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1 import matplotlib
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2 matplotlib.use('Agg')
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3 import matplotlib.pyplot as plt
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4
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5 from matplotlib import rcParams
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6 from matplotlib import colors
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7 from matplotlib import cm
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8
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33
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9 from matplotlib.patches import Rectangle
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10
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19
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11 from vhom import RegionRunner
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12
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13 from argparse import ArgumentParser
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14 from matplotlib.backends.backend_pdf import PdfPages
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15
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16 import os
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31
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17 import shutil
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18
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20
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19 import sys
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20
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21 import colorsys
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22
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23
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24
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25
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26 rcParams['figure.figsize'] = (6, 6)
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27 rcParams['figure.dpi'] = 100
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28 rcParams['axes.facecolor'] = 'white'
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29 rcParams['font.size'] = 10
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30 rcParams['patch.edgecolor'] = 'white'
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31 rcParams['patch.linewidth']=0.5
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32 rcParams['patch.facecolor'] = 'black'
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33 rcParams['font.family'] = 'StixGeneral'
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34
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35
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36 def color_variants(r,g,b):
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37 h,l2,s= colorsys.rgb_to_hls(r,g,b)
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38 l=[l2-0.4,l2-0.1,l2+0.2]
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39 hexs=[]
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40 for i in l:
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41 hexs.append(colors.rgb2hex(colorsys.hls_to_rgb(h,i,s)))
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42 return hexs
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43
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44 def rgb_color_variants(r,g,b):
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45 h,l2,s= colorsys.rgb_to_hls(r,g,b)
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46 l=[l2-0.4,l2-0.1,l2+0.2]
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47 rgbs={}
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48 rgbs["pathogen"]=colorsys.hls_to_rgb(h,l[0],s)
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49 rgbs["ambiguous"]=colorsys.hls_to_rgb(h,l[1],s)
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50 rgbs["human"]=colorsys.hls_to_rgb(h,l[2],s)
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51 return rgbs
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52
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53
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54
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55
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56 def remove_border(axes=None, top=False, right=False, left=True, bottom=True):
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57 """
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58 Minimize chartjunk by stripping out unnecesasry plot borders and axis ticks
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59
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60 The top/right/left/bottom keywords toggle whether the corresponding plot border is drawn
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61 """
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62 ax = axes or plt.gca()
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63 ax.spines['top'].set_visible(top)
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64 ax.spines['right'].set_visible(right)
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65 ax.spines['left'].set_visible(left)
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66 ax.spines['bottom'].set_visible(bottom)
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67
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68 #turn off all ticks
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69 ax.yaxis.set_ticks_position('none')
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70 ax.xaxis.set_ticks_position('none')
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71
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72 #now re-enable visibles
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73 if top:
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74 ax.xaxis.tick_top()
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75 if bottom:
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76 ax.xaxis.tick_bottom()
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77 if left:
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78 ax.yaxis.tick_left()
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79 if right:
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80 ax.yaxis.tick_right()
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81
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82
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83 def generateHTML(stat_dict,file,directory):
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84 rval=["<html><head><title>Homologous groups and regions derived from hit files </title></head><body><p/>\n"]
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85 rval.append("<a href='plot.pdf'>Download Plot</a>")
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86 n_samples=0
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87 for sample in stat_dict.iterkeys():
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88 n_samples+=1
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89 rval.append("<div id=%s_graph></div><p/>"%(sample))
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90 curr_dir = os.path.dirname(os.path.realpath(__file__))
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91 shutil.copy(os.path.join(curr_dir,"jquery-1.10.2.min.js"),directory)
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92 shutil.copy(os.path.join(curr_dir,"jqBarGraph.2.1.js"),directory)
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93 rval.append("<script type='text/javascript' src='jquery-1.10.2.min.js'></script>")
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94 rval.append("<script type='text/javascript' src='jqBarGraph.2.1.js'></script>")
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95 rval.append('<script>')
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96 i=0
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97 for sample in stat_dict.iterkeys():
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98 i+=1
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99 rval.append("%s_array = new Array(" %sample)
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100 for family in stat_dict[sample].iterkeys():
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101 values=[]
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102 for region,data in stat_dict[sample][family].iteritems():
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103 values.append([int(data[0][1]),int(data[0][2]), data[0][0], data[0][3],int(data[0][4]),int(region)])
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104 rval.append(str([values,family])+",")
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105 rval[-1]=rval[-1][:-1]
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106 rval.append(");")
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107 rval.append("%s_files=%s;"%(sample,str(getFiles(directory))))
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108 rval.append("$('#%s_graph').jqBarGraph({"%sample)
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109 rval.append("sample: '%s',"%sample)
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110 rval.append("data: %s_array,"%sample)
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111 rval.append("files: %s_files,"%sample)
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112 r,g,b,a=cm.hsv(1.*i/n_samples)
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113 rval.append("colors: %s," %color_variants(r,g,b))
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114 rval.append("legend: true,")
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115 rval.append("tab: 'reads',")
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116 rval.append("title: '<H3>Visualisation of Sample %s</H3>',"%sample)
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117 rval.append("width: %d"%((len(stat_dict[sample])*50)+150))
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118 rval.append("});")
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119 # rval.append("jQuery.get('test.py', function(data) {")
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120 # rval.append("alert(data)")
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121 # rval.append("})")
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122 rval.append("</script>")
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123
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124 rval.append( '</body></html>' )
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125 with open(file,'w') as file:
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126 file.write("\n".join( rval ))
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33
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127 def transformDict(stat_dict):
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128 dict={}
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129 position={}
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130 dict_label={}
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131 for sample in stat_dict.iterkeys():
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132 dict[sample]=[{},{}]
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133 position[sample]={}
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134 dict_label[sample]={}
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135 j=0
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136 for family in stat_dict[sample].iterkeys():
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137
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138 i=0
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139 for region,values in stat_dict[sample][family].iteritems():
