def main():
parser = argparse.ArgumentParser()
parser.add_argument("--out")
parser.add_argument("model_paths", nargs='+')
options = parser.parse_args()
model_paths = options.model_paths
if options.out is not None:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
print 'generating names...'
model_names = [model_path.replace('.pkl', '!') for model_path in
model_paths]
model_names = unique_substrings(model_names, min_size=10)
model_names = [model_name.replace('!','') for model_name in
model_names]
print '...done'
for i, arg in enumerate(model_paths):
try:
model = serial.load(arg)
except:
if arg.endswith('.yaml'):
print >> sys.stderr, arg + " is a yaml config file," + \
"you need to load a trained model."
quit(-1)
raise
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":" + model_names[i]
else:
postfix = ""
for channel in this_model_channels:
channels[channel+postfix] = this_model_channels[channel]
while True:
# Make a list of short codes for each channel so user can specify them
# easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels,
key = number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook['<'+channel_name+'>'] = channel_name
sorted_codes.append(code)
x_axis = 'example'
print 'set x_axis to example'
if len(channels.values()) == 0:
print "there are no channels to plot"
break
# If there is more than one channel in the monitor ask which ones to
# plot
prompt = len(channels.values()) > 1
if prompt:
# Display the codebook
for code in sorted_codes:
print code + '. ' + codebook[code]
print
print "Put e, b, s or h in the list somewhere to plot " + \
"epochs, batches, seconds, or hours, respectively."
response = raw_input('Enter a list of channels to plot ' + \
'(example: A, C,F-G, h, <test_err>) or q to quit' + \
'or o for options: ')
if response == 'o':
print '1: smooth all channels'
print 'any other response: do nothing, go back to plotting'
response = raw_input('Enter your choice: ')
if response == '1':
for channel in channels.values():
k = 5
new_val_record = []
for i in xrange(len(channel.val_record)):
new_val = 0.
count = 0.
for j in xrange(max(0, i-k), i+1):
new_val += channel.val_record[j]
count += 1.
new_val_record.append(new_val / count)
channel.val_record = new_val_record
continue
if response == 'q':
break
#Remove spaces
response = response.replace(' ','')
#Split into list
codes = response.split(',')
final_codes = set([])
for code in codes:
if code == 'e':
x_axis = 'epoch'
continue
elif code == 'b':
x_axis = 'batche'
elif code == 's':
x_axis = 'second'
elif code == 'h':
x_axis = 'hour'
elif code.startswith('<'):
assert code.endswith('>')
final_codes.add(code)
elif code.find('-') != -1:
#The current list element is a range of codes
rng = code.split('-')
if len(rng) != 2:
print "Input not understood: "+code
quit(-1)
found = False
for i in xrange(len(sorted_codes)):
if sorted_codes[i] == rng[0]:
found = True
break
if not found:
print "Invalid code: "+rng[0]
quit(-1)
found = False
for j in xrange(i,len(sorted_codes)):
if sorted_codes[j] == rng[1]:
found = True
break
if not found:
print "Invalid code: "+rng[1]
quit(-1)
final_codes = final_codes.union(set(sorted_codes[i:j+1]))
else:
#The current list element is just a single code
final_codes = final_codes.union(set([code]))
# end for code in codes
else:
final_codes ,= set(codebook.keys())
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
styles = list(colors)
styles += [color+'--' for color in colors]
styles += [color+':' for color in colors]
fig = plt.figure()
ax = plt.subplot(1,1,1)
# plot the requested channels
for idx, code in enumerate(sorted(final_codes)):
channel_name= codebook[code]
channel = channels[channel_name]
y = np.asarray(channel.val_record)
if np.any(np.isnan(y)):
print channel_name + ' contains NaNs'
if np.any(np.isinf(y)):
print channel_name + 'contains infinite values'
if x_axis == 'example':
x = np.asarray(channel.example_record)
elif x_axis == 'batche':
x = np.asarray(channel.batch_record)
elif x_axis == 'epoch':
try:
x = np.asarray(channel.epoch_record)
except AttributeError:
# older saved monitors won't have epoch_record
x = np.arange(len(channel.batch_record))
elif x_axis == 'second':
x = np.asarray(channel.time_record)
elif x_axis == 'hour':
x = np.asarray(channel.time_record) / 3600.
