#!/usr/bin/env python
# coding: utf-8

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filename = r'data/dsdna_d7+d17_50_50_1.spc'


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get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib.pyplot as plt
import numpy as np


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import phconvert as phc
phc.__version__


# # Author

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author = 'Eitan Lerner'
author_affiliation = 'UCLA'
creator = 'Antonino Ingargiola'
creator_affiliation = 'UCLA'


# # Sample

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comment = 'A demostrative smFRET-nsALEX measurement.'
sample_name = '50-50 mixture of two FRET samples'
dye_names = ['ATTO550', 'ATTO647N']
buffer_name = 'TE50'


# # Prepare data
# 
# ## Read the data

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d, meta = phc.loader.nsalex_bh(filename,
                               donor = 4,
                               acceptor = 6,
                               laser_repetition_rate = 40e6,
                               tcspc_range = 60e-9,
                               timestamps_unit = 60e-9,
                               alex_period_donor = (270, 1500),
                               alex_period_acceptor = (1800, 3300),
                               excitation_wavelengths = (532e-9, 635e-9),
                               detection_wavelengths = (580e-9, 680e-9),
                               time_reversed = False,
                               allow_missing_set = False)


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fig, ax = plt.subplots(figsize=(13, 4))
phc.plotter.alternation_hist(d, ax=ax)


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detectors = d['photon_data']['detectors']
print('Detector numbers: ', np.unique(detectors))


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print("Detector    Counts")
print("--------   --------")
for det, count in zip(*np.unique(detectors, return_counts=True)):
    print("%8d   %8d" % (det, count))


# ## Add author and sample info

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d['comment'] = comment

d['sample'] = dict(
    sample_name=sample_name,
    dye_names=[n.encode() for n in dye_names],
    buffer_name=buffer_name,
    num_dyes = len(dye_names))

d['identity'] = dict(
    author=author,
    author_affiliation=author_affiliation,
    creator=creator,
    creator_affiliation=creator_affiliation)


# # Validate the Photon-HDF5 structure
# 
# Before writing to disk, we assure the file structure follows the Photon-HDF5 format:

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phc.hdf5.assert_valid_photon_hdf5(d)  # Throws an error if not valid!


# # Save to Photon-HDF5

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phc.hdf5.save_photon_hdf5(d, close=False)


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#d['_data_file'].close()


# ## Save info from .SET file in `/user/bh_params`

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h5file = d['_data_file']


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h5file.create_group('/', 'user')
bh_group = h5file.create_group('/user', 'becker_hickl')


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phc.hdf5.dict_to_group(bh_group, meta)


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#h5file.close()


# ## Print HDF5 file content

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phc.hdf5.print_children(h5file, '/user')


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phc.hdf5.print_children(h5file, '/user/becker_hickl/identification')


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#phc.hdf5.print_children(h5file, '/user/becker_hickl/sys_params')


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phc.hdf5.dict_from_group(h5file.root.user.becker_hickl.identification)


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#phc.hdf5.dict_from_group(h5file.root.user.becker_hickl.sys_params)


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h5file.close()


# # Load Photon-HDF5

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from pprint import pprint


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filename = d['_data_file'].filename


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h5data = phc.hdf5.load_photon_hdf5(filename)


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phc.hdf5.dict_from_group(h5data.identity)


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phc.hdf5.dict_from_group(h5data.setup)


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pprint(phc.hdf5.dict_from_group(h5data.photon_data))


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