=tp.time_start,
                                                  samples_to_peak=tp.samples_to_peak,
                                                  samples_over_threshold=tp.samples_over_threshold,
                                                  channel=tp.channel,
                                                  plane=self.channel_map.get_plane_from_offline_channel(tp.channel),
                                                  element=ch_info.element,
                                                  adc_integral=tp.adc_integral,
                                                  adc_peak=tp.adc_peak,
                                                  detid=tp.detid,
                                                  flag=tp.flag,
                                                  id_ta=-1) )
        return tpd_list, None
 
class TriggerActivityUnpacker(TriggerDataUnpacker):
 
    trg_obj = trgdataformats.TriggerActivity
 
    def __init__(self,channel_map=None):
        super().__init__()
        if 'TPC' in channel_map:
            self.channel_map = detchannelmaps.make_tpc_map(channel_map)
        elif 'PDS' in channel_map:
            self.channel_map = detchannelmaps.make_pds_map(channel_map)
        else:
            self.channel_map = NullChannelMap
 
    def get_n_obj(self,frag):
        frag_data_size = frag.get_data_size()
        size_so_far = 0
        n_tobjs = 0
        while size_so_far < frag_data_size:
            tobj = self.trg_obj(frag.get_data(size_so_far))
            n_tobjs = n_tobjs + 1
            size_so_far = size_so_far + tobj.sizeof()
        return n_tobjs
 
    def get_trg_data_version(self,frag):
        if self.get_n_objget_n_obj(frag)==0:
            return None
        trig_obj = self.trg_obj(frag.get_data())
        return trig_obj.data.version
 
    def get_trg_obj_data(self,frag):
        frh = frag.get_header()
        ta_list = []
        tpd_list = []
        size_so_far = 0
        for i_ta in range(self.get_n_objget_n_obj(frag)):
            ta= self.trg_obj(frag.get_data(size_so_far))
            size_so_far = size_so_far + ta.sizeof()
            ch_info_ta = self.channel_map.get_channel_info_from_offline_channel(ta.data.channel_peak)
            ta_list.append( TriggerActivityData(run=frh.run_number,
                                                trigger=frh.trigger_number,
                                                sequence=frh.sequence_number,
                                                src_id=frh.element_id.id,
                                                id=i_ta,
                                                time_start=ta.data.time_start,
                                                time_end=ta.data.time_end,
                                                time_peak=ta.data.time_peak,
                                                time_activity=ta.data.time_activity,
                                                channel_start=ta.data.channel_start,
                                                channel_end=ta.data.channel_end,
                                                channel_peak=ta.data.channel_peak,
                                                plane=self.channel_map.get_plane_from_offline_channel(ta.data.channel_peak),
                                                element=ch_info_ta.element,
                                                adc_integral=ta.data.adc_integral,
                                                adc_peak=ta.data.adc_peak,
                                                detid=ta.data.detid,
                                                ta_type=ta.data.type,
                                                algorithm=ta.data.algorithm,
                                                n_tps=len(ta),
                                                id_tc=-1) )
            for i_tp in range(len(ta)):
                tp = ta[i_tp]
                ch_info_tp = self.channel_map.get_channel_info_from_offline_channel(tp.channel)
                tpd_list.append( TriggerPrimitiveData(run=frh.run_number,
                                                      trigger=frh.trigger_number,
                                                      sequence=frh.sequence_number,
                                                      src_id=frh.element_id.id,
                                                      time_start=tp.time_start,
                                                      samples_to_peak=tp.samples_to_peak,
                                                      samples_over_threshold=tp.samples_over_threshold,
                                                      channel=tp.channel,
                                                      plane=self.channel_map.get_plane_from_offline_channel(tp.channel),
                                                      element=ch_info_tp.element,
                                                      adc_integral=tp.adc_integral,
                                                      adc_peak=tp.adc_peak,
                                                      detid=tp.detid,
                                                      flag=tp.flag,
                                                      id_ta=i_ta) )
        
        if len(tpd_list)==0:
            tpd_list=None
        return ta_list, tpd_list
 
class TriggerCandidateUnpacker(TriggerDataUnpacker):
 
