def plot(self, measurement, *args, **kwargs):
"""
Plot heat-map for the measurement.
The code will plot any measurement that satisfies its requirements.
Arguments
-------------
measurement :: pandas.DataFrame with a MultiIndex
with index labels ('pre_mtype', 'post_mtype')
"""
def __get_value(pre_mtype, post_mtype):
"""
Get the value for pre-mtype to post-mtype.
"""
return measurement.loc(pre_mtype, post_mtype)["mean"]\
if (pre_mtype, post_mtype) in measurement.index\
else np.nan
index_mtypes =\
sorted(list({
mtype for tup in measurement.index.values
for mtype in tup}))
matrix = np.array([[
__get_value(pre_mtype, post_mtype) for pre_mtype in index_mtypes
] for post_mtype in index_mtypes])
xticks_rotation = 90
xvar = "post_mtype"
yvar = "pre_mtype"
figure =\
golden_figure(
height=self._height,
width=self._width)
axes =\
figure.add_axes(
[0.075, 0.125, 0.9, 0.8])
image =\
axes.imshow(
matrix_data,
interpolation="nearest")
n_data_points =\
len(index_mtypes)
axes.set_xlabel(xvar)
axes.set_xticklabels(index_mtypes,
rotation="vertical",
size="xx-small")
axes.set_ylabel(yvar)
axes.set_yticklabels(index_mtypes, size="xx-small")
color_limits = (np.nanmin(matrix), np.nanmax(matrix))
image.set_clim(color_limits)
colorbar=\
plt.colorbar(image)
return figure
def _section(label, subsections=NA):
"""
Each section will generate it's own 'CircuitAnalysisReport` instance,
just as we will implement `Report.sections` as a list of independent
reports.
"""
figure, axes =\
golden_figure(14, 12)
xs = np.linspace(0., 1., 100)
ys = np.cumsum(np.random.uniform(size=100))
measurement =\
pd.DataFrame({"x": xs, "y": ys}).set_index(["x"])
plt.plot(xs, ys)
return\
CircuitAnalysisReport(
author=Author.anonymous,
phenomenon="{}".format(label),
abstract="""
Abstract {}
""".format(label),
introduction="""
Introduce {}
""".format(label),
methods="""
Methods {}
""".format(label),
measurement=measurement,
figures={
"random_walk_{}".format(label): Figure(
figure,
caption="""
Each random walk step size is uniformly drawn from [0, 1).
The individual steps are added up cummulatively to obtain
the location of the walk at a given time.
""".format(label))},
results="""
Results {}
""".format(label),
discussion="""
Discussion {}
""".format(label),
references={"{}".format(label): "https://www.example.org/{}".format(label)},
sections=subsections,
provenance_model=provenance)
def plot(self, df, values=None):
groups, group_labels, group_patchdata, conn_angles\
= self.__plot_components__(df, values=values)
group_angles, group_colors = group_patchdata
source_angles, dest_angles = conn_angles
sz = 60 # len(pivot_table.index)*4
fig, ax = golden_figure(width=sz, height=sz)
# TODO: adapt limits to text
ax.set_xlim(left=-1.3, right=+1.3)
ax.set_ylim(bottom=-1.3, top=+1.3)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.add_collection(
matplotlib.collections.PatchCollection([
self._conn_patch(s_angles, dest_angles[from_][to],
group_colors[from_])
for from_, conn in source_angles.items()
for to, s_angles in conn.items()
],
match_original=True))
ax.add_collection(
matplotlib.collections.PatchCollection([
self._group_patch(angles, **group_colors[group])
for group, angles in group_angles.items()
],
match_original=True))
oldfont = plt.rcParams.get('font.size')
plt.rcParams.update({'font.size': sz})
textcirc = CircleTool(self.circle.radius * 1.2)
for t, a in group_labels.items():
plt.text(*textcirc.angles_to_points(a),
t,
rotation=90 - a * (180 / np.pi),
rotation_mode="anchor")
plt.rcParams.update({"font.size": oldfont})
return fig
def test_post():
"""
Reporter should be able to post the report to a location.
"""
figure, axes =\
golden_figure(14, 12)
xs = np.linspace(0., 1., 100)
ys = np.cumsum(np.random.uniform(size=100))
measurement =\
pd.DataFrame({"x": xs, "y": ys}).set_index(["x"])
plt.plot(xs, ys)
provenance =\
CircuitProvenance(
label="Test",
authors=3*[Author.anonymous],
date_release="XXXXXXXX",
uri="UnknownLocation",
animal="UnkownAnimal",
age="UnknownAge",
brain_region="UnknownBrainArea")
report =\
CircuitAnalysisReport(
author=Author.anonymous,
phenomenon="unknown",
abstract="""
This is an abstract.
""",
introduction="""
This is an introduction.
A single paragraph can have lines ending in at most a single endline
marker. If you insert two line breaks, such as follows
a new paragraph should start...
""",
measurement=measurement,
figures={
"random_walk_1": Figure(
figure,
caption="""
Random Walk
================
Each random walk step size is uniformly drawn from [0, 1).
The individual steps are added up cummulatively to obtain
the location of the walk at a given time.
""")},
methods="""
Describe how.
""",
results="""
Test results are good.
""",
discussion="""
No need to discuss.
""",
references={"xyz": "https://www.xxx.yyy.zzz/qqq"},
provenance_model=provenance)
reporter =\
CheetahReporter(
path_output_folder=os.path.join(
os.getcwd(), "random_walks"))
path_report =\
reporter.post(report)
return\
Record(
provenance=provenance,
report=report,
reporter=reporter,
path_report=path_report)