Source code for pymepix.processing.logic.packet_processor

# This file is part of Pymepix
#
# In all scientific work using Pymepix, please reference it as
#
# A. F. Al-Refaie, M. Johny, J. Correa, D. Pennicard, P. Svihra, A. Nomerotski, S. Trippel, and J. Küpper:
# "PymePix: a python library for SPIDR readout of Timepix3", J. Inst. 14, P10003 (2019)
# https://doi.org/10.1088/1748-0221/14/10/P10003
# https://arxiv.org/abs/1905.07999
#
# Pymepix is free software: you can redistribute it and/or modify it under the terms of the GNU
# General Public License as published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without
# even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with this program. If not,
# see <https://www.gnu.org/licenses/>.
from enum import IntEnum

import numpy as np

from pymepix.processing.logic.processing_step import ProcessingStep


[docs] class PixelOrientation(IntEnum): """Defines how row and col are intepreted in the output""" Up = 0 """Up is the default, x=column,y=row""" Left = 1 """x=row, y=-column""" Down = 2 """x=-column, y = -row """ Right = 3 """x=-row, y=column"""
[docs] class PacketProcessor(ProcessingStep): """Class responsible to transform the raw data coming from the timepix directly into an easier processible data format. Takes into account the pixel- and trigger data to calculate toa and tof dimensions. Methods ------- process(data): Process data and return the result. To use this class only this method should be used! Use the other methods only for testing or if you are sure about what you are doing """ def __init__( self, handle_events=True, event_window=(0.0, 10_000.0), position_offset=(0, 0), orientation=PixelOrientation.Up, start_time=0, timewalk_lut=None, *args, **kwargs, ): """ Constructor for the PacketProcessor. Parameters ---------- handle_events : boolean Calculate events (tof) only if handle_events is True. Otherwise only pixel-data (toa only) is provided. event_window : (float, float) The range of tof, used for processing data. Information/ data outside of this range is discarded. min_samples : (float, float) Offset/ shift of x- and y-position orientation : int start_time : int timewalk_lut Data for correction of the time-walk parameter_wrapper_classe : ProcessingParameter Class used to wrap the processing parameters to make them changable while processing is running (useful for online optimization) """ super().__init__("PacketProcessor", *args, **kwargs) self._handle_events = self.parameter_wrapper_class(handle_events) event_window_min, event_window_max = event_window self._event_window_min = self.parameter_wrapper_class(event_window_min) self._event_window_max = self.parameter_wrapper_class(event_window_max) self._orientation = orientation self._x_offset, self._y_offset = position_offset self._start_time = start_time self._timewalk_lut = timewalk_lut self._trigger_counter = 0 self.clearBuffers() @property def event_window(self): return (self._event_window_min.value, self._event_window_max.value) @event_window.setter def event_window(self, event_window): event_window_min, event_window_max = event_window self._event_window_min.value = event_window_min self._event_window_max.value = event_window_max @property def handle_events(self): """:noindex:""" return self._handle_events.value @handle_events.setter def handle_events(self, handle_events): self._handle_events.value = handle_events
[docs] def process(self, data): packet_view = memoryview(data) packet = np.frombuffer(packet_view[:-8], dtype=np.uint64) # needs to be an integer or "(ltime >> 28) & 0x3" fails longtime = int(np.frombuffer(packet_view[-8:], dtype=np.uint64)[0]) event_data, pixel_data, timestamps, triggers = None, None, None, None if len(packet) > 0: trigger1_data = None trigger2_data = None header = ((packet & 0xF000000000000000) >> 60) & 0xF subheader = ((packet & 0x0F00000000000000) >> 56) & 0xF pixels = packet[np.logical_or(header == 0xA, header == 0xB)] triggers1 = packet[ np.logical_and( np.logical_or(header == 0x4, header == 0x6), np.logical_or(subheader == 0xF, subheader == 0xA) ) ] triggers2 = packet[ np.logical_and( # sub headers for trigger identification # TDC1 rising edge: 0xF falling edge: 0xA # TDC2 rising edge: 0xE falling edge: 0xB header == 0x6, np.logical_or(subheader == 0xE, subheader == 0xB), ) ] if triggers1.size > 0: trigger1_front, trigger1_data = self.process_trigger1(np.int64(triggers1), longtime) self._trigger_counter += trigger1_front.size if triggers2.size > 0: trigger2_data = self.process_trigger2(np.int64(triggers2), longtime) if pixels.size > 0: pixel_data = self.process_pixels(np.int64(pixels), longtime) if self.handle_events: result = self.find_events_fast() if result is not None: event_data, timestamps = result triggers = [ trigger1_data, trigger2_data, ] return event_data, pixel_data, timestamps, triggers
[docs] def pre_process(self): self.log.info("Running with triggers? {}".format(self.handle_events))
[docs] def post_process(self): return self.find_events_fast_post()
[docs] def updateBuffers(self, val_filter): self._x = self._x[val_filter] self._y = self._y[val_filter] self._toa = self._toa[val_filter] self._tot = self._tot[val_filter]
[docs] def getBuffers(self, val_filter=None): if val_filter is None: return ( np.copy(self._x), np.copy(self._y), np.copy(self._toa), np.copy(self._tot), ) else: return ( np.copy(self._x[val_filter]), np.copy(self._y[val_filter]), np.copy(self._toa[val_filter]), np.copy(self._tot[val_filter]), )
[docs] def clearBuffers(self): self._x = None self._y = None self._tot = None self._toa = None self._triggers = None
[docs] def process_trigger1(self, trig1_data, longtime): subheader = ((trig1_data & 0x0F00000000000000) >> 56) & 0xF # TDC1 rising edge: 0xF falling edge: 0xA front_edge_type = subheader == 0xF coarsetime = trig1_data >> 12 & 0xFFFFFFFF coarsetime = self.correct_global_time(coarsetime, longtime) tmpfine = (trig1_data >> 5) & 0xF tmpfine = ((tmpfine - 1) << 9) // 12 trigtime_fine = (trig1_data & 0x0000000000000E00) | (tmpfine & 0x00000000000001FF) time_unit = 25.0 / 4096 tdc_time = coarsetime * 25e-9 + trigtime_fine * time_unit * 1e-9 m_trigTime = tdc_time[front_edge_type] tdc_time[front_edge_type == False] *= -1 if self.handle_events: if self._triggers is None: self._triggers = m_trigTime else: self._triggers = np.append(self._triggers, m_trigTime) return m_trigTime, tdc_time
[docs] def process_trigger2(self, trig2_data, longtime): subheader = ((trig2_data & 0x0F00000000000000) >> 56) & 0xF # TDC2 rising edge: 0xE falling edge: 0xB edge_type = subheader == 0xE coarsetime = trig2_data >> 12 & 0xFFFFFFFF coarsetime = self.correct_global_time(coarsetime, longtime) tmpfine = (trig2_data >> 5) & 0xF tmpfine = ((tmpfine - 1) << 9) // 12 trigtime_fine = (trig2_data & 0x0000000000000E00) | (tmpfine & 0x00000000000001FF) time_unit = 25.0 / 4096 tdc_time = coarsetime * 25e-9 + trigtime_fine * time_unit * 1e-9 tdc_time[edge_type == False] *= -1 # always look at it as abs, sign tells rising or falling edge return tdc_time
[docs] def orientPixels(self, col, row): """Orient the pixels based on Timepix orientation""" if self._orientation is PixelOrientation.Up: return col, row elif self._orientation is PixelOrientation.Left: return row, 255 - col elif self._orientation is PixelOrientation.Down: return 255 - col, 255 - row elif self._orientation is PixelOrientation.Right: return 255 - row, col
[docs] def process_pixels(self, pixdata, longtime): dcol = (pixdata & 0x0FE0000000000000) >> 52 spix = (pixdata & 0x001F800000000000) >> 45 pix = (pixdata & 0x0000700000000000) >> 44 col = dcol + pix // 4 row = spix + (pix & 0x3) data = (pixdata & 0x00000FFFFFFF0000) >> 16 spidr_time = pixdata & 0x000000000000FFFF ToA = (data & 0x0FFFC000) >> 14 FToA = data & 0xF ToT = ((data & 0x00003FF0) >> 4) * 25 time_unit = 25.0 / 4096 ToA_coarse = self.correct_global_time((spidr_time << 14) | ToA, longtime) & 0xFFFFFFFFFFFF globalToA = (ToA_coarse << 12) - (FToA << 8) globalToA += ((col // 2) % 16) << 8 globalToA[((col // 2) % 16) == 0] += 16 << 8 finalToA = globalToA * time_unit * 1e-9 if self._timewalk_lut is not None: finalToA -= self._timewalk_lut[np.int_(ToT // 25) - 1] * 1e3 x, y = self.orientPixels(col, row) x += self._x_offset y += self._y_offset if self.handle_events: if self._x is None: self._x = x self._y = y self._toa = finalToA self._tot = ToT else: self._x = np.append(self._x, x) self._y = np.append(self._y, y) self._toa = np.append(self._toa, finalToA) self._tot = np.append(self._tot, ToT) return x, y, finalToA, ToT
