def compchart_2dbarchart_jsonlogdata(settings, dataset):
"""This function is responsible for creating bar charts that compare data."""
dataset_types = shared.get_dataset_types(dataset)
data = shared.get_record_set_improved(settings, dataset, dataset_types)
# pprint.pprint(data)
fig, (ax1, ax2) = plt.subplots(nrows=2,
gridspec_kw={"height_ratios": [7, 1]})
ax3 = ax1.twinx()
fig.set_size_inches(10, 6)
#
# Puts in the credit source (often a name or url)
supporting.plot_source(settings, plt, ax1)
supporting.plot_fio_version(settings, data["fio_version"][0], plt, ax1)
ax2.axis("off")
return_data = create_bars_and_xlabels(settings, data, ax1, ax3)
rects1 = return_data["rects1"]
rects2 = return_data["rects2"]
ax1 = return_data["ax1"]
ax3 = return_data["ax3"]
#
# Set title
settings["type"] = ""
settings["iodepth"] = dataset_types["iodepth"]
if settings["rw"] == "randrw":
supporting.create_title_and_sub(settings, plt, skip_keys=["iodepth"])
else:
supporting.create_title_and_sub(settings, plt, skip_keys=[])
#
# Labeling the top of the bars with their value
shared.autolabel(rects1, ax1)
shared.autolabel(rects2, ax3)
tables.create_stddev_table(settings, data, ax2)
if settings["show_cpu"] and not settings["show_ss"]:
tables.create_cpu_table(settings, data, ax2)
if settings["show_ss"] and not settings["show_cpu"]:
tables.create_steadystate_table(settings, data, ax2)
# Create legend
ax2.legend(
(rects1[0], rects2[0]),
(data["y1_axis"]["format"], data["y2_axis"]["format"]),
loc="center left",
frameon=False,
)
#
# Save graph to PNG file
#
supporting.save_png(settings, plt, fig)
def chart_latency_histogram(settings, dataset):
"""This function is responsible to draw the 2D latency histogram,
(a bar chart)."""
record_set = shared.get_record_set_histogram(settings, dataset)
# We have to sort the data / axis from low to high
sorted_result_ms = sort_latency_data(record_set["data"]["latency_ms"])
sorted_result_us = sort_latency_data(record_set["data"]["latency_us"])
sorted_result_ns = sort_latency_data(record_set["data"]["latency_ns"])
# This is just to use easier to understand variable names
x_series = sorted_result_ms["keys"]
y_series1 = sorted_result_ms["values"]
y_series2 = sorted_result_us["values"]
y_series3 = sorted_result_ns["values"]
# us/ns histogram data is missing 2000/>=2000 fields that ms data has
# so we have to add dummy data to match x-axis size
y_series2.extend([0, 0])
y_series3.extend([0, 0])
# Create the plot
fig, ax1 = plt.subplots()
fig.set_size_inches(10, 6)
# Make the positioning of the bars for ns/us/ms
x_pos = np.arange(0, len(x_series) * 3, 3)
width = 1
# how much of the IO falls in a particular latency class ns/us/ms
coverage_ms = round(sum(y_series1), 2)
coverage_us = round(sum(y_series2), 2)
coverage_ns = round(sum(y_series3), 2)
# Draw the bars
rects1 = ax1.bar(x_pos, y_series1, width, color="r")
rects2 = ax1.bar(x_pos + width, y_series2, width, color="b")
rects3 = ax1.bar(x_pos + width + width, y_series3, width, color="g")
# Configure the axis and labels
ax1.set_ylabel("Percentage of I/O")
ax1.set_xlabel("Latency")
ax1.set_xticks(x_pos + width / 2)
ax1.set_xticklabels(x_series)
# Make room for labels by scaling y-axis up (max is 100%)
ax1.set_ylim(0, 100 * 1.1)
label_ms = "Latency in ms ({0:05.2f}%)".format(coverage_ms)
label_us = "Latency in us ({0:05.2f}%)".format(coverage_us)
label_ns = "Latency in ns ({0:05.2f}%)".format(coverage_ns)
# Configure the title
settings["type"] = ""
