| Total Complexity | 97 |
| Total Lines | 524 |
| Duplicated Lines | 29.2 % |
| Changes | 0 | ||
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like build.bika.lims.exportimport.instruments.panalytical.omnia often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | # -*- coding: utf-8 -*- |
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| 2 | # |
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| 3 | # This file is part of SENAITE.CORE. |
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| 4 | # |
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| 5 | # SENAITE.CORE is free software: you can redistribute it and/or modify it under |
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| 6 | # the terms of the GNU General Public License as published by the Free Software |
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| 7 | # Foundation, version 2. |
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| 8 | # |
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| 9 | # This program is distributed in the hope that it will be useful, but WITHOUT |
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| 10 | # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
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| 11 | # FOR A PARTICULAR PURPOSE. See the GNU General Public License for more |
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| 12 | # details. |
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| 13 | # |
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| 14 | # You should have received a copy of the GNU General Public License along with |
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| 15 | # this program; if not, write to the Free Software Foundation, Inc., 51 |
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| 16 | # Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. |
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| 17 | # |
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| 18 | # Copyright 2018-2019 by it's authors. |
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| 19 | # Some rights reserved, see README and LICENSE. |
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| 20 | |||
| 21 | """ Omnia Axios XRF |
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| 22 | """ |
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| 23 | from datetime import datetime |
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| 24 | from bika.lims.utils import to_unicode |
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| 25 | from bika.lims import bikaMessageFactory as _ |
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| 26 | from bika.lims.exportimport.instruments.resultsimport import \ |
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| 27 | AnalysisResultsImporter, InstrumentCSVResultsFileParser |
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| 28 | |||
| 29 | class AxiosXrfCSVMultiParser(InstrumentCSVResultsFileParser): |
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| 30 | |||
| 31 | def __init__(self, csv): |
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| 32 | InstrumentCSVResultsFileParser.__init__(self, csv) |
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| 33 | self._end_header = False |
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| 34 | self._columns = [] |
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| 35 | self.columns_name = False #To know if the next line contains |
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| 36 | #analytic's columns name |
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| 37 | |||
| 38 | |||
| 39 | def _parseline(self, line): |
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| 40 | # Process the line differenly if it pertains at header or results block |
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| 41 | if self._end_header == False: |
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| 42 | sline = line.strip(',') |
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| 43 | return self.parse_headerline(sline) |
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| 44 | else: |
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| 45 | return self.parse_resultline(line) |
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| 46 | |||
| 47 | def splitLine(self, line): |
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| 48 | # If pertains at header it split the line by ':' and then remove ',' |
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| 49 | # Else split by ',' and remove blank spaces |
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| 50 | if self._end_header == False: |
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| 51 | sline = line.split(':') |
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| 52 | return [token.strip(',') for token in sline] |
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| 53 | |||
| 54 | return [token.strip() for token in line.split(',')] |
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| 55 | |||
| 56 | def csvDate2BikaDate(self,DateTime): |
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| 57 | #11/03/2014 14:46:46 --> %d/%m/%Y %H:%M %p |
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| 58 | dtobj = datetime.strptime(DateTime,"%d/%m/%Y %H:%M:%S") |
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| 59 | return dtobj.strftime("%Y%m%d %H:%M:%S") |
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| 60 | |||
| 61 | def parse_headerline(self, line): |
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| 62 | #Process incoming header line |
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| 63 | """11/03/2014 14:46:46 |
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| 64 | PANalytical |
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| 65 | Results quantitative - Omnian 2013, |
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| 66 | |||
| 67 | Selected archive:,Omnian 2013 |
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| 68 | Number of results selected:,4 |
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| 69 | """ |
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| 70 | |||
| 71 | # Save each header field (that we know) and its own value in the dict |
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| 72 | if line.startswith('Results quantitative'): |
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| 73 | line = to_unicode(line) |
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| 74 | if len(self._header) == 0: |
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| 75 | self.err("Unexpected header format", numline=self._numline) |
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| 76 | return -1 |
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| 77 | |||
| 78 | line = line.replace(',', "") |
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| 79 | splitted = line.split(' - ') |
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| 80 | self._header['Quantitative'] = splitted[1] |
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| 81 | return 1 |
