def __init__(self, data, configs):
'''removes wrong data'''
for file in list(data.keys()):
if "contact chain" not in data[file]["header"][3].lower():
data.pop(file)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.df = []
self.basePlots = None
self.analysisname = "Contact_Chain"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
self.sort_parameter = self.config["Contact_Chain"]["Bar_chart"][
"CreateBarChart"]
self.Substrate_Type = ["Polysilicon", "N+", "P+"]
self.filename_df = pd.DataFrame(columns=[
"Filename", "Substrate Type", "_", "Batch", "Wafer No.", "_",
"HM location", "Test structure", "Resistance", "Standard deviation"
])
self.PlotDict["All"] = None
self.limits = {"Polysilicon": 4 * 10**7, "N+": 10**5, "P+": 8 * 10**4}
self.files_to_fit = self.config["files_to_fit"]
hvtext = hv.Text(0, 0, self.analysisname,
fontsize=20).opts(color="black", xlabel='', ylabel='')
box = hv.Polygons(hv.Box(0, 0,
1).opts(color="black")).opts(color="white")
self.PlotDict["All"] = box * hvtext
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.config = configs
self.analysisName = "Stripscan"
self.data = convert_to_df(data, abs=self.config.get("abs_value_only", False))
self.data = rename_columns(
self.data,
self.config.get(self.analysisName, {}).get("Measurement_aliases", {}),
)
self.finalPlot = None
self.df = []
self.measurements = self.data["columns"]
self.donts = ()
if "Pad" in self.measurements:
padidx = self.measurements.index("Pad")
self.xrow = "Pad"
else:
self.log.error("No 'Pad' column found in data. Analysis cannot be done!")
return
self.PlotDict = {"Name": self.analysisName}
self.donts = ["Pad", "Name"]
# Convert the units to the desired ones
for meas in self.measurements:
unit = (
self.config[self.analysisName].get(meas, {}).get("UnitConversion", None)
)
if unit:
self.data = convert_to_EngUnits(self.data, meas, unit)
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.config = configs
self.analysisName = "IVCV_HPK"
self.data = convert_to_df(data, abs=True)
self.data = rename_columns(
self.data,
self.config[self.analysisName].get("Measurement_aliases", {}))
self.basePlots = None
self.PlotDict = {
"Name": "IVCV"
} # Name of analysis and cnavas for all plots generated during this analysis
self.capincluded = False
self.measurements = self.data["columns"]
self.measurements.remove("VR")
self.measurements.remove("Name")
# Find CV measurement
for file in self.data["keys"]:
if "CV" in file:
self.data["keys"].append("1C2")
self.data["1C2"] = self.data[file].copy()
self.data["1C2"]["data"] = 1 / (
self.data[file]["data"][self.measurements] *
self.data[file]["data"][self.measurements])
self.data["1C2"]["data"]["VR"] = self.data[file]["data"]["VR"]
self.data["1C2"]["data"]["Name"] = (
self.data[file]["data"]["Name"] + "1c2")
self.capincluded = True
self.xaxis = "VR"
# The do not plot list, you can extend this list as you like
self.donts = ("Name", "VR")
def __init__(self, data, configs):
# Do the analysis of the gate diode files as the last one.
if not all(
analysis_type[0:6] == "IV_GCD"
for analysis_type in data[list(data.keys())[0]]["header"][2]
):
data = self.file_order(data)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False, keys="all")
self.config = configs
self.df = []
self.basePlots = None
self.basePlots_2 = None
self.name = "IV_PQC"
self.PlotDict = {"Name": "IV"}
self.capincluded = False
# Add different columns to the data frame;
self.data["columns"].insert(3, "CapacityCopy")
self.data["columns"].insert(4, "derivative")
self.data["columns"].insert(5, "derivative2")
self.data["columns"].insert(6, "1C2")
self.data["columns"].insert(7, "derivative1C2")
self.data["columns"].insert(8, "x")
self.data["columns"].insert(9, "N")
self.data["columns"].insert(10, "firstderivative_gate")
self.capincluded = True
self.measurements = self.data["columns"]
self.xaxis = self.measurements[0] # Select your x axis, normally voltage.
