build.bika.lims.exportimport.instruments.panalytical.omnia.AxiosXrfCSVMultiParser._parseline() - Code Metrics - Inspection of "fixing cobas integra instrument import interface (..." - senaite/senaite.core - Measure and Improve Code Quality continuously with Scrutinizer

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Push — master ( d8e2ec...90ae0b )

by Jordi

created 2019-03-11 15:48 UTC

AxiosXrfCSVMultiParser._parseline() A

↳ Parent: build.bika.lims.exportimport.instruments.panalytical.omnia

Complexity

Conditions

Size

Total Lines	7
Code Lines	5

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	5
dl	0
loc	7
rs	10
c	0
b	0
f	0
cc	2
nop	2

# -*- coding: utf-8 -*-
#
# This file is part of SENAITE.CORE
#
# Copyright 2018 by it's authors.
# Some rights reserved. See LICENSE.rst, CONTRIBUTORS.rst.

""" 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'):

            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'):

            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:

            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.'):


            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'):

            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'):

            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'):

            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'):

            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)'):

            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)'):

            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'):

            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'):

            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'):

            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:'):

            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

        # 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)


1		# -- coding: utf-8 --
2		#
3		# This file is part of SENAITE.CORE
4		#
5		# Copyright 2018 by it's authors.
6		# Some rights reserved. See LICENSE.rst, CONTRIBUTORS.rst.
7
8		""" Omnia Axios XRF
9		"""
10		from datetime import datetime
11		from bika.lims.utils import to_unicode
12		from bika.lims import bikaMessageFactory as _
13		from bika.lims.exportimport.instruments.resultsimport import \
14		AnalysisResultsImporter, InstrumentCSVResultsFileParser
15
16		class AxiosXrfCSVMultiParser(InstrumentCSVResultsFileParser):
17
18		def __init__(self, csv):
19		InstrumentCSVResultsFileParser.__init__(self, csv)
20		self._end_header = False
21		self._columns = []
22		self.columns_name = False #To know if the next line contains
23		#analytic's columns name
24
25
26		def _parseline(self, line):
27		# Process the line differenly if it pertains at header or results block
28		if self._end_header == False:
29		sline = line.strip(',')
30		return self.parse_headerline(sline)
31		else:
32		return self.parse_resultline(line)
33
34		def splitLine(self, line):
35		# If pertains at header it split the line by ':' and then remove ','
36		# Else split by ',' and remove blank spaces
37		if self._end_header == False:
38		sline = line.split(':')
39		return [token.strip(',') for token in sline]
40
41		return [token.strip() for token in line.split(',')]
42
43		def csvDate2BikaDate(self,DateTime):
44		#11/03/2014 14:46:46 --> %d/%m/%Y %H:%M %p
45		dtobj = datetime.strptime(DateTime,"%d/%m/%Y %H:%M:%S")
46		return dtobj.strftime("%Y%m%d %H:%M:%S")
47
48		def parse_headerline(self, line):
49		#Process incoming header line
50		"""11/03/2014 14:46:46
51		PANalytical
52		Results quantitative - Omnian 2013,
53
54		Selected archive:,Omnian 2013
55		Number of results selected:,4
56		"""
57
58		# Save each header field (that we know) and its own value in the dict
59		if line.startswith('Results quantitative'):
60		line = to_unicode(line)
61		if len(self._header) == 0:
62		self.err("Unexpected header format", numline=self._numline)
63		return -1
64
65		line = line.replace(',', "")
66		splitted = line.split(' - ')
67		self._header['Quantitative'] = splitted[1]
68		return 1
69
70	View Code Duplication	if line.startswith('Selected archive'):
		0 ignored issues – show Duplication introduced 2017-12-01 14:39 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
71		if len(self._header) == 0:
72		self.err("No header found", numline=self._numline)
73		return -1
74
75		splitted = self.splitLine(line)
76		if len(splitted) > 1:
77		self._header['Archive'] = splitted[1].replace('"', '').strip()
78		else:
79		self.warn('Unexpected header format', numline=self._numline)
80		return 0
81
82	View Code Duplication	if line.startswith('Number of'):
		0 ignored issues – show Duplication introduced 2017-12-01 14:39 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
83		if len(self._header) == 0:
84		self.err("No header found", numline=self._numline)