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| 82 | |||
| 83 | View Code Duplication | if line.startswith('Selected archive'): |
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|
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| 84 | if len(self._header) == 0: |
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| 85 | self.err("No header found", numline=self._numline) |
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| 86 | return -1 |
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| 87 | |||
| 88 | splitted = self.splitLine(line) |
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| 89 | if len(splitted) > 1: |
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| 90 | self._header['Archive'] = splitted[1].replace('"', '').strip() |
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| 91 | else: |
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| 92 | self.warn('Unexpected header format', numline=self._numline) |
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| 93 | return 0 |
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| 94 | |||
| 95 | View Code Duplication | if line.startswith('Number of'): |
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| 96 | if len(self._header) == 0: |
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| 97 | self.err("No header found", numline=self._numline) |
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| 98 | return -1 |
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| 99 | |||
| 100 | splitted = self.splitLine(line) |
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| 101 | if len(splitted) > 1: |
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| 102 | self._header['NumResults'] = splitted[1].replace('"', '').strip() |
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| 103 | else: |
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| 104 | self.warn('Unexpected header format', numline=self._numline) |
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| 105 | return 0 |
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| 106 | |||
| 107 | if line.startswith('Seq.'): |
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| 108 | if len(self._header) == 0: |
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| 109 | self.err("No header found", numline=self._numline) |
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| 110 | return -1 |
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| 111 | #Grab column names |
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| 112 | self._columns = line.split(',') |
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| 113 | self._end_header = True |
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| 114 | return 1 |
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| 115 | |||
| 116 | else: |
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| 117 | self._header['Date'] = line |
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| 118 | return 1 |
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| 119 | |||
| 120 | |||
| 121 | |||
| 122 | def parse_resultline(self, line): |
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| 123 | # Process incoming results line |
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| 124 | if not line.strip(): |
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| 125 | return 0 |
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| 126 | if line.startswith(',,'): |
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| 127 | return 0 |
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| 128 | |||
| 129 | rawdict = {} |
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| 130 | # Split by "," |
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| 131 | splitted = self.splitLine(line.strip(";")) |
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| 132 | |||
| 133 | errors = '' |
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| 134 | |||
| 135 | # Adjunt separated values from split by ',' |
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| 136 | for idx, result in enumerate(splitted): |
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| 137 | if result.startswith('"'): |
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| 138 | # It means that is the value's firts part |
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| 139 | # Consequently we take second part and append both |
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| 140 | result = (splitted[idx].strip('"') + "," + splitted[idx+1].strip('"')) |
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| 141 | splitted[idx] = result |
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| 142 | splitted.remove(splitted[idx+1]) |
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| 143 | |||
| 144 | result_type = '' |
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| 145 | result_sum = '' |
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| 146 | for idx, result in enumerate(splitted): |
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| 147 | if self._columns[idx] == 'Result type': |
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| 148 | result_type = result |
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| 149 | elif self._columns[idx].startswith('Sample name'): |
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| 150 | rid = result |
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| 151 | elif self._columns[idx].startswith('Seq.'): |
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| 152 | pass |
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| 153 | elif self._columns[idx] == 'Sum': |
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| 154 | result_sum = result |
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| 155 | else: |
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| 156 | rawdict[self._columns[idx]] = {'DefaultResult':result_type, |
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| 157 | # Replace to obtain UK values from default |
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| 158 | 'Concentration':result.replace(',','.'), |
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| 159 | 'Sum':result_sum} |
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| 160 | try: |
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| 161 | rawdict['DateTime'] = {'DateTime':self.csvDate2BikaDate(self._header['Date']), |
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| 162 | 'DefaultValue':'DateTime'} |
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| 163 | except: |
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| 164 | pass |
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| 165 | if not rid: |
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| 166 | self.err("No Sample defined", numline=self._numline) |
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| 167 | return 0 |
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| 168 | |||
| 169 | self._addRawResult(rid, rawdict, True) |
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| 170 | return 0 |
