opentimspy package¶
Submodules¶
opentimspy.opentims module¶
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class
opentimspy.opentims.OpenTIMS(analysis_directory)¶ Bases:
object-
frame2retention_time(frames)¶
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frame_array(frame)¶ Get a 2D array of data for a given frame.
- Parameters
frame (int, iterable, slice) – Frame to output.
- Returns
Array with 4 columns: frame numbers, scan numbers, time of flights, and intensities in the selected frame.
- Return type
np.array
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frame_arrays(frames)¶ Get raw data from a selection of frames.
Contains only those types that share the underlying type (uint32), which consists of ‘frame’,’scan’,’tof’, and ‘intensity’.
- Parameters
frames (iterable) – Frames to chose.
- Returns
raw data from the selection of frames.
- Return type
np.array
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frame_arrays_slice(frames_slice)¶ Get raw data from a slice of frames.
Contains only those types that share the underlying type (uint32), which consists of ‘frame’,’scan’,’tof’, and ‘intensity’.
- Parameters
frames_slice (slice) – A slice defining which frames to chose.
- Returns
raw data from the selection of frames.
- Return type
np.array
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framesTIC()¶ Get the Total Ion Current for each frame.
- Returns
Total Ion Current values per each frame (sums of intensities for each frame).
- Return type
np.array
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get_hash(columns=('frame', 'scan', 'tof', 'intensity'), algo=<class '_blake2.blake2b'>)¶ Calculate a data-set-wide hash.
Defaults to raw data that are all uint32.
- Parameters
columns (list) – Columns for which to calculate the hash.
algo (object) – Class with a call method for restarting hash calculations and an update method that accepts data.
- Returns
A hash.
- Return type
binary str
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get_hashes(columns=('frame', 'scan', 'tof', 'intensity'), algo=<class '_blake2.blake2b'>)¶ Calculate a hashes for each frame.
Defaults to raw data that are all uint32.
- Parameters
columns (list) – Columns for which to calculate the hash.
algo (object) – Class with a call method for restarting hash calculations and an update method that accepts data.
- Returns
Frame specifc hashes.
- Return type
list
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peaks_per_frame_cnts(frames, convert=True)¶ Return the numbers of peaks in chosen frames.
- Parameters
frames (list) – frames to extract the number of peaks from.
- Returns;
np.array: Number of peaks in each frame.
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query(frames, columns=('frame', 'scan', 'tof', 'intensity', 'mz', 'inv_ion_mobility', 'retention_time'))¶ Get data from a selection of frames.
- Parameters
frames (int, iterable) – Frames to choose. Passing an integer results in extracting that one frame.
columns (tuple) – which columns to extract? Defaults to all possible columns.
- Returns
columns to numpy array mapping.
- Return type
dict
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query_iter(frames, columns=('frame', 'scan', 'tof', 'intensity', 'mz', 'inv_ion_mobility', 'retention_time'))¶ Iterate data from a selection of frames.
- Parameters
frames (int, iterable, slice) – Frames to choose. Passing an integer results in extracting that one frame.
columns (tuple) – which columns to extract? Defaults to all possible columns.
- Yields
dict – columnt to numpy array mapping.
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rt_query(min_retention_time, max_retention_time, columns=('frame', 'scan', 'tof', 'intensity', 'mz', 'inv_ion_mobility', 'retention_time'))¶ Get data from a selection of frames based on retention times.
Get all frames corresponding to retention times in a set “[min_retention_time, max_retention_time)”.
- Parameters
min_retention_time (float) – Minimal retention time.
max_retention_time (float) – Maximal retention time to choose.
columns (tuple) – which columns to extract? Defaults to all possible columns.
- Returns
column to numpy array mapping.
- Return type
dict
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rt_query_iter(min_retention_time, max_retention_time, columns=('frame', 'scan', 'tof', 'intensity', 'mz', 'inv_ion_mobility', 'retention_time'))¶ Iterate data from a selection of frames based on retention times.
Get all frames corresponding to retention times in a set “[min_retention_time, max_retention_time)”.
- Parameters
min_retention_time (float) – Minimal retention time.
max_retention_time (float) – Maximal retention time to choose.
columns (tuple) – which columns to extract? Defaults to all possible columns.
- Yields
dict – column to numpy array mapping.
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opentimspy.opentims.hash_frame(X, columns=('frame', 'scan', 'tof', 'intensity'), algo=<class '_blake2.blake2b'>)¶