else:
assert False
ax.plot( x,
y,
styles[idx % len(styles)],
marker = '.', # add point margers to lines
label = channel_name)
plt.xlabel('# '+x_axis+'s')
ax.ticklabel_format( scilimits = (-3,3), axis = 'both')
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc='upper center',
bbox_to_anchor=(0.5,-0.1))
# 0.046 is the size of 1 legend box
fig.subplots_adjust(bottom=0.11 + 0.046 * len(final_codes))
plt.show()
plt.savefig(options.out)
if not prompt:
break
def main():
"""
.. todo::
WRITEME
"""
parser = argparse.ArgumentParser()
parser.add_argument("--out")
parser.add_argument("model_paths", nargs='+')
parser.add_argument("--yrange",
help='The y-range to be used for plotting, e.g. 0:1')
options = parser.parse_args()
model_paths = options.model_paths
if options.out is not None:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
print('generating names...')
model_names = [
model_path.replace('.pkl', '!') for model_path in model_paths
]
model_names = unique_substrings(model_names, min_size=10)
model_names = [model_name.replace('!', '') for model_name in model_names]
print('...done')
for i, arg in enumerate(model_paths):
try:
model = serial.load(arg)
except Exception:
if arg.endswith('.yaml'):
print(sys.stderr,
arg + " is a yaml config file," +
"you need to load a trained model.",
file=sys.stderr)
quit(-1)
raise
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":" + model_names[i]
else:
postfix = ""
for channel in this_model_channels:
channels[channel + postfix] = this_model_channels[channel]
del model
gc.collect()
while True:
# Make a list of short codes for each channel so user can specify them
# easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels,
key=number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook['<' + channel_name + '>'] = channel_name
sorted_codes.append(code)
x_axis = 'example'
print('set x_axis to example')
if len(channels.values()) == 0:
print("there are no channels to plot")
break
# If there is more than one channel in the monitor ask which ones to
# plot
prompt = len(channels.values()) > 1
if prompt:
# Display the codebook
for code in sorted_codes:
print(code + '. ' + codebook[code])
print()
print("Put e, b, s or h in the list somewhere to plot " +
"epochs, batches, seconds, or hours, respectively.")
response = input('Enter a list of channels to plot ' + \
'(example: A, C,F-G, h, <test_err>) or q to quit' + \
' or o for options: ')
if response == 'o':
print('1: smooth all channels')
print('any other response: do nothing, go back to plotting')
response = input('Enter your choice: ')
if response == '1':
for channel in channels.values():
k = 5
new_val_record = []
for i in xrange(len(channel.val_record)):
new_val = 0.
count = 0.
for j in xrange(max(0, i - k), i + 1):
new_val += channel.val_record[j]
count += 1.
new_val_record.append(new_val / count)
channel.val_record = new_val_record
continue
if response == 'q':
break
#Remove spaces
response = response.replace(' ', '')
#Split into list
codes = response.split(',')
final_codes = set([])
for code in codes:
if code == 'e':
x_axis = 'epoch'
continue
elif code == 'b':
x_axis = 'batche'
elif code == 's':
x_axis = 'second'
elif code == 'h':
x_axis = 'hour'
elif code.startswith('<'):
assert code.endswith('>')
final_codes.add(code)
elif code.find('-') != -1:
#The current list element is a range of codes
rng = code.split('-')
if len(rng) != 2:
print("Input not understood: " + code)
quit(-1)
found = False
for i in xrange(len(sorted_codes)):
if sorted_codes[i] == rng[0]:
found = True
break
if not found:
print("Invalid code: " + rng[0])
quit(-1)
found = False
for j in xrange(i, len(sorted_codes)):
if sorted_codes[j] == rng[1]:
found = True
break
if not found:
print("Invalid code: " + rng[1])
quit(-1)
final_codes = final_codes.union(set(sorted_codes[i:j + 1]))
else:
#The current list element is just a single code
final_codes = final_codes.union(set([code]))
# end for code in codes
else:
final_codes, = set(codebook.keys())
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
styles = list(colors)
styles += [color + '--' for color in colors]
styles += [color + ':' for color in colors]
fig = plt.figure()
ax = plt.subplot(1, 1, 1)
# plot the requested channels
for idx, code in enumerate(sorted(final_codes)):
channel_name = codebook[code]
channel = channels[channel_name]
y = np.asarray(channel.val_record)
if contains_nan(y):
print(channel_name + ' contains NaNs')
if contains_inf(y):
print(channel_name + 'contains infinite values')
if x_axis == 'example':
x = np.asarray(channel.example_record)
elif x_axis == 'batche':
x = np.asarray(channel.batch_record)
elif x_axis == 'epoch':
try:
x = np.asarray(channel.epoch_record)
except AttributeError:
# older saved monitors won't have epoch_record
x = np.arange(len(channel.batch_record))
elif x_axis == 'second':
x = np.asarray(channel.time_record)
elif x_axis == 'hour':
x = np.asarray(channel.time_record) / 3600.
