def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._columns = [] # The different columns names self._linedata = {} # The line with the data self._resid = '' self._method = '' self._date = ''
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._columns = [] self._period = [ False, '' ] # Variable to control results from period beginning and end.
def __init__(self, rsf): InstrumentCSVResultsFileParser.__init__(self, rsf) self._columns = [] # The different columns names self._values = {} # The analysis services from the same resid self._resid = '' # A stored resid self._rownum = None self._end_header = False
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._columns = [] # The different columns names self._end_header = False # This list contains all the rows without interesting data self.extrainfolist = ['Number', 'Average', 'Maximum', 'Minimum', 'Range', 'Std dev.', 'RSD(%)']
def __init__(self, csv, analysiskey): InstrumentCSVResultsFileParser.__init__(self, csv) self.data_header = None self.file_header = {} # Set this flag when we find the header-line beginning with "Date,". # Once this flag is set, all following lines are real data. self.main_data_found = False self.analysiskey = analysiskey
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._end_sequencetable = False self._sequences = [] self._sequencesheader = [] self._quantitationresultsheader = [] self._numline = 0
def __init__(self, infile): InstrumentCSVResultsFileParser.__init__(self, infile, encoding='utf-8-sig') self._separator = '\t' # values are separated by tabs self._is_header = False self._current_section = '' # current section of the file self._columns = None # Column names of Analyte Result table self._ar_keyword = None # Keyword of Analysis Service
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._columns = [] # The different columns names self._values = {} # The analysis services from the same resid self._rownum = None self._end_header = False # self._includedcolumns =['Ca', 'Cu', # 'Fe', 'Mg'] self._includedcolumns = ['CD4_PERC', 'CD4', 'CD8_PERC', 'CD8']
def __init__(self, rsf, fileformat=None): InstrumentCSVResultsFileParser.__init__(self, rsf) self._columns = [] # The different columns names self._values = {} # The analysis services from the same resid self._resid = '' # A stored resid self._rownum = None self._end_header = False self._fileformat = fileformat self._separator = ',' if self._fileformat == 'csv' else '\t'
def __init__(self, infile): InstrumentCSVResultsFileParser.__init__(self, infile, encoding='utf-16-le') self._cur_section = '' # Current section of CSV self._cur_sub_section = '' # Current subsection of CSV self._cur_res_id = '' # Sample or Patient ID of the current record self._cur_values = {} # Values of the last record self._is_header_line = False # To get headers of Analyte Result table self._columns = [] # Column names of Analyte Result table self._keyword = '' # Keyword of Analysis Service
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._end_sampleinformationtable = False self._sampleinformationresults = [] self._sampleinformation = [] self._quantitationresultsheader = [] self._sampleinformationheader = [] self._numline = 0
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._resid = '' # The Analysis Request ID self._sampleIDs = {} # A dict with the samples ID for ech row # self._sampleIDs example: # {'A': ['CP', '', '', '', '', '', '', '', '', '', '', ''], # 'B': ['CP', '', '', '', '', '', '', '', '', '', '', ''], # 'C': ['CN', '', '', '', '', '', '', '', '', '', '', '']} self._samplesID_section = False # Indicates if we are parsing the samples ID section self._simple_results_section = False # indicates if we are parsing the no computed results section self._simple_results = {} # This dictionary has the structure # self._simple_results example: # {'CN': {'leiatura1': '0.9638', 'leiatura2': '0.9785'}, # 'CP': {'leiatura1': '0.3407', 'leiatura2': '0.3456'}} self._is_data_header = False # Indicates if we are parsing the final results header self._data_header = [] # This list contains the values of the final/computed data header self._data_section = False # Indicates if we are parsing the computed results section
def __init__(self, csv, analysiskey=None, defaultresult=None): # analysiskey contains the value of the selected AS or None # defaultresult contains the data column key which will be tagged as DefaultResult in the AS results dictionary. InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._columns = [] # When AS isn't selected we need to know which columns don't contain data. Since we don't know in # which order this columns could be, we need to write an ugly list with the possible columns names to exclude. self._excludedcolumns = ['Instrument ID', 'Analysis Date', 'Analysis Time', 'Rack No.', 'Tube Pos.', 'Sample ID No', 'Sample ID Info', 'Analysis Mode', 'Patient ID', 'Analysis Info.', 'Sample Judgment Info.', 'Positive(Diff)', 'Positive(Morph)', 'Positive(Count)', 'Error(Func)', 'Error(Result)', 'Order Info.', 'WBC Abnormal', 'WBC Suspect', 'RBC Abnormal', 'RBC Suspect', 'PLT Abnormal', 'PLT Suspect', 'Unit Info.', 'Validate', 'Action Message(Diff)', 'Action Message(Delta)', 'Sample Comment', 'Patient Name', 'Date of Birth', 'Sex', 'Patient comment', 'Ward', 'Doctor', 'Transmitted Parameters', 'Sequence No.'] self.analysiskey = analysiskey self.defaultresult = defaultresult
