McsPyDataTools API Reference

McsPy

McsPy is a Python module/package to read, handle and operate on HDF5-based raw data files converted from recordings of devices of the Multi Channel Systems MCS GmbH.

copyright:

3. 2022 by Multi Channel Systems MCS GmbH

license:

see LICENSE for more details

class McsPy.McsHdf5Protocols

Class of supported MCS-HDF5 protocol types and version ranges

Entry: (Protocol Type Name => Tuple of supported version range from (including) the first version entry up to (including) the second version entry)

classmethod check_hdf5_protocol_version(protocol_name, version)

Check if the given version of the HDF5 protocol is supported

Parameters:

• protocol_name – name of the protocol that is tested
• version – version number that should be checked

Returns:

is true if the given protocol and version is supported

classmethod check_protocol_type_version(protocol_type_name, version)

Check if the given version of a protocol is supported by the implementation

Parameters:

• protocol_type_name – name of the protocol that is tested
• version – version number that should be checked

Returns:

is true if the given protocol and version is supported

class McsPy.McsHdf5Types

Class of supported MCS-HDF5 file structure types and version ranges

Entry: (Protocol TypeID => Tuple of supported version range from (including) the first version entry up to (including) the second version entry)

classmethod get_mcs_class_name(typeID)

Returns the McsPy class name, that corresponds to a given Mcs HDF5 file structure type. The function also checks if the requested class supports the Mcs HDF5 file structure type version

Parameters:typeID – name of the type that is tested Returns:a McsCMOSMEA class if the given type and version is supported

The ‘’McsData’’ module

class McsPy.McsData.RawData(raw_data_path)

This class holds the information of a complete MCS raw data file

Parameters:

• raw_data_path – path to the HDF5 file
• h5_file – h5py File handle
• mcs_hdf5_protocol_type – protocol type. Currently, only “RawData” is supported
• mcs_hdf5_protocol_type_version – protocol version
• comment – comment string
• clr_date – recording date string
• date_in_clr_ticks – recording date in CLR ticks (100 ns)
• date – datetime object representing the recording date
• file_guid – file GUID
• mea_layout – name of the MEA layout
• mea_sn – serial number of the MEA
• mea_name – name of the MEA
• program_name – name of the recording software that created the file
• program_version – version of the recording software that created the file

recordings

Access recordings

class McsPy.McsData.Recording(recording_grp)

Container class for one recording

Parameters:

• comment – recording comment
• duration – duration of the recording in microseconds
• label – recording label
• recording_id – recording ID
• recording_type – recording type
• timestamp – recording timestamp

Provides the content of the HDF5 Folder “Recording_x” in Python.

analog_streams

Access all analog streams - collection of AnalogStream objects

frame_streams

Access all frame streams - collection of FrameStream objects

event_streams

Access event streams - collection of EventStream objects

segment_streams

Access segment streams - collection of SegementStream objects

timestamp_streams

Access timestamp streams - collection of TimestampStream objects

duration_time

Duration of the recording

Data-Stream-Structures containing the data

class McsPy.McsData.Stream(stream_grp, info_type_name=None)

Base class for all stream types

class McsPy.McsData.AnalogStream(stream_grp)

Container class for one analog stream of several channels. Description for each channel is provided by a channel-associated object of ChannelInfo

Parameters:

• channel_data – numpy array (channels x samples) with channel data
• timestamp_index – numpy array (segment x 3) defining the timestamps for each data segment as [first_timestamp, first_index, last_index]. Interpretation: All samples in channel_data between first_index and last_index (inclusive) are in a continuous data segment and the timestamp of the samples at first_index is first_timestamp
• channel_infos – dict with channel metadata. Key: ChannelID, Value: ChannelInfo object
• info_version – version of the Info structure
• data_subtype – type of stream data (“Electrode”, “Auxiliary”, “Digital”, …)
• label – the stream label
• source_stream_guid – the GUID of the source stream
• stream_guid – the stream GUID
• stream_type – the stream type (“Analog”)

Provides the content of the HDF5 Sub-folder “Stream_x” of “AnalogStream” in Python.

get_channel(channel_id)

Get the signal of the given channel over the course of time and in its measured range.