else:
assert False
ax.plot(
x,
y,
styles[idx % len(styles)],
marker='.', # add point margers to lines
label=channel_name)
plt.xlabel('# ' + x_axis + 's')
ax.ticklabel_format(scilimits=(-3, 3), axis='both')
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles,
labels,
loc='upper center',
bbox_to_anchor=(0.5, -0.1))
# 0.046 is the size of 1 legend box
fig.subplots_adjust(bottom=0.11 + 0.046 * len(final_codes))
if (options.yrange is not None):
ymin, ymax = map(float, options.yrange.split(':'))
plt.ylim(ymin, ymax)
if options.out is None:
plt.show()
else:
plt.savefig(options.out)
if not prompt:
break
for i, arg in enumerate(sys.argv[1:]):
model = serial.load(arg)
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":model%d" % i
else:
postfix = ""
for channel in this_model_channels:
channels[channel+postfix] = this_model_channels[channel]
while True:
#Make a list of short codes for each channel so user can specify them easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels, key = number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
sorted_codes.append(code)
x_axis = 'example'
if len(channels.values()) == 0:
print "there are no channels to plot"
break
#if there is more than one channel in the monitor ask which ones to plot
prompt = len(channels.values()) > 1
for i, arg in enumerate(sys.argv[1:]):
model = serial.load(arg)
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":model%d" % i
else:
postfix = ""
for channel in this_model_channels:
channels[channel+postfix] = this_model_channels[channel]
while True:
#Make a list of short codes for each channel so user can specify them easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels, key = number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook['<'+channel_name+'>'] = channel_name
sorted_codes.append(code)
x_axis = 'example'
print 'set x_axis to example'
if len(channels.values()) == 0:
print "there are no channels to plot"
break
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--out")
parser.add_argument("model_paths", nargs='+')
options = parser.parse_args()
model_paths = options.model_paths
if options.out is not None:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
print 'generating names...'
model_names = [
model_path.replace('.pkl', '!') for model_path in model_paths
]
model_names = unique_substrings(model_names, min_size=10)
model_names = [model_name.replace('!', '') for model_name in model_names]
print '...done'
for i, arg in enumerate(model_paths):
try:
model = serial.load(arg)
except:
if arg.endswith('.yaml'):
print >> sys.stderr, arg + " is a yaml config file, you need to load a trained model."
quit(-1)
raise
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":" + model_names[i]
else:
postfix = ""
for channel in this_model_channels:
channels[channel + postfix] = this_model_channels[channel]
while True:
#Make a list of short codes for each channel so user can specify them easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels,
key=number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook['<' + channel_name + '>'] = channel_name
sorted_codes.append(code)
x_axis = 'example'
print 'set x_axis to example'
if len(channels.values()) == 0:
print "there are no channels to plot"
break
#if there is more than one channel in the monitor ask which ones to plot
prompt = len(channels.values()) > 1
if prompt:
#Display the codebook
for code in sorted_codes:
print code + '. ' + codebook[code]
print
print "Put e, b, s or h in the list somewhere to plot epochs, batches, seconds, or hours, respectively."
response = raw_input(
'Enter a list of channels to plot (example: A, C,F-G, h, <test_err>) or q to quit or o for options: '
)
if response == 'o':
print '1: smooth all channels'
print 'any other response: do nothing, go back to plotting'
response = raw_input('Enter your choice: ')
if response == '1':
for channel in channels.values():
k = 5
new_val_record = []
for i in xrange(len(channel.val_record)):
new_val = 0.
count = 0.