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| 171 | |||
| 172 | |||
| 173 | def getAttachmentFileType(self): |
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| 174 | return "PANalytical - Omnia Axios XRF" |
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| 175 | |||
| 176 | class AxiosXrfCSVParser(InstrumentCSVResultsFileParser): |
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| 177 | |||
| 178 | def __init__(self, csv): |
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| 179 | InstrumentCSVResultsFileParser.__init__(self, csv) |
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| 180 | self._end_header = False |
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| 181 | self._columns = [] |
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| 182 | self.columns_name = False #To know if the next line contains |
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| 183 | #analytic's columns name |
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| 184 | |||
| 185 | def _parseline(self, line): |
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| 186 | # Process the line differenly if it pertains at header or results block |
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| 187 | if self._end_header == False: |
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| 188 | sline = line.strip(',') |
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| 189 | return self.parse_headerline(sline) |
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| 190 | else: |
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| 191 | return self.parse_resultline(line) |
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| 192 | |||
| 193 | def csvDate2BikaDate(self,DateTime): |
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| 194 | #11/03/2014 14:46:46 --> %d/%m/%Y %H:%M %p |
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| 195 | dtobj = datetime.strptime(DateTime,"%d/%m/%Y %H:%M:%S") |
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| 196 | return dtobj.strftime("%Y%m%d %H:%M:%S") |
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| 197 | |||
| 198 | def splitLine(self, line): |
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| 199 | # If pertains at header it split the line by ':' and then remove ',' |
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| 200 | # Else split by ',' and remove blank spaces |
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| 201 | if self._end_header == False: |
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| 202 | sline = line.split(':') |
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| 203 | return [token.strip(',') for token in sline] |
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| 204 | |||
| 205 | return [token.strip() for token in line.split(',')] |
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| 206 | |||
| 207 | def parse_headerline(self, line): |
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| 208 | #Process incoming header line |
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| 209 | """ |
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| 210 | 29/11/2013 10:15:44 |
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| 211 | PANalytical |
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| 212 | "Quantification of sample ESFERA CINZA - 1g H3BO3 - 1:0,5 - NO PPC", |
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| 213 | |||
| 214 | R.M.S.:,"0,035" |
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| 215 | Result status:, |
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| 216 | Sum before normalization:,"119,5 %" |
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| 217 | Normalised to:,"100,0 %" |
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| 218 | Sample type:,Pressed powder |
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| 219 | Initial sample weight (g):,"2,000" |
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| 220 | Weight after pressing (g):,"3,000" |
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| 221 | Correction applied for medium:,No |
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| 222 | Correction applied for film:,No |
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| 223 | Used Compound list:,Oxides |
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| 224 | Results database:,omnian 2013 |
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| 225 | Results database in:,c:\panalytical\superq\userdata |
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| 226 | """ |
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| 227 | |||
| 228 | if line.startswith('"Quantification of sample') or line.startswith('Quantification of sample'): |
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| 229 | line = to_unicode(line) |
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| 230 | if len(self._header) == 0: |
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| 231 | self.warn('Unexpected header format', numline=self._numline) |
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| 232 | return -1 |
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| 233 | # Remove non important string and double comas to obtein |
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| 234 | # the sample name free |
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| 235 | line = line.replace("Quantification of sample ", "") |
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| 236 | line = line.replace('"', "") |
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| 237 | splitted = line.split(' - ') |
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| 238 | |||
| 239 | if len(splitted) > 3:# Maybe we don't need this, i could be all the sample's identifier... |
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| 240 | self._header['Sample'] = splitted[0].strip(' ') |
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| 241 | self._header['Quantity'] = splitted[1] |
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| 242 | self._header['????'] = splitted[2]# At present we |
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| 243 | # don't know what |
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| 244 | # is that |
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| 245 | self._header['PPC'] = splitted[3] |
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| 246 | |||
| 247 | elif len(splitted) == 1: |
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| 248 | self._header['Sample'] = splitted[0].replace('Quantification of sample','').strip(' ') |
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| 249 | |||
| 250 | else: |
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| 251 | self.warn('Unexpected header format', numline=self._numline) |
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| 252 | return 1 |
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| 253 | # Save each header field (that we know) and its own value in the dict |
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| 254 | View Code Duplication | if line.startswith('R.M.S.'): |
