bika.lims.exportimport.instruments.panalytical.omnia

Complexity

Total Complexity

97

Size/Duplication

Total Lines	524
Duplicated Lines	29.2 %

Importance

Changes

0

15 Methods

Rating	Name	Duplication	Size	Complexity
C	AxiosXrfCSVMultiParser.parse_headerline()	22	58	11
F	AxiosXrfCSVParser.parse_headerline()	131	216	44
A	AxiosXrfCSVMultiParser.getAttachmentFileType()	0	2	1
A	AxiosXrfCSVParser.splitLine()	0	8	2
A	AxiosXrfCSVMultiParser._parseline()	0	7	2
A	AxiosXrfCSVMultiParser.__init__()	0	5	1
D	AxiosXrfCSVMultiParser.parse_resultline()	0	49	12
F	AxiosXrfCSVParser.parse_resultline()	0	84	15
A	AxiosXrfCSVParser.__init__()	0	5	1
A	AxiosXrfCSVParser.csvDate2BikaDate()	0	4	1
A	AxiosXrfCSVParser._parseline()	0	7	2
A	AxiosXrfImporter.__init__()	0	8	1
A	AxiosXrfCSVParser.getAttachmentFileType()	0	2	1
A	AxiosXrfCSVMultiParser.csvDate2BikaDate()	0	4	1
A	AxiosXrfCSVMultiParser.splitLine()	0	8	2

# -*- coding: utf-8 -*-
#
# This file is part of SENAITE.CORE.
#
# SENAITE.CORE is free software: you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation, version 2.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# this program; if not, write to the Free Software Foundation, Inc., 51
# Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#
# Copyright 2018-2019 by it's authors.
# Some rights reserved, see README and LICENSE.

""" Omnia Axios XRF
"""
from datetime import datetime
from bika.lims.utils import to_unicode
from bika.lims import bikaMessageFactory as _
from bika.lims.exportimport.instruments.resultsimport import \
    AnalysisResultsImporter, InstrumentCSVResultsFileParser

class AxiosXrfCSVMultiParser(InstrumentCSVResultsFileParser):

    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
                                  #analytic's columns name


    def _parseline(self, line):
        # Process the line differenly if it pertains at header or results block
        if self._end_header == False:
            sline = line.strip(',')
            return self.parse_headerline(sline)
        else:
            return self.parse_resultline(line)

    def splitLine(self, line):
        # If pertains at header it split the line by ':' and then remove ','
        # Else split by ',' and remove blank spaces
        if self._end_header == False:
            sline = line.split(':')
            return [token.strip(',') for token in sline]

        return [token.strip() for token in line.split(',')]

    def csvDate2BikaDate(self,DateTime):
    #11/03/2014 14:46:46 --> %d/%m/%Y %H:%M %p
        dtobj = datetime.strptime(DateTime,"%d/%m/%Y %H:%M:%S")
        return dtobj.strftime("%Y%m%d %H:%M:%S")

    def parse_headerline(self, line):
        #Process incoming header line
        """11/03/2014 14:46:46
        PANalytical
        Results quantitative - Omnian 2013,

        Selected archive:,Omnian 2013
        Number of results selected:,4
        """
        
        # Save each header field (that we know) and its own value in the dict        
        if line.startswith('Results quantitative'):
            line = to_unicode(line)
            if len(self._header) == 0:
                self.err("Unexpected header format", numline=self._numline)
                return -1

            line = line.replace(',', "")
            splitted = line.split(' - ')
            self._header['Quantitative'] = splitted[1]
            return 1

        if line.startswith('Selected archive'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Archive'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)
            return 0

        if line.startswith('Number of'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['NumResults'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)
            return 0

        if line.startswith('Seq.'):
            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1
            #Grab column names
            self._columns = line.split(',')
            self._end_header = True
            return 1

        else:
            self._header['Date'] = line
            return 1



    def parse_resultline(self, line):
        # Process incoming results line
        if not line.strip():
            return 0
        if line.startswith(',,'):
            return 0

        rawdict = {}
        # Split by ","
        splitted = self.splitLine(line.strip(";"))

        errors = ''

