def test_PlotHistMST_plot_contour_extra_option():
hmst = mist.HistMST()
hmst.setup()
hmst.start_group()
for i in range(0, 10):
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
d, l, b, s = mst.get_stats()
mst_dict = hmst.get_hist(d, l, b, s)
mst_dict = hmst.end_group()
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(plt_output='close')
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(usebox=False, plt_output='close')
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(xlabels=['a', 'b', 'c', 'd'], plt_output='close')
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(usefraction=True, plt_output='close')
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(usefraction=True, usemean=False, plt_output='close')
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(units=r'^{\circ}', plt_output='close')
def createMSTandSTATS(self, mst, local_x, local_y):
d, l, b, s, l_index, b_index = mst.get_stats(include_index=True)
# begins by binning the data and storing this in a dictionary.
hmst = mist.HistMST()
hmst.setup()
mst_dict = hmst.get_hist(d, l, b, s)
# plotting which takes as input the dictionary created before.
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
def test_PlotHistMST_plot_usebox():
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
d, l, b, s = mst.get_stats()
hmst = mist.HistMST()
hmst.setup()
mst_dict = hmst.get_hist(d, l, b, s)
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot(usebox=False, plt_output='close')
def test_get_hist():
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
d, l, b, s = mst.get_stats()
hmst = mist.HistMST()
hmst.setup()
mst_hist = hmst.get_hist(d, l, b, s)
assert mst_hist['isgroup'] == False
assert len(mst_hist['x_d']) == 6
assert len(mst_hist['y_d']) == 6
assert len(mst_hist['x_l']) == 100
assert len(mst_hist['y_l']) == 100
assert len(mst_hist['x_b']) == 100
assert len(mst_hist['y_b']) == 100
assert len(mst_hist['x_s']) == 50
assert len(mst_hist['y_s']) == 50
def test_end_group():
hmst = mist.HistMST()
hmst.setup()
hmst.start_group()
for i in range(0, 10):
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
d, l, b, s = mst.get_stats()
_mst_hist = hmst.get_hist(d, l, b, s)
mst_hist = hmst.end_group()
assert hmst.group_mode == False
assert mst_hist['isgroup'] == True
assert len(mst_hist['y_d_std']) == 6
assert len(mst_hist['y_l_std']) == 100
assert len(mst_hist['y_b_std']) == 100
assert len(mst_hist['y_s_std']) == 50
def test_PlotHistMST_plot_comparison_envelope():
x_lf, y_lf, z_lf = mist.get_levy_flight(5000)
mst = mist.GetMST(x=x_lf, y=y_lf, z=z_lf)
d_lf, l_lf, b_lf, s_lf = mst.get_stats()
hmst = mist.HistMST()
hmst.setup(uselog=True)
hist_lf = hmst.get_hist(d_lf, l_lf, b_lf, s_lf)
hmst.start_group()
for i in range(0, 10):
x_alf, y_alf, z_alf = mist.get_adjusted_levy_flight(5000)
mst = mist.GetMST(x=x_alf, y=y_alf, z=z_alf)
d_alf, l_alf, b_alf, s_alf = mst.get_stats()
_hist_alf = hmst.get_hist(d_alf, l_alf, b_alf, s_alf)
hist_alf_group = hmst.end_group()
pmst = mist.PlotHistMST()
pmst.read_mst(hist_lf, label='Levy Flight')
pmst.read_mst(hist_alf_group, label='Adjusted Levy Flight')
pmst.plot(usecomp=True, plt_output='close')
def test_PlotHistMST_plot_comparison():
