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594 | class bAnalysisUtil:
def __init__(self):
# built in analysis results
self._statList = self._builStatList()
self._buildUserStatList()
self.configDict = self.configDefault()
# load preferences
if getattr(sys, "frozen", False):
# we are running in a bundle (frozen)
bundle_dir = sys._MEIPASS
else:
# we are running in a normal Python environment
bundle_dir = os.path.dirname(os.path.abspath(__file__))
self.configFilePath = os.path.join(bundle_dir, "AnalysisApp_Config.json")
self.configLoad()
# self.top = None # used by tkinter interface
def getStatList(self):
return self._statList
def getHumanFromStat(self, statName):
"""Get human readable stat name from backend stat name."""
ret = ""
for k, v in self._statList.items():
name = v["name"]
if name == statName:
ret = k
break
if ret == "":
logger.warning(f'Did not find "{statName}"')
#
return ret
def getStatFromHuman(self, humanStat):
"""Get backend stat name from human readable stat."""
ret = ""
try:
ret = self._statList[humanStat]["name"]
except KeyError as e:
logger.warning(f'Bad key "{humanStat}"')
#
return ret
# @staticmethod
# def _old_getStatList():
# """20210929 working on extending stat list with sanpy.userAnalysis
# We first define stat list in this function as statList
# We then ask for user defined stat functions static members xxx
# """
# coreStatList = statList # from global withing function
# # userStatList = sanpy.userAnalysis.findUserAnalysis()
# # userStatList = sanpy.userAnalysis.baseUserAnalysis.findUserAnalysis()
# # userStatList = findUserAnalysis()
# #logger.warning(f"need to reactivate getting user stats")
# """
# Each entry in statList looks like:
# statList['Spike Time (s)'] = {
# 'name': 'thresholdSec',
# 'units': 's',
# 'yStat': 'thresholdVal',
# 'yStatUnits': 'mV',
# 'xStat': 'thresholdSec',
# 'xStatUnits': 's'
# }
# """
# userStatList: List[
# dict
# ] = sanpy.user_analysis.baseUserAnalysis.findUserAnalysisStats()
# for userStatDict in userStatList:
# for k, v in userStatDict.items():
# if k in coreStatList.keys():
# logger.error(
# f'user analysis key "{k}" already exists in core stat List'
# )
# else:
# # name = v['name']
# # coreStatList[k] = {}
# # coreStatList[k][name] = name
# coreStatList[k] = v
# return coreStatList
# # 20220630, was this
# userStatList = sanpy.user_analysis.baseUserAnalysis.findUserAnalysis()
# for k, v in userStatList.items():
# # check if key exists !!!
# if k in coreStatList.keys():
# logger.error(
# f'user analysis key {"k"} already exists in core stat List'
# )
# else:
# name = v["name"]
# coreStatList[k] = {}
# coreStatList[k][name] = name
# return coreStatList
"""
@staticmethod
def humanStatToBackend(theStat):
return ''
"""
def _buildUserStatList(self):
"""Append user stats to self._statList
"""
userStatList: List[
dict
] = sanpy.user_analysis.baseUserAnalysis.findUserAnalysisStats()
for userStatDict in userStatList:
for k, v in userStatDict.items():
if k in self._statList.keys():
logger.error(
f'user analysis key "{k}" already exists in core stat List'
)
else:
# name = v['name']
# coreStatList[k] = {}
# coreStatList[k][name] = name
self._statList[k] = v
# return coreStatList
def _builStatList(self) -> dict:
statList = OrderedDict()