for j in xrange(max(0, i - k), i + 1):
new_val += channel.val_record[j]
count += 1.
new_val_record.append(new_val / count)
channel.val_record = new_val_record
continue
if response == 'q':
break
#Remove spaces
response = response.replace(' ', '')
#Split into list
codes = response.split(',')
final_codes = set([])
for code in codes:
if code == 'e':
x_axis = 'epoch'
continue
elif code == 'b':
x_axis = 'batche'
elif code == 's':
x_axis = 'second'
elif code == 'h':
x_axis = 'hour'
elif code.startswith('<'):
assert code.endswith('>')
final_codes.add(code)
elif code.find('-') != -1:
#The current list element is a range of codes
rng = code.split('-')
if len(rng) != 2:
print "Input not understood: " + code
quit(-1)
found = False
for i in xrange(len(sorted_codes)):
if sorted_codes[i] == rng[0]:
found = True
break
if not found:
print "Invalid code: " + rng[0]
quit(-1)
found = False
for j in xrange(i, len(sorted_codes)):
if sorted_codes[j] == rng[1]:
found = True
break
if not found:
print "Invalid code: " + rng[1]
quit(-1)
final_codes = final_codes.union(set(sorted_codes[i:j + 1]))
else:
#The current list element is just a single code
final_codes = final_codes.union(set([code]))
# end for code in codes
else:
final_codes, = set(codebook.keys())
plt.figure()
#Make 2 subplots so the legend gets a plot to itself and won't cover up the plot
ax = plt.subplot(1, 2, 1)
# Grow current axis' width by 30%
box = ax.get_position()
try:
x0 = box.x0
y0 = box.y0
width = box.width
height = box.height
except:
x0, width, y0, height = box
ax.set_position([x0, y0, width * 1.3, height])
ax.ticklabel_format(scilimits=(-3, 3), axis='both')
plt.xlabel('# ' + x_axis + 's')
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
styles = list(colors)
styles += [color + '--' for color in colors]
styles += [color + ':' for color in colors]
#plot the requested channels
for idx, code in enumerate(sorted(final_codes)):
channel_name = codebook[code]
channel = channels[channel_name]
y = np.asarray(channel.val_record)
if np.any(np.isnan(y)):
print channel_name + ' contains NaNs'
if np.any(np.isinf(y)):
print channel_name + 'contains infinite values'
if x_axis == 'example':
x = np.asarray(channel.example_record)
elif x_axis == 'batche':
x = np.asarray(channel.batch_record)
elif x_axis == 'epoch':
try:
x = np.asarray(channel.epoch_record)
except AttributeError:
# older saved monitors won't have epoch_record
x = np.arange(len(channel.batch_record))
elif x_axis == 'second':
x = np.asarray(channel.time_record)
elif x_axis == 'hour':
x = np.asarray(channel.time_record) / 3600.
else:
assert False
plt.plot(x, y, styles[idx % len(styles)], label=channel_name)
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
if options.out is None:
plt.show()
else:
plt.savefig(options.out)
if not prompt:
break
def main():
"""
.. todo::
WRITEME
"""
parser = argparse.ArgumentParser()
parser.add_argument("--out")
parser.add_argument("model_paths", nargs="+")
options = parser.parse_args()
model_paths = options.model_paths
if options.out is not None:
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
print "generating names..."
model_names = [model_path.replace(".pkl", "!") for model_path in model_paths]
model_names = unique_substrings(model_names, min_size=10)
model_names = [model_name.replace("!", "") for model_name in model_names]
print "...done"
for i, arg in enumerate(model_paths):
try:
model = serial.load(arg)
except:
if arg.endswith(".yaml"):
print >> sys.stderr, arg + " is a yaml config file," + "you need to load a trained model."
quit(-1)
raise
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":" + model_names[i]
else:
postfix = ""
for channel in this_model_channels:
channels[channel + postfix] = this_model_channels[channel]
del model
gc.collect()
while True:
# Make a list of short codes for each channel so user can specify them
# easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels, key=number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook["<" + channel_name + ">"] = channel_name
sorted_codes.append(code)
x_axis = "example"
print "set x_axis to example"
if len(channels.values()) == 0:
print "there are no channels to plot"
break
# If there is more than one channel in the monitor ask which ones to
# plot
prompt = len(channels.values()) > 1
if prompt:
# Display the codebook
for code in sorted_codes:
print code + ". " + codebook[code]
print
print "Put e, b, s or h in the list somewhere to plot " + "epochs, batches, seconds, or hours, respectively."
