1 | #!/usr/bin/python3
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2 | """
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3 | Python Script to plot values obtained by the rmit.py script
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4 | Runs a R.I.P.L.
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5 |
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6 | ./plot.py
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7 | -t trials
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8 | -o option:values
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9 | """
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10 |
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11 | import argparse
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12 | import itertools
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13 | import json
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14 | import math
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15 | import numpy
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16 | import re
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17 | import statistics
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18 | import sys
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19 |
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20 | import matplotlib.pyplot as plt
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21 | from matplotlib.ticker import EngFormatter
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22 |
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23 | class Field:
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24 | def __init__(self, unit, _min, _log):
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25 | self.unit = unit
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26 | self.min = _min
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27 | self.log = _log
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28 |
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29 | field_names = {
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30 | "ns per ops" : Field('ns' , 0, False),
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31 | "Number of processors" : Field('' , 1, False),
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32 | "Ops per procs" : Field('Ops' , 0, False),
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33 | "Ops per threads" : Field('Ops' , 0, False),
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34 | "ns per ops/procs" : Field('ns' , 0, False),
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35 | "Number of threads" : Field('' , 1, False),
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36 | "Total Operations(ops)" : Field('Ops' , 0, False),
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37 | "Ops/sec/procs" : Field('Ops' , 0, False),
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38 | "Total blocks" : Field('Blocks', 0, False),
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39 | "Ops per second" : Field('Ops' , 0, False),
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40 | "Cycle size (# thrds)" : Field('thrd' , 1, False),
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41 | "Duration (ms)" : Field('ms' , 0, False),
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42 | "Target QPS" : Field('' , 0, False),
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43 | "Actual QPS" : Field('' , 0, False),
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44 | "Average Read Latency" : Field('us' , 0, True),
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45 | "Median Read Latency" : Field('us' , 0, True),
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46 | "Tail Read Latency" : Field('us' , 0, True),
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47 | "Average Update Latency": Field('us' , 0, True),
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48 | "Median Update Latency" : Field('us' , 0, True),
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49 | "Tail Update Latency" : Field('us' , 0, True),
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50 | "Update Ratio" : Field('\%' , 0, False),
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51 | }
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52 |
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53 | def plot(in_data, x, y, out):
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54 | fig, ax = plt.subplots()
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55 | colors = itertools.cycle(['#0095e3','#006cb4','#69df00','#0aa000','#fb0300','#e30002','#fd8f00','#ff7f00','#8f00d6','#4b009a','#ffff00','#b13f00'])
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56 | series = {} # scatter data for each individual data point
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57 | groups = {} # data points for x value
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58 |
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59 | print("Preparing Data")
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60 |
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61 | for entry in in_data:
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62 | name = entry[0]
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63 | if not name in series:
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64 | series[name] = {'x':[], 'y':[]}
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65 |
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66 | if not name in groups:
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67 | groups[name] = {}
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68 |
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69 | if x in entry[2] and y in entry[2]:
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70 | xval = entry[2][x]
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71 | yval = entry[2][y]
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72 | series[name]['x'].append(xval)
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73 | series[name]['y'].append(yval)
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74 |
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75 | if not xval in groups[name]:
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76 | groups[name][xval] = []
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77 |
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78 | groups[name][xval].append(yval)
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79 |
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80 | print("Preparing Lines")
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81 |
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82 | lines = {} # lines from groups with min, max, median, etc.
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83 | for name, data in groups.items():
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84 | if not name in lines:
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85 | lines[name] = { 'x': [], 'min':[], 'max':[], 'med':[], 'avg':[] }
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86 |
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87 | for xkey in sorted(data):
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88 | ys = data[xkey]
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89 | lines[name]['x'] .append(xkey)
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90 | lines[name]['min'].append(min(ys))
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91 | lines[name]['max'].append(max(ys))
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92 | lines[name]['med'].append(statistics.median(ys))
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93 | lines[name]['avg'].append(statistics.mean(ys))
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94 |
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95 | print("Making Plots")
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96 |
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97 | for name, data in sorted(series.items()):
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98 | _col = next(colors)
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99 | plt.scatter(data['x'], data['y'], color=_col, label=name, marker='x')
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100 | plt.plot(lines[name]['x'], lines[name]['min'], '--', color=_col)
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101 | plt.plot(lines[name]['x'], lines[name]['max'], '--', color=_col)
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102 | plt.plot(lines[name]['x'], lines[name]['med'], '-', color=_col)
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103 |
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104 | print("Calculating Extremums")
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105 |
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106 | mx = max([max(s['x']) for s in series.values()])
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107 | my = max([max(s['y']) for s in series.values()])
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108 |
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109 | print("Finishing Plots")
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110 |
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111 | plt.ylabel(y)
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112 | # plt.xticks(range(1, math.ceil(mx) + 1))
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113 | plt.xlabel(x)
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114 | plt.grid(b = True)
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115 | ax.xaxis.set_major_formatter( EngFormatter(unit=field_names[x].unit) )
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116 | if field_names[x].log:
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117 | ax.set_xscale('log')
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118 | else:
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119 | plt.xlim(field_names[x].min, mx + 0.25)
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120 |
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121 | ax.yaxis.set_major_formatter( EngFormatter(unit=field_names[y].unit) )
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122 | if field_names[y].log:
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123 | ax.set_yscale('log')
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124 | else:
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125 | plt.ylim(field_names[y].min, my*1.2)
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126 |
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127 | plt.legend(loc='upper left')
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128 |
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129 | print("Results Ready")
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130 | if out:
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131 | plt.savefig(out)
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132 | else:
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133 | plt.show()
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134 |
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135 |
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136 | if __name__ == "__main__":
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137 | # ================================================================================
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138 | # parse command line arguments
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139 | parser = argparse.ArgumentParser(description='Python Script to draw R.M.I.T. results')
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140 | parser.add_argument('-f', '--file', nargs='?', type=argparse.FileType('r'), default=sys.stdin, help="Input file")
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141 | parser.add_argument('-o', '--out', nargs='?', type=str, default=None, help="Output file")
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142 | parser.add_argument('-y', nargs='?', type=str, default="", help="Which field to use as the Y axis")
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143 | parser.add_argument('-x', nargs='?', type=str, default="", help="Which field to use as the X axis")
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144 |
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145 | options = parser.parse_args()
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146 |
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147 | # ================================================================================
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148 | # load data
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149 | try :
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150 | data = json.load(options.file)
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151 | except :
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152 | print('ERROR: could not read input', file=sys.stderr)
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153 | parser.print_help(sys.stderr)
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154 | sys.exit(1)
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155 |
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156 | # ================================================================================
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157 | # identify the keys
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158 |
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159 | series = set()
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160 | fields = set()
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161 |
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162 | for entry in data:
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163 | series.add(entry[0])
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164 | for label in entry[2].keys():
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165 | fields.add(label)
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166 |
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167 | if not options.out :
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168 | print(series)
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169 | print("fields: ", ' '.join(fields))
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170 |
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171 | wantx = "Number of processors"
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172 | wanty = "ns per ops"
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173 |
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174 | if options.x:
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175 | if options.x in field_names.keys():
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176 | wantx = options.x
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177 | else:
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178 | print("Could not find X key '{}', defaulting to '{}'".format(options.x, wantx))
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179 |
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180 | if options.y:
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181 | if options.y in field_names.keys():
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182 | wanty = options.y
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183 | else:
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184 | print("Could not find Y key '{}', defaulting to '{}'".format(options.y, wanty))
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185 |
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186 |
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187 | plot(data, wantx, wanty, options.out)
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