[docs] def correct_global_time(self, arr, ltime): pixelbits = (arr >> 28) & 0x3 ltimebits = (ltime >> 28) & 0x3 # diff = (ltimebits - pixelbits).astype(np.int64) # neg = (diff == 1) | (diff == -3) # pos = (diff == -1) | (diff == 3) # zero = (diff == 0) | (diff == 2) # res = ( (ltime) & 0xFFFFC0000000) | (arr & 0x3FFFFFFF) diff = (ltimebits - pixelbits).astype(np.int64) globaltime = (ltime & 0xFFFFC0000000) | (arr & 0x3FFFFFFF) neg_diff = (diff == 1) | (diff == -3) globaltime[neg_diff] = ((ltime - 0x10000000) & 0xFFFFC0000000) | (arr[neg_diff] & 0x3FFFFFFF) pos_diff = (diff == -1) | (diff == 3) globaltime[pos_diff] = ((ltime + 0x10000000) & 0xFFFFC0000000) | (arr[pos_diff] & 0x3FFFFFFF) # res[neg] = ( (ltime - 0x10000000) & 0xFFFFC0000000) | (arr[neg] & 0x3FFFFFFF) # res[pos] = ( (ltime + 0x10000000) & 0xFFFFC0000000) | (arr[pos] & 0x3FFFFFFF) # arr[zero] = ( (ltime) & 0xFFFFC0000000) | (arr[zero] & 0x3FFFFFFF) # arr[zero] = ( (ltime) & 0xFFFFC0000000) | (arr[zero] & 0x3FFFFFFF) return globaltime
[docs] def find_events_fast(self): if self.__exist_enough_triggers(): self._triggers = self._triggers[np.argmin(self._triggers) :] if self.__toa_is_not_empty(): # Get our start/end triggers to bin events accordingly start = self._triggers if start.size > 1: trigger_counter = np.arange( self._trigger_counter, self._trigger_counter + start.size - 1, dtype=int, ) self._trigger_counter = trigger_counter[-1] + 1 # end = self._triggers[1:-1:] # Get the first and last triggers in pile first_trigger = start[0] last_trigger = start[-1] # Delete useless pixels before the first trigger self.updateBuffers(self._toa >= first_trigger) # grab only pixels we care about x, y, toa, tot = self.getBuffers(self._toa < last_trigger) self.updateBuffers(self._toa >= last_trigger) try: event_mapping = np.digitize(toa, start) - 1 except Exception as e: self.log.error("Exception has occured {} due to ", str(e)) self.log.error("Writing output TOA {}".format(toa)) self.log.error("Writing triggers {}".format(start)) self.log.error("Flushing triggers!!!") self._triggers = self._triggers[-1:] return None self._triggers = self._triggers[-1:] tof = toa - start[event_mapping] event_number = trigger_counter[event_mapping] event_window_min, event_window_max = self.event_window exp_filter = (tof >= event_window_min) & (tof <= event_window_max) result = ( event_number[exp_filter], x[exp_filter], y[exp_filter], tof[exp_filter], tot[exp_filter], ) if result[0].size > 0: event_triggers = start[np.unique(event_mapping)] timeStamps = np.uint64( event_triggers * 1e9 + self._start_time ) # timestamp in ns for trigger event return result, (np.unique(result[0]), event_triggers, timeStamps) return None # Clear out the triggers since they have nothing
def __exist_enough_triggers(self): return self._triggers is not None and self._triggers.size >= 2 def __toa_is_not_empty(self): return self._toa is not None and self._toa.size > 0
[docs] def find_events_fast_post(self): """Call this function at the very end of to also have the last two trigger events processed""" # add an imaginary last trigger event after last pixel event for np.digitize to work if self._toa is not None and self._toa.shape[0] > 0 and self._triggers is not None: self._triggers = np.concatenate((self._triggers, np.array([self._toa.max() + 1]))) else: return None, None, None, None event_data, timestamps = None, None result = self.find_events_fast() if result is not None: event_data, timestamps = result return event_data, None, timestamps, None