response = raw_input(
"Enter a list of channels to plot "
+ "(example: A, C,F-G, h, <test_err>) or q to quit"
+ " or o for options: "
)
if response == "o":
print "1: smooth all channels"
print "any other response: do nothing, go back to plotting"
response = raw_input("Enter your choice: ")
if response == "1":
for channel in channels.values():
k = 5
new_val_record = []
for i in xrange(len(channel.val_record)):
new_val = 0.0
count = 0.0
for j in xrange(max(0, i - k), i + 1):
new_val += channel.val_record[j]
count += 1.0
new_val_record.append(new_val / count)
channel.val_record = new_val_record
continue
if response == "q":
break
# Remove spaces
response = response.replace(" ", "")
# Split into list
codes = response.split(",")
final_codes = set([])
for code in codes:
if code == "e":
x_axis = "epoch"
continue
elif code == "b":
x_axis = "batche"
elif code == "s":
x_axis = "second"
elif code == "h":
x_axis = "hour"
elif code.startswith("<"):
assert code.endswith(">")
final_codes.add(code)
elif code.find("-") != -1:
# The current list element is a range of codes
rng = code.split("-")
if len(rng) != 2:
print "Input not understood: " + code
quit(-1)
found = False
for i in xrange(len(sorted_codes)):
if sorted_codes[i] == rng[0]:
found = True
break
if not found:
print "Invalid code: " + rng[0]
quit(-1)
found = False
for j in xrange(i, len(sorted_codes)):
if sorted_codes[j] == rng[1]:
found = True
break
if not found:
print "Invalid code: " + rng[1]
quit(-1)
final_codes = final_codes.union(set(sorted_codes[i : j + 1]))
else:
# The current list element is just a single code
final_codes = final_codes.union(set([code]))
# end for code in codes
else:
final_codes, = set(codebook.keys())
colors = ["b", "g", "r", "c", "m", "y", "k"]
styles = list(colors)
styles += [color + "--" for color in colors]
styles += [color + ":" for color in colors]
fig = plt.figure()
ax = plt.subplot(1, 1, 1)
# plot the requested channels
for idx, code in enumerate(sorted(final_codes)):
channel_name = codebook[code]
channel = channels[channel_name]
y = np.asarray(channel.val_record)
if np.any(np.isnan(y)):
print channel_name + " contains NaNs"
if np.any(np.isinf(y)):
print channel_name + "contains infinite values"
if x_axis == "example":
x = np.asarray(channel.example_record)
elif x_axis == "batche":
x = np.asarray(channel.batch_record)
elif x_axis == "epoch":
try:
x = np.asarray(channel.epoch_record)
except AttributeError:
# older saved monitors won't have epoch_record
x = np.arange(len(channel.batch_record))
elif x_axis == "second":
x = np.asarray(channel.time_record)
elif x_axis == "hour":
x = np.asarray(channel.time_record) / 3600.0
else:
assert False
ax.plot(x, y, styles[idx % len(styles)], marker=".", label=channel_name) # add point margers to lines
plt.xlabel("# " + x_axis + "s")
ax.ticklabel_format(scilimits=(-3, 3), axis="both")
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc="upper center", bbox_to_anchor=(0.5, -0.1))
# 0.046 is the size of 1 legend box
fig.subplots_adjust(bottom=0.11 + 0.046 * len(final_codes))
if options.out is None:
# plt.show()
plt.savefig("plot_value_over_all_epochs.png")
else:
plt.savefig(options.out)
if not prompt:
break
def main():
"""
.. todo::
WRITEME
"""
parser = argparse.ArgumentParser()
parser.add_argument("--out")
parser.add_argument("model_paths", nargs='+')
parser.add_argument("--yrange", help='The y-range to be used for plotting, e.g. 0:1')
options = parser.parse_args()
model_paths = options.model_paths
if options.out is not None:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
print('generating names...')
