detectionParams module

The bDetection class provides an interface to get and set detection paramers.

Example

import sanpy

# grab the presets for 'SA Node' cells
dDict = sanpy.bDetection().getDetectionDict('SA Node')
ba.spikeDetect(dDict)

# tweek individual parameters
dDict['dvdtThreshold'] = 50

# load a recording
myPath = 'data/19114001.abf'
ba = sanpy.bAnalysis(myPath)

# perform spike detection
ba.spikeDetect(dDict)

# browse results

Attributes

Classes

bDetection

Bases: object

Class to manage detection parameters.

Source code in sanpy/bDetection.py

class bDetection(object):
    """Class to manage detection parameters."""

    detectionTypes = detectionTypes_
    """ Enum with the type of spike detection, (dvdt, mv)"""

    def __init__(self, sanpy_paths: SanPyPaths | None = None) -> None:
        """Load all bundled and user detection presets.

        Args:
            sanpy_paths: Optional application path manager.
        """

        self._sanpy_paths = sanpy_paths or SanPyPaths()

        # dict with detection key and current value
        self._dDict = getDefaultDetection()

        # list of preset names including <user>SanPy/detection json files
        # use item=e[key] or item=e(value) then use item.name or item.value
        # _theDict, _userPresetsDict = self._getPresetsDict()
        self._detectionPreset = self._getPresetsDict()
        # self._detectionEnum = Enum("self.detectionEnum", self._detectionPreset)

        # dictionary of presets, each key is like 'sanode' and then value is a dict of
        #   detection param keys and their values
        # self._detectionPreset = {}
        # for item in self._detectionEnum:
            # item is like self.detectionEnum.sanode
            # logger.info(f'  loaded {item}, {item.name}, "{item.value}"')
            # was this
            # presetValues = self._getPresetValues(item)
            # if presetValues:
            #     # got value of built in preset
            #     self._detectionPreset[item.name] = presetValues
            # else:
            #     # find in user loaded presets
            #     _userKey = item.name
            #     try:
            #         self._detectionPreset[item.name] = _userPresetsDict[_userKey]
            #     except:
            #         logger.error(
            #             f"did not find item.name:{item.name} in _detectionPreset {self._detectionPreset.keys()}"
            #         )

    def getDetectionPresetList(self):
        """Get list of names of detection type.

        Used to make a list in popup in interface/ and interface/plugins
        """
        return list(self._detectionPreset.keys())

        # detectionList = []
        # for detectionPreset in self._detectionEnum:
        #     # detectionList.append(detectionPreset.value['detectionName'])
        #     detectionList.append(detectionPreset.name)
        # return detectionList

    def _old_getDetectionKey(self, humanName):
        """Map human readable name like 'SA Node' back to key 'sanode'
        """
        for detectionPreset in self._detectionEnum:
            if detectionPreset.value == humanName:
                return detectionPreset.name
        logger.error(f'did not find human name {humanName} in detection presets?')
        logger.error(f'  possible names are {self.getDetectionPresetList()}')

    def _getPresetsDict(self) -> dict:
        """Load detection presets from json files in 2 different folder:
            1) sanpy/detection-presets
            2) <user>/Documents/Sanpy/detection/

        For file name like 'Fast Neuron.json' make key 'fastneuron'

        Returns:
            userPresets (dict): One item per user file
        """

        def fileNameToKey(filePath):
            """Given full path to json file, return
            Filename without extension, and a well formed key.
            """
            fileName = os.path.split(filePath)[1]
            fileName = os.path.splitext(fileName)[0]

            fileNameKey = os.path.split(filePath)[1]
            fileNameKey = os.path.splitext(fileNameKey)[0]
            # reduce preset json filename to (lower case, no spaces, no dash)
            # fileNameKey = fileNameKey.lower()
            # fileNameKey = fileNameKey.replace(" ", "")
            # fileNameKey = fileNameKey.replace(
            #     "-", ""
            # )  # in case user specifies a '-' in file name
            return fileName, fileNameKey

        theDict = {}
        # userPresets = {}

        #
        # get files in our 'detection-presets' folder
        presetsPath = self._sanpy_paths.bundled_dir / 'detection-presets' / '*.json'
        files = glob.glob(str(presetsPath))
        for filePath in files:
            fileName, fileNameKey = fileNameToKey(filePath)
            # logger.info(f'detection-presets json fileNameKey:{fileNameKey} fileName:{fileName}')
            #
            # theDict[fileNameKey] = fileName

            if D_BJ_MANUSCRIPT:
                if 'Ca Kymograph' in filePath:
                    continue
                if 'Ca Spikes' in filePath:
                    continue
                if 'Sub Threshold' in filePath:
                    continue
                if 'Wu-iPSC' in filePath:
                    continue

            # load user preset json and grab (param keys and values)
            with open(filePath, "r") as f:
                userPresetsDict = json.load(f)
                theDict[fileNameKey] = userPresetsDict

        # theDict["sanode"] = "SA Node"
        # theDict["ventricular"] = "Ventricular"
        # theDict["neuron"] = "Neuron"
        # theDict["fastneuron"] = "Fast Neuron"
        # theDict["subthreshold"] = "Sub Threshold"
        # theDict["caspikes"] = "Ca Spikes"
        # theDict["cakymograph"] = "Ca Kymograph"

        #
        # get files in <users>/Documents/SanPy/detection/ folder
        files = self._getUserFiles()
        for filePath in files:
            fileName, fileNameKey = fileNameToKey(filePath)
            # theDict[fileNameKey] = fileName

            # load user preset json and grab (param keys and values)
            with open(filePath, "r") as f:
                userPresetsDict = json.load(f)
                theDict[fileNameKey] = userPresetsDict

        # make sure what we loaded has all the needed keys
        _defaultDetection = getDefaultDetection()
        for _fileNameKey, _loadedDetectionDict in theDict.items():
            for _key, _defaultDict in _defaultDetection.items():
                if _key not in _loadedDetectionDict.keys():
                    _loadedDetectionDict[_key] = _defaultDetection[_key]['defaultValue']

        return theDict  #, userPresets

    def _getUserFiles(self) -> list[pathlib.Path]:
        """Return paths to user detection-preset files.