    trg_obj = trgdataformats.TriggerCandidate
 
    def __init__(self,channel_map=None):
        super().__init__()
        if 'TPC' in channel_map:
            self.channel_map = detchannelmaps.make_tpc_map(channel_map)
        elif 'PDS' in channel_map:
            self.channel_map = detchannelmaps.make_pds_map(channel_map)
        else:
            self.channel_map = NullChannelMap
 
    def get_n_obj(self,frag):
        frag_data_size = frag.get_data_size()
        size_so_far = 0
        n_tobjs = 0
        while size_so_far < frag_data_size:
            tobj = self.trg_obj(frag.get_data(size_so_far))
            n_tobjs = n_tobjs + 1
            size_so_far = size_so_far + tobj.sizeof()
        return n_tobjs
 
    def get_trg_data_version(self,frag):
        if self.get_n_objget_n_obj(frag)==0:
            return None
        trig_obj = self.trg_obj(frag.get_data())
        return trig_obj.data.version
 
    def get_trg_obj_data(self,frag):
        frh = frag.get_header()
        tc_list = []
        ta_list = []
        size_so_far = 0
        for i_tc in range(self.get_n_objget_n_obj(frag)):
            tc = self.trg_obj(frag.get_data(size_so_far))
            size_so_far = size_so_far + tc.sizeof()
            tc_list.append( TriggerCandidateData(run=frh.run_number,
                                                trigger=frh.trigger_number,
                                                sequence=frh.sequence_number,
                                                src_id=frh.element_id.id,
                                                id=i_tc,
                                                time_start=tc.data.time_start,
                                                time_end=tc.data.time_end,
                                                time_candidate=tc.data.time_candidate,
                                                detid=tc.data.detid,
                                                tc_type=tc.data.type,
                                                algorithm=tc.data.algorithm,
                                                n_tas=len(tc) ) )
            for i_ta in range(len(tc)):
                ta = tc[i_ta]
                ch_info_ta = self.channel_map.get_channel_info_from_offline_channel(ta.data.channel_peak)
                ta_list.append( TriggerActivityData(run=frh.run_number,
                                                    trigger=frh.trigger_number,
                                                    sequence=frh.sequence_number,
                                                    src_id=frh.element_id.id,
                                                    id=i_ta,
                                                    time_start=ta.time_start,
                                                    time_end=ta.time_end,
                                                    time_peak=ta.time_peak,
                                                    time_activity=ta.time_activity,
                                                    channel_start=ta.channel_start,
                                                    channel_end=ta.channel_end,
                                                    channel_peak=ta.channel_peak,
                                                    plane=self.channel_map.get_plane_from_offline_channel(ta.channel_peak),
                                                    element=ch_info_ta.element,
                                                    adc_integral=ta.adc_integral,
                                                    adc_peak=ta.adc_peak,
                                                    detid=ta.detid,
                                                    ta_type=ta.type,
                                                    algorithm=ta.algorithm,
                                                    n_tps=-1,
                                                    id_tc=i_tc) )
        if len(ta_list)==0:
            ta_list=None
        return tc_list, ta_list
 
 
class DetectorFragmentUnpacker(FragmentUnpacker):
    
    is_detector_unpacker = True
 
    def __init__(self,ana_data_prescale=1,wvfm_data_prescale=None):
        super().__init__()
        self.ana_data_prescale = None if not ana_data_prescale else int(ana_data_prescale)
        self.wvfm_data_prescale = None if not wvfm_data_prescale else int(wvfm_data_prescale)
    
    def get_daq_header_version(self,frag):
        return None
    
    def get_det_data_version(self,frag):
        return None
 
    def get_timestamp_first(self,frag):
        return None
    
    def get_det_crate_slot_stream(self,frag):
        return None, None, None, None
 
    def get_daq_header_data(self,frag):
        frh = frag.get_header()
        det_id, crate_id, slot_id, stream_id = self.get_det_crate_slot_stream(frag)
        return [ DAQHeaderData(run=frh.run_number,
                               trigger=frh.trigger_number,
                               sequence=frh.sequence_number,
                               src_id=frh.element_id.id,
                               n_obj=self.get_n_obj(frag),
                               daq_header_version=self.get_daq_header_version(frag),
                               det_data_version=self.get_det_data_version(frag),
                               det_id=det_id,
                               crate_id=crate_id,
                               slot_id=slot_id,
                               stream_id=stream_id,
                               timestamp_first_dts=self.get_timestamp_first(frag)) ]
    
    def get_det_header_data(self,frag):
        return None
 
    def get_det_data_all(self,frag):
        return None, None
 
    def get_det_data(self,frag):
        det_ana_data, det_wvfm_data = self.get_det_data_all(frag)
        return self.get_daq_header_data(frag), self.get_det_header_data(frag), det_ana_data, det_wvfm_data
 
 
class WIBEthUnpacker(DetectorFragmentUnpacker):
 
    unpacker = rawdatautils.unpack.wibeth
    frame_obj = fddetdataformats.WIBEthFrame
    