model_names = [model_path.replace('.pkl', '!') for model_path in
model_paths]
model_names = unique_substrings(model_names, min_size=10)
model_names = [model_name.replace('!','') for model_name in
model_names]
print('...done')
for i, arg in enumerate(model_paths):
try:
model = serial.load(arg)
except Exception:
if arg.endswith('.yaml'):
print(sys.stderr, arg + " is a yaml config file," +
"you need to load a trained model.", file=sys.stderr)
quit(-1)
raise
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":" + model_names[i]
else:
postfix = ""
for channel in this_model_channels:
channels[channel+postfix] = this_model_channels[channel]
del model
gc.collect()
while True:
# Make a list of short codes for each channel so user can specify them
# easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels,
key = number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook['<'+channel_name+'>'] = channel_name
sorted_codes.append(code)
x_axis = 'example'
print('set x_axis to example')
if len(channels.values()) == 0:
print("there are no channels to plot")
break
# If there is more than one channel in the monitor ask which ones to
# plot
prompt = len(channels.values()) > 1
if prompt:
# Display the codebook
for code in sorted_codes:
print(code + '. ' + codebook[code])
print()
print("Put e, b, s or h in the list somewhere to plot " +
"epochs, batches, seconds, or hours, respectively.")
response = input('Enter a list of channels to plot ' + \
'(example: A, C,F-G, h, <test_err>) or q to quit' + \
' or o for options: ')
if response == 'o':
print('1: smooth all channels')
print('any other response: do nothing, go back to plotting')
response = input('Enter your choice: ')
if response == '1':
for channel in channels.values():
k = 5
new_val_record = []
for i in xrange(len(channel.val_record)):
new_val = 0.
count = 0.
for j in xrange(max(0, i-k), i+1):
new_val += channel.val_record[j]
count += 1.
new_val_record.append(new_val / count)
channel.val_record = new_val_record
continue
if response == 'q':
break
#Remove spaces
response = response.replace(' ','')
#Split into list
codes = response.split(',')
final_codes = set([])
for code in codes:
if code == 'e':
x_axis = 'epoch'
continue
elif code == 'b':
x_axis = 'batche'
elif code == 's':
x_axis = 'second'
elif code == 'h':
x_axis = 'hour'
elif code.startswith('<'):
assert code.endswith('>')
final_codes.add(code)
elif code.find('-') != -1:
#The current list element is a range of codes
rng = code.split('-')
if len(rng) != 2:
print("Input not understood: "+code)
quit(-1)
found = False
for i in xrange(len(sorted_codes)):
if sorted_codes[i] == rng[0]:
found = True
break
if not found:
print("Invalid code: "+rng[0])
quit(-1)
found = False
for j in xrange(i,len(sorted_codes)):
if sorted_codes[j] == rng[1]:
found = True
break
if not found:
print("Invalid code: "+rng[1])
quit(-1)
final_codes = final_codes.union(set(sorted_codes[i:j+1]))
else:
#The current list element is just a single code
final_codes = final_codes.union(set([code]))
# end for code in codes
else:
final_codes ,= set(codebook.keys())
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
styles = list(colors)
styles += [color+'--' for color in colors]
styles += [color+':' for color in colors]
fig = plt.figure()
ax = plt.subplot(1,1,1)
# plot the requested channels
for idx, code in enumerate(sorted(final_codes)):
channel_name= codebook[code]
channel = channels[channel_name]
y = np.asarray(channel.val_record)
if contains_nan(y):
print(channel_name + ' contains NaNs')
if contains_inf(y):
print(channel_name + 'contains infinite values')
if x_axis == 'example':
x = np.asarray(channel.example_record)
elif x_axis == 'batche':
x = np.asarray(channel.batch_record)
elif x_axis == 'epoch':
try:
x = np.asarray(channel.epoch_record)
except AttributeError:
# older saved monitors won't have epoch_record
x = np.arange(len(channel.batch_record))
elif x_axis == 'second':
x = np.asarray(channel.time_record)
elif x_axis == 'hour':
x = np.asarray(channel.time_record) / 3600.