Parameters:channel_id – ID of the channel Returns:Tuple (vector of the signal, unit of the values)

get_channel_in_range(channel_id, idx_start=0, idx_end=None)

Get the signal of the given channel over the course of time and in its measured range.

Parameters:

• channel_id – ID of the channel
• idx_start – index of the first sampled signal value that should be returned (0 <= idx_start < idx_end <= count samples). Default: 0
• idx_end – index of the last sampled signal value that should be returned (0 <= idx_start < idx_end <= count samples). Default: None (= last index)

Returns:

Tuple (vector of the signal, unit of the values)

get_channel_sample_timestamps(channel_id, idx_start=0, idx_end=None)

Get the timestamps of the sampled values.

Parameters:

• channel_id – ID of the channel
• idx_start – index of the first signal timestamp that should be returned (0 <= idx_start < idx_end <= count samples). Default: 0
• idx_end – index of the last signal timestamp that should be returned (0 <= idx_start < idx_end <= count samples). Default: None (= last index)

Returns:

Tuple (vector of the timestamps, unit of the timestamps)

class McsPy.McsData.FrameStream(stream_grp)

Container class for one frame stream with different entities

Parameters:

• frame_entity – list of FrameEntity objects
• info_version – version of the Info structure
• data_subtype – type of stream data
• label – the stream label
• source_stream_guid – the GUID of the source stream
• stream_guid – the stream GUID
• stream_type – the stream type (“Frame”)

Provides the content of the HDF5 Subfolder “Stream_x” of “FrameStream” in Python.

class McsPy.McsData.FrameEntity(frame_entity_group, frame_info)

Contains the stream of a specific frame entity. Meta-Information for this entity is available via an associated object of FrameEntityInfo

Parameters:

• data – numpy array (sensors_X x sensors_Y x time) of sensor data in ADC steps. Multiply with info.conversion_factors to get voltages.
• info – FrameEntityInfo object with Frame metadata
• timestamp_index – start timestamp of the Frame

Provides the content of the HDF5 Subfolder “Stream_x” of “FrameStream” and Subfolder “FrameDataEntity_x” in Python.

get_sensor_signal(sensor_x, sensor_y, idx_start, idx_end)

Get the signal of a single sensor over the curse of time and in its measured range.

Parameters:

• sensor_x – x coordinate of the sensor
• sensor_y – y coordinate of the sensor
• idx_start – index of the first sampled frame that should be returned (0 <= idx_start < idx_end <= count frames)
• idx_end – index of the last sampled frame that should be returned (0 <= idx_start < idx_end <= count frames)

Returns:

Tuple (vector of the signal, unit of the values)

get_frame_timestamps(idx_start, idx_end)

Get the timestamps of the sampled frames.

Parameters:

• idx_start – index of the first sampled frame that should be returned (0 <= idx_start < idx_end <= count frames)
• idx_end – index of the last sampled frame that should be returned (0 <= idx_start < idx_end <= count frames)

Returns:

Tuple (vector of the timestamps, unit of the timestamps)

class McsPy.McsData.EventStream(stream_grp)

Container class for one event stream with different entities

Parameters:

• event_entity – dict of event entities. Key: event ID, value: a EventEntity object
• info_version – version of the Info structure
• data_subtype – type of stream data (“DigitalInput”, “UserData”, …)
• label – the stream label
• source_stream_guid – the GUID of the source stream
• stream_guid – the stream GUID
• stream_type – the stream type (“Event”)

Provides the content of the HDF5 Subfolder “Stream_x” of “EventStream” in Python.

class McsPy.McsData.EventEntity(event_data, event_info)

Contains the event data of a specific entity. Meta-Information for this entity is available via an associated object of EventEntityInfo

Parameters:

• data – numpy array (5 x n_events) of event data. row 0: event timestamp in microsecond; row 1: event duration in microseconds; row 2: event type; row 3-4: reserved
• info – EventEntityInfo object with the event metadata

Maps data event entity content of the HDF5 Subfolder “Stream_x” of “EventStream” to Python structures.

count

Number of contained events

get_events(idx_start=None, idx_end=None)

Get all n events of this entity of the given index range (idx_start <= idx < idx_end)

Parameters:

• idx_start – start index of the range (including), if nothing is given -> 0
• idx_end – end index of the range (excluding, if nothing is given -> last index