    SAMPLING_PERIOD = 32
    N_CHANNELS_PER_FRAME = 64
    
    def __init__(self,channel_map=None,ana_data_prescale=1,wvfm_data_prescale=None):
        super().__init__(ana_data_prescale=ana_data_prescale, wvfm_data_prescale=wvfm_data_prescale)
        self.channel_map = detchannelmaps.make_tpc_map(channel_map) if channel_map else NullChannelMap
 
    def get_n_obj(self,frag):
        return self.unpacker.get_n_frames(frag)
 
    def get_daq_header_version(self,frag):
        return self.frame_obj(frag.get_data()).get_daqheader().version
 
    def get_timestamp_first(self,frag):
        return self.frame_obj(frag.get_data()).get_timestamp()
    
    def get_det_data_version(self,frag):
        return self.frame_obj(frag.get_data()).get_wibheader().version
 
    def get_det_crate_slot_stream(self,frag):
        dh = self.frame_obj(frag.get_data()).get_daqheader()
        return dh.det_id, dh.crate_id, dh.slot_id, dh.stream_id
 
    def get_det_header_data(self,frag):
        frh = frag.get_header()
 
        n_frames = self.get_n_objget_n_obj(frag)
 
        pulser_arr = np.empty(n_frames)
        calibration_arr = np.empty(n_frames)
        ready_arr = np.empty(n_frames)
        context_arr = np.empty(n_frames)
        wib_sync_arr = np.empty(n_frames)
        femb_sync_arr = np.empty(n_frames)
        cd_arr = np.empty(n_frames)
        crc_err_arr = np.empty(n_frames)
        link_valid_arr = np.empty(n_frames)
        lol_arr = np.empty(n_frames)
        colddata_ts0_arr = np.empty(n_frames)
        colddata_ts1_arr = np.empty(n_frames)
        
        for i in range(n_frames):
            wh = self.frame_obj(frag.get_data(i*self.frame_obj.sizeof())).get_wibheader()
 
            pulser_arr[i] = wh.pulser
            calibration_arr[i] = wh.calibration
            ready_arr[i] = wh.ready
            context_arr[i] = wh.context
 
            wib_sync_arr[i] = wh.wib_sync
            femb_sync_arr[i] = wh.femb_sync
 
            cd_arr[i] = wh.cd
            crc_err_arr[i] = wh.crc_err
            link_valid_arr[i] = wh.link_valid
            lol_arr[i] = wh.lol
 
            colddata_ts0_arr[i] = wh.colddata_timestamp_0
            colddata_ts1_arr[i] = wh.colddata_timestamp_1
 
        pulser_change_idx, pulser_change_val, _ = sparsify_array_diff_locs_and_vals(pulser_arr)
        calibration_change_idx, calibration_change_val, _ = sparsify_array_diff_locs_and_vals(calibration_arr)
        ready_change_idx, ready_change_val, _ = sparsify_array_diff_locs_and_vals(context_arr)
        context_change_idx, context_change_val, _ = sparsify_array_diff_locs_and_vals(context_arr)
 
        wib_sync_change_idx, wib_sync_change_val, _ = sparsify_array_diff_locs_and_vals(wib_sync_arr)
        femb_sync_change_idx, femb_sync_change_val, _ = sparsify_array_diff_locs_and_vals(femb_sync_arr)
 
        cd_change_idx, cd_change_val, _ = sparsify_array_diff_locs_and_vals(cd_arr)
        crc_err_change_idx, crc_err_change_val, _ = sparsify_array_diff_locs_and_vals(crc_err_arr)
        link_valid_change_idx, link_valid_change_val, _ = sparsify_array_diff_locs_and_vals(link_valid_arr)
        lol_change_idx, lol_change_val, _ = sparsify_array_diff_locs_and_vals(context_arr)
 
