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added moench04 support
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Erik Frojdh committed
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@@ -12,6 +12,7 @@ make
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And then have a look at the examples:
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- [Reading cluster files](examples/ClusterFile.ipynb)
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- [Reading Moench03/04 raw files](examples/RawFile.ipynb)
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## Build instructions
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+136
-12
@@ -1,29 +1,45 @@
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import json
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from pathlib import Path
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import numpy as np
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import re
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from . import RawFileReader
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from .enums import DetectorType
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class RawFile:
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"""
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Generic Raw File reader. Picks up settings from .json master file
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Currently supports: Moench03 =)
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"""
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def __init__(self, fname):
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def __init__(self, fname, header = False):
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self.findex = 0
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self.fname = fname
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self.json = False #Master file data comes from json
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fname = Path(fname)
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if fname.suffix != '.json':
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raise ValueError("Need a master file in json format")
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with open(fname) as f:
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self.master = json.load(f)
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if fname.suffix == '.json':
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with open(fname) as f:
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self.master = json.load(f)
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self.json = True
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elif fname.suffix == '.raw':
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with open(fname) as f:
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self._load_raw_master(f)
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else:
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raise ValueError(f'{fname.suffix} not supported')
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#Figure out which file to open
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if self.master['Detector Type'] == 'Moench' and self.master['Analog Samples'] == 5000:
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#TODO! pass settings to reader
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self._parse_fname()
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self.reader = RawFileReader(self.data_fname(0,0))
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self.reader = RawFileReader(self.data_fname(0,0), DetectorType.MOENCH_03, header = header)
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elif self.master['Detector Type'] == 'ChipTestBoard' and self.master['Analog Samples'] == 5000:
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self._parse_fname()
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#Do we read analog or analog+digital
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if self.master['Digital Flag'] == 1:
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dt = DetectorType.MOENCH_04_AD
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else:
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dt = DetectorType.MOENCH_04_AD
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self.reader = RawFileReader(self.data_fname(0,0), dt, header = header)
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else:
