def test_plot_limits():
fig1, ax1 = plot_limits(fig, ax)
nt.ok_(ax1.get_xlim() == xlim)
nt.ok_(ax1.get_ylim() == ylim)
fig1, ax1 = plot_limits(fig, ax, xlim=(0, 100), ylim=(-100, 0))
nt.ok_(ax1.get_xlim() == (0, 100))
nt.ok_(ax1.get_ylim() == (-100, 0))
fig2, ax2 = plot_limits(fig0, ax0)
nt.ok_(np.allclose(ax2.get_zlim(), zlim0))
fig2, ax2 = plot_limits(fig0, ax0, zlim=(0, 100))
nt.ok_(np.allclose(ax2.get_zlim(), (0, 100)))
def test_plot_limits():
fig1, ax1 = plot_limits(fig, ax)
nt.ok_(ax1.get_xlim() == xlim)
nt.ok_(ax1.get_ylim() == ylim)
fig1, ax1 = plot_limits(fig, ax, xlim=(0,100), ylim=(-100,0))
nt.ok_(ax1.get_xlim() == (0,100))
nt.ok_(ax1.get_ylim() == (-100,0))
fig2, ax2 = plot_limits(fig0, ax0)
nt.ok_(np.allclose(ax2.get_zlim(), zlim0))
fig2, ax2 = plot_limits(fig0, ax0, zlim=(0,100))
nt.ok_(np.allclose(ax2.get_zlim(), (0,100)))
def main(data_dir, mtype_file): # pylint: disable=too-many-locals
'''Run the stuff'''
# data structure to store results
stuff = load_neurite_features(data_dir)
sim_params = json.load(open(mtype_file))
# load histograms, distribution parameter sets and figures into arrays.
# To plot figures, do
# plots[i].fig.show()
# To modify an axis, do
# plots[i].ax.something()
_plots = []
for feat, d in stuff.items():
for typ, data in d.items():
dist = sim_params['components'][typ].get(feat, None)
print('Type = %s, Feature = %s, Distribution = %s' %
(typ, feat, dist))
# if no data available, skip this feature
if not data:
print("No data found for feature %s (%s)" % (feat, typ))
continue
# print 'DATA', data
num_bins = 100
limits = calc_limits(data, dist)
bin_edges = np.linspace(limits[0], limits[1], num_bins + 1)
histo = np.histogram(data, bin_edges, normed=True)
print('PLOT LIMITS:', limits)
# print 'DATA:', data
# print 'BIN HEIGHT', histo[0]
plot = Plot(*view_utils.get_figure(new_fig=True, subplot=111))
view_utils.plot_limits(plot.fig,
plot.ax,
xlim=limits,
no_ylim=True)
plot.ax.bar(histo[1][:-1], histo[0], width=bin_widths(histo[1]))
dp, bc = dist_points(histo[1], dist)
# print 'BIN CENTERS:', bc, len(bc)
if dp is not None:
# print 'DIST POINTS:', dp, len(dp)
plot.ax.plot(bc, dp, 'r*')
plot.ax.set_title('%s (%s)' % (feat, typ))
_plots.append(plot)
return _plots
def main(data_dir, mtype_file): # pylint: disable=too-many-locals
"""Run the stuff"""
# data structure to store results
stuff = load_neurite_features(data_dir)
sim_params = json.load(open(mtype_file))
# load histograms, distribution parameter sets and figures into arrays.
# To plot figures, do
# plots[i].fig.show()
# To modify an axis, do
# plots[i].ax.something()
_plots = []
for feat, d in stuff.items():
for typ, data in d.items():
dist = sim_params["components"][typ].get(feat, None)
print("Type = %s, Feature = %s, Distribution = %s" % (typ, feat, dist))
# if no data available, skip this feature
if not data:
print("No data found for feature %s (%s)" % (feat, typ))
continue
# print 'DATA', data
num_bins = 100
limits = calc_limits(data, dist)
bin_edges = np.linspace(limits[0], limits[1], num_bins + 1)
histo = np.histogram(data, bin_edges, normed=True)
print("PLOT LIMITS:", limits)
# print 'DATA:', data
# print 'BIN HEIGHT', histo[0]
plot = Plot(*view_utils.get_figure(new_fig=True, subplot=111))
view_utils.plot_limits(plot.fig, plot.ax, xlim=limits, no_ylim=True)
plot.ax.bar(histo[1][:-1], histo[0], width=bin_widths(histo[1]))
dp, bc = dist_points(histo[1], dist)
# print 'BIN CENTERS:', bc, len(bc)
if dp is not None:
# print 'DIST POINTS:', dp, len(dp)
plot.ax.plot(bc, dp, "r*")
plot.ax.set_title("%s (%s)" % (feat, typ))
_plots.append(plot)
return _plots