        Returns:
            Detection-preset JSON paths, or an empty list when unavailable.
        """
        userDetectionPath = self._sanpy_paths.detection_dir
        if userDetectionPath.is_dir():
            return list(userDetectionPath.glob("*.json"))
        return []

    def toJson(self):
        """Get key and defaultValue"""
        theDict = {}
        for k, v in self._dDict.items():
            theDict[k] = v["defaultValue"]

        # logger.info('theDict:')
        # pprint(theDict)

        # with open(savePath, 'w') as f:
        #    json.dump(self._dDict, f, indent=4)
        theJson = json.dumps(theDict, indent=4)
        # logger.info('theJson:')
        return theJson

    def old_saveAs(
        self,
        detectionType: str,
        filename: str,
        path: str | pathlib.Path | None = None,
    ) -> None:
        """Save a detection dictionary to json.

        If running in GUI, main SanPy app will specify the correct path.

        This is only for user defined sets, we never save our built in detection (hard coded in code).

        Args:
            detectionType: human readable like 'SA Node', will become 'SA Node.json'
            filename: Name of file to save (no extension, will append .json)
            path: Optional explicit output path.
        """
        # _keyName = self._detectionEnum(detectionType).name
        if path is None:
            # get <user>/Documents/SanPy/xxx folder
            savePath = self._sanpy_paths.detection_dir / f"{filename}.json"
        else:
            savePath = pathlib.Path(path)
        logger.info(str(savePath))
        with open(savePath, "w") as f:
            dDict = self.getDetectionDict(detectionType)
            dDict["detectionName"] = filename
            json.dump(dDict, f, indent=4)

    def printDict(self):
        for k in self._dDict.keys():
            v = self._dDict[k]["currentValue"]
            print(f'  {k}: "{v}" {type(v)}')

    def getMasterDict(self, detectionType: str):
        """Get the full dictionary from self._dDict getDefaultDetection()

        This is needed by sanpy/interface/plugins/detectionParams.py
        """

        retDict = copy.deepcopy(self._dDict)

        # detectionTypeKey = self._detectionEnum(detectionType).name
        # oneType = self._detectionPreset[detectionTypeKey]

        oneType = self.getDetectionDict(detectionType)
        for k, v in oneType.items():
            retDict[k]["currentValue"] = v

        return retDict

    def getDetectionDict(self, detectionType: str, allParameter=True):
        """Get a full detection dict.

        Presets like 'SA Node' only over-ride a subset of the defaults, thus need to merge.
        User saved detection parameters will have all keys.

        Args:
            detectionType : detection type key, like 'SA Node'
        """
        return self._detectionPreset[detectionType]

        try:
            if allParameter:
                dDict = {}

                # master template to get all default values
                for k, v in self._dDict.items():
                    dDict[k] = v["currentValue"]

                # use specified detection type to get over-written values
                detectionTypeKey = self._detectionEnum(detectionType).name
                oneType = self._detectionPreset[detectionTypeKey]
                for k, v in oneType.items():
                    dDict[k] = v
            return dDict
        except KeyError as e:
            logger.error(f'Did not find detectionType:"{detectionType}"')
        except ValueError as e:
            logger.error(f'Did not find detectionType:"{detectionType}"')

    def getValue(self, detectionType: str, key):
        """Get current value from key. Valid keys are defined in getDefaultDetection().

        Args:
            detectionType : string value from enum, like 'SA Node'
        """
        try:
            # return self._dDict[key]['currentValue']
            return self._detectionPreset[detectionType][key]
        except KeyError as e:
            logger.warning(
                f'Did not find detectionType "{detectionType}" or key "{key}" to get current value'
            )
            # TODO: define default when not found ???
            return None

    def setValue(self,
                    detectionType: str,
                    key: str,
                    value):
        """Set current value for key. Valid keys are defined in getDefaultDetection.

        For float values that need to take on none, value comes in as -1e9

        Args:
            detectionType : str
                Name of detection type (corresonds to json file)
            key: str
                Detection parameter name
            value:
                the value to set
        """
        try:
            valueType = type(value)
            valueIsNumber = isinstance(value, numbers.Number)
            valueIsString = isinstance(value, str)
            valueIsBool = isinstance(value, bool)
            valueIsList = isinstance(value, list)
            valueIsNone = value is None

            # from the master list
            expectedType = self._dDict[key]["type"]  # (number, string, boolean)
            allowNone = self._dDict[key][
                "allowNone"
            ]  # used to turn off a detection param