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raise ValueError('unsupported file')
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@@ -35,20 +51,128 @@ class RawFile:
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except:
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raise ValueError(f"Could not parse master file name: {self.fname}")
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def _load_raw_master(self, f):
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self.master = {}
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lines = f.readlines()
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it = iter(lines)
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for line in it:
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if line.startswith("#Frame"):
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break
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if line == "\n":
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continue
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if line.startswith("Scan Parameters"):
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while not line.endswith("]\n"):
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line += next(it)
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field, value = line.split(":", 1)
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self.master[field.strip(" ")] = value.strip(" \n")
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frame_header = {}
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for line in it:
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field, value = line.split(":", 1)
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frame_header[field.strip()] = value.strip(" \n")
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self.master["Frame Header"] = frame_header
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self.master["Version"] = float(self.master["Version"])
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self._parse_values()
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def _parse_values(self):
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int_fields = set(
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(
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"Analog Samples",
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"Analog Flag",
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"Digital Flag",
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"Digital Samples",
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"Max Frames Per File",
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"Image Size",
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"Frame Padding",
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"Total Frames",
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"Dynamic Range",
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"Ten Giga",
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"Quad",
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"Number of Lines read out",
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"Number of UDP Interfaces"
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)
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)
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time_fields = set((
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"Exptime",
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"Exptime1",
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"Exptime2",
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"Exptime3",
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"GateDelay1",
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"GateDelay2",
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"GateDelay3",
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"SubExptime",#Eiger
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"SubPeriod", #Eiger
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"Period"
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))
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#some fields might not exist for all detectors
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#hence using intersection
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for field in time_fields.intersection(self.master.keys()):
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self.master[field] = self.to_nanoseconds(self.master[field])
