def plot_by_variable(details):
'''Plot each .csv files under @plot_node as a line on a shared plot.'''
builder = ColMapBuilder()
config_nodes = []
# Decode file names into configuration dicts
for line_path, line_node in details.node.children.iteritems():
encoded = line_path[:line_path.index(".csv")]
try:
line_config = ColMap.decode(encoded)
except:
line_config = {'name': encoded}
for k, v in line_config.iteritems():
builder.try_add(k, v)
config_nodes += [(line_config, line_node)]
col_map = builder.build()
style_map = make_styler(col_map)
figure = plot.figure()
axes = figure.add_subplot(111)
# Create a line for each file node and its configuration
for line_config, line_node in config_nodes:
style = style_map.get_style(line_config)
values = sorted(line_node.values, key=lambda tup: tup[0])
xvalues, yvalues = zip(*values)
plot.plot(xvalues, yvalues, style.fmt())
axes.set_title(details.title)
lines, labels = zip(*style_map.get_key())
axes.legend(
tuple(lines),
tuple(labels),
prop={'size': 10},
# This code places the legend slightly to the right of the plot
bbox_to_anchor=(1.05, 1),
loc=2,
borderaxespad=0.0)
axes.set_ylabel(details.value)
axes.set_xlabel(details.variable)
axes.set_xlim(0, axes.get_xlim()[1])
axes.set_ylim(0, axes.get_ylim()[1])
plot.savefig(
details.out,
format=OUT_FORMAT,
# Using 'tight' causes savefig to rescale the image for non-plot
# artists, which in our case is just the legend
bbox_inches='tight')
return True
def plot_by_variable(details):
'''Plot each .csv files under @plot_node as a line on a shared plot.'''
builder = ColMapBuilder()
config_nodes = []
# Decode file names into configuration dicts
for line_path, line_node in details.node.children.iteritems():
encoded = line_path[:line_path.index(".csv")]
try:
line_config = ColMap.decode(encoded)
except:
line_config = {'name': encoded}
for k, v in line_config.iteritems():
builder.try_add(k, v)
config_nodes += [(line_config, line_node)]
col_map = builder.build()
style_map = make_styler(col_map)
figure = plot.figure()
axes = figure.add_subplot(111)
# Create a line for each file node and its configuration
for line_config, line_node in config_nodes:
style = style_map.get_style(line_config)
values = sorted(line_node.values, key=lambda tup: tup[0])
xvalues, yvalues = zip(*values)
plot.plot(xvalues, yvalues, style.fmt())
axes.set_title(details.title)
lines, labels = zip(*style_map.get_key())
axes.legend(tuple(lines), tuple(labels), prop={'size':10},
# This code places the legend slightly to the right of the plot
bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0)
axes.set_ylabel(details.value)
axes.set_xlabel(details.variable)
axes.set_xlim(0, axes.get_xlim()[1])
axes.set_ylim(0, axes.get_ylim()[1])
plot.savefig(details.out, format=OUT_FORMAT,
# Using 'tight' causes savefig to rescale the image for non-plot
# artists, which in our case is just the legend
bbox_inches='tight')
return True
def plot_by_variable(details):
'''Plot each .csv files under @plot_node as a line on a shared plot.'''
builder = ColMapBuilder()
config_nodes = []
# Generate mapping of (column)=>(line property to vary) for consistently
# formatted plots
for line_path, line_node in details.node.children.iteritems():
encoded = line_path[:line_path.index(".csv")]
try:
line_config = ColMap.decode(encoded)
except:
line_config = {'name': encoded}
for k, v in line_config.iteritems():
builder.try_add(k, v)
config_nodes += [(line_config, line_node)]
col_map = builder.build()
style_map = StyleMap(col_map.columns(), col_map.get_values())
figure = plot.figure()
axes = figure.add_subplot(111)
# Create a line for each file node and its configuration
for line_config, line_node in config_nodes:
# Create line style to match this configuration
style = style_map.get_style(line_config)
values = sorted(line_node.values, key=lambda tup: tup[0])
xvalues, yvalues = zip(*values)
plot.plot(xvalues, yvalues, style.fmt())
axes.set_title(details.title)
lines, labels = zip(*style_map.get_key())
axes.legend(tuple(lines), tuple(labels), prop={'size':10})
axes.set_ylabel(details.value)
axes.set_xlabel(details.variable)
axes.set_xlim(0, axes.get_xlim()[1] + 1)
axes.set_ylim(0, axes.get_ylim()[1] + 1)
plot.savefig(details.out, format=OUT_FORMAT)
return True
def create_exps(self, out_dir, force, trials):
'''Create experiments for all possible combinations of params in
@out_dir. Overwrite existing files if @force is True.'''