            # logger.info(f'expectedType:{expectedType} value type is {type(value)}')

            if allowNone and valueIsNone:
                pass
            elif expectedType == "number" and not valueIsNumber:
                logger.warning(
                    f'Type mismatch (number) setting key "{key}", got {valueType}, expecting {expectedType}'
                )
                return False
            elif expectedType == "string" and not valueIsString:
                logger.warning(
                    f'Type mismatch (string) setting "{key}", got {valueType}, expecting {expectedType}'
                )
                return False
            elif expectedType == "boolean" and not valueIsBool:
                logger.warning(
                    f'Type mismatch (bool) setting "{key}", got {valueType}, expecting {expectedType}'
                )
                return False
            elif expectedType == "list" and not valueIsList:
                logger.warning(
                    f'Type mismatch (list) setting "{key}", got {valueType}, expecting {expectedType}'
                )
                return False
            """
            elif expectedType=='sanpy.bDetection.detectionTypes':
                try:
                    value = sanpy.bDetection.detectionTypes[value].name
                    #print(value == sanpy.bDetection.detectionTypes.dvdt)
                    #print(value == sanpy.bDetection.detectionTypes.mv)
                except (KeyError) as e:
                    logger.error(f'sanpy.bDetection.detectionTypes does not contain value "{value}"')
            """
            #
            # set
            # self._dDict[key]['currentValue'] = value
            self._detectionPreset[detectionType][key] = value

            logger.info(
                f"now detectionType:{detectionType} key:{key}: {self._detectionPreset[detectionType][key]} {type(self._detectionPreset[detectionType][key])}"
            )

            return True

        except KeyError as e:
            logger.warning(
                f'Did not find detectionType:{detectionType}, key:"{key}" to set current value to "{value}"'
            )
            logger.warning(f'  available detectionType are: {self._detectionPreset.keys()}')
            return False

    def old_save(self, saveBase):
        """
        Save underlying dict to json file

        Args:
            save base (str): basename to append '-detection.json'
        """

        # convert

        savePath = saveBase + "-detection.json"

        with open(savePath, "w") as f:
            json.dump(self._dDict, f, indent=4)

    def _old_load(self, loadBase):
        """
        Load detection from json file.

        Fill in underlying dict
        """

        loadPath = loadBase + "-detection.json"

        if not os.path.isfile(loadPath):
            logger.error(f"Did not find file: {loadPath}")
            return

        with open(loadPath, "r") as f:
            self._dDict = json.load(f)

        # convert

    def _old_getPresetValues(self, detectionPreset):
        """Depreciated, now loaded from json


        detectionName : corresponds to key in enum self._detectionEnum
        """

        theDict = {}

        if detectionPreset == self._detectionEnum.sanode:
            theDict["detectionName"] = "SA Node"
            theDict["dvdtThreshold"] = 20
            theDict["mvThreshold"] = -20
            theDict["refractory_ms"] = 170  # max freq of 5 Hz
            theDict["peakWindow_ms"] = 100
            theDict["halfWidthWindow_ms"] = 200
            theDict["preSpikeClipWidth_ms"] = 200
            theDict["postSpikeClipWidth_ms"] = 500
        elif detectionPreset == self._detectionEnum.ventricular:
            theDict["detectionName"] = "Ventricular"
            theDict["dvdtThreshold"] = 100
            theDict["mvThreshold"] = -20
            theDict["refractory_ms"] = 200  # max freq of 5 Hz
            theDict["peakWindow_ms"] = 100
            theDict["halfWidthWindow_ms"] = 300
            theDict["preSpikeClipWidth_ms"] = 200
            theDict["postSpikeClipWidth_ms"] = 500
        elif detectionPreset == self._detectionEnum.neuron:
            theDict["detectionName"] = "Neuron"
            theDict["dvdtThreshold"] = 20
            theDict["mvThreshold"] = -40
            theDict["refractory_ms"] = 4
            theDict["peakWindow_ms"] = 5
            theDict["halfWidthWindow_ms"] = 4
            theDict["dvdtPreWindow_ms"] = 2
            theDict["dvdtPostWindow_ms"] = 2
            theDict["preSpikeClipWidth_ms"] = 2
            theDict["postSpikeClipWidth_ms"] = 2
        elif detectionPreset == self._detectionEnum.fastneuron:
            theDict["detectionName"] = "Fast Neuron"
            theDict["dvdtThreshold"] = 20
            theDict["mvThreshold"] = -40
            theDict["refractory_ms"] = 3
            theDict["peakWindow_ms"] = 2
            theDict["halfWidthWindow_ms"] = 4
            theDict["dvdtPreWindow_ms"] = 2
            theDict["dvdtPostWindow_ms"] = 2
            theDict["preSpikeClipWidth_ms"] = 2
            theDict["postSpikeClipWidth_ms"] = 2
        elif detectionPreset == self._detectionEnum.subthreshold:
            theDict["detectionName"] = "Subthreshold"
            theDict["dvdtThreshold"] = math.nan
            theDict["mvThreshold"] = -20  # user specifies
            theDict["refractory_ms"] = 100  # max freq is 10 Hz
            theDict["peakWindow_ms"] = 50
            theDict["halfWidthWindow_ms"] = 100
            theDict["preSpikeClipWidth_ms"] = 100
            theDict["postSpikeClipWidth_ms"] = 200
            theDict["onlyPeaksAbove_mV"] = None
            theDict["onlyPeaksBelow_mV"] = -20
            # todo: add onlyPeaksBelow_mV
        elif detectionPreset == self._detectionEnum.caspikes:
            theDict["detectionName"] = "Ca Spikes"
            # theDict['detectionType'] = sanpy.bDetection.detectionTypes.mv # ('dvdt', 'mv')
            theDict[
                "dvdtThreshold"
            ] = math.nan  # if None then detect only using mvThreshold
            theDict["mvThreshold"] = 0.5
            # theDict['refractory_ms'] = 200 #170 # reject spikes with instantaneous frequency
            # theDict['halfWidthWindow_ms'] = 200 #was 20
        elif detectionPreset == self._detectionEnum.cakymograph:
            theDict["detectionName"] = "Ca Kymograph"
            theDict["detectionType"] = sanpy.bDetection.detectionTypes["dvdt"].value
            # rosie, was math.nan #if None then detect only using mvThreshold
            theDict["dvdtThreshold"] = 0.05
            theDict["mvThreshold"] = 0.5
            theDict["peakWindow_ms"] = 400  # rosie, was 700
            theDict["halfWidthWindow_ms"] = 400  # rosie, was 800
            theDict["refractory_ms"] = 500
            theDict["doBackupSpikeVm"] = False
            # theDict['SavitzkyGolay_pnts'] = 5
            theDict["preSpikeClipWidth_ms"] = 200
            theDict["postSpikeClipWidth_ms"] = 1000
        else:
            logger.error(f"did not understand detectionPreset: {detectionPreset}")

