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1 '''
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2 Created on Feb2018
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3
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4 @author: bob brown
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5 '''
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6
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7 import sys, traceback, argparse
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8 import numpy as np
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9 from Matrix_Validate_import import reader
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10 #import matplotlib.pyplot as plt
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11 from Matrix_Filters import Variance_Percent_Filter_row, Variance_Percent_Filter_col
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12
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13 #Define argparse Function
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14 def get_args():
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15 parser = argparse.ArgumentParser()
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16 parser.add_argument('input_file_txt', help='tab delimited text file input matrix(include .txt in name)')
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17 parser.add_argument('choice',type=str, help='Variance Filter Method (Variance or Range)')
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18 parser.add_argument('thresh', help='Thershold for Variance Filtering')
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19 parser.add_argument('axes', help='Axes to Filter on (Either Row or Column')
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20 parser.add_argument('output_file_txt', help='tab delimited text file output name (include .txt in name)')
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21 args = parser.parse_args()
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22 return args
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23
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24
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25 #Define Function Which Labels Rows/Columns on Output
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26 def labeler(matrix,filter_rows,filter_cols,output_file_txt):
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27
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28 #Write Data to Specified Text File Output
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29 with open(output_file_txt,'w') as f:
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30 f.write("")
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31 for k in range(0,len(filter_cols)):
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32 f.write('\t' + filter_cols[k])
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33 f.write('\n')
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34 for i in range(0,len(filter_rows)):
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35 f.write(filter_rows[i])
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36 for j in range(0,len(matrix[0])):
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37 f.write('\t' + format(matrix[i][j]))
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38 f.write('\n')
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39
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40
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41 def Histo(matrix):
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42 numBins= 20
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43 data = []
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44 # numRow,numCol= np.shape(matrix)
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45 for i in range(len(matrix[0])):
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46 data.append(np.nanmean([row[i] for row in matrix]))
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47
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48 # print(str(np.nanmean([row[i] for row in matrix])))
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49
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50 #https://stackoverflow.com/questions/5328556/histogram-matplotlib
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51 #bins = [0, 40, 60, 75, 90, 110, 125, 140, 160, 200]
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52 minBin = int(min(data)-0.5)
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53 maxBin = int(max(data)+0.5)
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54 binWidth = float(maxBin-minBin)/numBins
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55 bins= []
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56 """
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57 for j in range(numBins):
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58 bins.append(minBin+ j*binWidth)
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59 #bins= 20
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60 n, bins, patches = plt.hist(data,bins, normed=False)
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61 #n, bins, patches = plt.hist(data,bins, normed=1, color='green')
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62 #hist, bins = np.histogram(data, bins=bins)
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63 width = np.diff(bins)
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64 center = (minBin + bins[1:]) / 2
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65
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66 cm = plt.cm.get_cmap('RdYlBu_r')
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67 #col = (n-n.min())/(n.max()-n.min())
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68 for c, p in zip(bins, patches):
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69 plt.setp( p, 'facecolor', cm(c/numBins))
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70 fig, ax = plt.subplots(num=1, figsize=(8,3))
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71 ax.set_title("Distribution of Column Means")
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72 #ax.bar(center,bins, align='center', width=width)
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73 #ax.bar(center, hist, align='center', width=width)
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74 #ax.set_xticks(bins)
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75 # fig.savefig("/Users/bobbrown/Desktop/Matrix-tools-Test-output/Column_Mean_Histogram.png")
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76
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77 plt.show()
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78 """
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79 return()
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80
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81 #========== test create variable number output files in Galaxy
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82 def CreateFiles(output_file_info):
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83
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84 for i in range(3):
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85 fd= open( output_file_info, 'w')
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86 fd.write('File number = '+ str(i)+"\n")
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87 fd.close()
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88
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89 return()
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90
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91 #==================
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92
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93 #Define Main Function
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94 def main():
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95 try:
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96 args = get_args()
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97 #sys.stdout.write(str(args)+"\n")
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98 nanList= ["NAN", "NA", "N/A", "-","?","nan", "na", "n/a"]
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99
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100 matrix, og_cols,og_rows = reader(args.input_file_txt)
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101 #old_reader matrix, og_rows, og_cols = reader(args.input_file_txt)
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102 # if float(args.thresh) < 0.000001:
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103 # print('Invalid negative threshold chosen = '+str(args.thresh)+" choose positive value")
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104 # sys.exit(-4)
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105
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106 if args.choice == "Histogram":
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107 Histo(matrix)
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108 elif args.choice == "CreateFiles":
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109 CreateFiles(args.output_file_info)
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110
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111 elif args.choice == "Variance":
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112 if args.axes == "Row":
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113 matrix, filter_rows, filter_cols,delCnt,minVal,maxVal = Variance_Percent_Filter_row(matrix,1,og_rows,og_cols,True)
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114 labeler(matrix,filter_rows,filter_cols,args.output_file_txt)
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115 # if delCnt < 1:
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116 # print('\nNO Filtering occurred for rows using variance < '+str(args.thresh)+ ' by row. Matrix row minimum variance= %.2f' % minVal+' and maximum variance= %.2f' % maxVal)
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117 # sys.stderr.write('\nFiltering out rows using variance < '+str(args.thresh)+ ' removed '+str(delCnt)+' rows')
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118 # sys.exit(-1)
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119 # else:
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120 # print('\nFiltering out rows using variance < '+str(args.thresh)+ ' removed '+str(delCnt)+' rows')
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121 elif args.axes == "Column":
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122 matrix, filter_rows, filter_cols,delCnt,minVal,maxVal = Variance_Percent_Filter_col(matrix,1,og_rows,og_cols,True)
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123 labeler(matrix,filter_rows,filter_cols,args.output_file_txt)
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124 # if delCnt < 1:
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125 # print('\nNO Filtering occurred for columns using variance < '+str(args.thresh)+ ' by columns. Matrix columns minimum variance= %.2f' % minVal+' and maximum variance= %.2f' % maxVal)
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126 # sys.stderr.write('\nFiltering out rows using variance < '+str(args.thresh)+ ' removed '+str(delCnt)+' rows')
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127 # sys.exit(-1)
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128 # else:
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129 # print('\nFiltering out columns using variance < '+str(args.thresh)+ ' removed '+str(delCnt)+' columns')
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130 else:
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131 print('Invalid Axes = '+str(args.axes))
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132 sys.exit(-1)
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133 else:
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134 print("Invalid Filter Choice = "+str(args.choice))
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135 sys.exit(-2)
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136
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137
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138 except Exception as err:
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139 traceback.print_exc()
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140 sys.exit(-3)
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141
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142 if __name__ == '__main__':
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143 main()
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144 print("\nFini")
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145 sys.exit(0) |