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| 255 | |||
| 256 | if len(self._header) == 0: |
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| 257 | self.err("No header found", numline=self._numline) |
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| 258 | return -1 |
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| 259 | |||
| 260 | splitted = self.splitLine(line) |
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| 261 | if len(splitted) > 1: |
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| 262 | self._header['R.M.S.'] = splitted[1].replace('"', '').strip() |
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| 263 | else: |
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| 264 | self.warn('Unexpected header format', numline=self._numline) |
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| 265 | return 0 |
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| 266 | |||
| 267 | View Code Duplication | if line.startswith('Result status'): |
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| 268 | if len(self._header) == 0: |
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| 269 | self.err("No header found", numline=self._numline) |
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| 270 | |||
| 271 | splitted = self.splitLine(line) |
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| 272 | if len(splitted) > 1: |
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| 273 | self._header['Result status'] = splitted[1].replace('"', '').strip() |
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| 274 | else: |
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| 275 | self.warn('Unexpected header format', numline=self._numline) |
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| 276 | |||
| 277 | return 0 |
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| 278 | |||
| 279 | View Code Duplication | if line.startswith('Sum before normalization'): |
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| 280 | if len(self._header) == 0: |
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| 281 | self.err("No header found", numline=self._numline) |
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| 282 | return -1 |
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| 283 | |||
| 284 | splitted = self.splitLine(line) |
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| 285 | if len(splitted) > 1: |
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| 286 | self._header['Sum'] = splitted[1].replace('"', '').strip() |
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| 287 | else: |
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| 288 | self.warn('Unexpected header format', numline=self._numline) |
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| 289 | |||
| 290 | return 0 |
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| 291 | |||
| 292 | View Code Duplication | if line.startswith('Normalised to'): |
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| 293 | if len(self._header) == 0: |
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| 294 | self.err("No header found", numline=self._numline) |
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| 295 | return -1 |
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| 296 | |||
| 297 | splitted = self.splitLine(line) |
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| 298 | if len(splitted) > 1: |
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| 299 | self._header['Normalized'] = splitted[1].replace('"', '').strip() |
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| 300 | else: |
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| 301 | self.warn('Unexpected header format', numline=self._numline) |
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| 302 | |||
| 303 | return 0 |
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| 304 | |||
| 305 | View Code Duplication | if line.startswith('Sample type'): |
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| 306 | if len(self._header) == 0: |
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| 307 | self.err("No header found", numline=self._numline) |
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| 308 | return -1 |
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| 309 | |||
| 310 | splitted = self.splitLine(line) |
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| 311 | if len(splitted) > 1: |
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| 312 | self._header['Sample type'] = splitted[1].strip() |
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| 313 | else: |
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| 314 | self.warn('Unexpected header format', numline=self._numline) |
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| 315 | |||
| 316 | return 0 |
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| 317 | |||
| 318 | View Code Duplication | if line.startswith('Initial sample weight (g)'): |
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| 319 | if len(self._header) == 0: |
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| 320 | self.err("No header found", numline=self._numline) |
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| 321 | return -1 |
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| 322 | |||
| 323 | splitted = self.splitLine(line) |
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| 324 | if len(splitted) > 1: |
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| 325 | self._header['Initial sample weight'] = splitted[1].replace('"', '').strip() |
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| 326 | else: |
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| 327 | self.warn('Unexpected header format', numline=self._numline) |
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| 328 | |||
| 329 | return 0 |
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| 330 | |||
| 331 | View Code Duplication | if line.startswith('Weight after pressing (g)'): |
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| 332 | if len(self._header) == 0: |
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| 333 | self.err("No header found", numline=self._numline) |
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| 334 | return -1 |
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| 335 | |||
| 336 | splitted = self.splitLine(line) |
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| 337 | if len(splitted) > 1: |
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| 338 | self._header['Weight after pressing'] = splitted[1].replace('"', '').strip() |
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| 339 | else: |
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| 340 | self.warn('Unexpected header format', numline=self._numline) |
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| 341 | |||
| 342 | return 0 |
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| 343 | |||
| 344 | View Code Duplication | if line.startswith('Correction applied for medium'): |