        return theDict

Attributes

detectionTypes = detectionTypes_ class-attribute instance-attribute

Enum with the type of spike detection, (dvdt, mv)

Methods:

__init__(sanpy_paths=None)

Load all bundled and user detection presets.

Args: sanpy_paths: Optional application path manager.

Source code in sanpy/bDetection.py

def __init__(self, sanpy_paths: SanPyPaths | None = None) -> None:
    """Load all bundled and user detection presets.

    Args:
        sanpy_paths: Optional application path manager.
    """

    self._sanpy_paths = sanpy_paths or SanPyPaths()

    # dict with detection key and current value
    self._dDict = getDefaultDetection()

    # list of preset names including <user>SanPy/detection json files
    # use item=e[key] or item=e(value) then use item.name or item.value
    # _theDict, _userPresetsDict = self._getPresetsDict()
    self._detectionPreset = self._getPresetsDict()

getDetectionDict(detectionType, allParameter=True)

Get a full detection dict.

Presets like 'SA Node' only over-ride a subset of the defaults, thus need to merge. User saved detection parameters will have all keys.

Args: detectionType : detection type key, like 'SA Node'

Source code in sanpy/bDetection.py

def getDetectionDict(self, detectionType: str, allParameter=True):
    """Get a full detection dict.

    Presets like 'SA Node' only over-ride a subset of the defaults, thus need to merge.
    User saved detection parameters will have all keys.

    Args:
        detectionType : detection type key, like 'SA Node'
    """
    return self._detectionPreset[detectionType]

    try:
        if allParameter:
            dDict = {}

            # master template to get all default values
            for k, v in self._dDict.items():
                dDict[k] = v["currentValue"]

            # use specified detection type to get over-written values
            detectionTypeKey = self._detectionEnum(detectionType).name
            oneType = self._detectionPreset[detectionTypeKey]
            for k, v in oneType.items():
                dDict[k] = v
        return dDict
    except KeyError as e:
        logger.error(f'Did not find detectionType:"{detectionType}"')
    except ValueError as e:
        logger.error(f'Did not find detectionType:"{detectionType}"')

getDetectionPresetList()

Get list of names of detection type.

Used to make a list in popup in interface/ and interface/plugins

Source code in sanpy/bDetection.py

def getDetectionPresetList(self):
    """Get list of names of detection type.

    Used to make a list in popup in interface/ and interface/plugins
    """
    return list(self._detectionPreset.keys())

getMasterDict(detectionType)

Get the full dictionary from self._dDict getDefaultDetection()

This is needed by sanpy/interface/plugins/detectionParams.py

Source code in sanpy/bDetection.py

def getMasterDict(self, detectionType: str):
    """Get the full dictionary from self._dDict getDefaultDetection()

    This is needed by sanpy/interface/plugins/detectionParams.py
    """

    retDict = copy.deepcopy(self._dDict)

    # detectionTypeKey = self._detectionEnum(detectionType).name
    # oneType = self._detectionPreset[detectionTypeKey]

    oneType = self.getDetectionDict(detectionType)
    for k, v in oneType.items():
        retDict[k]["currentValue"] = v

    return retDict

getValue(detectionType, key)

Get current value from key. Valid keys are defined in getDefaultDetection().

Args: detectionType : string value from enum, like 'SA Node'

Source code in sanpy/bDetection.py

def getValue(self, detectionType: str, key):
    """Get current value from key. Valid keys are defined in getDefaultDetection().

    Args:
        detectionType : string value from enum, like 'SA Node'
    """
    try:
        # return self._dDict[key]['currentValue']
        return self._detectionPreset[detectionType][key]
    except KeyError as e:
        logger.warning(
            f'Did not find detectionType "{detectionType}" or key "{key}" to get current value'
        )
        # TODO: define default when not found ???
        return None

old_save(saveBase)

Save underlying dict to json file

Args: save base (str): basename to append '-detection.json'

Source code in sanpy/bDetection.py

def old_save(self, saveBase):
    """
    Save underlying dict to json file

    Args:
        save base (str): basename to append '-detection.json'
    """

    # convert

    savePath = saveBase + "-detection.json"

    with open(savePath, "w") as f:
        json.dump(self._dDict, f, indent=4)

old_saveAs(detectionType, filename, path=None)

Save a detection dictionary to json.

If running in GUI, main SanPy app will specify the correct path.

This is only for user defined sets, we never save our built in detection (hard coded in code).

Args: detectionType: human readable like 'SA Node', will become 'SA Node.json' filename: Name of file to save (no extension, will append .json) path: Optional explicit output path.

Source code in sanpy/bDetection.py

def old_saveAs(
    self,
    detectionType: str,
    filename: str,
    path: str | pathlib.Path | None = None,
) -> None:
    """Save a detection dictionary to json.

