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1 '''
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2 Created on 31 dec. 2014
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3
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4 @author: lukas007
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5 '''
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6 import shutil
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7 import subprocess
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8 import csv
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9 from collections import OrderedDict
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10
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11 def copy_dir(src, dst):
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12 shutil.copytree(src, dst)
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13
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9
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14 def log_message(log_file, log_message):
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15 with open(log_file, "a") as text_file:
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16 text_file.write(log_message + "\n")
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17
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0
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18 def copy_file(src, dst):
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19 shutil.copy(src, dst)
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20
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21 def get_process_list():
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22 p = subprocess.Popen(['ps', '-A'], stdout=subprocess.PIPE)
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23 out, err = p.communicate()
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24 return out.splitlines()
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25
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26 def get_process_pid(process_name):
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27 pid = -1
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28 for line in get_process_list():
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29 if process_name in line:
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30 pid = int(line.split(None, 1)[0])
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31 return pid
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32
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33
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34 def get_as_dict(in_tsv):
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35 '''
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36 Generic method to parse a tab-separated file returning a dictionary with named columns
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37 @param in_tsv: input filename to be parsed
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38 '''
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39 data = list(csv.reader(open(in_tsv, 'rU'), delimiter='\t'))
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40 header = data.pop(0)
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41 # Create dictionary with column name as key
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42 output = {}
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43 for index in xrange(len(header)):
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44 output[header[index]] = [row[index] for row in data]
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45 return output
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46
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47 def save_dict_as_tsv(dict, out_tsv):
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48 '''
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49 Writes tab-separated data to file
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50 @param data: dictionary containing merged dataset
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51 @param out_tsv: output tsv file
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52 '''
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53
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54 # Open output file for writing
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55 out_file = open(out_tsv, 'wb')
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56 output_writer = csv.writer(out_file, delimiter="\t")
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57
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58 # Write headers
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59 output_writer.writerow(list(dict.keys()))
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60
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61 # Write
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62 for record_index in xrange(len(dict[dict.keys()[0]])):
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63 row = [dict[k][record_index] for k in dict]
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64 output_writer.writerow(row)
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65
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66
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67
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68
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69 def get_nist_out_as_dict(nist_result_file):
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70 '''
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71 Method to parse NIST specific output into a dictionary.
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72 @param nist_result_file: result file as produced by NIST nistms$.exe
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73 '''
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74 # Create dictionary with column name as key
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75 output = OrderedDict()
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76 output['id'] = []
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77 output['compound_name'] = []
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78 output['formula'] = []
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79 output['lib_name'] = []
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80 output['id_in_lib'] = []
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81 output['mf'] = []
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82 output['rmf'] = []
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83 output['prob'] = []
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84 output['cas'] = []
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85 output['mw'] = []
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86
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87
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88 for line in open(nist_result_file):
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89 row = line.split('<<')
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90 if row[0].startswith('Unknown'):
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91 title_row = row[0]
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92 continue
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93 elif row[0].startswith('Hit'):
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94 hit = row
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95
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96 output['id'].append(title_row.split(': ')[1].split(' ')[0])
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97 output['compound_name'].append((hit[1].split('>>')[0]).decode('utf-8', errors='replace')) # see http://blog.webforefront.com/archives/2011/02/python_ascii_co.html
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98 output['formula'].append(hit[2].split('>>')[0])
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99 output['lib_name'].append(hit[3].split('>>')[0])
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100
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101 other_fields_list = (hit[2].split('>>')[1] + hit[3].split('>>')[1]).split(';')
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102 count = 0
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103 for field in other_fields_list:
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104 if field.startswith(' MF: '):
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105 count += 1
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106 output['mf'].append(field.split('MF: ')[1])
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107 elif field.startswith(' RMF: '):
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108 count += 1
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109 output['rmf'].append(field.split('RMF: ')[1])
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110 elif field.startswith(' Prob: '):
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111 count += 1
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112 output['prob'].append(field.split('Prob: ')[1])
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113 elif field.startswith(' CAS:'):
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114 count += 1
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115 output['cas'].append(field.split('CAS:')[1])
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116 elif field.startswith(' Mw: '):
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117 count += 1
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118 output['mw'].append(field.split('Mw: ')[1])
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119 elif field.startswith(' Id: '):
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120 count += 1
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121 output['id_in_lib'].append(field.split('Id: ')[1][0:-2]) # the [0:-2] is to avoid the last 2 characters, namely a '.' and a \n
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122 elif field != '' and field != ' Lib: ':
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123 raise Exception('Error: unexpected field in NIST output: ' + field)
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124
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125 if count != 6:
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126 raise Exception('Error: did not find all expected fields in NIST output')
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127
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128 return output
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129
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130 def get_spectra_file_as_dict(spectrum_file):
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131 '''
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132 Method to parse spectra file in NIST MSP input format into a dictionary.
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133 The idea is to parse the following :
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134
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135 Name: spectrum1
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136 DB#: 1
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137 Num Peaks: 87
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138 14 8; 15 15; 27 18; 28 15; 29 15;
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139 30 11; 32 19; 39 32; 40 12; 41 68;
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140
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141 into:
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142
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143 dict['spectrum1'] = "14 8; 15 15; 27 18; 28 15; 29 15; 30 11; 32 19; 39 32; 40 12; 41 68;"
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144
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145 @param spectrum_file: spectra file in MSP format (e.g. also the format returned by MsClust)
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146 '''
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147
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148 output = OrderedDict()
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149 name = ''
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150 spectrum = ''
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151 for line in open(spectrum_file):
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152 if line.startswith('Name: '):
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153 if name != '':
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154 # store spectrum:
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155 output[name] = spectrum
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156 name = line.split('Name: ')[1].replace('\n','')
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157 spectrum = ''
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158 elif line[0].isdigit():
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159 # parse spectra:
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160 spectrum += line.replace('\n','')
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161
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162 # store also last spectrum:
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163 output[name] = spectrum
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164
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165 return output
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166 |
