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e26f91e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 | #!/usr/bin/env python
import inspect
import os
import random
import sys
import matplotlib.cm as cmx
import matplotlib.colors as colors
import matplotlib.pyplot as plt
import matplotlib.legend as lgd
import matplotlib.markers as mks
import colorsys
def get_log_parsing_script():
dirname = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
return dirname + '/parse_log.sh'
def get_log_file_suffix():
return '.log'
def get_chart_type_description_separator():
return ' vs. '
def is_x_axis_field(field):
x_axis_fields = ['Iters', 'Seconds']
return field in x_axis_fields
def create_field_index():
train_key = 'Train'
test_key = 'Test'
field_index = {train_key:{'Iters':0, 'Seconds':1, train_key + ' loss':2,
train_key + ' learning rate':3},
test_key:{'Iters':0, 'Seconds':1, test_key + ' accuracy':2,
test_key + ' loss':3}}
fields = set()
for data_file_type in field_index.keys():
fields = fields.union(set(field_index[data_file_type].keys()))
fields = list(fields)
fields.sort()
return field_index, fields
def get_supported_chart_types():
field_index, fields = create_field_index()
num_fields = len(fields)
supported_chart_types = []
for i in xrange(num_fields):
if not is_x_axis_field(fields[i]):
for j in xrange(num_fields):
if i != j and is_x_axis_field(fields[j]):
supported_chart_types.append('%s%s%s' % (
fields[i], get_chart_type_description_separator(),
fields[j]))
return supported_chart_types
def get_chart_type_description(chart_type):
supported_chart_types = get_supported_chart_types()
chart_type_description = supported_chart_types[chart_type]
return chart_type_description
def get_data_file_type(chart_type):
description = get_chart_type_description(chart_type)
data_file_type = description.split()[0]
return data_file_type
def get_data_file(chart_type, path_to_log):
return os.path.basename(path_to_log) + '.' + get_data_file_type(chart_type).lower()
def get_field_descriptions(chart_type):
description = get_chart_type_description(chart_type).split(
get_chart_type_description_separator())
y_axis_field = description[0]
x_axis_field = description[1]
return x_axis_field, y_axis_field
def get_field_indecies(chart_type,x_axis_field, y_axis_field):
data_file_type = get_data_file_type(chart_type)
fields = create_field_index()[0][data_file_type]
return fields[x_axis_field], fields[y_axis_field]
def load_data(data_file, field_idx0, field_idx1):
data = [[], []]
with open(data_file, 'r') as f:
for line in f:
line = line.strip()
if line[0] != '#':
fields = line.split()
data[0].append(float(fields[field_idx0].strip()))
data[1].append(float(fields[field_idx1].strip()))
return data
def random_marker():
markers = mks.MarkerStyle.markers
num = len(markers.values())
idx = random.randint(0, num - 1)
return markers.values()[idx]
def get_data_label(path_to_log):
label = path_to_log[path_to_log.rfind('/')+1 : path_to_log.rfind(
get_log_file_suffix())]
return label
def get_legend_loc(chart_type):
x_axis, y_axis = get_field_descriptions(chart_type)
loc = 'lower right'
if y_axis.find('accuracy') != -1:
pass
if y_axis.find('loss') != -1 or y_axis.find('learning rate') != -1:
loc = 'upper right'
return loc
def plot_chart(chart_type, path_to_png, path_to_log_list, ylim = None):
N = len(path_to_log_list)
HSV_tuples = [(x*1.0/N, 0.5, 1) for x in range(N)]
RGB_tuples = map(lambda x: colorsys.hsv_to_rgb(*x), HSV_tuples)
for ind, path_to_log in enumerate(path_to_log_list):
os.system('%s %s' % (get_log_parsing_script(), path_to_log))
data_file = get_data_file(chart_type, path_to_log)
x_axis_field, y_axis_field = get_field_descriptions(chart_type)
x, y = get_field_indecies(chart_type, x_axis_field, y_axis_field)
data = load_data(data_file, x, y)
## TODO: more systematic color cycle for lines
label = get_data_label(path_to_log)
linewidth = 2
## If there too many datapoints, do not use marker.
## use_marker = False
use_marker = True
if not use_marker:
plt.plot(data[0], data[1], label = label, color = color,
linewidth = linewidth)
else:
ok = False
## Some markers throw ValueError: Unrecognized marker style
while not ok:
try:
marker = random_marker()
plt.plot(data[0], data[1], label = label, color = RGB_tuples[ind],
marker = marker, linewidth = linewidth)
ok = True
except:
pass
legend_loc = get_legend_loc(chart_type)
#plt.legend(loc = legend_loc, ncol = 1) # ajust ncol to fit the space
plt.legend(path_to_log_list, loc='upper center', bbox_to_anchor=(.5, -0.1))
plt.title(get_chart_type_description(chart_type))
plt.xlabel(x_axis_field)
plt.ylabel(y_axis_field)
if ylim:
plt.ylim(ylim)
#plt.savefig(path_to_png)
plt.show()
def print_help():
print """This script mainly serves as the basis of your customizations.
Customization is a must.
You can copy, paste, edit them in whatever way you want.
Be warned that the fields in the training log may change in the future.
You had better check the data files and change the mapping from field name to
field index in create_field_index before designing your own plots.
Usage:
./plot_log.sh chart_type[0-%s] /where/to/save.png /path/to/first.log ...
Notes:
1. Supporting multiple logs.
2. Log file name must end with the lower-cased "%s".
Supported chart types:""" % (len(get_supported_chart_types()) - 1,
get_log_file_suffix())
supported_chart_types = get_supported_chart_types()
num = len(supported_chart_types)
for i in xrange(num):
print ' %d: %s' % (i, supported_chart_types[i])
exit
def is_valid_chart_type(chart_type):
return chart_type >= 0 and chart_type < len(get_supported_chart_types())
if __name__ == '__main__':
if len(sys.argv) < 4:
print_help()
else:
chart_type = int(sys.argv[1])
if not is_valid_chart_type(chart_type):
print_help()
path_to_png = sys.argv[2]
if not path_to_png.endswith('.png'):
print 'Path must ends with png' % path_to_png
exit
path_to_logs = sys.argv[3:]
for path_to_log in path_to_logs:
if not os.path.exists(path_to_log):
print 'Path does not exist: %s' % path_to_log
exit
if not path_to_log.endswith(get_log_file_suffix()):
print_help()
## plot_chart accpets multiple path_to_logs
plot_chart(chart_type, path_to_png, path_to_logs)
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