    If running in GUI, main SanPy app will specify the correct path.

    This is only for user defined sets, we never save our built in detection (hard coded in code).

    Args:
        detectionType: human readable like 'SA Node', will become 'SA Node.json'
        filename: Name of file to save (no extension, will append .json)
        path: Optional explicit output path.
    """
    # _keyName = self._detectionEnum(detectionType).name
    if path is None:
        # get <user>/Documents/SanPy/xxx folder
        savePath = self._sanpy_paths.detection_dir / f"{filename}.json"
    else:
        savePath = pathlib.Path(path)
    logger.info(str(savePath))
    with open(savePath, "w") as f:
        dDict = self.getDetectionDict(detectionType)
        dDict["detectionName"] = filename
        json.dump(dDict, f, indent=4)

setValue(detectionType, key, value)

Set current value for key. Valid keys are defined in getDefaultDetection.

For float values that need to take on none, value comes in as -1e9

Args: detectionType : str Name of detection type (corresonds to json file) key: str Detection parameter name value: the value to set

Source code in sanpy/bDetection.py

def setValue(self,
                detectionType: str,
                key: str,
                value):
    """Set current value for key. Valid keys are defined in getDefaultDetection.

    For float values that need to take on none, value comes in as -1e9

    Args:
        detectionType : str
            Name of detection type (corresonds to json file)
        key: str
            Detection parameter name
        value:
            the value to set
    """
    try:
        valueType = type(value)
        valueIsNumber = isinstance(value, numbers.Number)
        valueIsString = isinstance(value, str)
        valueIsBool = isinstance(value, bool)
        valueIsList = isinstance(value, list)
        valueIsNone = value is None

        # from the master list
        expectedType = self._dDict[key]["type"]  # (number, string, boolean)
        allowNone = self._dDict[key][
            "allowNone"
        ]  # used to turn off a detection param

        # logger.info(f'expectedType:{expectedType} value type is {type(value)}')

        if allowNone and valueIsNone:
            pass
        elif expectedType == "number" and not valueIsNumber:
            logger.warning(
                f'Type mismatch (number) setting key "{key}", got {valueType}, expecting {expectedType}'
            )
            return False
        elif expectedType == "string" and not valueIsString:
            logger.warning(
                f'Type mismatch (string) setting "{key}", got {valueType}, expecting {expectedType}'
            )
            return False
        elif expectedType == "boolean" and not valueIsBool:
            logger.warning(
                f'Type mismatch (bool) setting "{key}", got {valueType}, expecting {expectedType}'
            )
            return False
        elif expectedType == "list" and not valueIsList:
            logger.warning(
                f'Type mismatch (list) setting "{key}", got {valueType}, expecting {expectedType}'
            )
            return False
        """
        elif expectedType=='sanpy.bDetection.detectionTypes':
            try:
                value = sanpy.bDetection.detectionTypes[value].name
                #print(value == sanpy.bDetection.detectionTypes.dvdt)
                #print(value == sanpy.bDetection.detectionTypes.mv)
            except (KeyError) as e:
                logger.error(f'sanpy.bDetection.detectionTypes does not contain value "{value}"')
        """
        #
        # set
        # self._dDict[key]['currentValue'] = value
        self._detectionPreset[detectionType][key] = value

        logger.info(
            f"now detectionType:{detectionType} key:{key}: {self._detectionPreset[detectionType][key]} {type(self._detectionPreset[detectionType][key])}"
        )

        return True

    except KeyError as e:
        logger.warning(
            f'Did not find detectionType:{detectionType}, key:"{key}" to set current value to "{value}"'
        )
        logger.warning(f'  available detectionType are: {self._detectionPreset.keys()}')
        return False

toJson()

Get key and defaultValue

Source code in sanpy/bDetection.py

def toJson(self):
    """Get key and defaultValue"""
    theDict = {}
    for k, v in self._dDict.items():
        theDict[k] = v["defaultValue"]

    # logger.info('theDict:')
    # pprint(theDict)

    # with open(savePath, 'w') as f:
    #    json.dump(self._dDict, f, indent=4)
    theJson = json.dumps(theDict, indent=4)
    # logger.info('theJson:')
    return theJson

detectionTypes_

Bases: Enum

Detection type is one of (dvdt, mv).

dvdt: Search for threshold crossings in first derivative of membrane potential. mv: Search for threshold crossings in membrane potential.

Source code in sanpy/bDetection.py

class detectionTypes_(Enum):
    """
    Detection type is one of (dvdt, mv).

    dvdt: Search for threshold crossings in first derivative of membrane potential.
    mv: Search for threshold crossings in membrane potential.
    """

    dvdt = "dvdt"
    mv = "mv"

Functions:

getDefaultDetection()

Build the authoritative detection-parameter definition dictionary.

Returns: A new ordered dictionary mapping internal parameter names to their runtime definitions, including presentation categories.

Source code in sanpy/bDetection.py

def getDefaultDetection() -> dict[str, dict[str, Any]]:
    """Build the authoritative detection-parameter definition dictionary.