Returns:

Tuple of (2 x n matrix of timestamp (1. row) and duration (2. row), Used unit of time)

get_event_timestamps(idx_start=None, idx_end=None)

Get all n event timestamps of this entity of the given index range

Parameters:

• idx_start – start index of the range, if nothing is given -> 0
• idx_end – end index of the range, if nothing is given -> last index

Returns:

Tuple of (n-length array of timestamps, Used unit of time)

get_event_durations(idx_start=None, idx_end=None)

Get all n event durations of this entity of the given index range

Parameters:

• idx_start – start index of the range, if nothing is given -> 0
• idx_end – end index of the range, if nothing is given -> last index

Returns:

Tuple of (n-length array of duration, Used unit of time)

class McsPy.McsData.SegmentStream(stream_grp)

Container class for one segment stream of different segment entities

Parameters:

• segment_entity – dict of segment entities. Key: segment ID, value: for data_subtype == “Cutout”: SegmentEntity object, for data_subtype == “Average: AverageSegmentEntity object
• info_version – version of the Info structure
• data_subtype – type of stream data (“Cutout”, “Average”, …)
• label – the stream label
• source_stream_guid – the GUID of the source stream
• stream_guid – the stream GUID
• stream_type – the stream type (“Segment”)

Provides the content of the HDF5 Subfolder “Stream_x” of “SegmentStream” in Python.

class McsPy.McsData.SegmentEntity(segment_data, segment_ts, segment_info)

Segment entity class, Meta-Information for this entity is available via an associated object of SegmentEntityInfo

Parameters:

• data – numpy array (n_segments x samples) or (n_segments x n_multi x samples) with segment data
• data_ts – numpy vector (n_segments) with timestamps for every segment
• info –

  segment metadata as a SegmentEntityInfo object

  DataSubType != Average → Maps segement entity content of the HDF5 Subfolder “Stream_x” of “SegmentStream” to Python structures.

segment_sample_count

Number of contained samples of segments (2d) or multi-segments (3d)

segment_count

Number of segments that are sampled for one time point (2d) -> 1 and (3d) -> n

get_segment_in_range(segment_id, flat=False, idx_start=None, idx_end=None)

Get the a/the segment signals in its measured range.

Parameters:

• segment_id – id resp. number of the segment (0 if only one segment is present or the index inside the multi-segment collection)
• flat – true -> one-dimensional vector of the sequentially ordered segments, false -> k x n matrix of the n segments of k sample points
• idx_start – index of the first segment that should be returned (0 <= idx_start < idx_end <= count segments)
• idx_end – index of the last segment that should be returned (0 <= idx_start < idx_end <= count segments)

Returns:

Tuple (of a flat vector of the sequentially ordered segments or a k x n matrix of the n segments of k sample points depending on the value of flat , and the unit of the values)

get_segment_sample_timestamps(segment_id, flat=False, idx_start=None, idx_end=None)

Get the timestamps of the sample points of the measured segment.

Parameters:

• segment_id – id resp. number of the segment (0 if only one segment is present or the index inside the multi-segment collection)
• flat – true -> one-dimensional vector of the sequentially ordered segment timestamps, false -> k x n matrix of the k timestamps of n segments
• idx_start – index of the first segment for that timestamps should be returned (0 <= idx_start < idx_end <= count segments)
• idx_end – index of the last segment for that timestamps should be returned (0 <= idx_start < idx_end <= count segments)

Returns:

Tuple (of a flat vector of the sequentially ordered segments or a k x n matrix of the n segments of k sample points depending on the value of flat , and the unit of the values)

class McsPy.McsData.AverageSegmentTuple(mean, std_dev, time_tick_unit, signal_unit)

Named tuple that describe one or more average segments (mean, std_dev, time_tick_unit, signal_unit).