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| 345 | if len(self._header) == 0: |
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| 346 | self.warn('Unexpected header format', numline=self._numline) |
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| 347 | return -1 |
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| 348 | |||
| 349 | splitted = self.splitLine(line) |
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| 350 | if len(splitted) > 1: |
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| 351 | self._header['Correction medium'] = splitted[1].replace('"', '').strip() |
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| 352 | else: |
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| 353 | self.warn('Unexpected header format', numline=self._numline) |
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| 354 | |||
| 355 | return 0 |
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| 356 | |||
| 357 | View Code Duplication | if line.startswith('Correction applied for film'): |
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| 358 | if len(self._header) == 0: |
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| 359 | self.err("No header found", numline=self._numline) |
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| 360 | return -1 |
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| 361 | |||
| 362 | splitted = self.splitLine(line) |
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| 363 | if len(splitted) > 1: |
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| 364 | self._header['Correction film'] = splitted[1].replace('"', '').strip() |
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| 365 | else: |
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| 366 | self.warn('Unexpected header format', numline=self._numline) |
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| 367 | |||
| 368 | return 0 |
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| 369 | |||
| 370 | View Code Duplication | if line.startswith('Used Compound list'): |
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| 371 | if len(self._header) == 0: |
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| 372 | self.err("No header found", numline=self._numline) |
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| 373 | return -1 |
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| 374 | |||
| 375 | splitted = self.splitLine(line) |
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| 376 | if len(splitted) > 1: |
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| 377 | self._header['Used compound'] = splitted[1].replace('"', '').strip() |
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| 378 | else: |
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| 379 | self.warn('Unexpected header format', numline=self._numline) |
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| 380 | |||
| 381 | return 0 |
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| 382 | View Code Duplication | if line.startswith('Results database:'): |
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| 383 | if len(self._header) == 0: |
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| 384 | self.err("No header found", numline=self._numline) |
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| 385 | return -1 |
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| 386 | |||
| 387 | splitted = self.splitLine(line) |
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| 388 | if len(splitted) > 1: |
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| 389 | self._header['Result database'] = splitted[1].replace('"', '').strip() |
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| 390 | else: |
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| 391 | self.warn('Unexpected header format', numline=self._numline) |
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| 392 | |||
| 393 | return 0 |
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| 394 | |||
| 395 | |||
| 396 | if self.columns_name: |
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| 397 | if len(self._header) == 0: |
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| 398 | self.err("No header found", numline=self._numline) |
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| 399 | return -1 |
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| 400 | |||
| 401 | #Grab column names |
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| 402 | self._end_header = True |
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| 403 | self._columns = self.splitLine(line) |
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| 404 | return 1 |
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| 405 | |||
| 406 | if line.startswith('Results database in'): |
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| 407 | if len(self._header) == 0: |
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| 408 | self.err("No header found", numline=self._numline) |
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| 409 | return -1 |
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| 410 | |||
| 411 | splitted = self.splitLine(line) |
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| 412 | if len(splitted) > 1: |
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| 413 | self._header['Database path'] = splitted[1]+splitted[2] |
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| 414 | self.columns_name = True |
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| 415 | else: |
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| 416 | self.warn('Unexpected header format', numline=self._numline) |
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| 417 | |||
| 418 | return 1 |
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| 419 | |||
| 420 | else: |
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| 421 | self._header['Date'] = line |
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| 422 | return 1 |
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| 423 | |||
| 424 | def parse_resultline(self, line): |
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| 425 | # Process incoming results line |
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| 426 | if not line.strip(): |
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| 427 | return 0 |
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| 428 | |||
| 429 | rawdict = {} |
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| 430 | # Split by "," |
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| 431 | splitted = self.splitLine(line.strip(";")) |
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| 432 | # Look to know if the first value is an enumerate field |
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| 433 | try: |
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| 434 | int(splitted[0]) |
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| 435 | rawdict["num"] = splitted[0] |
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| 436 | splitted = splitted[1:] |
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| 437 | except ValueError: |