x_lf, y_lf, z_lf = mist.get_levy_flight(5000)
x_alf, y_alf, z_alf = mist.get_adjusted_levy_flight(5000)
mst = mist.GetMST(x=x_lf, y=y_lf, z=z_lf)
d_lf, l_lf, b_lf, s_lf = mst.get_stats()
mst = mist.GetMST(x=x_alf, y=y_alf, z=z_alf)
d_alf, l_alf, b_alf, s_alf = mst.get_stats()
hmst = mist.HistMST()
hmst.setup(uselog=True)
hist_lf = hmst.get_hist(d_lf, l_lf, b_lf, s_lf)
x_alf, y_alf, z_alf = mist.get_adjusted_levy_flight(5000)
mst = mist.GetMST(x=x_alf, y=y_alf, z=z_alf)
d_alf, l_alf, b_alf, s_alf = mst.get_stats()
hist_alf = hmst.get_hist(d_alf, l_alf, b_alf, s_alf)
pmst = mist.PlotHistMST()
pmst.read_mst(hist_lf, label='Levy Flight')
pmst.read_mst(hist_alf, label='Adjusted Levy Flight')
pmst.plot(usecomp=True, plt_output='close')
pmst = mist.PlotHistMST()
pmst.read_mst(hist_lf, label='Levy Flight')
pmst.read_mst(hist_alf, label='Adjusted Levy Flight')
pmst.plot(usebox=False, usecomp=True, plt_output='close')
def test_PlotHistMST_read_mst_uselog():
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
d, l, b, s = mst.get_stats()
hmst = mist.HistMST()
hmst.setup(uselog=True)
mst_hist = hmst.get_hist(d, l, b, s)
pmst = mist.PlotHistMST()
pmst.read_mst(mst_hist,
color='dodgerblue',
linewidth=1.,
linestyle=':',
alpha=0.5,
label='check',
alpha_envelope=0.5)
assert pmst.colors[0] == 'dodgerblue'
assert pmst.linewidths[0] == 1.
assert pmst.linestyles[0] == ':'
assert pmst.alphas[0] == 0.5
assert pmst.labels[0] == 'check'
assert pmst.alphas_envelope[0] == 0.5
assert pmst.need_envelopes[0] == False
assert pmst.use_sqrt_s == True
def plotMSTandSTATS(self, mst, local_x, local_y):
plt.figure(figsize=(8., 5.))
d, l, b, s, l_index, b_index = mst.get_stats(include_index=True)
# plotting nodes:
plt.scatter(local_x, local_y, s=10)
# plotting branches:
for i in range(0, len(b_index)):
plt.plot([
local_x[l_index[0][b_index[i][0]]],
local_x[l_index[1][b_index[i][0]]]
], [
local_y[l_index[0][b_index[i][0]]],
local_y[l_index[1][b_index[i][0]]]
],
color='C0',
linestyle=':')
plt.plot([
local_x[l_index[0][b_index[i][1:-1]]],
local_x[l_index[1][b_index[i][1:-1]]]
], [
local_y[l_index[0][b_index[i][1:-1]]],
local_y[l_index[1][b_index[i][1:-1]]]
],
color='C0')
plt.plot([
local_x[l_index[0][b_index[i][-1]]],
local_x[l_index[1][b_index[i][-1]]]
], [
local_y[l_index[0][b_index[i][-1]]],
local_y[l_index[1][b_index[i][-1]]]
],
color='C0',
linestyle=':')
# ploting MST edges:
plt.plot([local_x[l_index[0]], local_x[l_index[1]]],
[local_y[l_index[0]], local_y[l_index[1]]],
color='grey',
linewidth=2,
alpha=0.25)
plt.plot([], [], color='C0', label=r'$Branch$ $Mid$')
plt.plot([], [], color='C0', label=r'$Branch$ $End$', linestyle=':')
plt.plot([], [], color='grey', alpha=0.25, label=r'$MST$ $Edges$')
plt.xlabel(r'$X$', size=16)
plt.ylabel(r'$Y$', size=16)
plt.legend(loc='best')
plt.tight_layout()
plt.show()
# begins by binning the data and storing this in a dictionary.
hmst = mist.HistMST()
hmst.setup()
mst_dict = hmst.get_hist(d, l, b, s)
# plotting which takes as input the dictionary created before.
pmst = mist.PlotHistMST()
pmst.read_mst(mst_dict)
pmst.plot()
def test_start_group():
hmst = mist.HistMST()
hmst.setup()
hmst.start_group()
assert hmst.group_mode == True