Note

• mean - mean signal values
• std_dev - standard deviation of the signal value (it is 0 if there was only one sample segment)
• time_tick_unit - sampling interval with time unit
• signal_unit - measured unit of the signal

mean

Alias for field number 0

signal_unit

Alias for field number 3

std_dev

Alias for field number 1

time_tick_unit

Alias for field number 2

class McsPy.McsData.AverageSegmentEntity(segment_average_data, segment_average_annotation, segment_info)

Contains a number of signal segments that are calcualted as averages of number of segments occured in a given time range. Meta-Information for this entity is available via an associated object of SegmentEntityInfo

Parameters:

• data – numpy array (2 x n_samples x n_averages) with averages and standard deviations. First row is the mean per sample data, second row is the standard deviation per sample data.
• data_annotation – numpy array (3 x n_averages) with metadata describing how each average was created. row 0 and 1: start and end timestamp in microseconds of the time window in which signal segments were averaged. row 2: number of averaged signal segments in this time window
• info – metadata for the average as a SegmentEntityInfo object

DataSubType == Average → Maps segment entity content of the HDF5 DataSubType-Average: Subfolder “Stream_x” of “SegmentStream” to Python structures.

number_of_averages

Number of average segments inside this average entity

sample_length

Number of sample points of an average segment

time_ranges()

List of time range tuples for all contained average segments

Returns:List of tuple with start and end time point

time_range(average_segment_idx)

Get the time range for that the average segment was calculated

Parameters:average_segment_idx – index resp. number of the average segment Returns:Tuple with start and end time point

average_counts()

List of counts of samples for all contained average segments

Parameters:average_segment_idx – id resp. number of the average segment Returns:sample count

average_count(average_segment_idx)

Count of samples that were used to calculate the average

Parameters:average_segment_idx – id resp. number of the average segment Returns:sample count

get_scaled_average_segments()

Get all contained average segments in its measured physical range.

Returns:AverageSegmentTuple containing the k x n matrices for mean and standard deviation of all contained average segments n with the associated sampling and measuring information

get_scaled_average_segment(average_segment_idx)

Get the selected average segment in its measured physical range.

Parameters:segment_idx – index resp. number of the average segment Returns:AverageSegmentTuple containing the mean and standard deviation vector of the average segment with the associated sampling and measuring information

get_average_segments()

Get all contained average segments AD-offset in ADC values with its measuring conditions

Returns:AverageSegmentTuple containing the mean and standard deviation vector of the average segment in ADC steps with sampling tick and ADC-Step definition

get_average_segment(average_segment_idx)

Get the AD-offset corrected average segment in ADC values with its measuring conditions

Parameters:segment_id – id resp. number of the segment Returns:AverageSegmentTuple containing the k x n matrices for mean and standard deviation of all contained average segments in ADC steps with sampling tick and ADC-Step definition

class McsPy.McsData.TimeStampStream(stream_grp)

Container class for one timestamp stream with different entities

Parameters:

• timestamp_entity – dict of timestamp entities. Key: timestamp ID, value: a TimeStampEntity object
• info_version – version of the Info structure
• data_subtype – type of stream data
• label – the stream label
• source_stream_guid – the GUID of the source stream
• stream_guid – the stream GUID
• stream_type – the stream type (“Timestamp”)

Provides the content of the HDF5 Subfolder “Stream_x” of “TimeStampStream” in Python.

class McsPy.McsData.TimeStampEntity(timestamp_data, timestamp_info)

Time-Stamp entity class, Meta-Information for this entity is available via an associated object of TimestampEntityInfo

Parameters:

• data – numpy vector (n_timestamps) with timestamp data
• info – timestamp metadata as a TimeStampEntityInfo object

Maps data timestamp entity data of the HDF5 Subfolder “Stream_x” of “TimeStampStream” to Python structures.

count

Number of contained timestamps

get_timestamps(idx_start=None, idx_end=None)

Get all n time stamps of this entity of the given index range (idx_start <= idx < idx_end)

Parameters:

• idx_start – start index of the range (including), if nothing is given -> 0
• idx_end – end index of the range (excluding, if nothing is given -> last index

Returns:

Tuple of (n-length array of timestamps, Used unit of time)

Info-Classes containing Meta-Information for the data

class McsPy.McsData.Info(info_data)

Base class of all info classes

Derived classes contain meta information for data structures and fields.

get_field(name)

Get the field with that name -> access to the raw info array

group_id

Get the id of the group that the objects belongs to

label

Label of this object

data_type

Raw data type of this object

class McsPy.McsData.ChannelInfo(info_version, info)