        # Adjunt separated values from split by ','
        for idx, result in enumerate(splitted):
            if result.startswith('"'):
                # It means that is the value's firts part
                # Consequently we take second part and append both
                result = (splitted[idx].strip('"') + "," + splitted[idx+1].strip('"'))
                splitted[idx] = result
                splitted.remove(splitted[idx+1])
                
        result_type = ''
        result_sum = ''
        for idx, result in enumerate(splitted):
            if self._columns[idx] == 'Result type':
                result_type = result
            elif self._columns[idx].startswith('Sample name'):
                    rid = result
            elif self._columns[idx].startswith('Seq.'):
                pass
            elif self._columns[idx] == 'Sum':
                    result_sum = result
            else:
                rawdict[self._columns[idx]] = {'DefaultResult':result_type,
                                               # Replace to obtain UK values from default
                                               'Concentration':result.replace(',','.'),
                                               'Sum':result_sum}
        try:
            rawdict['DateTime'] = {'DateTime':self.csvDate2BikaDate(self._header['Date']),
                                   'DefaultValue':'DateTime'}
        except:
            pass
        if not rid:

The variable rid does not seem to be defined in case the for loop on line 146 is not entered. Are you sure this can never be the case?

            self.err("No Sample defined", numline=self._numline)
            return 0

        self._addRawResult(rid, rawdict, True)
        return 0


    def getAttachmentFileType(self):
        return "PANalytical - Omnia Axios XRF"

class AxiosXrfCSVParser(InstrumentCSVResultsFileParser):

    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
                                  #analytic's columns name

    def _parseline(self, line):
        # Process the line differenly if it pertains at header or results block
        if self._end_header == False:
            sline = line.strip(',')
            return self.parse_headerline(sline)
        else:
            return self.parse_resultline(line)

    def csvDate2BikaDate(self,DateTime):
    #11/03/2014 14:46:46 --> %d/%m/%Y %H:%M %p
        dtobj = datetime.strptime(DateTime,"%d/%m/%Y %H:%M:%S")
        return dtobj.strftime("%Y%m%d %H:%M:%S")

    def splitLine(self, line):
        # If pertains at header it split the line by ':' and then remove ','
        # Else split by ',' and remove blank spaces
        if self._end_header == False:
            sline = line.split(':')
            return [token.strip(',') for token in sline]

        return [token.strip() for token in line.split(',')]

    def parse_headerline(self, line):
        #Process incoming header line
        """
        29/11/2013 10:15:44
        PANalytical
        "Quantification of sample ESFERA CINZA - 1g H3BO3 -  1:0,5 - NO PPC",

        R.M.S.:,"0,035"
        Result status:,
        Sum before normalization:,"119,5 %"
        Normalised to:,"100,0 %"
        Sample type:,Pressed powder
        Initial sample weight (g):,"2,000"
        Weight after pressing (g):,"3,000"
        Correction applied for medium:,No
        Correction applied for film:,No
        Used Compound list:,Oxides
        Results database:,omnian 2013
        Results database in:,c:\panalytical\superq\userdata
        """

        if line.startswith('"Quantification of sample') or line.startswith('Quantification of sample'):
            line = to_unicode(line)
            if len(self._header) == 0:
                self.warn('Unexpected header format', numline=self._numline)
                return -1
            # Remove non important string and double comas to obtein
            # the sample name free
            line = line.replace("Quantification of sample ", "")
            line = line.replace('"', "")
            splitted = line.split(' - ')

            if len(splitted) > 3:# Maybe we don't need this, i could be all the sample's identifier...
                self._header['Sample'] = splitted[0].strip(' ')
                self._header['Quantity'] = splitted[1]
                self._header['????'] = splitted[2]# At present we
                                                  # don't know what
                                                  # is that
                self._header['PPC'] = splitted[3]
            
            elif len(splitted) == 1:
                self._header['Sample'] = splitted[0].replace('Quantification of sample','').strip(' ')

            else:
                self.warn('Unexpected header format', numline=self._numline)
            return 1
        # Save each header field (that we know) and its own value in the dict
        if line.startswith('R.M.S.'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['R.M.S.'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)
            return 0

        if line.startswith('Result status'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Result status'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Sum before normalization'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Sum'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Normalised to'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Normalized'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Sample type'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Sample type'] = splitted[1].strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Initial sample weight (g)'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Initial sample weight'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Weight after pressing (g)'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Weight after pressing'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Correction applied for medium'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.warn('Unexpected header format', numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Correction medium'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Correction applied for film'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Correction film'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

        if line.startswith('Used Compound list'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Used compound'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0
        if line.startswith('Results database:'):

This code seems to be duplicated in your project.