# Convert the units to the desired ones
for meas in self.measurements:
unit = self.config[self.name].get(meas, {}).get("UnitConversion", None)
if unit:
self.data = convert_to_EngUnits(self.data, meas, unit)
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.config = configs
self.analysisName = "MemoryEffect_IMS"
self.data = convert_to_df(data,
abs=self.config.get("abs_value_only", False))
self.data = rename_columns(
self.data,
self.config[self.analysisName].get("Measurement_aliases", {}))
self.basePlots = None
self.PlotDict = {
"Name": "MemoryEffect_IMS"
} # Name of analysis and cnavas for all plots generated during this analysis
self.measurements = self.data["columns"]
self.xaxis = self.measurements[7]
# The do not plot list, you can extend this list as you like
self.donts = [
"stdC11R11", "stdC127R127", "stdC255R257", "step", "Name"
]
self.errors = {
"C11R11": self.data["All"]["stdC11R11"],
"C127R127": self.data["All"]["stdC127R127"],
"C255R257": self.data["All"]["stdC255R257"]
}
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.df = []
self.basePlots = None
self.analysisname = "COVID19"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"][
4:] # Cut the non measurement lines
#hv.renderer('bokeh')
self.keys_basenames = [
name.split("_")[-2] for name in self.data["keys"]
]
self.countries = []
# Plot canvas:
self.Plots = None
self.cases = None
self.recovered = None
self.deaths = None
self.casesrelgrowth = None
self.recoveredrelgrowth = None
self.deathsrelgrowth = None
self.casesNorm = None
self.recoveredNorm = None
self.deathsNorm = None
self.GrowthvsCases = None
self.DeathvsCases = None
def analysis(self):
"""Does the analysis"""
average_len = 1
# Manipulate data
for entry in self.data:
self.data[entry]["data"]["measurement"] = np.array(
range(0, 1000 - (average_len - 1)))
self.data[entry]["measurements"].insert(0, "measurement")
self.data[entry]["units"].insert(0, "#")
# Do moving average over all data arrays
for col in self.data[entry]["data"]:
if col != "measurement":
self.data[entry]["data"][col] = moving_average(
self.data[entry]["data"][col], average_len)
# Do rpoly conversion
rpolyvoltage = -1
for file in self.data:
self.data[file]["data"][
"R1"] = rpolyvoltage / self.data[file]["data"]["R1"]
indx = self.data[file]["measurements"].index("R1")
self.data[file]["units"][indx] = "Ohm"
# Convert to df
self.data = convert_to_df(self.data, abs=False)
self.measurements = self.data["columns"]
self.xaxis = "measurement"
def __init__(self, data, configs):
for file in list(data.keys()):
if "FET" not in data[file]["header"][3]:
data.pop(file)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.basePlots = None
self.analysisname = "FET"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
self.PlotDict["All"] = None
self.do_analysis_1 = True
self.do_analysis_2 = True
self.do_analysis_3 = True
self.df = pd.DataFrame(columns=["Name", "_", "Batch", "Wafer No.", "_", "_", "HM location", "Test structure",
"ELR Method", "Second Derivative", "Second Derivative log"])
self.sort_parameter = self.config["FET"]["Bar_chart"]["CreateBarChart"]
'''turns all headers into dictionaries and creates entries in self.data '''
for file in self.data["keys"]:
self.data[file]["Ana 1"] = "_"
self.data[file]["Ana 2"] = "_"
self.data[file]["Ana 3"] = "_"
self.data[file]["header"] = self.list_to_dict(self.data[file]["header"])
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.df = []
self.basePlots = None
self.PlotDict = {"Name": "Curve_plots"}
self.measurements = self.data["columns"]
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=True)
self.config = configs
self.df = []
self.Plots = []
self.allPlots = None
self.individual = None
self.PlotDict = {"Name": "Relaxation time"}
self.measurements = self.data["columns"]
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.config = configs
self.analysisName = "IVCV_QTC"
self.data = convert_to_df(data, abs=self.config.get("abs_value_only", False))
self.data = rename_columns(
self.data, self.config[self.analysisName].get("Measurement_aliases", {})
)
self.basePlots = None
self.PlotDict = {
"Name": "IVCV"
} # Name of analysis and cnavas for all plots generated during this analysis
self.capincluded = False
if (
"capacitance" in self.data[self.data["keys"][0]]["data"]
or "CV" in self.data[self.data["keys"][0]]["data"]
):
self.data["columns"].insert(3, "1C2") # because we are adding it later on
self.capincluded = True
self.measurements = self.data["columns"]
self.xaxis = self.measurements[0]
# The do not plot list, you can extend this list as you like
self.donts = [
"Name",
"voltage_1",
"Idark",
"Idiel",
"Rpoly",
"Cac",
"Cint",
"Rint",
"Pad",
"Istrip",
]
if "voltage" in self.measurements:
self.xaxis = "voltage"
padidx = self.measurements.index("voltage")
del self.measurements[padidx]
else:
self.log.error(
"No 'voltage' entry found in data, cannot do IVC analysis. Maybe you have to set an alias for your measurement."