    Returns:
        A new ordered dictionary mapping internal parameter names to their
        runtime definitions, including presentation categories.
    """

    theDict = OrderedDict()  # {}

    """
    key = 'include'
    theDict[key] = {}
    theDict[key]['defaultValue'] = True
    theDict[key]['type'] = 'bool'
    theDict[key]['allowNone'] = False
    theDict[key]['units'] = ''
    theDict[key]['humanName'] = 'Include'
    theDict[key]['errors'] = ('')
    theDict[key]['description'] = 'Include analysis for this file'
    """

    key = "detectionName"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.GENERAL
    theDict[key]["defaultValue"] = "default"  # detectionPreset.value # ('dvdt', 'mv')
    theDict[key]["type"] = "string"
    theDict[key][
        "allowNone"
    ] = False  # To do, have 2x entry points to bAnalysis detect, never set this to nan
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "Detection Preset Name"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "The name of detection preset"

    key = "userSaveName"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.GENERAL
    theDict[key]["defaultValue"] = ""  # detectionPreset.value # ('dvdt', 'mv')
    theDict[key]["type"] = "string"
    theDict[key][
        "allowNone"
    ] = False  # To do, have 2x entry points to bAnalysis detect, never set this to nan
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "Saved Detection Params"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "The name of saved user detection params"

    key = "detectionType"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.DETECTION
    theDict[key]["defaultValue"] = sanpy.bDetection.detectionTypes[
        "dvdt"
    ].value  # ('dvdt', 'mv')
    theDict[key]["type"] = "sanpy.bDetection.detectionTypes"
    theDict[key][
        "allowNone"
    ] = False  # To do, have 2x entry points to bAnalysis detect, never set this to nan
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "Detection Type"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Detect using derivative (dvdt) or membrane potential (mV)"

    key = "dvdtThreshold"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.DETECTION
    theDict[key]["defaultValue"] = 20
    theDict[key]["type"] = "float"
    theDict[key][
        "allowNone"
    ] = True  # To do, have 2x entry points to bAnalysis detect, never set this to nan
    theDict[key]["units"] = "dVdt"
    theDict[key]["humanName"] = "dV/dt Threshold"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "dV/dt threshold for a spike, will be backed up to dvdt_percentOfMax and have xxx error when this fails"

    key = "mvThreshold"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.DETECTION
    theDict[key]["defaultValue"] = -20
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "mV"
    theDict[key]["humanName"] = "mV Threshold"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "mV threshold for spike AND minimum spike mV when detecting with dV/dt"

    key = "startSeconds"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = None
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = True
    theDict[key]["units"] = "s"
    theDict[key]["humanName"] = "Start(s)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Start seconds of analysis"

    key = "stopSeconds"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = None
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = True
    theDict[key]["units"] = "s"
    theDict[key]["humanName"] = "Stop(s)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Stop seconds of analysis"

    key = "cellType"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.GENERAL
    theDict[key]["defaultValue"] = ""
    theDict[key]["type"] = "string"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "Cell Type"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Cell Type"

    key = "sex"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.GENERAL
    theDict[key]["defaultValue"] = ""
    theDict[key]["type"] = "string"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "Sex"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Sex"

    key = "condition"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.GENERAL
    theDict[key]["defaultValue"] = ""
    theDict[key]["type"] = "string"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "Condition"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Condition"

    key = "userType"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.GENERAL
    theDict[key]["defaultValue"] = "0"
    theDict[key]["type"] = "int"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "User Type"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "User Type"

    key = "dvdt_percentOfMax"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.DETECTION
    theDict[key]["defaultValue"] = 0.1
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "Percent"
    theDict[key]["humanName"] = "dV/dt Percent of max"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "For dV/dt detection, the final TOP is when dV/dt drops to this percent from dV/dt AP peak"

    key = "onlyPeaksAbove_mV"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WAVEFORM
    theDict[key]["defaultValue"] = None
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = True
    theDict[key]["units"] = "mV"
    theDict[key]["humanName"] = "Accept Peaks Above (mV)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Only accept APs with peaks above this value (mV)"

    key = "onlyPeaksBelow_mV"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WAVEFORM
    theDict[key]["defaultValue"] = None
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = True
    theDict[key]["units"] = "mV"
    theDict[key]["humanName"] = "Accept Peaks Below (mV)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Only accept APs below this value (mV)"

    # TODO: get rid of this and replace with foot
    key = "doBackupSpikeVm"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.ADVANCED
    theDict[key]["defaultValue"] = False
    theDict[key]["type"] = "boolean"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "Boolean"
    theDict[key]["humanName"] = "Backup Vm Spikes"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "If true, APs detected with just mV will be backed up until Vm falls to xxx"

    key = "refractory_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 170
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Minimum AP interval (ms)"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "APs with interval (wrt previous AP) less than this will be removed"

    key = "peakWindow_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 100
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Peak Window (ms)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Window after TOP (ms) to seach for AP peak (mV)"

    key = "dvdtPreWindow_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 10
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "dV/dt Pre Window (ms)"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Window (ms) to search before each TOP for real threshold crossing"

    key = "dvdtPostWindow_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 20
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "dV/dt Post Window (ms)"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Window (ms) to search after each AP peak for minimum in dv/dt"

    key = "mdp_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.DETECTION
    theDict[key]["defaultValue"] = 250
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Pre AP MDP window (ms)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Window (ms) before an AP to look for MDP"

    key = "avgWindow_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 5
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "MDP averaging window (ms)"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Window (ms) to calculate MDP (mV) as a mean rather than mV at single point for MDP"

    key = "lowEddRate_warning"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.ADVANCED
    theDict[key]["defaultValue"] = 8
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "EDD slope"
    theDict[key]["humanName"] = "EDD slope warning"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Generate warning when EED slope is lower than this value."

