def test_plot_multiple():
from dask.diagnostics.profile_visualize import visualize
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, "c")
p = visualize([prof, rprof],
label_size=50,
title="Not the default",
show=False,
save=False)
# Grid plot layouts changed in Bokeh 3.
# See https://github.com/dask/dask/issues/9257 for more details
if BOKEH_VERSION().major < 3:
figures = [r[0] for r in p.children[1].children]
else:
figures = [r[0] for r in p.children]
assert len(figures) == 2
assert figures[0].title.text == "Not the default"
assert figures[0].xaxis[0].axis_label is None
assert figures[1].title is None
assert figures[1].xaxis[0].axis_label == "Time (s)"
# Test empty, checking for errors
prof.clear()
rprof.clear()
visualize([prof, rprof], show=False, save=False)
def test_plot_multiple():
from dask.diagnostics.profile_visualize import visualize
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, "c")
p = visualize(
[prof, rprof], label_size=50, title="Not the default", show=False, save=False
)
bokeh_version = LooseVersion(bokeh.__version__)
if bokeh_version >= "1.1.0":
figures = [r[0] for r in p.children[1].children]
elif bokeh_version >= "0.12.0":
figures = [r.children[0] for r in p.children[1].children]
else:
figures = [r[0] for r in p.children]
assert len(figures) == 2
assert check_title(figures[0], "Not the default")
assert figures[0].xaxis[0].axis_label is None
assert figures[1].title is None
assert figures[1].xaxis[0].axis_label == "Time (s)"
# Test empty, checking for errors
prof.clear()
rprof.clear()
visualize([prof, rprof], show=False, save=False)
def test_plot_multiple():
from dask.diagnostics.profile_visualize import visualize
from bokeh.models import GridPlot
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, 'c')
p = visualize([prof, rprof], label_size=50,
title="Not the default", show=False, save=False)
assert isinstance(p, GridPlot)
assert len(p.children) == 2
assert p.children[0][0].title == "Not the default"
assert p.children[0][0].xaxis[0].axis_label is None
assert p.children[1][0].title is None
assert p.children[1][0].xaxis[0].axis_label == 'Time (s)'
# Test empty, checking for errors
prof.clear()
rprof.clear()
visualize([prof, rprof], show=False, save=False)
def test_plot_multiple():
from dask.diagnostics.profile_visualize import visualize
from bokeh.plotting import GridPlot
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, 'c')
p = visualize([prof, rprof], label_size=50,
title="Not the default", show=False, save=False)
assert isinstance(p, GridPlot)
assert len(p.children) == 2
assert p.children[0][0].title == "Not the default"
assert p.children[0][0].xaxis[0].axis_label is None
assert p.children[1][0].title is None
assert p.children[1][0].xaxis[0].axis_label == 'Time (s)'
# Test empty, checking for errors
prof.clear()
rprof.clear()
visualize([prof, rprof], show=False, save=False)
def test_plot_multiple():
from dask.diagnostics.profile_visualize import visualize
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, "c")
p = visualize(
[prof, rprof], label_size=50, title="Not the default", show=False, save=False
)
figures = [r[0] for r in p.children[1].children]
assert len(figures) == 2
assert figures[0].title.text == "Not the default"
assert figures[0].xaxis[0].axis_label is None
assert figures[1].title is None
assert figures[1].xaxis[0].axis_label == "Time (s)"
# Test empty, checking for errors
prof.clear()
rprof.clear()
visualize([prof, rprof], show=False, save=False)
def visualize(self, **kwargs):
"""Visualize the profiling run in a bokeh plot.
See also
--------
dask.diagnostics.profile_visualize.visualize
"""
from dask.diagnostics.profile_visualize import visualize
return visualize(self, **kwargs)
def test_plot_multiple():
from dask.diagnostics.profile_visualize import visualize
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, 'c')
p = visualize([prof, rprof], label_size=50,
title="Not the default", show=False, save=False)
if LooseVersion(bokeh.__version__) >= '0.12.0':
figures = [r.children[0] for r in p.children[1].children]
else:
figures = [r[0] for r in p.children]
assert len(figures) == 2
assert check_title(figures[0], "Not the default")
assert figures[0].xaxis[0].axis_label is None
assert figures[1].title is None
assert figures[1].xaxis[0].axis_label == 'Time (s)'
# Test empty, checking for errors
prof.clear()
rprof.clear()
visualize([prof, rprof], show=False, save=False)
def test_plot_both():
from dask.diagnostics.profile_visualize import visualize
from bokeh.plotting import GridPlot
with ResourceProfiler(dt=0.01) as rprof:
with prof:
get(dsk2, 'c')
p = visualize([prof, rprof], label_size=50,
title="Not the default", show=False, save=False)
assert isinstance(p, GridPlot)
assert len(p.children) == 2
assert p.children[0][0].title == "Not the default"
assert p.children[0][0].xaxis[0].axis_label is None
assert p.children[1][0].title is None
assert p.children[1][0].xaxis[0].axis_label == 'Time (s)'
result = (da_input**2. + da_input**3.).mean(axis=0)
result
# %% [markdown]
# ### Note that result hasn't been computed yet
#
# Here is a graph of how the calculation will be split among 4 threads
# %%
from dask.dot import dot_graph
dot_graph(result.dask)
# %% [markdown]
# ### Now do the calculation
# %%
with Profiler() as prof, ResourceProfiler(dt=0.1) as rprof,\
CacheProfiler() as cprof:
answer = result.compute()
# %% [markdown]
# Visualize the cpu, memory and cache for the 4 threads
# %%
visualize([prof, rprof, cprof], min_border_top=15, min_border_bottom=15)
# %% [markdown]
# ### You can evaluate your own functions on dask arrays
#
# If your functons release the GIL, you can get multithreaded computation using [dask.delayed](http://dask.pydata.org/en/latest/delayed.html)