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| 438 | pass |
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| 439 | |||
| 440 | # Enumerate the list to obtain: [(0,data0),(1,data1),...] |
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| 441 | e_splitted = list(enumerate(splitted)) |
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| 442 | errors = '' |
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| 443 | |||
| 444 | com = False |
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| 445 | for idx, result in e_splitted: |
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| 446 | if result.startswith('"'): |
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| 447 | # It means that is the first value part |
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| 448 | # Consequently we take second part and append both |
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| 449 | result = (e_splitted[idx][1].strip('"') + "," + e_splitted[idx+1][1].strip('"')) |
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| 450 | e_splitted[idx] = (idx,result) |
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| 451 | e_splitted.remove(e_splitted[idx+1]) |
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| 452 | com = True |
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| 453 | rawdict[self._columns[idx]] = result |
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| 454 | conc = self._columns[idx] # Main value's name |
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| 455 | |||
| 456 | |||
| 457 | elif com:# We have rm the 2nd part value, consequently we |
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| 458 | # need to decrement idx |
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| 459 | if len(self._columns) <= idx-1: |
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| 460 | self.err("Orphan value in column ${index}", |
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| 461 | mapping={"index":str(idx + 1)}, |
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| 462 | numline=self._numline) |
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| 463 | break |
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| 464 | # We add and sync the result with its value's name |
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| 465 | rawdict[self._columns[idx-1]] = result |
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| 466 | |||
| 467 | else: |
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| 468 | if len(self._columns) <= idx: |
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| 469 | self.err("Orphan value in column ${index}", |
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| 470 | mapping={"index":str(idx + 1)}, |
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| 471 | numline=self._numline) |
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| 472 | break |
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| 473 | rawdict[self._columns[idx]] = result |
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| 474 | |||
| 475 | aname = rawdict[self._columns[0]]# The fisrt column is analytic name |
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| 476 | if not aname: |
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| 477 | self.err("No Analysis Name defined", numline=self._numline) |
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| 478 | return 0 |
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| 479 | elif aname == "<H>": |
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| 480 | # <H> maybe is data error header? We need more examples... |
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| 481 | errors = rawdict.get('Compound') |
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| 482 | notes = rawdict.get('Calibration') |
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| 483 | rawdict['Notes'] = notes |
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| 484 | |||
| 485 | rid = self._header['Sample'] |
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| 486 | if not rid: |
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| 487 | self.err("No Sample defined", numline=self._numline) |
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| 488 | return 0 |
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| 489 | |||
| 490 | notes = rawdict.get('Notes', '') |
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| 491 | notes = "Notes: %s" % notes if notes else '' |
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| 492 | rawdict['DefaultResult'] = conc |
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| 493 | # Replace to obtain UK values from default |
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| 494 | rawdict[conc] = rawdict[conc].replace(',','.') |
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| 495 | rawdict['Remarks'] = ' '.join([errors, notes]) |
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| 496 | rawres = self.getRawResults().get(rid, []) |
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| 497 | raw = rawres[0] if len(rawres) > 0 else {} |
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| 498 | raw[aname] = rawdict |
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| 499 | if not 'DateTime' in raw: |
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| 500 | try: |
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| 501 | raw['DateTime'] = {'DateTime':self.csvDate2BikaDate(self._header['Date']), |
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| 502 | 'DefaultValue':'DateTime'} |
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| 503 | except: |
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| 504 | pass |
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| 505 | |||
| 506 | self._addRawResult(rid, raw, True) |
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| 507 | return 0 |
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| 508 | |||
| 509 | |||
| 510 | def getAttachmentFileType(self): |
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| 511 | return "PANalytical - Omnia Axios XRF" |
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| 512 | |||
| 513 | |||
| 514 | class AxiosXrfImporter(AnalysisResultsImporter): |
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| 515 | |||
| 516 | def __init__(self, parser, context, override, |
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| 517 | allowed_ar_states=None, allowed_analysis_states=None, |
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| 518 | instrument_uid=None): |
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| 519 | AnalysisResultsImporter.__init__(self, parser, context, |
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| 520 | override, |
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| 521 | allowed_ar_states, |
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| 522 | allowed_analysis_states, |
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| 523 | instrument_uid) |
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| 524 |