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#Parse bothx .json and .raw master files
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if self.json:
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self.master['Image Size'] = self.master["Image Size in bytes"]
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self.master['Pixels'] = (self.master['Pixels']['x'], self.master['Pixels']['y'])
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self.master['nmod'] = int(self.master['Geometry']['x']*self.master['Geometry']['y'] )#ports not modules
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if self.master['Detector Type'] == 'Eiger':
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self.master['nmod'] = self.master['nmod'] // 2
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else:
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for field in int_fields.intersection(self.master.keys()):
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self.master[field] = int(self.master[field].split()[0])
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self.master["Pixels"] = tuple(
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int(i) for i in self.master["Pixels"].strip("[]").split(",")
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)
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if "Rate Corrections" in self.master:
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self.master["Rate Corrections"] = (
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self.master["Rate Corrections"].strip("[]").split(",")
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)
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n = len(self.master["Rate Corrections"])
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assert (
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self.master["nmod"] == n
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), f'nmod from Rate Corrections {n} differs from nmod {self.master["nmod"]}'
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#Parse threshold for Mythen3 (if needed)
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if "Threshold Energies" in self.master.keys():
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th = self.master["Threshold Energies"]
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if isinstance(th, str):
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th = [int(i) for i in th.strip('[]').split(',')]
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self.master["Threshold Energies"] = th
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@staticmethod
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def to_nanoseconds(t):
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nanoseconds = {"s": 1000 * 1000 * 1000, "ms": 1000 * 1000, "us": 1000, "ns": 1}
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try:
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value = re.match(r"(\d+(?:\.\d+)?)", t).group()
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unit = t[len(value) :]
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value = int(float(value) * nanoseconds[unit])
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value = np.timedelta64(value, 'ns')
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except:
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raise ValueError(f"Could not convert: {t} to nanoseconds")
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return value
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def data_fname(self, i, findex=0):
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return Path(f"{self.base}_d{i}_f{findex}_{self.run_id}.raw")
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def read(self):
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return self.reader.read()
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def read(self, *args):
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return self.reader.read(*args)
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# Support iteration
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def __iter__(self):
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return self
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def __next__(self):
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frame = self.reader.read()
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if frame.shape[0] == 0:
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res = self.reader.read()
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if res.shape[0] == 0:
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raise StopIteration
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# Support with statement
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+3
-1
@@ -2,4 +2,6 @@
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from _creader import *
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from .file_utils import open_file
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from .ClusterFile import ClusterFile
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from .ClusterFile import ClusterFile
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from .enums import DetectorType
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from .RawFile import RawFile
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@@ -0,0 +1,8 @@
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from enum import IntEnum
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class DetectorType(IntEnum):
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#TODO! Move defenition to C to avoid mismatch
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GENERIC = 0
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MOENCH_03 = 3
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MOENCH_04_A = 4
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MOENCH_04_AD = 5
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@@ -0,0 +1,205 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "7c600ac0",
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"metadata": {},
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"source": [
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"# Using RawFile"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "38912c9c",
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"metadata": {},
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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"import numpy as np \n",
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"import matplotlib.pyplot as plt\n",
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"import boost_histogram as bh\n",
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"import time\n",
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"\n",
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"#Python cluster reader\n",
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"from creader import RawFile\n",
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"path = Path('/mnt/sls_det_storage/moench_data/cluster_reader_test/')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f06378a1",
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"metadata": {},
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"source": [
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"## Moench03 data\n",
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"\n",
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"Fetches info from the master file\n",
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"\n",
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"### Frames only"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "218e2897",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<Figure size 1000x500 with 3 Axes>"
|
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]
|
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},
|
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"metadata": {},
|
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"output_type": "display_data"
|
||||
}
|
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],
|
||||
"source": [
|
||||
"with RawFile(path/'Moench03_master_0.json') as f:\n",
|
||||
" frames = f.read(100)\n",
|
||||
" \n",
|
||||
"fig, ax = plt.subplots(1,3, figsize = (10,5))\n",
|
||||
"im0 = ax[0].imshow(frames[0])\n",
|
||||
"im1 = ax[1].imshow(frames[9])\n",
|
||||
"im1 = ax[2].imshow(frames[0]-frames[9])\n",
|
||||
"fig.tight_layout()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "3f92db90",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[<matplotlib.lines.Line2D at 0x7fc4ccea5d50>]"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 640x480 with 1 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"fig, ax = plt.subplots()\n",
|
||||