statList["Spike Time (s)"] = {
"name": "thresholdSec",
"units": "s",
"yStat": "thresholdVal",
"yStatUnits": "mV",
"xStat": "thresholdSec",
"xStatUnits": "s",
}
statList["Spike Number"] = {
"name": "spikeNumber",
"units": "",
"yStat": "",
"yStatUnits": "",
"xStat": "spikeNumber",
"xStatUnits": "",
}
statList["Sweep Spike Number"] = {
"name": "sweepSpikeNumber",
"units": "",
"yStat": "",
"yStatUnits": "",
"xStat": "sweepSpikeNumber",
"xStatUnits": "",
}
statList["Sweep Number"] = {
"name": "sweep",
"units": "",
"yStat": "sweep",
"yStatUnits": "",
"xStat": "",
"xStatUnits": "",
}
# removed 20230320
# statList['DAC Command'] = {
# 'name': 'dacCommand',
# 'units': '',
# 'yStat': 'dacCommand',
# 'yStatUnits': '',
# 'xStat': '',
# 'xStatUnits': ''
# }
# added 20230320
# stimulus epoch number a spike is within
statList["Epoch"] = {
"name": "epoch",
"units": "",
"yStat": "epoch",
"yStatUnits": "",
"xStat": "",
"xStatUnits": "",
}
# added 20230320
# the epoch level (for I-Clamp, corresponds to DAC command)
statList["Epoch DAC"] = {
"name": "epochLevel",
"units": "",
"yStat": "epochLevel",
"yStatUnits": "",
"xStat": "",
"xStatUnits": "",
}
# added 20230320
# the spike number within the epoch
# not implemented
# 20230914 BUG in bAnalysisResults we define 'epoch', not 'epochSpikeNumber'
# WE need to sync these two interface !!!!
statList["Epoch Spike Number"] = {
# "name": "epochSpikeNumber",
"name": "epoch",
"units": "",
# "yStat": "epochSpikeNumber",
"yStat": "epoch",
"yStatUnits": "",
"xStat": "",
"xStatUnits": "",
}
statList["Take Off Potential (mV)"] = {
"name": "thresholdVal",
"units": "mV",
"yStat": "thresholdVal",
"yStatUnits": "mV",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
statList["Spike Frequency (Hz)"] = {
"name": "spikeFreq_hz",
"units": "Hz",
"yStat": "spikeFreq_hz",
"yStatUnits": "Hz",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
statList["Inter-Spike-Interval (ms)"] = {
"name": "isi_ms",
"units": "ms",
"yStat": "isi_ms",
"yStatUnits": "ms",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
statList["Cycle Length (ms)"] = {
"name": "cycleLength_ms",
"units": "ms",
"yStat": "cycleLength_ms",
"yStatUnits": "ms",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
statList["AP Peak (mV)"] = {
"name": "peakVal",
"units": "mV",
"yStat": "peakVal",
"yStatUnits": "mV",
"xStat": "peakPnt",
"xStatUnits": "Points",
}
# spikeDict['peakVal'] - spikeDict['thresholdVal']
statList["AP Height (mV)"] = {
"name": "peakHeight",
"units": "mV",
"yStat": "peakHeight",
"yStatUnits": "mV",
"xStat": "peakPnt",
"xStatUnits": "Points",
}
# new 20220122
statList["Time To Peak (ms)"] = {
"name": "timeToPeak_ms",
"units": "ms",
"yStat": "peakVal",
"yStatUnits": "mV",
"xStat": "peakPnt",
"xStatUnits": "Points",
}
statList["Pre AP Min (mV)"] = {
"name": "preMinVal",
"units": "mV",
"yStat": "preMinVal",
"yStatUnits": "mV",
"xStat": "preMinPnt",
"xStatUnits": "Points",
}
statList["Post AP Min (mV)"] = {
"name": "postMinVal",
"units": "mV",
"yStat": "postMinVal",
"yStatUnits": "mV",
"xStat": "postMinPnt",
"xStatUnits": "Points",
}
# new 20231201
statList["Fast AHP (mV)"] = {
"name": "fastAhpValue",
"units": "mV",
"yStat": "fastAhpValue",
"yStatUnits": "mV",
"xStat": "fastAhpPnt",
"xStatUnits": "Points",
}
# todo: fix this
statList["Early Diastolic Depol Rate (dV/s)"] = {
"name": "earlyDiastolicDurationRate",
"units": "dV/s",
"yStat": "earlyDiastolicDurationRate",
"yStatUnits": "dV/s",
"xStat": "",
"xStatUnits": "",
}
# todo: fix this
statList["Early Diastolic Duration (ms)"] = {
"name": "earlyDiastolicDuration_ms",
"units": "ms",
"yStat": "earlyDiastolicDuration_ms",
"yStatUnits": "dV/s",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
statList["Diastolic Duration (ms)"] = {
"name": "diastolicDuration_ms",
"units": "ms",
"yStat": "diastolicDuration_ms",
"yStatUnits": "dV/s",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
statList["Max AP Upstroke (mV)"] = {
"name": "preSpike_dvdt_max_val",
"units": "mV",
"yStat": "preSpike_dvdt_max_val",
"yStatUnits": "dV/s",
"xStat": "preSpike_dvdt_max_pnt",
"xStatUnits": "Points",
}
statList["Max AP Upstroke (dV/dt)"] = {
"name": "preSpike_dvdt_max_val2",
"units": "dV/dt",
"yStat": "preSpike_dvdt_max_val2",
"yStatUnits": "dV/dt",
"xStat": "preSpike_dvdt_max_pnt",
"xStatUnits": "Points",
}
statList["Max AP Repolarization (mV)"] = {
"name": "postSpike_dvdt_min_val",