builder = ColMapBuilder()
# Track changing values so only relevant parameters are included
# in directory names
for dp in DesignPointGenerator(self.params):
for k, v in dp.iteritems():
builder.try_add(k, v)
col_map = builder.build()
for dp in DesignPointGenerator(self.params):
for trial in xrange(trials):
# Create directory name from relevant parameters
dir_leaf = "sched=%s_%s" % (self.scheduler, col_map.encode(dp))
dir_leaf = dir_leaf.strip('_') # If there are none
dir_leaf += ("_trial=%s" % trial) if trials > 1 else ""
dir_path = "%s/%s" % (out_dir, dir_leaf.strip('_'))
if os.path.exists(dir_path):
if force:
sh.rmtree(dir_path)
else:
print("Skipping existing experiment: '%s'" % dir_path)
continue
os.mkdir(dir_path)
if trials > 1:
dp[PARAMS['trial']] = trial
self.out_dir = dir_path
self._create_exp(dict(dp))
del(self.out_dir)
if PARAMS['trial'] in dp:
del dp[PARAMS['trial']]
def create_exps(self, out_dir, force, trials):
'''Create experiments for all possible combinations of params in
@out_dir. Overwrite existing files if @force is True.'''
builder = ColMapBuilder()
# Track changing values so only relevant parameters are included
# in directory names
for dp in DesignPointGenerator(self.params):
for k, v in dp.iteritems():
builder.try_add(k, v)
col_map = builder.build()
for dp in DesignPointGenerator(self.params):
for trial in xrange(trials):
# Create directory name from relevant parameters
dir_leaf = "sched=%s_%s" % (self.scheduler, col_map.encode(dp))
dir_leaf = dir_leaf.strip('_') # If there are none
dir_leaf += ("_trial=%s" % trial) if trials > 1 else ""
dir_path = "%s/%s" % (out_dir, dir_leaf.strip('_'))
if os.path.exists(dir_path):
if force:
sh.rmtree(dir_path)
else:
print("Skipping existing experiment: '%s'" % dir_path)
continue
os.mkdir(dir_path)
if trials > 1:
dp[PARAMS['trial']] = trial
self.out_dir = dir_path
self._create_exp(dict(dp))
del (self.out_dir)
if PARAMS['trial'] in dp:
del dp[PARAMS['trial']]
def write_collapsed_csvs(table, opts):
sys.stderr.write("Collapse option specified. "
"Only one numeric column at a time will be plotted.\n"
"The values of others will be averaged. "
"This is dangerous and can hide important trends!\n")
original_map = table.get_col_map()
builder = ColMapBuilder()
numeric_cols = []
# Add only nonnumeric fields to builder
for column in original_map.columns():
numeric = True
for v in original_map.get_values()[column]:
try:
float(v)
except ValueError:
numeric = False
builder.try_add(column, v)
if numeric:
numeric_cols += [column]
for num_column in numeric_cols:
# Only going to consider a single number column at a time
for num_value in original_map.get_values()[column]:
builder.try_add(num_column, num_value)
next_map = builder.build()
next_table = TupleTable(next_map)
# Re-sort data into new table using this new key
for mapped_key, points in table:
kv = original_map.get_kv(mapped_key)
next_table[kv] += points
write_csvs(next_table, opts.out)
builder.try_remove(num_column)
def write_collapsed_csvs(table, opts):
sys.stderr.write("Collapse option specified. "
"Only one numeric column at a time will be plotted.\n"
"The values of others will be averaged. "
"This is dangerous and can hide important trends!\n")
original_map = table.get_col_map()
builder = ColMapBuilder()
numeric_cols = []
# Add only nonnumeric fields to builder
for column in original_map.columns():
numeric = True
for v in original_map.get_values()[column]:
try:
float(v)
except ValueError:
numeric = False
builder.try_add(column, v)
if numeric:
numeric_cols += [column]
for num_column in numeric_cols:
# Only going to consider a single number column at a time
for num_value in original_map.get_values()[column]:
builder.try_add(num_column, num_value)
next_map = builder.build()
next_table = TupleTable(next_map)
# Re-sort data into new table using this new key
for mapped_key, points in table:
kv = original_map.get_kv(mapped_key)
next_table[kv] += points
write_csvs(next_table, opts.out)
builder.try_remove(num_column)