            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Result database'] = splitted[1].replace('"', '').strip()
            else:
                self.warn('Unexpected header format', numline=self._numline)

            return 0

       
        if self.columns_name:
            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1

            #Grab column names
            self._end_header = True
            self._columns = self.splitLine(line)
            return 1

        if line.startswith('Results database in'):
            if len(self._header) == 0:
                self.err("No header found", numline=self._numline)
                return -1
            
            splitted = self.splitLine(line)
            if len(splitted) > 1:
                self._header['Database path'] = splitted[1]+splitted[2]
                self.columns_name = True
            else:
                self.warn('Unexpected header format', numline=self._numline)
                
            return 1
            
        else:
            self._header['Date'] = line
            return 1

    def parse_resultline(self, line):
        # Process incoming results line
        if not line.strip():
            return 0

        rawdict = {}
        # Split by ","
        splitted = self.splitLine(line.strip(";"))
        # Look to know if the first value is an enumerate field
        try:
            int(splitted[0])
            rawdict["num"] = splitted[0]
            splitted = splitted[1:]
        except ValueError:
            pass

        # Enumerate the list to obtain: [(0,data0),(1,data1),...]
        e_splitted = list(enumerate(splitted))
        errors = ''

        com = False
        for idx, result in e_splitted:
            if result.startswith('"'):
                # It means that is the first value part
                # Consequently we take second part and append both
                result = (e_splitted[idx][1].strip('"') + "," + e_splitted[idx+1][1].strip('"'))
                e_splitted[idx] = (idx,result)
                e_splitted.remove(e_splitted[idx+1])
                com = True
                rawdict[self._columns[idx]] = result
                conc = self._columns[idx] # Main value's name
                                
               
            elif com:# We have rm the 2nd part value, consequently we
                    # need to decrement idx
                if len(self._columns) <= idx-1:
                    self.err("Orphan value in column ${index}",
                             mapping={"index":str(idx + 1)},
                             numline=self._numline)
                    break
                # We add and sync the result with its value's name
                rawdict[self._columns[idx-1]] = result

            else:
                if len(self._columns) <= idx:
                    self.err("Orphan value in column ${index}",
                             mapping={"index":str(idx + 1)},
                             numline=self._numline)
                    break
                rawdict[self._columns[idx]] = result

        aname = rawdict[self._columns[0]]# The fisrt column is analytic name  
        if not aname:
            self.err("No Analysis Name defined", numline=self._numline)
            return 0
        elif aname == "<H>":
            # <H> maybe is data error header? We need more examples...
            errors = rawdict.get('Compound')
            notes = rawdict.get('Calibration')
            rawdict['Notes'] = notes

        rid = self._header['Sample']
        if not rid:
            self.err("No Sample defined", numline=self._numline)
            return 0

        notes = rawdict.get('Notes', '')
        notes = "Notes: %s" % notes if notes else ''
        rawdict['DefaultResult'] = conc

The variable conc does not seem to be defined in case the for loop on line 445 is not entered. Are you sure this can never be the case?

        # Replace to obtain UK values from default
        rawdict[conc] = rawdict[conc].replace(',','.')
        rawdict['Remarks'] = ' '.join([errors, notes])
        rawres = self.getRawResults().get(rid, [])
        raw = rawres[0] if len(rawres) > 0 else {}
        raw[aname] = rawdict
        if not 'DateTime' in raw:
            try:
                raw['DateTime'] = {'DateTime':self.csvDate2BikaDate(self._header['Date']),
                                   'DefaultValue':'DateTime'}
            except:
                pass
            
        self._addRawResult(rid, raw, True)
        return 0


    def getAttachmentFileType(self):
        return "PANalytical - Omnia Axios XRF"


class AxiosXrfImporter(AnalysisResultsImporter):

    def __init__(self, parser, context,  override,
                 allowed_ar_states=None, allowed_analysis_states=None,
                 instrument_uid=None):
        AnalysisResultsImporter.__init__(self, parser, context,
                                          override,
                                         allowed_ar_states,
                                         allowed_analysis_states,
                                         instrument_uid)