85		return -1
86
87		splitted = self.splitLine(line)
88		if len(splitted) > 1:
89		self._header['NumResults'] = splitted[1].replace('"', '').strip()
90		else:
91		self.warn('Unexpected header format', numline=self._numline)
92		return 0
93
94		if line.startswith('Seq.'):
95		if len(self._header) == 0:
96		self.err("No header found", numline=self._numline)
97		return -1
98		#Grab column names
99		self._columns = line.split(',')
100		self._end_header = True
101		return 1
102
103		else:
104		self._header['Date'] = line
105		return 1
106
107
108
109		def parse_resultline(self, line):
110		# Process incoming results line
111		if not line.strip():
112		return 0
113		if line.startswith(',,'):
114		return 0
115
116		rawdict = {}
117		# Split by ","
118		splitted = self.splitLine(line.strip(";"))
119
120		errors = ''
121
122		# Adjunt separated values from split by ','
123		for idx, result in enumerate(splitted):
124		if result.startswith('"'):
125		# It means that is the value's firts part
126		# Consequently we take second part and append both
127		result = (splitted[idx].strip('"') + "," + splitted[idx+1].strip('"'))
128		splitted[idx] = result
129		splitted.remove(splitted[idx+1])
130
131		result_type = ''
132		result_sum = ''
133		for idx, result in enumerate(splitted):
134		if self._columns[idx] == 'Result type':
135		result_type = result
136		elif self._columns[idx].startswith('Sample name'):
137		rid = result
138		elif self._columns[idx].startswith('Seq.'):
139		pass
140		elif self._columns[idx] == 'Sum':
141		result_sum = result
142		else:
143		rawdict[self._columns[idx]] = {'DefaultResult':result_type,
144		# Replace to obtain UK values from default
145		'Concentration':result.replace(',','.'),
146		'Sum':result_sum}
147		try:
148		rawdict['DateTime'] = {'DateTime':self.csvDate2BikaDate(self._header['Date']),
149		'DefaultValue':'DateTime'}
150		except:
151		pass
152		if not rid:
		0 ignored issues – show introduced 2018-07-25 08:58 UTC by Report Bug Copy Issue Report The variable `rid` does not seem to be defined in case the `for` loop on line `133` is not entered. Are you sure this can never be the case? Loading history...
153		self.err("No Sample defined", numline=self._numline)
154		return 0
155
156		self._addRawResult(rid, rawdict, True)
157		return 0
158
159
160		def getAttachmentFileType(self):
161		return "PANalytical - Omnia Axios XRF"
162
163		class AxiosXrfCSVParser(InstrumentCSVResultsFileParser):
164
165		def __init__(self, csv):
166		InstrumentCSVResultsFileParser.__init__(self, csv)
167		self._end_header = False
168		self._columns = []
169		self.columns_name = False #To know if the next line contains
170		#analytic's columns name
171
172		def _parseline(self, line):
173		# Process the line differenly if it pertains at header or results block
174		if self._end_header == False:
175		sline = line.strip(',')
176		return self.parse_headerline(sline)
177		else:
178		return self.parse_resultline(line)
179
180		def csvDate2BikaDate(self,DateTime):
181		#11/03/2014 14:46:46 --> %d/%m/%Y %H:%M %p
182		dtobj = datetime.strptime(DateTime,"%d/%m/%Y %H:%M:%S")
183		return dtobj.strftime("%Y%m%d %H:%M:%S")
184
185		def splitLine(self, line):
186		# If pertains at header it split the line by ':' and then remove ','
187		# Else split by ',' and remove blank spaces
188		if self._end_header == False:
189		sline = line.split(':')
190		return [token.strip(',') for token in sline]
191
192		return [token.strip() for token in line.split(',')]
193
194		def parse_headerline(self, line):
195		#Process incoming header line
196		"""
197		29/11/2013 10:15:44
198		PANalytical
199		"Quantification of sample ESFERA CINZA - 1g H3BO3 - 1:0,5 - NO PPC",
200
201		R.M.S.:,"0,035"
202		Result status:,
203		Sum before normalization:,"119,5 %"
204		Normalised to:,"100,0 %"
205		Sample type:,Pressed powder
206		Initial sample weight (g):,"2,000"
207		Weight after pressing (g):,"3,000"
208		Correction applied for medium:,No
209		Correction applied for film:,No
210		Used Compound list:,Oxides
211		Results database:,omnian 2013
212		Results database in:,c:\panalytical\superq\userdata
213		"""
214
215		if line.startswith('"Quantification of sample') or line.startswith('Quantification of sample'):
216		line = to_unicode(line)
217		if len(self._header) == 0:
218		self.warn('Unexpected header format', numline=self._numline)
219		return -1
220		# Remove non important string and double comas to obtein
221		# the sample name free
222		line = line.replace("Quantification of sample ", "")
223		line = line.replace('"', "")
224		splitted = line.split(' - ')
225
226		if len(splitted) > 3:# Maybe we don't need this, i could be all the sample's identifier...
227		self._header['Sample'] = splitted[0].strip(' ')
228		self._header['Quantity'] = splitted[1]
229		self._header['????'] = splitted[2]# At present we
230		# don't know what
