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Plot different algebra-plugins
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@niermann999
niermann999 committed Jan 6, 2025
1 parent 7fca7c7 commit 5aa5cea
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Showing 5 changed files with 107 additions and 139 deletions.
67 changes: 43 additions & 24 deletions tests/tools/python/impl/plot_benchmark_results.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
""" Read google benchmark data from json file """


def read_benchmark_data(input_path, logging, det_name, plugins):
def read_benchmark_data(input_path, logging, det_name, plugin):

# Input data directory
input_dir = os.fsencode(input_path)
Expand All @@ -29,7 +29,9 @@ def read_benchmark_data(input_path, logging, det_name, plugins):
for file_item in os.listdir(input_dir):
file_name = os.fsdecode(file_item)

if file_name.find(det_name + "_benchmark_data") != -1:
if (file_name.find(det_name + "_benchmark_data_") != -1) and (
file_name.find(plugin) != -1
):
file_path = input_path + file_name
with open(file_path, "r") as file:
results = json.load(file)
Expand All @@ -39,6 +41,12 @@ def read_benchmark_data(input_path, logging, det_name, plugins):

return context, data

logging.error(
f"Could not find benchmark results for '{det_name}' and plugin '{plugin}'"
)

return None, None


""" Adds a column 'x' to the data frame that contains the number of tracks """

Expand Down Expand Up @@ -78,7 +86,7 @@ def compactify_proc_name(name):
""" Plot the benchmark results for different hardware and algebra plugins """


def plot_benchmarks(context, df, detector, plot_factory, out_format="pdf"):
def plot_benchmarks(context, df, plot_factory, out_format="pdf", plot=None):

assert len(df["x"]) != 0, "Data frame has to provide column 'x'"
assert len(df["real_time"]) != 0, "Data frame has to provide column 'real_time'"
Expand Down Expand Up @@ -106,24 +114,35 @@ def plot_benchmarks(context, df, detector, plot_factory, out_format="pdf"):
lgd_ops = plotting.get_legend_options()
lgd_ops._replace(loc=ldg_loc)

# Plot the propagation latency agains the number of tracks
plot_data = plot_factory.graph2D(
x=n_tracks,
y=real_time,
y_errors=real_time_stddev,
x_label="No. tracks",
y_label="t [ns]",
title="Propagation Latency",
label=plot_label,
lgd_ops=lgd_ops,
set_log_x=True,
set_log_y=True,
figsize=(12, 8),
)

plot_data.ax.set_xscale("log", base=2)
plot_data.ax.set_xticks(n_tracks)

plot_factory.write_plot(
plot_data, detector + f"_prop_latency_{plot_label}", out_format
)
plot_data = plotting.plt_data(None, None, None, None, None, None, None, None)
if plot is None:
# Plot the propagation latency agains the number of tracks
plot_data = plot_factory.graph2D(
x=n_tracks,
y=real_time,
y_errors=real_time_stddev,
x_label="No. tracks",
y_label="t [ns]",
title="Propagation Latency",
label=plot_label,
lgd_ops=lgd_ops,
set_log_x=True,
set_log_y=True,
figsize=(12, 8),
)

plot_data.ax.set_xscale("log", base=2)
plot_data.ax.set_xticks(n_tracks)
else:
# Add new data to exiting plot
plot_data = plot_factory.add_graph(
plot=plot,
x=n_tracks,
y=real_time,
y_errors=real_time_stddev,
label=plot_label,
marker="+",
color="tab:orange",
)

return plot_data
2 changes: 1 addition & 1 deletion tests/tools/python/options/plotting_options.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@ def plotting_options():
"--output_format",
"-of",
help=("Format of the plot files (svg|png|pdf)."),
default="png",
default="pdf",
type=str,
)

Expand Down
2 changes: 1 addition & 1 deletion tests/tools/python/plotting/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,3 @@
from .plot_helpers import filter_data
from .pyplot_factory import pyplot_factory
from .pyplot_factory import legend_options, get_legend_options
from .pyplot_factory import plt_data, legend_options, get_legend_options
45 changes: 41 additions & 4 deletions tests/tools/python/plotting/pyplot_factory.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -91,7 +91,6 @@ def graph2D(
self,
x,
y,
x_errors=None,
y_errors=None,
x_label="x",
y_label="y",
Expand Down Expand Up @@ -137,7 +136,7 @@ def graph2D(

if len(x) != len(y):
self.logger.debug(rf" create graph: x range does match y range {label}")
return plt_data(fig, ax, None, None, None, None, None, None)
return plt_data(fig, ax, None, None, None, None, None, y_errors)

data = ax.errorbar(x=x, y=y, label=label, yerr=y_errors, marker=marker)

Expand All @@ -156,7 +155,45 @@ def graph2D(
if set_log_y:
ax.set_yscale("log")

return plt_data(fig, ax, lgd, data, None, None, None, None)
return plt_data(fig, ax, lgd, data, None, None, None, y_errors)

""" Add new graph to an existing plot """

def add_graph(
self,
plot,
x,
y,
y_errors=None,
label="",
marker="+",
color="tab:orange",
alpha=0.75,
):
# Nothing left to do
if len(y) == 0 or plot.data is None:
self.logger.debug(rf" add graph: empty data {label}")
return plot