"units": "mV",
"yStat": "postSpike_dvdt_min_val",
"yStatUnits": "mV",
"xStat": "postSpike_dvdt_min_pnt",
"xStatUnits": "Points",
}
# todo: fix this
statList["AP Duration (ms)"] = {
"name": "apDuration_ms",
"units": "ms",
"yStat": "apDuration_ms",
"yStatUnits": "ms",
"xStat": "thresholdPnt",
"xStatUnits": "Points",
}
# new 20210211
statList["Half Width 10 (ms)"] = {
"name": "widths_10",
"yStat": "widths_10",
"yStatUnits": "ms",
"xStat": "",
"xStatUnits": "",
}
statList["Half Width 20 (ms)"] = {
"name": "widths_20",
"yStat": "widths_20",
"yStatUnits": "ms",
"xStat": "",
"xStatUnits": "",
}
statList["Half Width 50 (ms)"] = {
"name": "widths_50",
"yStat": "widths_50",
"yStatUnits": "ms",
"xStat": "",
"xStatUnits": "",
}
statList["Half Width 80 (ms)"] = {
"name": "widths_80",
"yStat": "widths_80",
"yStatUnits": "ms",
"xStat": "",
"xStatUnits": "",
}
statList["Half Width 90 (ms)"] = {
"name": "widths_90",
"yStat": "widths_90",
"yStatUnits": "ms",
"xStat": "",
"xStatUnits": "",
}
statList["User Type"] = {
"name": "userType",
"yStat": "userType",
"yStatUnits": "",
"xStat": "",
"xStatUnits": "",
}
statList["Condition"] = {
"name": "condition",
"yStat": "condition",
"yStatUnits": "",
"xStat": "",
"xStatUnits": "",
}
# sa node specific
"""
statList['Region'] = {
'yStat': 'Region',
'yStatUnits': '',
'xStat': '',
'xStatUnits': ''
}
"""
# kymograph analysis
if DO_KYMOGRAPH_ANALYSIS:
statList["Ca++ Delay (s)"] = {
"yStat": "caDelay_sec",
"yStatUnits": "s",
"xStat": "",
"xStatUnits": "",
}
statList["Ca++ Width (ms)"] = {
"yStat": "caWidth_ms",
"yStatUnits": "ms",
"xStat": "",
"xStatUnits": "",
}
return statList
def prettyPrint(self):
print(json.dumps(self.configDict, indent=4, sort_keys=True))
def getDetectionConfig(self):
return self.config
def getDetectionParam(self, theParam):
if theParam in self.configDict["detection"].keys():
return self.configDict["detection"][theParam]["value"]
else:
print(
"error: bAnalysisUtil.getDetectionParam() detection parameter not found:",
theParam,
)
return None
def getDetectionDescription(self, theParam):
if theParam in self.configDict["detection"].keys():
return self.configDict["detection"][theParam]["meaning"]
else:
print(
"error: bAnalysisUtil.getDetectionDescription() detection parameter not found:",
theParam,
)
return None
def setDetectionParam(self, theParam, theValue):
if theParam in self.configDict["detection"].keys():
self.configDict["detection"][theParam]["value"] = theValue
else:
print(
"error: bAnalysisUtil.setDetectionParam() detection parameter not found:",
theParam,
)
return None
def configSave(self):
print("bAnalysisUtil.configSave()")
with open(self.configFilePath, "w") as outfile:
json.dump(self.configDict, outfile, indent=4, sort_keys=True)
def configLoad(self):
if os.path.isfile(self.configFilePath):
print(
" bAnalysisUtil.configLoad() loading configFile file:",
self.configFilePath,
)
with open(self.configFilePath) as f:
self.configDict = json.load(f)
else:
# print(' bAnalysisUtil.preferencesLoad() using program provided default options')
self.configDefault()
def configDefault(self):
theRet = OrderedDict()
theRet["detection"] = OrderedDict()
theRet["detection"]["dvdtThreshold"] = OrderedDict()
theRet["detection"]["dvdtThreshold"] = {
"value": 100,
"meaning": "Threshold crossing in dV/dt",
}
theRet["detection"]["minSpikeVm"] = OrderedDict()
theRet["detection"]["minSpikeVm"] = {
"value": -20,
"meaning": "Minimum Vm to accept a detected spike",
}
theRet["detection"]["medianFilter"] = OrderedDict()
theRet["detection"]["medianFilter"] = {
"value": 5,
"meaning": "Median filter for Vm (must be odd)",
}
theRet["detection"]["minISI_ms"] = OrderedDict()
theRet["detection"]["minISI_ms"] = {
"value": 75,
"meaning": "Minimum allowable inter-spike-interval (ms), anything shorter than this will be rejected",
}
return theRet
def _print(self):
"""Print out human readable detection parameters and convert to markdown table
This is then pasted as a markdown table into the SanPy docs methods section
TODO: Add a generation date to the resulting markdown.
Requires:
pip install tabulate
"""
import pandas as pd
# statList is a dict with keys, one key per stat
d = self._statList
dictList = []
for k, v in d.items():
stat = k
oneDict = {
"Stat": stat,
}
for k2, v2 in v.items():
oneDict[k2] = v2
dictList.append(oneDict)
#
df = pd.DataFrame(dictList)
str = df.to_markdown()
print(str)
|