else:
assert False
ax.plot( x,
y,
styles[idx % len(styles)],
marker = '.', # add point margers to lines
label = channel_name)
plt.xlabel('# '+x_axis+'s')
ax.ticklabel_format( scilimits = (-3,3), axis = 'both')
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc = 'upper left',
bbox_to_anchor = (1.05, 1.02))
# Get the axis positions and the height and width of the legend
plt.draw()
ax_pos = ax.get_position()
pad_width = ax_pos.x0 * fig.get_size_inches()[0]
pad_height = ax_pos.y0 * fig.get_size_inches()[1]
dpi = fig.get_dpi()
lgd_width = ax.get_legend().get_frame().get_width() / dpi
lgd_height = ax.get_legend().get_frame().get_height() / dpi
# Adjust the bounding box to encompass both legend and axis. Axis should be 3x3 inches.
# I had trouble getting everything to align vertically.
ax_width = 3
ax_height = 3
total_width = 2*pad_width + ax_width + lgd_width
total_height = 2*pad_height + np.maximum(ax_height, lgd_height)
fig.set_size_inches(total_width, total_height)
ax.set_position([pad_width/total_width, 1-6*pad_height/total_height, ax_width/total_width, ax_height/total_height])
if(options.yrange is not None):
ymin, ymax = map(float, options.yrange.split(':'))
plt.ylim(ymin, ymax)
if options.out is None:
plt.show()
else:
plt.savefig(options.out)
if not prompt:
break
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--out")
parser.add_argument("model_paths", nargs='+')
options = parser.parse_args()
model_paths = options.model_paths
if options.out is not None:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
print 'generating names...'
model_names = [model_path.replace('.pkl', '!') for model_path in model_paths]
model_names = unique_substrings(model_names, min_size=10)
model_names = [model_name.replace('!','') for model_name in model_names]
print '...done'
for i, arg in enumerate(model_paths):
try:
model = serial.load(arg)
except:
if arg.endswith('.yaml'):
print >> sys.stderr, arg+" is a yaml config file, you need to load a trained model."
quit(-1)
raise
this_model_channels = model.monitor.channels
if len(sys.argv) > 2:
postfix = ":" + model_names[i]
else:
postfix = ""
for channel in this_model_channels:
channels[channel+postfix] = this_model_channels[channel]
while True:
#XD
maxval = 0
baseval = 0
xlen = 0
start = 10
stop = 0
#Make a list of short codes for each channel so user can specify them easily
tag_generator = _TagGenerator()
codebook = {}
sorted_codes = []
for channel_name in sorted(channels, key = number_aware_alphabetical_key):
code = tag_generator.get_tag()
codebook[code] = channel_name
codebook['<'+channel_name+'>'] = channel_name
sorted_codes.append(code)
#x_axis = 'example'
x_axis = 'epoch' #XD add
#print 'set x_axis to example'
if len(channels.values()) == 0:
print "there are no channels to plot"
break
#if there is more than one channel in the monitor ask which ones to plot
prompt = len(channels.values()) > 1
if prompt:
#Display the codebook
for code in sorted_codes:
print code + '. ' + codebook[code]
print
print "Put e, b, s or h in the list somewhere to plot epochs, batches, seconds, or hours, respectively."
print "Put max=xx or base=xx in the list somewhere to set bounds or baseline for plotting." #XD add
response = raw_input('Enter a list of channels to plot (example: A, C,F-G, h, <test_err>) or q to quit or o for options: ')
if response == 'o':
print '1: smooth all channels'
print 'any other response: do nothing, go back to plotting'
response = raw_input('Enter your choice: ')
if response == '1':
for channel in channels.values():
k = 5
new_val_record = []
for i in xrange(len(channel.val_record)):
new_val = 0.
count = 0.
for j in xrange(max(0, i-k), i+1):
new_val += channel.val_record[j]
count += 1.