"ax.plot(frames.sum(axis =1).sum(axis = 1))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d25663bd",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Frames and header"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "befafb31",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Frame Number, Timestamp \n",
|
||||
"201 1107824650\n",
|
||||
"202 1108024651\n",
|
||||
"203 1108224652\n",
|
||||
"204 1108424653\n",
|
||||
"205 1108624654\n",
|
||||
"206 1108824655\n",
|
||||
"207 1109024656\n",
|
||||
"208 1109224657\n",
|
||||
"209 1109424658\n",
|
||||
"210 1109624659\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"with RawFile(path/'Moench03_master_0.json', header = True) as f:\n",
|
||||
" frames, header = f.read(10)\n",
|
||||
" \n",
|
||||
" \n",
|
||||
"print(f'{\"Frame Number,\":<15} {\"Timestamp\":<10}')\n",
|
||||
"for h in header:\n",
|
||||
" print(f\"{h['Frame Number']:<15} {h['Timestamp']:<10}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "991c2729",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Moench 04 data"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "15fcde89",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 1000x1000 with 4 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"#if the file has analog and digital data it's automatically read\n",
|
||||
"\n",
|
||||
"with RawFile(path/'Moench04_digital_master_0.raw', header = True) as f:\n",
|
||||
" analog, digital, header = f.read(20)\n",
|
||||
" \n",
|
||||
"fig, ax = plt.subplots(2,2, figsize = (10,10))\n",
|
||||
"im0 = ax[0][0].imshow(analog[0], origin = 'lower')\n",
|
||||
"im1 = ax[0][1].imshow(digital[0], origin = 'lower')\n",
|
||||
"im2 = ax[1][0].imshow(analog[9], origin = 'lower')\n",
|
||||
"im3 = ax[1][1].imshow(digital[9], origin = 'lower')\n",
|
||||
"\n",
|
||||
"fig.tight_layout()"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.3"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
+61
-24
@@ -1,7 +1,7 @@
|
||||
#include "RawFileReader.h"
|
||||
#include "arr_desc.h"
|
||||
#include "data_types.h"
|
||||
#include "raw_reader.h"
|
||||
#include "arr_desc.h"
|
||||
|
||||
#include <stdbool.h>
|
||||
|
||||
@@ -11,6 +11,7 @@ typedef struct {
|
||||
// additional fields for size and decoder?
|
||||
int dtype;
|
||||
bool read_header;
|
||||
int detector;
|
||||
} RawFileReader;
|
||||
//clang-format on
|
||||
|
||||
@@ -28,11 +29,12 @@ static int RawFileReader_init(RawFileReader *self, PyObject *args,
|
||||
|
||||
// Should we read the header
|
||||
self->read_header = false;
|
||||
self->detector = DT_GENERIC;
|
||||
|
||||
static char *kwlist[] = {"fname", "header", NULL};
|
||||
static char *kwlist[] = {"fname", "detector_type", "header", NULL};
|
||||
|
||||
if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|p", kwlist, &fname_obj,
|
||||
&self->read_header)) {
|
||||
if (!PyArg_ParseTupleAndKeywords(args, kwds, "Oi|p", kwlist, &fname_obj,
|
||||
&self->detector, &self->read_header)) {
|
||||
return -1;
|
||||
}
|
||||
|
||||
@@ -41,12 +43,13 @@ static int RawFileReader_init(RawFileReader *self, PyObject *args,
|
||||
return -1;
|
||||
|
||||
PyBytes_AsStringAndSize(fname_bytes, &fname, &len);
|
||||
|
||||
#ifdef CR_VERBOSE
|
||||
printf("fname: %s\n read_header: %d\n", fname, self->read_header);
|
||||
printf("fname: %s\n read_header: %d detector type: %d\n", fname,
|
||||
self->read_header, self->detector);
|
||||
#endif
|
||||
self->fp = fopen(fname, "rb");
|
||||
|
||||
|
||||
// Keep the return code to not return before releasing buffer
|
||||
int rc = 0;
|
||||
|
||||
@@ -77,27 +80,46 @@ static PyObject *RawFileReader_read(RawFileReader *self, PyObject *args) {
|
||||
self->dtype = NPY_UINT16;
|
||||
const int ndim = 3;
|
||||
Py_ssize_t n_frames = 1; // default number of frames to read
|
||||
// Py_ssize_t moench_version = 3;
|
||||
// Py_ssize_t analog_digital = 0;
|
||||
if (!PyArg_ParseTuple(args, "|n", &n_frames))
|
||||
return NULL;
|
||||
|
||||
npy_intp dims[3] = {n_frames, 400, 400};
|
||||
PyObject *frames = PyArray_SimpleNew(ndim, dims, self->dtype);
|
||||
char *out_buf = PyArray_DATA((PyArrayObject *)frames);
|
||||
PyObject *digital_frames = NULL;
|
||||
char *digital_out = NULL;
|
||||
|
||||
PyArray_FILLWBYTE((PyArrayObject *)frames, 0);
|
||||
|
||||
//Optional return the header
|
||||
// Optional return the header
|
||||
PyObject *header = NULL;
|
||||
char* header_out = NULL;
|
||||
if(self->read_header){
|
||||
char *header_out = NULL;
|
||||
if (self->read_header) {
|
||||
header = PyArray_SimpleNewFromDescr(1, dims, frame_header_dt());
