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