231		# is that
232		self._header['PPC'] = splitted[3]
233
234		elif len(splitted) == 1:
235		self._header['Sample'] = splitted[0].replace('Quantification of sample','').strip(' ')
236
237		else:
238		self.warn('Unexpected header format', numline=self._numline)
239		return 1
240		# Save each header field (that we know) and its own value in the dict
241	View Code Duplication	if line.startswith('R.M.S.'):
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242
243		if len(self._header) == 0:
244		self.err("No header found", numline=self._numline)
245		return -1
246
247		splitted = self.splitLine(line)
248		if len(splitted) > 1:
249		self._header['R.M.S.'] = splitted[1].replace('"', '').strip()
250		else:
251		self.warn('Unexpected header format', numline=self._numline)
252		return 0
253
254	View Code Duplication	if line.startswith('Result status'):
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255		if len(self._header) == 0:
256		self.err("No header found", numline=self._numline)
257
258		splitted = self.splitLine(line)
259		if len(splitted) > 1:
260		self._header['Result status'] = splitted[1].replace('"', '').strip()
261		else:
262		self.warn('Unexpected header format', numline=self._numline)
263
264		return 0
265
266	View Code Duplication	if line.startswith('Sum before normalization'):
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267		if len(self._header) == 0:
268		self.err("No header found", numline=self._numline)
269		return -1
270
271		splitted = self.splitLine(line)
272		if len(splitted) > 1:
273		self._header['Sum'] = splitted[1].replace('"', '').strip()
274		else:
275		self.warn('Unexpected header format', numline=self._numline)
276
277		return 0
278
279	View Code Duplication	if line.startswith('Normalised to'):
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280		if len(self._header) == 0:
281		self.err("No header found", numline=self._numline)
282		return -1
283
284		splitted = self.splitLine(line)
285		if len(splitted) > 1:
286		self._header['Normalized'] = splitted[1].replace('"', '').strip()
287		else:
288		self.warn('Unexpected header format', numline=self._numline)
289
290		return 0
291
292	View Code Duplication	if line.startswith('Sample type'):
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293		if len(self._header) == 0:
294		self.err("No header found", numline=self._numline)
295		return -1
296
297		splitted = self.splitLine(line)
298		if len(splitted) > 1:
299		self._header['Sample type'] = splitted[1].strip()
300		else:
301		self.warn('Unexpected header format', numline=self._numline)
302
303		return 0
304
305	View Code Duplication	if line.startswith('Initial sample weight (g)'):
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306		if len(self._header) == 0:
307		self.err("No header found", numline=self._numline)
308		return -1
309
310		splitted = self.splitLine(line)
311		if len(splitted) > 1:
312		self._header['Initial sample weight'] = splitted[1].replace('"', '').strip()
313		else:
314		self.warn('Unexpected header format', numline=self._numline)
315
316		return 0
317
318	View Code Duplication	if line.startswith('Weight after pressing (g)'):
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319		if len(self._header) == 0:
320		self.err("No header found", numline=self._numline)
321		return -1
322
323		splitted = self.splitLine(line)
324		if len(splitted) > 1:
325		self._header['Weight after pressing'] = splitted[1].replace('"', '').strip()
326		else:
327		self.warn('Unexpected header format', numline=self._numline)
328
329		return 0
330
331	View Code Duplication	if line.startswith('Correction applied for medium'):
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332		if len(self._header) == 0:
333		self.warn('Unexpected header format', numline=self._numline)
334		return -1
335
336		splitted = self.splitLine(line)
337		if len(splitted) > 1:
338		self._header['Correction medium'] = splitted[1].replace('"', '').strip()
339		else:
340		self.warn('Unexpected header format', numline=self._numline)
341
342		return 0
343
344	View Code Duplication	if line.startswith('Correction applied for film'):
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345		if len(self._header) == 0:
346		self.err("No header found", numline=self._numline)
347		return -1
348
349		splitted = self.splitLine(line)
350		if len(splitted) > 1:
351		self._header['Correction film'] = splitted[1].replace('"', '').strip()
352		else:
353		self.warn('Unexpected header format', numline=self._numline)
354
355		return 0
356
357	View Code Duplication	if line.startswith('Used Compound list'):
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358		if len(self._header) == 0:
359		self.err("No header found", numline=self._numline)
360		return -1
361
362		splitted = self.splitLine(line)
363		if len(splitted) > 1:
364		self._header['Used compound'] = splitted[1].replace('"', '').strip()