)
# Convert the units to the desired ones
for meas in self.measurements:
unit = (
self.config[self.analysisName].get(meas, {}).get("UnitConversion", None)
)
if unit:
self.data = convert_to_EngUnits(self.data, meas, unit)
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.config = configs
self.analysisName = "Alibava"
self.data = convert_to_df(data, abs=self.config.get("abs_value_only", False))
self.data = rename_columns(
self.data, self.config[self.analysisName].get("Measurement_aliases", {})
)
self.basePlots = None
self.PlotDict = {
"Name": "IVCV"
} # Name of analysis and cnavas for all plots generated during this analysis
self.xaxis = "Temperature"
self.donts = []
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.df = []
self.basePlots = None
self.analysisname = "TCAD"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
# hv.renderer('bokeh')
self.areafactors = self.config["AreaFactors"]
self.scalefactors = self.config["ScalingFactors"]
self.to_plot = [
(
"IV",
"IV_1",
self.areafactors.get("IV", 1),
self.scalefactors.get("IV", 1),
),
(
"CV",
"CV_1",
self.areafactors.get("CV", 1),
self.scalefactors.get("CV", 1),
),
(
"1c2",
"1c2_1",
self.areafactors.get("1c2", 1),
self.scalefactors.get("1c2", 1),
),
(
"oxide_charges",
"interstrip_resistance",
self.areafactors.get("interstrip_resistance", 1),
self.scalefactors.get("interstrip_resistance", 1),
),
(
"pstop_depth",
"interstrip_resistance",
self.areafactors.get("interstrip_resistance", 1),
self.scalefactors.get("interstrip_resistance", 1),
),
]
def __init__(self, data, configs):
'''removes wrong data'''
for file in list(data.keys()):
if "Linewidth".lower() not in data[file]["header"][3].lower():
data.pop(file)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.df = []
self.basePlots = None
self.analysisname = "Linewidth"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
self.PlotDict["All"] = None
self.sort_parameter = self.config["Linewidth"]["Bar_chart"][
"CreateBarChart"]
self.Substrate_Type = ["P+", "N+", "P-stop"]
self.filename_df = pd.DataFrame(columns=[
"Filename", "Substrate Type", "_", "Batch", "Wafer No.", "_",
"HM location", "Test structure", "Linewidth [um]",
"Standard deviation"
])
self.limits = {"P+": 0.05, "N+": 0.00001, "P-stop": 0.0005}
self.files_to_fit = self.config["files_to_fit"]
self.sheet_dic = {
"P+": self.config["Linewidth"]["parameter"]["sheet_r_p+"],
"N+": self.config["Linewidth"]["parameter"]["sheet_r_N+"],
"P-stop": self.config["Linewidth"]["parameter"]["sheet_r_ps"]
}
self.std_dic = {
"P+": self.config["Linewidth"]["parameter"]["std_p+"],
"N+": self.config["Linewidth"]["parameter"]["std_N+"],
"P-stop": self.config["Linewidth"]["parameter"]["std_ps"]
}
hvtext = hv.Text(0, 0, self.analysisname,
fontsize=25).opts(color="black", xlabel='', ylabel='')
box = hv.Polygons(hv.Box(0, 0,
300).opts(color="black")).opts(color="white")
self.PlotDict["All"] = box * hvtext
def __init__(self, data, configs):
'''removes wrong data'''
for file in list(data.keys()):
if "van-der-pauw" not in data[file]["header"][3].lower(
) and "bulk cross" not in data[file]["header"][3].lower():
data.pop(file)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.df = []
self.basePlots = None
self.analysisname = "Van_der_Pauw"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
self.PlotDict["All"] = None
self.sort_parameter = self.config["Van_der_Pauw"]["Bar_chart"][
"CreateBarChart"]
self.Substrate_Type = [
"P-stop", "Polysilicon", "N+", "P+", "Metal", "bulk"