Contains all describing meta data for one sampled channel

Parameters:info – dict containing the channel metadata

channel_id

Get the ID of the channel

row_index

Get the index of the row that contains the associated channel data inside the data matrix

adc_step

Size and unit of one ADC step for this channel

version

Version number of the Type-Definition

class McsPy.McsData.InfoSampledData(info)

Base class of all info classes for evenly sampled data

sampling_frequency

Get the used sampling frequency in Hz

sampling_tick

Get the used sampling tick

class McsPy.McsData.EventEntityInfo(info_version, info)

Contains all meta data for one event entity

Parameters:info – dict containing the event metadata

id

Event ID

raw_data_bytes

Length of raw data in bytes

source_channel_ids

IDs of all channels that were involved in the event generation.

source_channel_labels

Labels of the channels that were involved in the event generation.

version

Version number of the type definition

class McsPy.McsData.SegmentEntityInfo(info_version, info, source_channel_infos)

Contains all meta data for one segment entity

Parameters:

• info – dict containing the segment metadata
• source_channel_of_segment – dict containing the channel metadata for each source channel of the segment. Key: source channel index, value: ChannelInfo object

id

Segment ID

pre_interval

Interval [start of the segment <- defining event timestamp]

post_interval

Interval [defining event timestamp -> end of the segment]

type

Type of the segment like ‘Average’ or ‘Cutout’

count

Count of segments inside the segment entity

version

Version number of the Type-Definition

class McsPy.McsData.TimeStampEntityInfo(info_version, info)

Contains all meta data for one timestamp entity

Parameters:info – dict containing the timestamp metadata

id

Timestamp entity ID

unit

Unit in which the timestamps are measured

exponent

Exponent for the unit in which the timestamps are measured

measuring_unit

Unit in which the timestamp entity was measured

data_type

DataType for the timestamps

source_channel_ids

ID’s of all channels that were involved in the timestamp generation.

source_channel_labels

Labels of the channels that were involved in the timestamp generation.

version

Version number of the Type-Definition

The ‘’McsCMOSMEA’’ module

class McsPy.McsCMOSMEA.McsCMOSMEAData(cmos_data_path)

This class holds the information of a complete MCS CMOS-MEA data file system

classmethod sensorID_to_coordinates(sensorID)

Computes the [x,y] chip coordinates of a sensor. Note: both, sensor IDs and coordinates are base 1

classmethod coordinates_to_sensorID(row: int, col: int) → int

Computes the sensor ID for row and column coordinates. Note: sensor IDs and rows and columns are base 1

class McsPy.McsCMOSMEA.McsGroup(h5py_group_object)

this class subclasses the h5py.Group object and extends it with McsPy toolbox functionality

class IDSetGroup(h5py, mcs_instanceid, mcspy, mcs_typeid)

h5py

Alias for field number 0

mcs_instanceid

Alias for field number 1

mcs_typeid

Alias for field number 3

mcspy

Alias for field number 2

class IDSetDataset(h5py, mcs_instanceid, mcspy, mcs_typeid)

h5py

Alias for field number 0

mcs_instanceid

Alias for field number 1

mcs_typeid

Alias for field number 3

mcspy

Alias for field number 2

ischild(id)

Takes an identifier and checks if it is a valid identifier for a child of this group:

Parameters:id – mcs instanceid, h5py name , mcspy name as instance of ‘str’ Returns:False if id is not valid, set of identifiers of the child

tree(name='mcspy', mcs_type=False, max_level=None)

builds the hdf5 hierarchy beginning with the current group then traversing all subentities depth first as a string

Parameters:

• name – cfg variable for the type of name that is to be printed for each entity in the h5py group, default: ‘h5py’, options: ‘mcspy’
• mcs_type – cfg variable to show mcs type in the tree, default: False
• max_level – cfg variable to limit the number of tree levels shown, default: None (show all)

class McsPy.McsCMOSMEA.McsDataset(h5py_dataset_object)

This class subclasses the h5py.Dataset object and extends it with McsPy toolbox functionality

iscompound()

Determines whether Dataset is a Compound Dataset

Return Boolean:True if Dataset object represents h5py Compound Dataset, False otherwise

to_pdDataFrame()

Returns the data set as a pandas DataFrame

Raw Data (.cmcr) files

class McsPy.McsCMOSMEA.Acquisition(acquisition_group)

Container class for acquisition data.