        colddata_ts0_diff = np.diff(colddata_ts0_arr)
        colddata_ts0_diff[colddata_ts0_diff<0] = colddata_ts0_diff[colddata_ts0_diff<0]+0x8000
        colddata_ts0_diff_change_idx, colddata_ts0_diff_change_val, _ = sparsify_array_diff_locs_and_vals(colddata_ts0_diff)
        
        colddata_ts1_diff = np.diff(colddata_ts1_arr)
        colddata_ts1_diff[colddata_ts1_diff<0] = colddata_ts1_diff[colddata_ts1_diff<0]+0x8000
        colddata_ts1_diff_change_idx, colddata_ts1_diff_change_val, _ = sparsify_array_diff_locs_and_vals(colddata_ts1_diff)
 
        ts_arr = self.unpacker.np_array_timestamp(frag)
        ts_diff_change_idx, ts_diff_change_val, _ = sparsify_array_diff_locs_and_vals(np.diff(ts_arr))
        
        wh = self.frame_obj(frag.get_data()).get_wibheader()
        ts_diff_vals, ts_diff_counts = np.unique(np.diff(self.unpacker.np_array_timestamp(frag)),return_counts=True)
        return [ WIBEthHeaderData(run=frh.run_number,
                                  trigger=frh.trigger_number,
                                  sequence=frh.sequence_number,
                                  src_id=frh.element_id.id,
                                  femb_id=(wh.channel>>1)&0x3,
                                  colddata_id=wh.channel&0x1,
                                  version=wh.version,
                                  pulser_vals=pulser_change_val, pulser_idx=pulser_change_idx,
                                  calibration_vals=calibration_change_val, calibration_idx=calibration_change_idx,
                                  ready_vals=ready_change_val, ready_idx=ready_change_idx,
                                  context_vals=context_change_val, context_idx=context_change_idx,
                                  wib_sync_vals=wib_sync_change_val, wib_sync_idx=wib_sync_change_idx,
                                  femb_sync_vals=femb_sync_change_val, femb_sync_idx=femb_sync_change_idx,
                                  cd_vals=cd_change_val, cd_idx=cd_change_idx,
                                  crc_err_vals=crc_err_change_val, crc_err_idx=crc_err_change_idx,
                                  link_valid_vals=link_valid_change_val, link_valid_idx=link_valid_change_idx,
                                  lol_vals=lol_change_val, lol_idx=lol_change_idx,
                                  colddata_timestamp_0_diff_vals=colddata_ts0_diff_change_val,
                                  colddata_timestamp_0_diff_idx=colddata_ts0_diff_change_idx,
                                  colddata_timestamp_0_first=colddata_ts0_arr[0],
                                  colddata_timestamp_1_diff_vals=colddata_ts1_diff_change_val,
                                  colddata_timestamp_1_diff_idx=colddata_ts1_diff_change_idx,
                                  colddata_timestamp_1_first=colddata_ts1_arr[0],
                                  timestamp_dts_diff_vals=ts_diff_change_val, timestamp_dts_diff_idx=ts_diff_change_idx,
                                  timestamp_dts_first=ts_arr[0],
                                  n_frames=n_frames,
                                  n_channels=self.N_CHANNELS_PER_FRAME,
                                  sampling_period=self.SAMPLING_PERIOD) ]
 
    def get_det_data_all(self,frag):
        frh = frag.get_header()
        trigger_number = frh.trigger_number
 
        get_ana_data = (self.ana_data_prescale is not None and (trigger_number % self.ana_data_prescale)==0)
        get_wvfm_data = (self.wvfm_data_prescale is not None and (trigger_number % self.wvfm_data_prescale)==0)
 