|
||||
header_out = PyArray_DATA((PyArrayObject *)header);
|
||||
}
|
||||
|
||||
const size_t frame_size = 400 * 400 * 2;
|
||||
char *out_buf = PyArray_DATA((PyArrayObject *)frames);
|
||||
int64_t n_read =
|
||||
read_raw(self->fp, n_frames, frame_size, out_buf, header_out);
|
||||
// Both analog and digital data
|
||||
if (self->detector == DT_MOENCH_04_AD) {
|
||||
digital_frames = PyArray_SimpleNew(ndim, dims, NPY_UINT8);
|
||||
PyArray_FILLWBYTE((PyArrayObject *)digital_frames, 0);
|
||||
digital_out = PyArray_DATA((PyArrayObject *)digital_frames);
|
||||
}
|
||||
|
||||
int64_t n_read = 0;
|
||||
|
||||
switch (self->detector) {
|
||||
case DT_MOENCH_03:
|
||||
n_read = read_raw_m03(self->fp, n_frames, out_buf, header_out);
|
||||
break;
|
||||
case DT_MOENCH_04_A:
|
||||
case DT_MOENCH_04_AD:
|
||||
n_read =
|
||||
read_raw_m04(self->fp, n_frames, out_buf, digital_out, header_out);
|
||||
break;
|
||||
default:
|
||||
break;
|
||||
}
|
||||
|
||||
if (n_read != n_frames) {
|
||||
// resize the array to match the number of read photons
|
||||
@@ -114,20 +136,35 @@ static PyObject *RawFileReader_read(RawFileReader *self, PyObject *args) {
|
||||
// resize the array to match the number of clusters read
|
||||
PyArray_Resize((PyArrayObject *)frames, &new_shape, 1, NPY_ANYORDER);
|
||||
|
||||
//if we also read header we need to reshape the header
|
||||
if(self->read_header){
|
||||
// if we also read header we need to reshape the header
|
||||
if (self->read_header) {
|
||||
new_shape.len = 1;
|
||||
PyArray_Resize((PyArrayObject *)header, &new_shape, 1, NPY_ANYORDER);
|
||||
PyArray_Resize((PyArrayObject *)header, &new_shape, 1,
|
||||
NPY_ANYORDER);
|
||||
}
|
||||
|
||||
}
|
||||
PyObject *ret = frames;
|
||||
if(self->read_header){
|
||||
ret = PyTuple_Pack(2, frames, header);
|
||||
Py_DECREF(header);
|
||||
|
||||
// Build up a tuple with the return values
|
||||
PyObject *ret = PyTuple_Pack(1, frames);
|
||||
if (self->detector == DT_MOENCH_04_AD){
|
||||
_PyTuple_Resize(&ret, 2);
|
||||
PyTuple_SET_ITEM(ret, 1, digital_frames);
|
||||
}
|
||||
|
||||
if (self->read_header){
|
||||
Py_ssize_t old_size = PyTuple_GET_SIZE(ret);
|
||||
_PyTuple_Resize(&ret, old_size+1);
|
||||
PyTuple_SET_ITEM(ret, old_size, header);
|
||||
}
|
||||
|
||||
// if we only have one item in the tuple lets return it instead of the tuple
|
||||
if(PyTuple_GET_SIZE(ret) == 1){
|
||||
Py_DECREF(ret);
|
||||
return frames;
|
||||
}else{
|
||||
Py_DECREF(frames);
|
||||
return ret;
|
||||
}
|
||||
return ret;
|
||||
|
||||
}
|
||||
|
||||
|
||||
+7
-1
@@ -34,7 +34,12 @@ typedef struct {
|
||||
uint32_t c;
|
||||
} ClusterAnalysis;
|
||||
|
||||
enum Decoder { MOENCH_03 = 3 };
|
||||
enum DetectorType {
|
||||
DT_GENERIC = 0,
|
||||
DT_MOENCH_03 = 3,
|
||||
DT_MOENCH_04_A = 4,
|
||||
DT_MOENCH_04_AD = 5
|
||||
};
|
||||
|
||||
typedef struct
|
||||
{
|
||||
@@ -55,4 +60,5 @@ typedef struct
|
||||
} Header;
|
||||
|
||||
|
||||
|
||||
#endif
|
||||
+126
-31
@@ -1,13 +1,14 @@
|
||||
#include "raw_reader.h"
|
||||
#include "data_types.h"
|
||||
|
||||
#include <stdbool.h>
|
||||
#include <stdlib.h>
|
||||
#include <string.h>
|
||||
|
||||
int64_t read_raw(FILE *fp, int64_t n_frames, size_t frame_size, char* out_buf, Header* header_out) {
|
||||
|
||||
|
||||
int64_t read_raw_m03(FILE *fp, int64_t n_frames, char *frame_out,
|
||||
Header *header_out) {
|
||||
|
||||
const size_t frame_size = 400 * 400 * 2;
|
||||
char *tmp = malloc(frame_size);
|
||||
Header h;
|
||||
|
||||
@@ -17,9 +18,9 @@ int64_t read_raw(FILE *fp, int64_t n_frames, size_t frame_size, char* out_buf, H
|
||||
if (fread(&h, sizeof(Header), 1, fp) != 1) {
|
||||
break;
|
||||
}
|
||||
if(header_out){
|
||||
memcpy(header_out, &h, sizeof(Header));
|
||||
header_out++;
|
||||
if (header_out) {
|
||||
memcpy(header_out, &h, sizeof(Header));
|
||||
header_out++;
|
||||
}
|
||||
|
||||
// Read frame to temporary buffer
|
||||
@@ -28,9 +29,9 @@ int64_t read_raw(FILE *fp, int64_t n_frames, size_t frame_size, char* out_buf, H
|
||||
}
|
||||
|
||||
// Decode frame and write to numpy output array
|
||||
decode_moench03((uint16_t *)tmp, (uint16_t *)out_buf);
|
||||
decode_moench03((uint16_t *)tmp, (uint16_t *)frame_out);
|
||||
|
||||
out_buf += frame_size;
|
||||
frame_out += frame_size;
|
||||
frames_read++;
|
||||
}
|
||||
|
||||
@@ -38,29 +39,123 @@ int64_t read_raw(FILE *fp, int64_t n_frames, size_t frame_size, char* out_buf, H
|
||||
return frames_read;
