-
-
Notifications
You must be signed in to change notification settings - Fork 14
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Implement reader for PicoQuant cor files (#199)
* Update numpy to >v1, add PicoQuant cor format * Add more descriptive file type wildcard to gui * Update docstring for accuracy
- Loading branch information
Showing
10 changed files
with
151 additions
and
51 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,97 @@ | ||
| """PicoQuant .cor files""" | ||
| import csv | ||
| import pathlib | ||
| import warnings | ||
|
|
||
| import numpy as np | ||
|
|
||
| class LoadCORError(BaseException): | ||
| pass | ||
|
|
||
| def get_header_index(L, elem): | ||
| try: | ||
| index = L.index(elem) | ||
| except ValueError: | ||
| raise ValueError(f'Expected {elem} in the data header, but found only {L}') | ||
|
|
||
| return index | ||
|
|
||
| def openCOR(path, filename=None): | ||
| """ | ||
| Read data from a PicoQuant .cor file. | ||
| This format consists of a metadata header, a blank line, then a | ||
| whitespace-delimited data header followed by a data array. | ||
| ------------------------------------------------------------ | ||
| TTTR Correlator Export | ||
| PicoHarp Software version 3.0.0.3 format version 3.0 | ||
| Raw data: c:\\users\\baker lab 432-a\\desktop\\grant fcs\\default_013.ptu | ||
| Recorded: 16/12/22 17:40:13 | ||
| Mode: T2 | ||
| Routing Mask A: 0 1 0 0 0 | ||
| Routing Mask B: 1 0 0 0 0 | ||
| Start time [s]: 0.000000 | ||
| Time span [s]: 7.545534 | ||
| Counts A: 382989 | ||
| Counts B: 523316 | ||
| Tau resolution [s]: 0.00000002500000 | ||
| taustep tau/s G(A,A) G(B,B) G(A,B) | ||
| 6 0.0000001500 0.8375 0.3556 0.1708 | ||
| 7 0.0000001750 0.6503 0.2652 0.1445 | ||
| 9 0.0000002250 0.5680 0.2173 0.1264 | ||
| 11 0.0000002750 0.4836 0.1594 0.1614 | ||
| 13 0.0000003250 0.3241 0.1528 0.1486 | ||
| 15 0.0000003750 0.2819 0.1236 0.1641 | ||
| 17 0.0000004250 0.3591 0.1467 0.1102 | ||
| [...] | ||
| ------------------------------------------------------------ | ||
| Returns: | ||
| A dictionary containing: | ||
| Trace: list of 2d np.array containing two columns: | ||
| 1st: tau in ms | ||
| 2nd: corresponding correlation signal | ||
| Type: list of strings indictating the type of each correlation | ||
| Filename: the basename for each file loaded | ||
| Trace: blank list, since cor does not store intensity traces | ||
| """ | ||
| path = pathlib.Path(path) | ||
| if filename is not None: | ||
| warnings.warn("Using `filename` is deprecated.", DeprecationWarning) | ||
| path = path / filename | ||
| filename = path.name | ||
|
|
||
| s_to_ms = 1000 # cor provides seconds, we want ms | ||
|
|
||
| corfile = path.open('r', encoding='utf-8') | ||
| header = list() | ||
| for line in corfile: | ||
| header.append(line.strip()) | ||
| if header[-1] == '': | ||
| break | ||
|
|
||
| if header[0] != 'TTTR Correlator Export': | ||
| raise ValueError(f'Error while reading {path.name}. Expected the first line to be "TTTR Correlator Export"') | ||
|
|
||
| data_header = next(corfile).split() | ||
| data = np.loadtxt(corfile) | ||
|
|
||
| tau = data[:, get_header_index(data_header, 'tau/s')]*s_to_ms | ||
| correlation_names = ['G(A,A)', 'G(A,B)', 'G(B,B)'] | ||
| correlation_types = ['AC', 'CC', 'AC' ] | ||
| correlations = list() | ||
|
|
||
| for correlation_name in correlation_names: | ||
| correlation = data[:, get_header_index(data_header, correlation_name)] | ||
| cor = np.zeros((len(correlation), 2), dtype=correlation.dtype) | ||
| cor[:, 0] = tau | ||
| cor[:, 1] = correlation | ||
| correlations.append(cor) | ||
|
|
||
| dictionary = dict() | ||
| dictionary['Correlation'] = correlations | ||
| dictionary['Trace'] = [[] for _ in dictionary['Correlation']] | ||
| dictionary['Type'] = correlation_types | ||
| dictionary['Filename'] = [path.name for _ in dictionary['Correlation']] | ||
| return dictionary |