        #print(f'\t\tTrigger number {trigger_number}: get_ana_data? {get_ana_data} get_wvfm_data? {get_wvfm_data}')
 
        if not (get_ana_data or get_wvfm_data):
            return None,None
 
        ana_data = None
        wvfm_data = None
        
        adcs = self.unpacker.np_array_adc(frag)
        det, crate, slot, stream = self.get_det_crate_slot_streamget_det_crate_slot_stream(frag)
        channels = [ self.channel_map.get_offline_channel_from_det_crate_slot_stream_chan(det, crate, slot, stream, c) for c in range(self.N_CHANNELS_PER_FRAME) ]
        planes = [ self.channel_map.get_plane_from_offline_channel(uc) for uc in channels ]
        elements = [ self.channel_map.get_element_id_from_offline_channel(uc) for uc in channels ]
        wib_chans = range(self.N_CHANNELS_PER_FRAME)
        
        if get_ana_data:
            adc_mean = np.mean(adcs,axis=0)
            adc_rms = np.std(adcs,axis=0)
            adc_max = np.max(adcs,axis=0)
            adc_min = np.min(adcs,axis=0)
            adc_median = np.median(adcs,axis=0)
            ana_data = [ WIBEthAnalysisData(run=frh.run_number,
                                            trigger=frh.trigger_number,
                                            sequence=frh.sequence_number,
                                            src_id=frh.element_id.id,
                                            channel=channels[i_ch],
                                            plane=planes[i_ch],
                                            element=elements[i_ch],
                                            wib_chan=wib_chans[i_ch],
                                            adc_mean=adc_mean[i_ch],
                                            adc_rms=adc_rms[i_ch],
                                            adc_max=adc_max[i_ch],
                                            adc_min=adc_min[i_ch],
                                            adc_median=adc_median[i_ch]) for i_ch in range(self.N_CHANNELS_PER_FRAME) ]
        if get_wvfm_data:
            timestamps = self.unpacker.np_array_timestamp(frag)
            ffts = np.abs(np.fft.rfft(adcs,axis=0))
            wvfm_data = [ WIBEthWaveformData(run=frh.run_number,
                                             trigger=frh.trigger_number,
                                             sequence=frh.sequence_number,
                                             src_id=frh.element_id.id,
                                             channel=channels[i_ch],
                                             plane=planes[i_ch],
                                             element=elements[i_ch],
                                             wib_chan=wib_chans[i_ch],
                                             timestamps=timestamps,
                                             adcs=adcs[:,i_ch],
                                             fft_mag=ffts[:,i_ch]) for i_ch in range(self.N_CHANNELS_PER_FRAME) ]
        
        return ana_data, wvfm_data
 
 
class TDEEthUnpacker(DetectorFragmentUnpacker):
 
    unpacker = rawdatautils.unpack.tde
    frame_obj = fddetdataformats.TDEEthFrame
 
    SAMPLING_PERIOD = 31.25
    N_CHANNELS_PER_FRAME = 64
 
    def __init__(self,channel_map=None,ana_data_prescale=1,wvfm_data_prescale=None):
        super().__init__(ana_data_prescale=ana_data_prescale, wvfm_data_prescale=wvfm_data_prescale)
        if 'TPC' in channel_map:
            self.channel_map = detchannelmaps.make_tpc_map(channel_map)
        elif 'PDS' in channel_map:
            self.channel_map = detchannelmaps.make_pds_map(channel_map)
        else:
            self.channel_map = NullChannelMap
 
    def get_n_obj(self,frag):
        return self.unpacker.get_n_frames(frag)
 
    def get_daq_header_version(self,frag):
        return self.frame_obj(frag.get_data()).get_daqheader().version
 
    def get_timestamp_first(self,frag):
        return self.frame_obj(frag.get_data()).get_timestamp()
 
    def get_det_data_version(self,frag):
        return self.frame_obj(frag.get_data()).get_tdeheader().version
 
    def get_det_crate_slot_stream(self,frag):
        dh = self.frame_obj(frag.get_data()).get_daqheader()
        return dh.det_id, dh.crate_id, dh.slot_id, dh.stream_id
 
    def get_det_header_data(self,frag):
        frh = frag.get_header()
 
        n_frames = self.get_n_objget_n_obj(frag)
 
        errors_arr = np.empty(n_frames)
        tai_time_arr = np.empty(n_frames)
 
        for i in range(n_frames):
            tdeh = self.frame_obj(frag.get_data(i*self.frame_obj.sizeof())).get_tdeheader()
 
            errors_arr[i] = tdeh.tde_errors
            tai_time_arr[i] = tdeh.TAItime
 
        errors_change_idx, errors_change_val, _ = sparsify_array_diff_locs_and_vals(errors_arr)
 