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140
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141 if i not in dict[sample][0]:
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142 dict[sample][0][i]=[]
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143 dict[sample][1][i]=[]
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144 position[sample][i]=[]
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145 dict_label[sample][i]=[]
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146 dict[sample][0][i].append(int(values[0][1]))
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147 dict[sample][1][i].append(int(values[0][2]))
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148 position[sample][i].append(j)
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149 dict_label[sample][i].append(values[0][0])
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150 i+=1
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151 j+=1
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152 return dict,position,dict_label
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153
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154 def customeLegend(color_map):
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155 legend_map=[[],[]]
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156 for label in color_map:
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157 box=Rectangle((0,0),1,1,color=color_map[label],fill=True)
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158 legend_map[0].append(box)
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159 legend_map[1].append(label)
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160 plt.figlegend(legend_map[0],legend_map[1],loc=8,ncol=len(color_map))
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161
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162
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163
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164
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165 def generatePyPlot(stat_dict,output_file):
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166 pp = PdfPages(output_file)
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167 fig = plt.figure()
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168
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169 n_samples=len(stat_dict)
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170 dict,position,dict_label=transformDict(stat_dict)
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171
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172 i=0
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173 for sample in dict.iterkeys():
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174 fig = plt.figure()
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175
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176 fig.subplots_adjust(bottom=0.25,hspace=0.5)
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177
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178 r,g,b,a=cm.hsv(1.*i/n_samples)
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179 color_map=rgb_color_variants(r,g,b)
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180
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181 for sub in [0,1]:
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182 plt.subplot(1,2,sub+1)
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183 bottom={}
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184 for level,values in dict[sample][sub].iteritems():
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185 colors=[color_map[r] for r in dict_label[sample][level]]
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186
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187 if level==0:
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188
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189 plt.bar(position[sample][level],values,bottom=0, width=0.8 ,color=colors)
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190 else:
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191 lastvalues=[]
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192 for oldpos in range(len(values)):
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193 lastvalues.append(bottom[position[sample][level][oldpos]])
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194
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195 plt.bar(position[sample][level],values, width=0.8,bottom=lastvalues ,color=colors)
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196 for pos in range(len(values)):
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197 if position[sample][level][pos] not in bottom:
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198 bottom[position[sample][level][pos]]=0
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199 else:
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200 bottom[position[sample][level][pos]]+=values[pos]
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201 pos=[x+0.4 for x in range(len(stat_dict[sample]))]
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202 plt.xticks(pos, stat_dict[sample].keys(), rotation='vertical')
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203 if(sub==0):
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204 plt.ylabel("Cumulative reads assigned to family")
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205 else:
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206 plt.ylabel("Cumulative basepairs assigned to family")
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207 plt.xlabel("")
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208 fig.subplots_adjust(bottom=0.25,wspace=0.5)
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209 remove_border()
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210
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211 customeLegend(color_map)
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212 plt.suptitle(sample)
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213 pp.savefig(fig)
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214 i+=1
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215 pp.close()
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216
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217
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218
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219 def parseStatFile(filename):
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220
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221 with open(filename,'r') as file:
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222 values=[ map(str,line.split('\t')) for line in file ]
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223
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224 dict={}
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225 for line in values[1:]:
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226 if line[3] not in dict:
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227 dict[line[3]]={}
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228 dict[line[3]][line[1]]={}
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229 dict[line[3]][line[1]][line[2]]=[[line[4],line[5],line[7],line[0],line[6]]]
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230 else:
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231 if line[1] not in dict[line[3]]:
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232 dict[line[3]][line[1]]={}
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233 dict[line[3]][line[1]][line[2]]=[[line[4],line[5],line[7],line[0],line[6]]]
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234 else:
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235 if line[2] not in dict[line[3]][line[1]]:
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236 dict[line[3]][line[1]][line[2]]=[[line[4],line[5],line[7],line[0],line[6]]]
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237 else:
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238 dict[line[3]][line[1]][line[2]].append([line[4],line[5],line[7],line[0],line[6]])
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239 # for key in dict.iterkeys():
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240 # for family_key,values in dict[key].iteritems():
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241 # for line in values:
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242 # print key,family_key,line
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243 return dict
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244 def getFiles(directory):
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245 rval={}
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246 dlist = os.listdir(directory)
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247 for dire in dlist:
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248 if(os.path.isdir(os.path.join(directory,dire))):
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249 rval[dire]={}
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250 flist = os.listdir(os.path.join(directory,dire))
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251 for file in flist:
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252 split=file.split("_")
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253 region=split[1]
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254 if region not in rval[dire]:
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255 rval[dire][region]=[file]
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256 else:
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257 rval[dire][region].append(file)
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258
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259 return rval
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260
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261
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262
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263 if __name__ == "__main__":
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264
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265
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266 parser = ArgumentParser()
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267
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268 a = parser.add_argument
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269 a("--html_file",dest="html_file")
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270 a("--directory",dest="directory")
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271 a("--stats",dest="stat_file")
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272
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273 (options,args)= parser.parse_known_args()
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274
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275 args.insert(0,"dummy")
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276 try:
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277 RegionRunner.run(argv=args)
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278 except SystemExit:
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279 stat_dict=parseStatFile(options.stat_file)
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280 generatePyPlot(stat_dict,os.path.join(options.directory,"plot.pdf"))
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281 generateHTML(stat_dict,options.html_file,options.directory)
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282
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283
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284
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285
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286 |