new_val_record.append(new_val / count)
channel.val_record = new_val_record
continue
if response == 'q':
break
#Remove spaces
response = response.replace(' ','')
#Split into list
codes = response.split(',')
final_codes = set([])
for code in codes:
"""
if code == 'e':
x_axis = 'epoch'
continue
elif code == 'b':
x_axis = 'batche'
elif code == 's':
x_axis = 'second'
elif code == 'h':
x_axis = 'hour'
elif code.startswith('<'):
assert code.endswith('>')
final_codes.add(code)
"""
#XD add
if code.startswith('max='):
maxval = float(code.split('=')[-1])
print 'maxval=', maxval #XD debug
elif code.startswith('base='):
baseval = float(code.split('=')[-1])
elif code.startswith('xlen='):
xlen = float(code.split('=')[-1])
elif code.startswith('start='):
start = float(code.split('=')[-1])
elif code.startswith('stop='):
stop = float(code.split('=')[-1])
elif code.find('-') != -1:
#The current list element is a range of codes
rng = code.split('-')
if len(rng) != 2:
print "Input not understood: "+code
quit(-1)
found = False
for i in xrange(len(sorted_codes)):
if sorted_codes[i] == rng[0]:
found = True
break
if not found:
print "Invalid code: "+rng[0]
quit(-1)
found = False
for j in xrange(i,len(sorted_codes)):
if sorted_codes[j] == rng[1]:
found = True
break
if not found:
print "Invalid code: "+rng[1]
quit(-1)
final_codes = final_codes.union(set(sorted_codes[i:j+1]))
else:
#The current list element is just a single code
final_codes = final_codes.union(set([code]))
# end for code in codes
else:
final_codes ,= set(codebook.keys())
plt.figure()
"""XD
#Make 2 subplots so the legend gets a plot to itself and won't cover up the plot
ax = plt.subplot(1,2,1)
# Grow current axis' width by 30%
box = ax.get_position()
try:
x0 = box.x0
y0 = box.y0
width = box.width
height = box.height
except:
x0, width, y0, height = box
ax.set_position([x0, y0, width * 1.3, height])
ax.ticklabel_format( scilimits = (-3,3), axis = 'both')
"""
plt.xlabel('# '+x_axis+'s')
colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k']
styles = list(colors)
styles += [color+'--' for color in colors]
styles += [color+':' for color in colors]
#plot the requested channels
for idx, code in enumerate(sorted(final_codes)):
#code = code.upper() #XD
#channel_name= codebook[code]
channel_name= codebook[code.upper()] #XD
print 'channel_name =', channel_name #XD
channel = channels[channel_name]
y = np.asarray(channel.val_record)
if np.any(np.isnan(y)):
print channel_name + ' contains NaNs'
if np.any(np.isinf(y)):
print channel_name + 'contains infinite values'
#XD add
if maxval != 0:
y = y * (y < maxval) + maxval * (y > maxval)
if x_axis == 'example':
x = np.asarray(channel.example_record)
elif x_axis == 'batche':
x = np.asarray(channel.batch_record)
elif x_axis == 'epoch':
try:
x = np.asarray(channel.epoch_record)
except AttributeError:
# older saved monitors won't have epoch_record
x = np.arange(len(channel.batch_record))
elif x_axis == 'second':
x = np.asarray(channel.time_record)
elif x_axis == 'hour':
x = np.asarray(channel.time_record) / 3600.
else:
assert False
#XD add
if xlen != 0:
y = y[:xlen]
x = x[:xlen]
if start != 0 and stop !=0:
y = y[start:stop]
x = x[start:stop]
elif start != 0:
y = y[start:]
x = x[start:]
if stop !=0:
y = y[:stop]
x = x[:stop]
"""
if channel_name == 'train_incprobs.5-1-1_nll':
y /= train_incprobs555_nll
if channel_name == 'train_incprobs.5-1-1_misclass':
y /= train_incprobs555_misclass
if channel_name == 'train_incprobs.7-1-1_nll':
y /= train_incprobs755_nll
if channel_name == 'train_incprobs.7-1-1_misclass':
y /= train_incprobs755_misclass
if channel_name == 'train_y_nll':
y = y /train_objective *5
#y = y * 20
if channel_name == 'train_iptincprob.5_entropy':
y = y + 0.05
if channel_name == 'train_iptincprob.6_entropy':
y = y + 0.055
if channel_name == 'train_incprob.5_nll':
y = y + 0.009
if channel_name == 'train_y_entropy':
y = y * 5 + 0.023
"""
#print 'channel_name before plot =', channel_name #XD
plt.plot( x,
y,
#styles[idx % len(styles)],
styles[(idx+1) % len(styles)], # XD add
label = channel_name)
if baseval !=0 and idx == 0:
y = y*0.0+baseval
plt.plot(x, y, styles[idx % len(styles)], label = 'baseline=' + str(baseval)) # XD add
#plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
plt.legend(loc=2) #XD
if options.out is None:
plt.show()
else:
plt.savefig(options.out)
if not prompt:
break