        tai_time_diff = np.diff(tai_time_arr)
        tai_time_diff_change_idx, tai_time_diff_change_val, _ = sparsify_array_diff_locs_and_vals(tai_time_diff)
 
        ts_arr = self.unpacker.np_array_timestamp(frag)
        ts_diff_change_idx, ts_diff_change_val, _ = sparsify_array_diff_locs_and_vals(np.diff(ts_arr))
 
        tdeh = self.frame_obj(frag.get_data()).get_tdeheader()
        ts_diff_vals, ts_diff_counts = np.unique(np.diff(self.unpacker.np_array_timestamp(frag)),return_counts=True)
        return [ TDEEthHeaderData(run=frh.run_number,
                                  trigger=frh.trigger_number,
                                  sequence=frh.sequence_number,
                                  src_id=frh.element_id.id,
                                  channel_id=tdeh.channel,
                                  tde_header=tdeh.tde_header,
                                  version=tdeh.version,
                                  errors_vals=errors_change_val, errors_idx=errors_change_idx,
                                  tai_time_diff_vals=tai_time_diff_change_val,
                                  tai_time_diff_idx=tai_time_diff_change_idx,
                                  tai_time_first=tai_time_arr[0],
                                  timestamp_dts_diff_vals=ts_diff_change_val,
                                  timestamp_dts_diff_idx=ts_diff_change_idx,
                                  timestamp_dts_first=ts_arr[0],
                                  n_frames=n_frames,
                                  n_channels=self.N_CHANNELS_PER_FRAME,
                                  sampling_period=self.SAMPLING_PERIOD) ]
 
    def get_det_data_all(self,frag):
        frh = frag.get_header()
        trigger_number = frh.trigger_number
 
        get_ana_data = (self.ana_data_prescale is not None and (trigger_number % self.ana_data_prescale)==0)
        get_wvfm_data = (self.wvfm_data_prescale is not None and (trigger_number % self.wvfm_data_prescale)==0)
 
        #print(f'\t\tTrigger number {trigger_number}: get_ana_data? {get_ana_data} get_wvfm_data? {get_wvfm_data}')
 
        if not (get_ana_data or get_wvfm_data):
            return None,None
 
        ana_data = None
        wvfm_data = None
 
        adcs = self.unpacker.np_array_adc(frag)
        det, crate, slot, stream = self.get_det_crate_slot_streamget_det_crate_slot_stream(frag)
        channels = [ self.channel_map.get_offline_channel_from_det_crate_slot_stream_chan(det, crate, slot, stream, c) for c in range(self.N_CHANNELS_PER_FRAME) ]
        planes = [ self.channel_map.get_plane_from_offline_channel(uc) for uc in channels ]
        elements = [ self.channel_map.get_element_id_from_offline_channel(uc) for uc in channels ]
        tde_chans = range(self.N_CHANNELS_PER_FRAME)
 
        if get_ana_data:
            adc_mean = np.mean(adcs,axis=0)
            adc_rms = np.std(adcs,axis=0)
            adc_max = np.max(adcs,axis=0)
            adc_min = np.min(adcs,axis=0)
            adc_median = np.median(adcs,axis=0)
            ana_data = [ TDEEthAnalysisData(run=frh.run_number,
                                            trigger=frh.trigger_number,
                                            sequence=frh.sequence_number,
                                            src_id=frh.element_id.id,
                                            channel=channels[i_ch],
                                            plane=planes[i_ch],
                                            element=elements[i_ch],
                                            tde_chan=tde_chans[i_ch],
                                            adc_mean=adc_mean[i_ch],
                                            adc_rms=adc_rms[i_ch],
                                            adc_max=adc_max[i_ch],
                                            adc_min=adc_min[i_ch],
                                            adc_median=adc_median[i_ch]) for i_ch in range(self.N_CHANNELS_PER_FRAME) ]
        if get_wvfm_data:
            timestamps = self.unpacker.np_array_timestamp(frag)
            ffts = np.abs(np.fft.rfft(adcs,axis=0))
            wvfm_data = [ TDEEthWaveformData(run=frh.run_number,
                                             trigger=frh.trigger_number,
                                             sequence=frh.sequence_number,
                                             src_id=frh.element_id.id,
                                             channel=channels[i_ch],
                                             plane=planes[i_ch],
                                             element=elements[i_ch],
                                             tde_chan=tde_chans[i_ch],
                                             timestamps=timestamps,
                                             adcs=adcs[:,i_ch],
                                             fft_mag=ffts[:,i_ch]) for i_ch in range(self.N_CHANNELS_PER_FRAME) ]
 
        return ana_data, wvfm_data
 
class DAPHNEStreamUnpacker(DetectorFragmentUnpacker):
 
    unpacker = rawdatautils.unpack.daphne
    frame_obj = fddetdataformats.DAPHNEStreamFrame
 
