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137 lines
3.4 KiB
Python
137 lines
3.4 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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plt.ion()
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import aare
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from aare import CtbRawFile
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print('aare imported')
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from aare import transform
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print('transform imported')
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from pathlib import Path
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import json
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def decode(frames, rawdata):
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# rawdata = np.fromfile(f, dtype = np.uint16)
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counters = int((np.shape(rawdata)[0]/frames-56)/(48*48))
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print('Counters:', counters)
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rawdata = rawdata.reshape(frames,-1)[:,56:]
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rawdata = rawdata.reshape(frames,576*counters,4) #Data come in "blocks" of 4 pixels/receiver
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tr1 = rawdata[:,0:576*counters:2] #Transceiver1
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tr1=tr1.reshape((frames,48*counters,24))
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tr2 = rawdata[:,1:576*counters:2] #Transceiver2
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tr2=tr2.reshape((frames,48*counters,24))
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data = np.append(tr1,tr2,axis=2)
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return data
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def get_Mh02_frames(fname):
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# this function gives you the data from a file that is not a scan
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# it returns a (frames,48*counters,48)
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jsonf = open(fname)
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jsonpar = json.load(jsonf)
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jsonf.close()
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frames=jsonpar["Frames in File"]
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print('Frames:', frames)
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rawf = fname.replace('master','d0_f0')
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rawf = rawf.replace('.json','.raw')
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with open(rawf, 'rb') as f:
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rawdata = np.fromfile(f, dtype = np.uint16)
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data = decode(frames, rawdata)
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print('Data:', np.shape(data))
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return data
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#target format
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# [frame, counter, row, col]
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# plt.imshow(data[0,0])
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# p = Path('/Users/erik/data/aare_test_data/jungfrau/jungfrau_single_master_0.json')
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# f = aare.File(p)
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# frame = f.read_frame()
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# fig, ax = plt.subplots()
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# im = ax.imshow(frame, cmap='viridis')
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# fpath = Path('/Users/erik/data/Moench03old/test_034_irradiated_noise_g4_hg_exptime_2000us_master_0.json')
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# # fpath = Path('/Users/erik/data/Moench05/moench05_multifile_master_0.json')
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# # f = aare.CtbRawFile(fpath, transform = transform.moench05)
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# # with CtbRawFile(fpath, transform = transform.moench05) as f:
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# # for header, image in f:
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# # print(f'Frame number: {header["frameNumber"]}')
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# # m = aare.RawMasterFile(fpath)
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# f = aare.File(fpath)
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# cf = aare.ClusterFinder((400,400),(3,3))
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# for i in range(100):
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# cf.push_pedestal_frame(f.read_frame())
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# f.seek(0)
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# pd = f.read_n(100).mean(axis=0)
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# clusters = cf.find_clusters_without_threshold(f.read_frame())
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base = Path('/Users/erik/data/matterhorn/raw')
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fpath = Path(base / 'scan_15keV_vrf700_vrsh700_th0_master_0.json')
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f = aare.CtbRawFile(fpath, transform=transform.matterhorn02)
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f.seek(100)
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header1, image1 = f.read_frame()
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fpath = Path(base / 'scan_all15keV_vrf500_vrsh700_th0_master_0.json')
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f = aare.CtbRawFile(fpath, transform=transform.matterhorn02)
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f.seek(100)
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header4, image4 = f.read_frame()
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# n_counters = image.shape[1] / 48**2 / 2
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# for i in range(100):
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# header, image = f.read_frame()
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# print(header['frameNumber'])
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#Data come in "blocks" of 4 pixels/receiver
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data = get_Mh02_frames(fpath.as_posix())
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# rawi = np.zeros(48*48*4+56, dtype = np.uint16)
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# for i,v in enumerate(rawi[56:]):
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# rawi[i+56] = i
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# raw = image.view(np.uint16)
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# pixel_map = decode(1, rawi)
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# # img = np.take(raw, pixel_map)
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# pm = np.zeros((4, 48,48), dtype = np.int64)
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# for counter in range(4):
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# for row in range(48):
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# for col in range(48):
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# pm[counter, row, col] = row*48 + col+counter*48*48
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f2 = aare.CtbRawFile(fpath, transform=transform.matterhorn02)
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header, data = f2.read()
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plt.plot(data[:,0,20,20])
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