# Add new data to old plot axis
data = plot.ax.errorbar(
x=x,
y=y,
label=label,
yerr=y_errors,
color=color,
marker=marker,
)

# Update legend
lgd = plot.lgd
handles, labels = lgd.axes.get_legend_handles_labels()
lgd._legend_box = None
lgd._init_legend_box(handles, labels)
lgd._set_loc(lgd._loc)
lgd.set_title(lgd.get_title().get_text())

return plt_data(plot.fig, plot.ax, plot.lgd, data, None, None, None, y_errors)

"""
Create a histogram from given input data. The normalization is achieved by
Expand Down Expand Up @@ -305,7 +342,7 @@ def hist1D(

return plt_data(fig, ax, lgd, data, bins, mean, stdev, err)

""" Add new data to an existing plot """
""" Add new histogram to an existing plot """

def add_hist(
self,
Expand Down
130 changes: 21 additions & 109 deletions tests/tools/python/propagation_benchmarks.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -108,11 +108,11 @@ def __main__():
# Gather and check benchmark executables for every plugin
cpu_benchmarks = []
cuda_benchmarks = []
algebra_plugins = list(args.algebra_plugins)
algebra_plugins = set(args.algebra_plugins)
if "array" not in algebra_plugins:
algebra_plugins.insert(0, "array")

for plugin in set(algebra_plugins):
for plugin in algebra_plugins:
cpu_benchmark = bindir + "/detray_propagation_benchmark_cpu_" + plugin
cuda_benchmark = bindir + "/detray_detector_validation_cuda_" + plugin

Expand Down Expand Up @@ -187,7 +187,7 @@ def __main__():
logging.debug("Running CPU Propagation Benchmarks")

for benchmark in cpu_benchmarks:
plugin = benchmark.split("_")[-1]
plugin = benchmark.split("benchmark_cpu_")[-1]
subprocess.run(
[
benchmark,
Expand Down Expand Up @@ -234,122 +234,34 @@ def __main__():
plot_factory = plt_factory(out_dir, logging)

# Read the benchmark data into a pandas frame
context, data = read_benchmark_data(input_dir, logging, det_name, algebra_plugins)
context, data = read_benchmark_data(input_dir, logging, det_name, "array")
if context is None or data is None:
sys.exit(1)

# Add the number of tracks per benchmark case as new column 'x'
add_track_multiplicity_column(data)

# Plot the data against the number of tracks
benchmark_plotter.plot_benchmarks(context, data, det_name, plot_factory)

"""
plot_detector_scan_data(args, det_name, plot_factory, "ray", ray_scan_df, "png")
plot_detector_scan_data(args, det_name, plot_factory, "helix", helix_scan_df, "png")
# Plot distributions of track parameter values
# Only take initial track parameters from generator
ray_intial_trk_df = ray_scan_df.drop_duplicates(subset=["track_id"])
helix_intial_trk_df = helix_scan_df.drop_duplicates(subset=["track_id"])
plot_track_params(
args, det_name, "helix", plot_factory, out_format, helix_intial_trk_df
)
plot_track_params(
args, det_name, "ray", plot_factory, out_format, ray_intial_trk_df
)
# Read the recorded data
(
ray_nav_df,
ray_truth_df,
ray_nav_cuda_df,
helix_nav_df,
helix_truth_df,
helix_nav_cuda_df,
) = read_navigation_data(
datadir, det_name, str(args.transverse_momentum), args.cuda, logging
)
# Plot
label_cpu = "navigation (CPU)"
label_cuda = "navigation (CUDA)"
plot_navigation_data(
args,
det_name,
plot_factory,
"ray",
ray_truth_df,
"truth",
ray_nav_df,
label_cpu,
out_format,
)
plot_navigation_data(
args,
det_name,
plot_factory,
"helix",
helix_truth_df,
"truth",
helix_nav_df,
label_cpu,
out_format,
plot_data = benchmark_plotter.plot_benchmarks(
context, data, plot_factory, out_format
)

if args.cuda:
# Truth vs. Device
plot_navigation_data(
args,
det_name,
plot_factory,
"ray",
ray_truth_df,
"truth",
ray_nav_cuda_df,
label_cuda,
out_format,
)
# Add plots for the other algebra plugins
for plugin in algebra_plugins:
if plugin != "array":
context, data = read_benchmark_data(input_dir, logging, det_name, plugin)
if context is None or data is None:
sys.exit(1)

plot_navigation_data(
args,
det_name,
plot_factory,
"helix",
helix_truth_df,
"truth",
helix_nav_cuda_df,
label_cuda,
out_format,
)
add_track_multiplicity_column(data)

# Host vs. Device
plot_navigation_data(
args,
det_name,
plot_factory,
"ray",
ray_nav_df,
label_cpu,
ray_nav_cuda_df,
label_cuda,
out_format,
)
plot_navigation_data(
args,
det_name,
plot_factory,
"helix",
helix_nav_df,
label_cpu,
helix_nav_cuda_df,
label_cuda,
out_format,
)
"""
# Add new data to 'plot_data'
benchmark_plotter.plot_benchmarks(
context, data, plot_factory, out_format, plot_data
)

logging.info("\nDone.\n")
# Write to disk
plot_factory.write_plot(plot_data, det_name + f"_prop_latency", out_format)


# ------------------------------------------------------------------------------
Expand Down

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