    SAMPLING_PERIOD = 1
    N_CHANNELS_PER_FRAME = 4
    
    def get_n_obj(self,frag):
        return self.unpacker.get_n_frames_stream(frag)
 
    def get_daq_header_version(self,frag):
        return self.frame_obj(frag.get_data()).get_daqheader().version
 
    def get_timestamp_first(self,frag):
        return self.frame_obj(frag.get_data()).get_timestamp()
    
    def get_det_data_version(self,frag):
        return 0
 
    def get_det_crate_slot_stream(self,frag):
        dh = self.frame_obj(frag.get_data()).get_daqheader()
        return dh.det_id, dh.crate_id, dh.slot_id, dh.link_id
 
    def get_det_header_data(self,frag):
        frh = frag.get_header()
        dh = self.frame_obj(frag.get_data()).get_header()
        ts_diffs_vals, ts_diffs_counts = np.unique(np.diff( np.array(self.unpacker.np_array_timestamp_stream(frag), dtype=np.int64)), return_counts=True)
        return [ DAPHNEStreamHeaderData(run=frh.run_number,
                                        trigger=frh.trigger_number,
                                        sequence=frh.sequence_number,
                                        src_id=frh.element_id.id,
                                        n_channels=self.N_CHANNELS_PER_FRAME,
                                        sampling_period=self.SAMPLING_PERIOD,
                                        ts_diffs_vals=ts_diffs_vals,
                                        ts_diffs_counts=ts_diffs_counts) ]
 
    def get_det_data_all(self,frag):
        frh = frag.get_header()
        trigger_number = frh.trigger_number
 
        get_ana_data = (self.ana_data_prescale is not None and (trigger_number % self.ana_data_prescale)==0)
        get_wvfm_data = (self.wvfm_data_prescale is not None and (trigger_number % self.wvfm_data_prescale)==0)
 
        if not (get_ana_data or get_wvfm_data):
            return None,None
 
        ana_data = None
        wvfm_data = None
 
        adcs = self.unpacker.np_array_adc_stream(frag)
        dh = self.frame_obj(frag.get_data()).get_header()
        channels = [ dh.channel_0, dh.channel_1, dh.channel_2, dh.channel_3 ]
        daphne_chans = [ dh.channel_0, dh.channel_1, dh.channel_2, dh.channel_3 ]
 
        if get_ana_data:
            adc_mean = np.mean(adcs,axis=0)
            adc_rms = np.std(adcs,axis=0)
            adc_max = np.max(adcs,axis=0)
            adc_min = np.min(adcs,axis=0)
            adc_median = np.median(adcs,axis=0)
            ana_data = [ DAPHNEStreamAnalysisData(run=frh.run_number,
                                                  trigger=frh.trigger_number,
                                                  sequence=frh.sequence_number,
                                                  src_id=frh.element_id.id,
                                                  channel=channels[i_ch],
                                                  daphne_chan=daphne_chans[i_ch],
                                                  adc_mean=adc_mean[i_ch],
                                                  adc_rms=adc_rms[i_ch],
                                                  adc_max=adc_max[i_ch],
                                                  adc_min=adc_min[i_ch],
                                                  adc_median=adc_median[i_ch]) for i_ch in range(self.N_CHANNELS_PER_FRAME) ]
        if get_wvfm_data:
            timestamps = self.unpacker.np_array_timestamp_stream(frag)
            ffts = np.abs(np.fft.rfft(adcs,axis=0))
            wvfm_data = [ DAPHNEStreamWaveformData(run=frh.run_number,
                                                   trigger=frh.trigger_number,
                                                   sequence=frh.sequence_number,
                                                   src_id=frh.element_id.id,
                                                   channel=channels[i_ch],
                                                   daphne_chan=channels[i_ch],
                                                   adcs=adcs[:,i_ch],
                                                   timestamps=timestamps,
                                                   fft_mag=ffts[:,i_ch]) for i_ch in range(self.N_CHANNELS_PER_FRAME) ]
        return ana_data, wvfm_data
 
 
class DAPHNEUnpacker(DetectorFragmentUnpacker):
 
    unpacker = rawdatautils.unpack.daphne
    frame_obj = fddetdataformats.DAPHNEFrame
 