Acquisition Group can hold different types of streams: Analog Streams, Event Streams, Timestamp Streams, Segment Streams, Spike Streams

class McsPy.McsCMOSMEA.McsInfo(meta_data_set)

Container class for Stream Meta Data

class McsPy.McsCMOSMEA.McsStream(stream_grp, data_typeid, meta_typeid, *args)

Base class for all stream types

Data

Access all datasets - collection of McsDataset objects

Meta

Access meta data

class McsPy.McsCMOSMEA.McsChannelStream(channel_stream_grp)

Container class for one analog stream of several channels.

DataChunk

The continuous data segments in the stream

class McsPy.McsCMOSMEA.McsChannelEntity(channel_stream_entity_dataset, mcspy_parent)

Container class for one ChannelStream Entity.

Meta

reads the subset of Meta data that belongs to the channels

class McsPy.McsCMOSMEA.McsEventStream(event_stream_grp)

Container class for one Event Stream.

EventData

All events of all event entities in the stream

EventMeta

The meta data for all event entities

EventEntity

All event entities in the stream

class McsPy.McsCMOSMEA.McsEventEntity(parent, event_id)

Container class for Event Entity object

events

The ids, timestamps and durations of the occurences of the event entity

meta

The meta data for an event entity

class McsPy.McsCMOSMEA.McsSensorStream(sensor_stream_grp)

Container class for one Event Stream.

DataChunk

The groups of data that have been acquired. Intended for acquisition of multiple time windows

Regions

The regions of interest (ROI) on the sensor for which data has been acquired, usually from a rectangular subset of the sensors

SensorData

The sensor data as a numpy array of shape (frames x sensors_Y x sensors_X)

SensorMeta

The meta data for the acquired sensor data

class McsPy.McsCMOSMEA.McsSensorEntity(sensor_stream_entity_dataset, mcspy_parent)

Container class for one McsSensorEntity - a sensor stream entity.

class McsPy.McsCMOSMEA.McsSpikeStream(spike_stream_grp, spike_data_typeid='3e8aaacc-268b-4057-b0bb-45d7dc9ec73b')

Container class for one Spike Stream.

get_spikes_at_sensor(sensor_id)

retrieves all spikes that occured at the sensor with id sensor_id

Parameters:sensor_id – valid identifier for a sensor on the MCS CMOS chip as int: 1 <= sensor_id <= 65*65 Returns:numpy structured array of all spikes that have been detected on the sensor with id sensor_id

get_spikes_in_interval(interval)

Retrieves all spikes that occured in a given time interval. Intervals exceeding the time range of the dataset will throw a warning, and retrieval of maximally sized subset of the interval is attempted.

Parameters:interval –

interval in s as instance of

• list(start,stop) of length 2
• tuple(start,stop) of length 2

start must be a number, stop must be a number or the keyword ‘end’, start and stop must satisfy start < stop

Result:numpy structured array which includes all spikes occuring in the given interval

get_spike_timestamps_at_sensors(sensor_ids)

Retrieves all spike timestamps for all given sensors as a dictionary

Parameters:sensor_ids – valid identifiers for sensors on the MCS CMOS chip as int: 1 <= sensor_id <= 65*65 Returns:dictionary of all spike timestamps that have been detected on the given sensors. Key: sensor_id, value: spike timestamps

get_spike_cutouts_at_sensor(sensor_id)

Retrieves the spike cutouts for all spikes for the given sensor_id

Parameters:sensor_id – valid identifier for a sensor on the MCS CMOS chip as int: 1 <= sensor_id <= 65*65 Returns:Numpy array spikes x samples of the spike cutouts

SpikeData

The detected spikes, each with a sensor ID, a timestamp and (optionally) with a cutout

SpikeMeta

The meta data for spike detection, e.g. pre- and post interval

class McsPy.McsCMOSMEA.McsSpikeEntity(spike_stream_entity_dataset, mcspy_parent)

Container class for one SpikeStream Entity.

class McsPy.McsCMOSMEA.McsSegmentStream(segment_stream_grp)

Container class for one segment stream of different segment entities

class McsPy.McsCMOSMEA.McsSegmentStreamEntity

Segment entity class,

class McsPy.McsCMOSMEA.McsTimeStampStream(timestamp_stream_grp)

Container class for one TimeStamp stream

class McsPy.McsCMOSMEA.McsTimeStampStreamEntity

TimeStamp stream entity class

Processed Data (.cmtr) files

class McsPy.McsCMOSMEA.NetworkExplorer(network_explorer_group)

Container class for a NetworkExplorer object

get_sta_entity_by_sourceID(key)

Retrieve the STA Entity for the given source ID.

