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Metadata plotting #33

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f24bac7
initial commit
SATheinen Aug 21, 2024
7caa001
add simulator_version and completion time to dict
SATheinen Aug 21, 2024
c936f80
add simulator_version and completion time to dict
SATheinen Aug 21, 2024
5b8ebe5
handle empty cells
SATheinen Aug 21, 2024
0787fc8
handle empty cells
SATheinen Aug 21, 2024
78d56df
fix name for annotation time
SATheinen Sep 28, 2024
11c3a13
add annotation time
SATheinen Sep 28, 2024
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85 changes: 45 additions & 40 deletions bennchplot/bennchplot.py
100644 → 100755
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,8 @@ def __init__(self, x_axis,
color_params=pp.color_params,
additional_params=pp.additional_params,
label_params=pp.label_params,
time_scaling=1):
time_scaling=1,
df=None):

self.x_axis = x_axis
self.x_ticks = x_ticks
Expand All @@ -72,6 +73,7 @@ def __init__(self, x_axis,
self.label_params = label_params
self.time_scaling = time_scaling

self.df = df
self.load_data(data_file)
self.compute_derived_quantities()

Expand All @@ -90,48 +92,50 @@ def load_data(self, data_file):
------
ValueError
"""
try:
self.df = pd.read_csv(data_file, delimiter=',')
except FileNotFoundError:
print('File could not be found')
quit()
if self.df is None:
try:
self.df = pd.read_csv(data_file, delimiter=',')
except FileNotFoundError:
print('File could not be found')
quit()

for py_timer in ['py_time_create', 'py_time_connect']:
if py_timer not in self.df:
self.df[py_timer] = np.nan
raise ValueError('Warning! Python timers are not found. ' +
'Construction time measurements will not ' +
'be accurate.')

self.df.fillna(0, inplace=True)

dict_ = {'num_nodes': 'first',
'threads_per_task': 'first',
'tasks_per_node': 'first',
'model_time_sim': 'first',
'wall_time_create': ['mean', 'std'],
'wall_time_connect': ['mean', 'std'],
'wall_time_sim': ['mean', 'std'],
'wall_time_phase_collocate': ['mean', 'std'],
'wall_time_phase_communicate': ['mean', 'std'],
'wall_time_phase_deliver': ['mean', 'std'],
'wall_time_phase_update': ['mean', 'std'],
'wall_time_communicate_target_data': ['mean', 'std'],
'wall_time_gather_spike_data': ['mean', 'std'],
'wall_time_gather_target_data': ['mean', 'std'],
'wall_time_communicate_prepare': ['mean', 'std'],
'annotation_time': 'first',
'simulator_version': 'first',
'time_construction_create': ['mean', 'std'],
'time_construction_connect': ['mean', 'std'],
'time_simulate': ['mean', 'std'],
'time_collocate_spike_data': ['mean', 'std'],
'time_communicate_spike_data': ['mean', 'std'],
'time_deliver_spike_data': ['mean', 'std'],
'time_update': ['mean', 'std'],
'time_communicate_target_data': ['mean', 'std'],
'time_gather_spike_data': ['mean', 'std'],
'time_gather_target_data': ['mean', 'std'],
'time_communicate_prepare': ['mean', 'std'],
'py_time_create': ['mean', 'std'],
'py_time_connect': ['mean', 'std'],
'base_memory': ['mean', 'std'],
'network_memory': ['mean', 'std'],
'init_memory': ['mean', 'std'],
'total_memory': ['mean', 'std'],
'num_connections': ['mean', 'std'],
'local_spike_counter': ['mean', 'std'],

}
'num_connections': ['mean', 'std']}

col = ['num_nodes', 'threads_per_task', 'tasks_per_node',
'model_time_sim', 'wall_time_create',
'wall_time_create_std', 'wall_time_connect',
'model_time_sim', 'annotation_time', 'simulator_version',
'wall_time_create', 'wall_time_create_std', 'wall_time_connect',
'wall_time_connect_std', 'wall_time_sim',
'wall_time_sim_std', 'wall_time_phase_collocate',
'wall_time_phase_collocate_std', 'wall_time_phase_communicate',
Expand All @@ -152,14 +156,16 @@ def load_data(self, data_file):
'network_memory', 'network_memory_std',
'init_memory', 'init_memory_std',
'total_memory', 'total_memory_std',
'num_connections', 'num_connections_std',
'local_spike_counter', 'local_spike_counter_std']
'num_connections', 'num_connections_std']

self.df = self.df.drop('rng_seed', axis=1).groupby(
['num_nodes',
'threads_per_task',
'tasks_per_node',
'model_time_sim'], as_index=False).agg(dict_)
'model_time_sim',
'annotation_time',
'simulator_version'], as_index=False).agg(dict_)
print(self.df)
self.df.columns = col

def compute_derived_quantities(self):
Expand Down Expand Up @@ -244,9 +250,9 @@ def plot_fractions(self, axis, fill_variables,

fill_height = 0
for fill in fill_variables:
axis.fill_between(np.squeeze(self.df[self.x_axis]),
axis.fill_between(self.df[self.x_axis].to_numpy().squeeze(axis=1),
fill_height,
np.squeeze(self.df[fill]) + fill_height,
self.df[fill].to_numpy() + fill_height,
label=self.label_params[fill],
facecolor=self.color_params[fill],
interpolate=interpolate,
Expand All @@ -255,18 +261,17 @@ def plot_fractions(self, axis, fill_variables,
linewidth=0.5,
edgecolor='#444444')
if error:
axis.errorbar(np.squeeze(self.df[self.x_axis]),
np.squeeze(self.df[fill]) + fill_height,
yerr=np.squeeze(self.df[fill + '_std']),
axis.errorbar(self.df[self.x_axis].to_numpy().squeeze(axis=1),
self.df[fill].to_numpy() + fill_height,
yerr=self.df[fill + '_std'].to_numpy(),
capsize=3,
capthick=1,
color='k',
fmt='none'
)
fmt='none')
fill_height += self.df[fill].to_numpy()

if self.x_ticks == 'data':
axis.set_xticks(np.squeeze(self.df[self.x_axis]))
axis.set_xticks(self.df[self.x_axis].to_numpy().squeeze(axis=1))
else:
axis.set_xticks(self.x_ticks)

Expand Down Expand Up @@ -297,17 +302,17 @@ def plot_main(self, quantities, axis, log=(False, False),

for y in quantities:
if not error:
axis.plot(self.df[self.x_axis],
self.df[y],
axis.plot(self.df[self.x_axis].to_numpy().squeeze(axis=1),
self.df[y].to_numpy(),
marker=None,
label=self.label_params[y],
color=self.color_params[y],
linewidth=2)
else:
axis.errorbar(
self.df[self.x_axis].values,
self.df[y].values,
yerr=self.df[y + '_std'].values,
self.df[self.x_axis].to_numpy().squeeze(axis=1),
self.df[y].to_numpy(),
yerr=self.df[y + '_std'].to_numpy(),
marker=None,
capsize=3,
capthick=1,
Expand All @@ -316,7 +321,7 @@ def plot_main(self, quantities, axis, log=(False, False),
fmt=fmt)

if self.x_ticks == 'data':
axis.set_xticks(self.df[self.x_axis].values)
axis.set_xticks(self.df[self.x_axis].to_numpy().squeeze(axis=1))
else:
axis.set_xticks(self.x_ticks)

Expand Down