|
||||
}
|
||||
|
||||
void decode_moench03(const uint16_t *buf, uint16_t *out_buf)
|
||||
{
|
||||
int adc_numbers[32] = {12, 13, 14, 15, 12, 13, 14, 15, 8, 9, 10, 11, 8, 9, 10, 11,
|
||||
4, 5, 6, 7, 4, 5, 6, 7, 0, 1, 2, 3, 0, 1, 2, 3};
|
||||
for (int n_pixel = 0; n_pixel < 5000; n_pixel++)
|
||||
{
|
||||
int64_t read_raw_m04(FILE *fp, int64_t n_frames, char *frame_out,
|
||||
char *digital_out, Header *header_out) {
|
||||
|
||||
for (int i_sc = 0; i_sc < 32; i_sc++)
|
||||
{
|
||||
// analog part
|
||||
int adc_nr = adc_numbers[i_sc];
|
||||
int col = ((adc_nr * 25) + (n_pixel % 25));
|
||||
int row = 0;
|
||||
if (i_sc / 4 % 2 == 0)
|
||||
{
|
||||
row = 199 - (n_pixel / 25);
|
||||
}
|
||||
else
|
||||
{
|
||||
row = 200 + (n_pixel / 25);
|
||||
}
|
||||
int i_analog = n_pixel * 32 + i_sc;
|
||||
out_buf[row * 400 + col] = buf[i_analog] & 0x3FFF;
|
||||
const size_t frame_size = 400 * 400 * 2;
|
||||
const size_t digital_frame_size = 5000 * 8;
|
||||
char *tmp = malloc(frame_size);
|
||||
char *digital_tmp = malloc(digital_frame_size);
|
||||
Header h;
|
||||
|
||||
int64_t frames_read = 0;
|
||||
#ifdef CR_VERBOSE
|
||||
printf("MOENCH04: digital_out: %p\n", digital_out);
|
||||
#endif
|
||||
while (frames_read < n_frames) {
|
||||
// Read header to temp buffer, return on fail
|
||||
if (fread(&h, sizeof(Header), 1, fp) != 1) {
|
||||
break;
|
||||
}
|
||||
if (header_out) {
|
||||
memcpy(header_out, &h, sizeof(Header));
|
||||
header_out++;
|
||||
}
|
||||
|
||||
// Read frame to temporary buffer
|
||||
if (fread(tmp, frame_size, 1, fp) != 1) {
|
||||
break;
|
||||
}
|
||||
|
||||
if (digital_out) {
|
||||
if (fread(digital_tmp, digital_frame_size, 1, fp) != 1) {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Decode frame and write to numpy output array
|
||||
// decode_moench03((uint16_t *)tmp, (uint16_t *)frame_out);
|
||||
decode_moench04(tmp, digital_tmp, frame_out, digital_out);
|
||||
|
||||
frame_out += frame_size;
|
||||
if (digital_out)
|
||||
digital_out += 400*400; //one byte per pixel
|
||||
|
||||
frames_read++;
|
||||
}
|
||||
|
||||
free(tmp);
|
||||
free(digital_tmp);
|
||||
return frames_read;
|
||||
}
|
||||
|
||||
void decode_moench03(const uint16_t *buf, uint16_t *out_buf) {
|
||||
int adc_numbers[32] = {12, 13, 14, 15, 12, 13, 14, 15, 8, 9, 10,
|
||||
11, 8, 9, 10, 11, 4, 5, 6, 7, 4, 5,
|
||||
6, 7, 0, 1, 2, 3, 0, 1, 2, 3};
|
||||
for (int n_pixel = 0; n_pixel < 5000; n_pixel++) {
|
||||
|
||||
for (int i_sc = 0; i_sc < 32; i_sc++) {
|
||||
// analog part
|
||||
int adc_nr = adc_numbers[i_sc];
|
||||
int col = ((adc_nr * 25) + (n_pixel % 25));
|
||||
int row = 0;
|
||||
if (i_sc / 4 % 2 == 0) {
|
||||
row = 199 - (n_pixel / 25);
|
||||
} else {
|
||||
row = 200 + (n_pixel / 25);
|
||||
}
|
||||
int i_analog = n_pixel * 32 + i_sc;
|
||||
out_buf[row * 400 + col] = buf[i_analog] & 0x3FFF;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void decode_moench04(const uint16_t *analog_data, const uint64_t *digital_data,
|
||||
uint16_t *analog_frame, uint8_t *digital_frame) {
|
||||
|
||||
int adc_numbers[32] = {9, 8, 11, 10, 13, 12, 15, 14, 1, 0, 3,
|
||||
2, 5, 4, 7, 6, 23, 22, 21, 20, 19, 18,
|
||||
17, 16, 31, 30, 29, 28, 27, 26, 25, 24};
|
||||
|
||||
int dbits_bit[32] = {-1, -1, -1, -1, -1, -1, 1, 3, 5, 7, -1,
|
||||
-1, -1, -1, -1, -1, 62, 60, 58, 56, 54, 52,
|
||||
50, 48, 63, 61, 59, 57, 55, 53, 51, 49};
|
||||
|
||||
for (int n_pixel = 0; n_pixel < 5000; n_pixel++) {
|
||||
|
||||
uint64_t current_dbits = digital_data[n_pixel];
|
||||
for (int i_sc = 0; i_sc < 32; i_sc++) {
|
||||
// analog part
|
||||
int adc_nr = adc_numbers[i_sc];
|
||||
int col = ((adc_nr % 16) * 25) + (n_pixel % 25);
|
||||
int row = 0;
|
||||
if (i_sc < 16) {
|
||||
row = 199 - (n_pixel / 25);
|
||||
} else {
|
||||
row = 200 + (n_pixel / 25);
|
||||
}
|
||||
int i_analog = n_pixel * 32 + i_sc;
|
||||
analog_frame[row * 400 + col] = analog_data[i_analog] & 0x3FFF;
|
||||
|
||||
// if we pass digital data to be decoded
|
||||
if (digital_frame) {
|
||||
int bit_loc = dbits_bit[adc_nr];
|
||||
|
||||
if (bit_loc < 0) {
|
||||
digital_frame[row * 400 + col] = 2;
|
||||
} else {
|
||||
uint8_t dbit = (current_dbits >> bit_loc) & 1U;
|
||||
|
||||
if ((6 <= adc_nr) & (adc_nr <= 9)) {
|
||||
digital_frame[row * 400 + col] = dbit;
|
||||
} else {
|
||||
digital_frame[row * 400 + col] = 1 - dbit;
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// digital_frame[row * 400 + col] = 2;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