supporting.create_title_and_sub(settings, plt, ["type", "filter"])
# Configure legend
ax1.legend(
(rects1[0], rects2[0], rects3[0]),
(label_ms, label_us, label_ns),
frameon=False,
loc="best",
)
# puts a percentage above each bar (ns/us/ms)
autolabel(rects1, ax1)
autolabel(rects2, ax1)
autolabel(rects3, ax1)
supporting.plot_source(settings, plt, ax1)
supporting.plot_fio_version(settings, record_set["fio_version"], plt, ax1)
# if settings['source']:
# sourcelength = len(settings['source'])
# offset = 1.0 - sourcelength / 120
# fig.text(offset, 0.03, settings['source'])
#
# Save graph to PNG file
#
supporting.save_png(settings, plt, fig)
def chart_2d_log_data(settings, dataset):
#
# Raw data must be processed into series data + enriched
#
data = supporting.process_dataset(settings, dataset)
datatypes = data["datatypes"]
directories = logdata.get_unique_directories(dataset)
# pprint.pprint(data)
#
# Create matplotlib figure and first axis. The 'host' axis is used for
# x-axis and as a basis for the second and third y-axis
#
fig, host = plt.subplots()
fig.set_size_inches(9, 5)
plt.margins(0)
#
# Generates the axis for the graph with a maximum of 3 axis (per type of
# iops,lat,bw)
#
axes = supporting.generate_axes(host, datatypes)
#
# Create title and subtitle
#
supporting.create_title_and_sub(settings, plt)
#
# The extra offsets are requred depending on the size of the legend, which
# in turn depends on the number of legend items.
#
if settings["colors"]:
support2d.validate_colors(settings["colors"])
extra_offset = (len(datatypes) * len(settings["iodepth"]) *
len(settings["numjobs"]) * len(settings["filter"]))
bottom_offset = 0.18 + (extra_offset / 120)
if "bw" in datatypes and (len(datatypes) > 2):
#
# If the third y-axis is enabled, the graph is ajusted to make room for
# this third y-axis.
#
fig.subplots_adjust(left=0.21)
try:
fig.subplots_adjust(bottom=bottom_offset)
except ValueError as v:
print(f"\nError: {v} - probably too many lines in the graph.\n")
sys.exit(1)
supportdata = {
"lines": [],
"labels": [],
"colors": support2d.get_colors(settings),
"marker_list": list(markers.MarkerStyle.markers.keys()),
"fontP": FontProperties(family="monospace"),
"maximum": supporting.get_highest_maximum(settings, data),
"axes": axes,
"host": host,
"maxlabelsize": support2d.get_max_label_size(settings, data,
directories),
"directories": directories,
}
supportdata["fontP"].set_size("xx-small")
#
# Converting the data and drawing the lines
#
for item in data["dataset"]:
for rw in settings["filter"]:
if rw in item.keys():
support2d.drawline(settings, item, rw, supportdata)
#
# Generating the legend
#
values, ncol = support2d.generate_labelset(settings, supportdata)
host.legend(
supportdata["lines"],
values,
prop=supportdata["fontP"],
bbox_to_anchor=(0.5, -0.18),
loc="upper center",
ncol=ncol,
frameon=False,
)
def get_axis_for_label(axes):
axis = list(axes.keys())[0]
ax = axes[axis]
return ax
#
# A ton of work to get the Fio-version from .json output if it exists.
#
jsondata = support2d.get_json_data(settings)
ax = get_axis_for_label(axes)
if jsondata[0]["data"] and not settings["disable_fio_version"]:
fio_version = jsondata[0]["data"][0]["fio_version"]
supporting.plot_fio_version(settings, fio_version, plt, ax, -0.12)
else:
supporting.plot_fio_version(settings, None, plt, ax, -0.12)
#
# Print source
#
ax = get_axis_for_label(axes)
supporting.plot_source(settings, plt, ax, -0.12)
#
# Save graph to PNG file
#
supporting.save_png(settings, plt, fig)