365		else:
366		self.warn('Unexpected header format', numline=self._numline)
367
368		return 0
369	View Code Duplication	if line.startswith('Results database:'):
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370		if len(self._header) == 0:
371		self.err("No header found", numline=self._numline)
372		return -1
373
374		splitted = self.splitLine(line)
375		if len(splitted) > 1:
376		self._header['Result database'] = splitted[1].replace('"', '').strip()
377		else:
378		self.warn('Unexpected header format', numline=self._numline)
379
380		return 0
381
382
383		if self.columns_name:
384		if len(self._header) == 0:
385		self.err("No header found", numline=self._numline)
386		return -1
387
388		#Grab column names
389		self._end_header = True
390		self._columns = self.splitLine(line)
391		return 1
392
393		if line.startswith('Results database in'):
394		if len(self._header) == 0:
395		self.err("No header found", numline=self._numline)
396		return -1
397
398		splitted = self.splitLine(line)
399		if len(splitted) > 1:
400		self._header['Database path'] = splitted[1]+splitted[2]
401		self.columns_name = True
402		else:
403		self.warn('Unexpected header format', numline=self._numline)
404
405		return 1
406
407		else:
408		self._header['Date'] = line
409		return 1
410
411		def parse_resultline(self, line):
412		# Process incoming results line
413		if not line.strip():
414		return 0
415
416		rawdict = {}
417		# Split by ","
418		splitted = self.splitLine(line.strip(";"))
419		# Look to know if the first value is an enumerate field
420		try:
421		int(splitted[0])
422		rawdict["num"] = splitted[0]
423		splitted = splitted[1:]
424		except ValueError:
425		pass
426
427		# Enumerate the list to obtain: [(0,data0),(1,data1),...]
428		e_splitted = list(enumerate(splitted))
429		errors = ''
430
431		com = False
432		for idx, result in e_splitted:
433		if result.startswith('"'):
434		# It means that is the first value part
435		# Consequently we take second part and append both
436		result = (e_splitted[idx][1].strip('"') + "," + e_splitted[idx+1][1].strip('"'))
437		e_splitted[idx] = (idx,result)
438		e_splitted.remove(e_splitted[idx+1])
439		com = True
440		rawdict[self._columns[idx]] = result
441		conc = self._columns[idx] # Main value's name
442
443
444		elif com:# We have rm the 2nd part value, consequently we
445		# need to decrement idx
446		if len(self._columns) <= idx-1:
447		self.err("Orphan value in column ${index}",
448		mapping={"index":str(idx + 1)},
449		numline=self._numline)
450		break
451		# We add and sync the result with its value's name
452		rawdict[self._columns[idx-1]] = result
453
454		else:
455		if len(self._columns) <= idx:
456		self.err("Orphan value in column ${index}",
457		mapping={"index":str(idx + 1)},
458		numline=self._numline)
459		break
460		rawdict[self._columns[idx]] = result
461
462		aname = rawdict[self._columns[0]]# The fisrt column is analytic name
463		if not aname:
464		self.err("No Analysis Name defined", numline=self._numline)
465		return 0
466		elif aname == "<H>":
467		# <H> maybe is data error header? We need more examples...
468		errors = rawdict.get('Compound')
469		notes = rawdict.get('Calibration')
470		rawdict['Notes'] = notes
471
472		rid = self._header['Sample']
473		if not rid:
474		self.err("No Sample defined", numline=self._numline)
475		return 0
476
477		notes = rawdict.get('Notes', '')
478		notes = "Notes: %s" % notes if notes else ''
479		rawdict['DefaultResult'] = conc
		0 ignored issues – show introduced 2018-07-25 08:58 UTC by Report Bug Copy Issue Report The variable `conc` does not seem to be defined in case the `for` loop on line `432` is not entered. Are you sure this can never be the case? Loading history...
480		# Replace to obtain UK values from default
481		rawdict[conc] = rawdict[conc].replace(',','.')
482		rawdict['Remarks'] = ' '.join([errors, notes])
483		rawres = self.getRawResults().get(rid, [])
484		raw = rawres[0] if len(rawres) > 0 else {}
485		raw[aname] = rawdict
486		if not 'DateTime' in raw:
487		try:
488		raw['DateTime'] = {'DateTime':self.csvDate2BikaDate(self._header['Date']),
489		'DefaultValue':'DateTime'}
490		except:
491		pass
492
493		self._addRawResult(rid, raw, True)
494		return 0
495
496
497		def getAttachmentFileType(self):
498		return "PANalytical - Omnia Axios XRF"
499
500
501		class AxiosXrfImporter(AnalysisResultsImporter):
502
503		def __init__(self, parser, context, override,
504		allowed_ar_states=None, allowed_analysis_states=None,
505		instrument_uid=None):
506		AnalysisResultsImporter.__init__(self, parser, context,
507		override,
508		allowed_ar_states,
509		allowed_analysis_states,
510		instrument_uid)
511

senaite / senaite.core

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AxiosXrfCSVMultiParser._parseline() A

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