    key = "halfHeights"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WAVEFORM
    theDict[key]["defaultValue"] = [10, 20, 50, 80, 90]
    theDict[key]["type"] = "list"  # list of number
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "AP Durations (%)"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "AP Durations as percent of AP height (AP Peak (mV) - TOP (mV))"

    key = "halfWidthWindow_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 200
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Half Width Window (ms)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Window (ms) after TOP to look for AP Durations"

    key = "preSpikeClipWidth_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 200
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Pre AP Clip Width (ms)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "The pre duration of generated AP clips (Before AP)"

    key = "postSpikeClipWidth_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 500
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Post AP Clip Width (ms)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "The post duration of generated AP clips (After AP)"

    # new 20231201, for mich lab
    key = "fastAhpWindow_ms"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.WINDOWS
    theDict[key]["defaultValue"] = 8
    theDict[key]["type"] = "float"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "ms"
    theDict[key]["humanName"] = "Fast AHP Window (ms)"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Window (ms) after peak to look for a fast AHP"

    key = "medianFilter"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.FILTERING
    theDict[key]["defaultValue"] = 0
    theDict[key]["type"] = "int"
    theDict[key]["allowNone"] = True  # 0 is no median filter (see SavitzkyGolay_pnts)
    theDict[key]["units"] = "points"
    theDict[key]["humanName"] = "Median Filter Points"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Number of points in median filter, must be odd, 0 for no filter"

    key = "SavitzkyGolay_pnts"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.FILTERING
    theDict[key]["defaultValue"] = 5  # 20211001 was 5
    theDict[key]["type"] = "int"
    theDict[key]["allowNone"] = True  # 0 is no filter
    theDict[key]["units"] = "points"
    theDict[key]["humanName"] = "SavitzkyGolay Points"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "Number of points in SavitzkyGolay filter, must be odd, 0 for no filter"

    key = "SavitzkyGolay_poly"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.FILTERING
    theDict[key]["defaultValue"] = 2
    theDict[key]["type"] = "int"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = ""
    theDict[key]["humanName"] = "SavitzkyGolay Poly Deg"
    theDict[key]["errors"] = ""
    theDict[key][
        "description"
    ] = "The degree of the polynomial for Savitzky-Golay filter"

    # key = 'dateAnalyzed'
    # theDict[key] = {}
    # theDict[key]['defaultValue'] = ''
    # theDict[key]['type'] = 'str'
    # theDict[key]['allowNone'] = False
    # theDict[key]['units'] = ''
    # theDict[key]['humanName'] = 'Date Analyzed'
    # theDict[key]['errors'] = ('')
    # theDict[key]['description'] = 'The date of analysis (yyyymmdd)'

    key = "verbose"
    theDict[key] = {}
    theDict[key]["category"] = DetectionParameterCategory.ADVANCED
    theDict[key]["defaultValue"] = False
    theDict[key]["type"] = "boolean"
    theDict[key]["allowNone"] = False
    theDict[key]["units"] = "Boolean"
    theDict[key]["humanName"] = "Verbose"
    theDict[key]["errors"] = ""
    theDict[key]["description"] = "Verbose Detection Reporting"

    # assign each detection param current value to it default value
    for k, v in theDict.items():
        defaultValue = theDict[k]["defaultValue"]
        theDict[k]["currentValue"] = defaultValue

    """
    if detectionPreset == bDetection.detectionPresets.default:
        # these are defaults from above
        pass
    elif detectionPreset == bDetection.detectionPresets.sanode:
        # these are defaults from above
        pass
    elif detectionPreset == bDetection.detectionPresets.ventricular:
        theDict['dvdtThreshold']['defaultValue'] = 100
        theDict['mvThreshold']['defaultValue'] = -20
        theDict['refractory_ms']['defaultValue'] = 200  # max freq of 5 Hz
        theDict['peakWindow_ms']['defaultValue'] = 100
        theDict['halfWidthWindow_ms']['defaultValue'] = 300
        theDict['preSpikeClipWidth_ms']['defaultValue'] = 200
        theDict['postSpikeClipWidth_ms']['defaultValue'] = 500
    elif detectionPreset == bDetection.detectionPresets.neuron:
        theDict['dvdtThreshold']['defaultValue'] = 20
        theDict['mvThreshold']['defaultValue'] = -40
        theDict['refractory_ms']['defaultValue'] = 4
        theDict['peakWindow_ms']['defaultValue'] = 5
        theDict['halfWidthWindow_ms']['defaultValue'] = 4
        theDict['dvdtPreWindow_ms']['defaultValue'] = 2
        theDict['dvdtPostWindow_ms']['defaultValue'] = 2
        theDict['preSpikeClipWidth_ms']['defaultValue'] = 2
        theDict['postSpikeClipWidth_ms']['defaultValue'] = 2
    elif detectionPreset == bDetection.detectionPresets.fastneuron:
        theDict['dvdtThreshold']['defaultValue'] = 20
        theDict['mvThreshold']['defaultValue'] = -40
        theDict['refractory_ms']['defaultValue'] = 3
        theDict['peakWindow_ms']['defaultValue'] = 2
        theDict['halfWidthWindow_ms']['defaultValue'] = 4
        theDict['dvdtPreWindow_ms']['defaultValue'] = 2
        theDict['dvdtPostWindow_ms']['defaultValue'] = 2
        theDict['preSpikeClipWidth_ms']['defaultValue'] = 2
        theDict['postSpikeClipWidth_ms']['defaultValue'] = 2
    elif detectionPreset == bDetection.detectionPresets.subthreshold:
        theDict['dvdtThreshold']['defaultValue'] = math.nan
        theDict['mvThreshold']['defaultValue'] = -20  # user specifies
        theDict['refractory_ms']['defaultValue'] = 100  # max freq is 10 Hz
        theDict['peakWindow_ms']['defaultValue'] = 50
        theDict['halfWidthWindow_ms']['defaultValue'] = 100
        theDict['preSpikeClipWidth_ms']['defaultValue'] = 100
        theDict['postSpikeClipWidth_ms']['defaultValue'] = 200
        theDict['onlyPeaksAbove_mV']['defaultValue'] = None
        theDict['onlyPeaksBelow_mV']['defaultValue'] = -20
        # todo: add onlyPeaksBelow_mV
    elif detectionPreset == bDetection.detectionPresets.caspikes:
        #theDict['detectionType']['defaultValue'] = sanpy.bDetection.detectionTypes.mv # ('dvdt', 'mv')
        theDict['dvdtThreshold']['defaultValue'] = math.nan #if None then detect only using mvThreshold
        theDict['mvThreshold']['defaultValue'] = 0.5
        #theDict['refractory_ms']['defaultValue'] = 200 #170 # reject spikes with instantaneous frequency
        #theDict['halfWidthWindow_ms']['defaultValue'] = 200 #was 20
    elif detectionPreset == bDetection.detectionPresets.cakymograph:
        theDict['detectionType']['defaultValue'] = sanpy.bDetection.detectionTypes['mv'].value
        theDict['dvdtThreshold']['defaultValue'] = math.nan #if None then detect only using mvThreshold
        theDict['mvThreshold']['defaultValue'] = 1.2
        theDict['peakWindow_ms']['defaultValue'] = 700
        theDict['halfWidthWindow_ms']['defaultValue'] = 800
        theDict['refractory_ms']['defaultValue'] = 500
        theDict['doBackupSpikeVm']['defaultValue'] = False
        # theDict['SavitzkyGolay_pnts']['defaultValue'] = 5
        theDict['preSpikeClipWidth_ms']['defaultValue'] = 200
        theDict['postSpikeClipWidth_ms']['defaultValue'] = 1000
    else:
        logger.error(f'Did not understand detection type "{detectionPreset}"')
        logger.error(f'    bDetection.detectionPresets.fastneuron: {bDetection.detectionPresets.fastneuron}')
        logger.error(f'    type(bDetection.detectionPresets.fastneuron): {type(bDetection.detectionPresets.fastneuron)}')
        logger.error(f'    detectionPreset == bDetection.detectionPresets.fastneuron: {detectionPreset == bDetection.detectionPresets.fastneuron}')
    """