+21
-2
@@ -1,8 +1,27 @@
|
||||
#pragma once
|
||||
#include <stdbool.h>
|
||||
#include <stdint.h>
|
||||
#include <stdio.h>
|
||||
#include "data_types.h"
|
||||
|
||||
int64_t read_raw(FILE *fp, int64_t n_frames, size_t frame_size, char* out_buf, Header* header_out);
|
||||
int64_t read_raw_m03(
|
||||
FILE *fp,
|
||||
int64_t n_frames,
|
||||
char* frame_out,
|
||||
Header* header_out
|
||||
);
|
||||
|
||||
void decode_moench03(const uint16_t *buf, uint16_t *out_buf);
|
||||
int64_t read_raw_m04(
|
||||
FILE *fp,
|
||||
int64_t n_frames,
|
||||
char* frame_out,
|
||||
char* digital_out,
|
||||
Header* header_out
|
||||
);
|
||||
|
||||
void decode_moench03(const uint16_t *buf, uint16_t *out_buf);
|
||||
|
||||
void decode_moench04(const uint16_t *analog_data,
|
||||
const uint64_t *digital_data,
|
||||
uint16_t *analog_frame,
|
||||
uint8_t *digital_frame);
|
||||
+48
-10
@@ -1,31 +1,69 @@
|
||||
import pytest
|
||||
import os, sys
|
||||
from creader import RawFileReader
|
||||
from creader import RawFileReader, DetectorType
|
||||
from fixtures import data_path
|
||||
import numpy as np
|
||||
|
||||
m03 = DetectorType.MOENCH_03
|
||||
m04a= DetectorType.MOENCH_04_A
|
||||
m04ad= DetectorType.MOENCH_04_AD
|
||||
|
||||
def test_references_on_read(data_path):
|
||||
fname= data_path/'test_d0_f0_0.raw'
|
||||
r = RawFileReader(fname)
|
||||
fname= data_path/'Moench03_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m03)
|
||||
frames = r.read(10)
|
||||
assert sys.getrefcount(frames) == 2 #Over counts by one due to call by reference
|
||||
|
||||
def test_references_on_read_with_header(data_path):
|
||||
fname= data_path/'test_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, header = True)
|
||||
fname= data_path/'Moench03_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m03, header = True)
|
||||
frames, header = r.read(100)
|
||||
assert sys.getrefcount(frames) == 2 #Over counts by one due to call by reference
|
||||
assert sys.getrefcount(header) == 2
|
||||
|
||||
def test_reading_frame_numbers(data_path):
|
||||
fname= data_path/'test_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, header = True)
|
||||
fname= data_path/'Moench03_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, header = True, detector_type = m03)
|
||||
frames, header = r.read(1000)
|
||||
assert (header['Frame Number'] == np.arange(201,1201, dtype = np.uint64)).all()
|
||||
|
||||
def test_reading_more_files_than_available(data_path):
|
||||
fname= data_path/'test_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, header = True)
|
||||
fname= data_path/'Moench03_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m03, header = True)
|
||||
frames, header = r.read(1500)
|
||||
assert frames.shape == (1000,400, 400)
|
||||
assert header.size == 1000
|
||||
assert header.size == 1000
|
||||
|
||||
def test_references_on_m04_a(data_path):
|
||||
fname= data_path/'Moench04_no_digital_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m04a)
|
||||
frames = r.read(3)
|
||||
assert sys.getrefcount(frames) == 2 #Over counts by one due to call by reference
|
||||
assert frames.shape == (3,400,400)
|
||||
|
||||
def test_references_on_m04_a_with_heaer(data_path):
|
||||
fname= data_path/'Moench04_no_digital_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m04a, header = True)
|
||||
frames, header = r.read(7)
|
||||
assert sys.getrefcount(frames) == 2 #Over counts by one due to call by reference
|
||||
assert frames.shape == (7,400,400)
|
||||
|
||||
assert sys.getrefcount(header) == 2
|
||||
assert header.size == 7
|
||||
|
||||
def test_references_on_m04_ad(data_path):
|
||||
fname= data_path/'Moench04_digital_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m04ad)
|
||||
analog, digital = r.read(3)
|
||||
assert sys.getrefcount(analog) == 2 #Over counts by one due to call by reference
|
||||
assert analog.shape == (3,400,400)
|
||||
assert sys.getrefcount(digital) == 2
|
||||
|
||||
def test_references_on_m04_ad_with_header(data_path):
|
||||
fname= data_path/'Moench04_digital_d0_f0_0.raw'
|
||||
r = RawFileReader(fname, m04ad, header = True)
|
||||
analog, digital, header = r.read(3)
|
||||
assert sys.getrefcount(analog) == 2 #Over counts by one due to call by reference
|
||||
assert analog.shape == (3,400,400)
|
||||
assert sys.getrefcount(digital) == 2
|
||||
assert sys.getrefcount(header) == 2
|
||||
Reference in new issue
Block a user