def __init__(self, csv, analysiskey=None, defaultresult=None): # analysiskey contains the value of the selected AS or None # defaultresult contains the data column key which will be tagged as DefaultResult in the AS results dictionary. InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._columns = [] # When AS isn't selected we need to know which columns don't contain data. Since we don't know in # which order this columns could be, we need to write an ugly list with the possible columns names to exclude. self._excludedcolumns = [ 'Instrument ID', 'Analysis Date', 'Analysis Time', 'Rack No.', 'Tube Pos.', 'Sample ID No', 'Sample ID Info', 'Analysis Mode', 'Patient ID', 'Analysis Info.', 'Sample Judgment Info.', 'Positive(Diff)', 'Positive(Morph)', 'Positive(Count)', 'Error(Func)', 'Error(Result)', 'Order Info.', 'WBC Abnormal', 'WBC Suspect', 'RBC Abnormal', 'RBC Suspect', 'PLT Abnormal', 'PLT Suspect', 'Unit Info.', 'Validate', 'Action Message(Diff)', 'Action Message(Delta)', 'Sample Comment', 'Patient Name', 'Date of Birth', 'Sex', 'Patient comment', 'Ward', 'Doctor', 'Transmitted Parameters', 'Sequence No.' ] self.analysiskey = analysiskey self.defaultresult = defaultresult
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._keywords = [] self._quantitationresultsheader = [] self._numline = 0
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._column_header = [] self._end_header = False self._column_header_stripped = None self.allowed_quan_types = ['ExtCal.Average', 'IntCal.Average']
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self.currentheader = None
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._columns = []
def __init__(self, tsv, analysis1, analysis2): InstrumentCSVResultsFileParser.__init__(self, tsv) self._analysis1 = analysis1 self._analysis2 = analysis2
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._columns = [] self.columns_name = False #To know if the next line contains
def __init__(self, csv, analysiskey): InstrumentCSVResultsFileParser.__init__(self, csv) self.analysiskey = analysiskey self.header = None
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._currentresultsheader = [] self._currentanalysiskw = '' self._numline = 0
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv)
def __init__(self , csv): InstrumentCSVResultsFileParser.__init__(self,csv) self.columns = [] self.resid='' #to be passes in addRawResult() self.is_head = True
def __init__(self, slk): InstrumentCSVResultsFileParser.__init__(self, slk) self._columns = {} #The diferents data columns names self._linedata = {}#The line with the data self._rownum = None self._isFirst = True #Used to know if is the first linedata
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._resultsheader = [] self._numline = 0
def __init__(self, csv, analysiskey): InstrumentCSVResultsFileParser.__init__(self, csv) self._labels = False # If true, we are in a line where are the sample names self._data = False # If true, we are in a line where are the analysis results self._labels_values = {} # The labels' values self.analysiskey = analysiskey # The analysis key whose results will be related
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._end_header = False self._columns = [] self._period = [False,''] # Variable to control results from period beginning and end.
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._columns = [] # The different columns names self._linedata = {} # The line with the data self._rownum = None self._end_header = False
def __init__(self, tsv): InstrumentCSVResultsFileParser.__init__(self, tsv) self._end_header = False self._columns = []
def __init__(self, infile, encoding=None): InstrumentCSVResultsFileParser.__init__(self, infile) self._end_header = False self._delimiter = ','
def __init__(self, slk): InstrumentCSVResultsFileParser.__init__(self, slk) self._columns = {} #The diferents data columns names self._linedata = {} #The line with the data self._rownum = None self._isFirst = True #Used to know if is the first linedata
def __init__(self, csv): InstrumentCSVResultsFileParser.__init__(self, csv) self._columns = [] # The different columns names self._linedata = {} # The line with the data self._end_header = False