    SAMPLING_PERIOD = 1
    N_CHANNELS_PER_FRAME = 1
            
    def get_n_obj(self,frag):
        return self.unpacker.get_n_frames(frag)
 
    def get_daq_header_version(self,frag):
        return self.frame_obj(frag.get_data()).get_daqheader().version
 
    def get_timestamp_first(self,frag):
        return self.frame_obj(frag.get_data()).get_timestamp()
    
    def get_det_data_version(self,frag):
        return 0
 
    def get_det_crate_slot_stream(self,frag):
        dh = self.frame_obj(frag.get_data()).get_daqheader()
        return dh.det_id, dh.crate_id, dh.slot_id, dh.link_id
 
    def get_det_header_data(self,frag):
        return None
 
    def get_det_data_all(self,frag):
        frh = frag.get_header()
        trigger_number = frh.trigger_number
        wvfm_data = None
        ana_data = None
 
        get_ana_data = (self.ana_data_prescale is not None and (trigger_number % self.ana_data_prescale)==0)
        get_wvfm_data = (self.wvfm_data_prescale is not None and (trigger_number % self.wvfm_data_prescale)==0)
 
        if not (get_ana_data or get_wvfm_data):
            return None,None
 
        n_frames = self.get_n_objget_n_obj(frag)
        adcs = self.unpacker.np_array_adc(frag)
 
        daphne_headers = [ self.frame_obj(frag.get_data(iframe*self.frame_obj.sizeof())).get_header() for iframe in range(n_frames) ]
        timestamp = self.unpacker.np_array_timestamp(frag)
 
        if (len(adcs)) == 0:
            return None, None
    
        if get_ana_data:
            ax = 1
            adc_mean = np.mean(adcs,axis=ax)
            adc_rms = np.std(adcs,axis=ax)
            adc_max = np.max(adcs,axis=ax)
            adc_min = np.min(adcs,axis=ax)
            adc_median = np.median(adcs,axis=ax)
            ts_max = np.argmax(adcs,axis=ax)*self.SAMPLING_PERIOD + timestamp
            ts_min = np.argmin(adcs,axis=ax)*self.SAMPLING_PERIOD + timestamp
 
            ana_data = [ DAPHNEAnalysisData(run=frh.run_number,
                                            trigger=frh.trigger_number,
                                            sequence=frh.sequence_number,
                                            src_id=frh.element_id.id,
                                            channel=daphne_headers[iframe].channel,
                                            daphne_chan=daphne_headers[iframe].channel,
                                            timestamp_dts=timestamp[iframe],
                                            trigger_sample_value=daphne_headers[iframe].trigger_sample_value,
                                            threshold=daphne_headers[iframe].threshold,
                                            baseline=daphne_headers[iframe].baseline,
                                            adc_mean=adc_mean[iframe],
                                            adc_rms=adc_rms[iframe],
                                            adc_max=adc_max[iframe],
                                            adc_min=adc_min[iframe],
                                            adc_median=adc_median[iframe],
                                            timestamp_max_dts=ts_max[iframe],
                                            timestamp_min_dts=ts_min[iframe]) for iframe in range(n_frames) ]
 
 
        if get_wvfm_data:
 
            wvfm_data = [ DAPHNEWaveformData(run=frh.run_number,
                                             trigger=frh.trigger_number,
                                             sequence=frh.sequence_number,
                                             src_id=frh.element_id.id,
                                             channel=daphne_headers[iframe].channel,
                                             daphne_chan=daphne_headers[iframe].channel,
                                             timestamp_dts=timestamp[iframe],
                                             timestamps=np.arange(np.size(adcs[iframe,:]))*self.SAMPLING_PERIOD+timestamp[iframe],
                                             adcs=adcs[iframe,:]) for iframe in range(n_frames) ]
 
        return ana_data, wvfm_data