    # assign each detection param current value to it default value
    """
    for k,v in theDict.items():
        defaultValue = theDict[k]['defaultValue']
        theDict[k]['currentValue'] = defaultValue
    """

    return theDict.copy()

printDocs()

Print or save human-readable detection-parameter documentation.

This developer utility currently writes a CSV file used when maintaining SanPy documentation.

Source code in sanpy/bDetection.py

def printDocs() -> None:
    """Print or save human-readable detection-parameter documentation.

    This developer utility currently writes a CSV file used when maintaining
    SanPy documentation.
    """
    logger.info("")

    import pandas as pd

    # detectionPreset = bDetection.detectionPresets.default  # detectionPresets_ is an enum class
    d = getDefaultDetection()
    dictList = []
    for k, v in d.items():
        parameter = k
        oneDict = {
            "Parameter": parameter,
            "Category": v["category"],
            "Default Value": v["defaultValue"],
            "Units": v["units"],
            "Human Readable": v["humanName"],
            "Description": v["description"],
        }
        dictList.append(oneDict)
    #
    df = pd.DataFrame(dictList)

    # spit out markdown to copy/paste into mkdocs md file
    # REMEMBER: This requires `pip install tabulate`
    # outStr = df.to_markdown()
    # print(outStr)

    # save to csv for making a table for manuscript
    path = "/Users/cudmore/Desktop/sanpy-detection-params-20230316.csv"
    print("saving to:", path)
    df.to_csv(path, index=False)

test_0()

Testing get/set of detection params

Source code in sanpy/bDetection.py

def test_0():
    """
    Testing get/set of detection params
    """

    bd = bDetection()

    # xxx = bd.getValue('xxx')

    # ok = bd.setValue('xxx', 2)
    # print('ok:', ok)

    ok1 = bd.setValue("dvdtThreshold", None)
    if not ok1:
        print("ok1:", ok1)

    ok1_5 = bd.setValue("mvThreshold", None)
    if not ok1_5:
        print("failure ok ok1_5:", ok1_5)

    ok2 = bd.setValue("cellType", "111")
    if not ok2:
        print("ok2:", ok2)

    # for setting list, check that (i) not empty and (ii) list[i] == expected type
    ok3 = bd.setValue("halfHeights", [])
    if not ok3:
        print("ok3:", ok3)

    # start/stop seconds defaults to None but we want 'number'
    ok4 = bd.setValue("startSeconds", 1e6)
    if not ok4:
        print("ok4:", ok4)

    tmpDict = {
        "Idx": 2.0,
        "Include": 1.0,
        "File": "19114001.abf",
        "Dur(s)": 60.0,
        "kHz": 20.0,
        "Mode": "fix",
        "Cell Type": "",
        "Sex": "",
        "Condition": "",
        "Start(s)": math.nan,
        "Stop(s)": math.nan,
        "dvdtThreshold": 50.0,
        "mvThreshold": -20.0,
        "refractory_ms": math.nan,
        "peakWindow_ms": math.nan,
        "halfWidthWindow_ms": math.nan,
        "Notes": "",
    }
    for k, v in tmpDict.items():
        print("  ", k, ":", v)
    okSetFromDict = bd.setFromDict(tmpDict)