Parameters:key – A valid source ID. See the sourceIDs attribute for a list of valid source IDs Returns:The STA Entity for the given source ID

get_sta_entity_by_sensorID(key)

Retrieve the STA Entity for the given sensor ID.

Parameters:key – A valid sensor ID. See the sensorIDs attribute for a list of valid sensor IDs Returns:The STA Entity for the given sensor ID

get_sta_entity(key)

Retrieve the STA Entity for the given key.

Parameters:key – A valid key, either a sensor or a source ID, depending on the sta_key_type attribute Returns:The STA Entity for the given key

set_sta_entity(key, value)

Sets an entity to a value

del_sta_entity(key)

Deletes an entity

get_axon_for_entity_by_sourceID(key, axon=1, segment=1)

Retrieve the path of the axon for a given sensor or source ID.

Parameters:

• key – A valid key, either a sensor or a source ID, depending on the sta_key_type attribute
• axon – A valid axon ID, in case multiple axons have been found for a unit. Default: 1
• segment – A valid axon ID, in case multiple segments have been found for an axon. Default: 1

Returns:

The axon path as a list of (X,Y) tuples in sensor coordinates. Returns None if no axon is found

sta_key_type

The type of key used in the access functions. Either ‘sourceID’ or ‘sensorID’

sourceIDs

A list of valid source IDs

sensorIDs

A list of valid sensor IDs

class McsPy.McsCMOSMEA.STAEntity(sta_explorer, sta_entity, spikes_entity=None, stastddev_entity=None, axon=None)

Container Class for a STAEntity object

data

The STA data as a numpy array of shape (frames x sensors_Y x sensor_X)

spikes

Detected spikes in the STA

sta_stddev

Returns the standard deviation for each channel in the STA. Used for spike detection on the STA

sensor_coordinates

Returns the STA source coordinates on the chip as [X,Y]. Note: X and Y are 1-based

axon

Returns the axon path as a list of (X,Y) tuples in sensor coordinates. None if no axon has been found

class McsPy.McsCMOSMEA.SpikeExplorer(spike_explorer_group)

Container Class for an SpikeExplorer object

class McsPy.McsCMOSMEA.SpikeSorter(spike_sorter_group)

Container for SpikeSorter object

get_unit(unit_id)

Retrieves a single unit by its UnitID

Parameters:unit_id – A valid unit ID.

get_units_by_id()

Returns a list of units sorted by unit ID

get_units_by_measure(measure, descending=True)

Returns a list of units ordered by the given quality measure.

Parameters:

• measure – The name of a quality measure. See get_unit_measures() for a list of valid quality measure names.
• descending – The ordering of the list. Default: True (=descending order)

get_unit_measures()

Returns a list of the available unit quality measure names

class McsPy.McsCMOSMEA.SpikeSorterUnitEntity(unit_group)

Container for Spike Sorter Units

get_peaks()

Retrieves all peaks in the source signal where the ‘IncludePeak’ flag is set.

get_peaks_timestamps()

Retrieves the timestamps for all peaks in the source signal where the ‘IncludePeak’ flag is set.

get_peaks_amplitudes()

Retrieves the peak amplitudes for all peaks in the source signal where the ‘IncludePeak’ flag is set.

get_peaks_cutouts()

Retrieves the cutouts for all peaks in the source signal where the ‘IncludePeak’ flag is set.

get_measures()

Gets a list of valid unit quality measures names

get_measure(measure)

Gets a quality measure for this unit

Parameters:measure – The name of a quality measure. See get_measures() for a list of valid quality measure names.

class McsPy.McsCMOSMEA.FilterTool(filter_tool)

Container for FilterTool object

class McsPy.McsCMOSMEA.ActivitySummary(activity_summary)

Container for ActivitySummary object