]
'''columns have to be fitted according to sample_name + sample_type layout'''
self.filename_df = pd.DataFrame(columns=[
"Filename", "Substrate Type", "_", "Batch", "Wafer No.", "_",
"HM location", "Test structure", "_", "Sheet Resistance [Ohm/sq]",
"Standard deviation"
])
self.limits = {
"P-stop": 25000,
"Polysilicon": 3000,
"N+": 50,
"P+": 1300,
"Metal": 0.03,
"bulk": 70000
}
self.files_to_fit = self.config["files_to_fit"]
hvtext = hv.Text(0, 0, self.analysisname,
fontsize=13).opts(color="black", xlabel='', ylabel='')
box = hv.Polygons(hv.Box(0, 0,
2).opts(color="black")).opts(color="white")
self.PlotDict["All"] = box * hvtext
def __init__(self, data, configs):
'''removes wrong data'''
for file in list(data.keys()):
if "meander" not in data[file]["header"][3]:
data.pop(file)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(
data, abs=False
) ## funktioniert nicht komplet da metal und poly andere messungen haben
self.complete_df(data)
self.config = configs
self.df = []
self.basePlots = None
self.analysisname = "Meander"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
self.sort_parameter = self.config["Meander"]["Bar_chart"][
"CreateBarChart"]
self.Substrate_Type = ["Polysilicon", "Metal"]
self.filename_df = pd.DataFrame(columns=[
"Filename", "Substrate Type", "_", "Batch", "Wafer No.", "_",
"HM location", "Test structure", "_", "Resistivity",
"Standard deviation", "specific Resistivity [Ohm/sq]"
])
self.PlotDict["All"] = None
self.limits = {"Polysilicon": 2 * 10**6, "Metal": 450}
self.files_to_fit = self.config["files_to_fit"]
self.squares = {
"Polysilicon": self.config["Meander"]["parameter"]["squares_poly"],
"Metal": self.config["Meander"]["parameter"]["squares_m"]
}
hvtext = hv.Text(0, 0, self.analysisname,
fontsize=13).opts(color="black", xlabel='', ylabel='')
box = hv.Polygons(hv.Box(0, 0,
2).opts(color="black")).opts(color="white")
self.PlotDict["All"] = box * hvtext
def __init__(self, data, configs):
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False, keys="all")
self.config = configs
self.df = []
self.basePlots = None
self.name = "IV_PQC"
self.PlotDict = {"Name": "IV"}
self.measurements = self.data["columns"]
self.xaxis = "voltage"
self.donts = ["timestamp", "voltage"]
#hv.renderer('bokeh')
c2 = 1 / (self.data['ChuckLeakage-Default_HME_S-PQC_Flute_1-Diode_IV']['data']["current"] *
self.data['ChuckLeakage-Default_HME_S-PQC_Flute_1-Diode_IV']['data']["current"])
# Convert the units to the desired ones
for meas in self.measurements:
unit = self.config[self.name].get(meas, {}).get("UnitConversion", None)
if unit:
self.data = convert_to_EngUnits(self.data, meas, unit)
def __init__(self, data, configs):
'''removes wrong data'''
for file in list(data.keys()):
if "MOS capacitor" not in data[file]["header"][0]:
data.pop(file)
self.log = logging.getLogger(__name__)
self.data = convert_to_df(data, abs=False)
self.config = configs
self.basePlots = None
self.analysisname = "MOS_CV"
self.PlotDict = {"Name": self.analysisname}
self.measurements = self.data["columns"]
self.interpolation_der = self.config[
self.analysisname]["Derivative"]["interpolate"]
self.do_derivative = self.config[self.analysisname]["Derivative"]["do"]
self.plot_der = self.config[self.analysisname]["Derivative"]["plot"]
self.interpolation_fit = self.config[
self.analysisname]["Fit"]["interpolate"]
self.do_fit = self.config[self.analysisname]["Fit"]["do"]
self.PlotDict["All"] = None
