def produceTrainingSequences(self):
warnings.filterwarnings("ignore", category=DeprecationWarning)
datasetOfGraphSequences = []
clusters = self.generateClusters(self.number_of_generations)
for point_cluster in clusters:
x, y = self.getXandYCoordinatesOfClusterAsNumpyArrays(
point_cluster)
cluster_points, hull_base = self.fillCoordinateArrayAndIndexedPointarrayWithCoordinates(
x, y)
mst = mist.GetMST(x, y)
roots = self.defineRootIndexedPoints(hull_base)
self.createMSTandSTATS(mst, x, y)
edges = self.buildMSTEdgesIndexedPointArray(mst, cluster_points)
rootSortedEdges = self.sortEdgesFromHullpointRootsAndReturnAsArray(
roots, edges)
datasetOfGraphSequences.append(
self.
consolidateAllSequencesToOneDataSetFromAllSortedEdgesOfGraph(
rootSortedEdges))
return datasetOfGraphSequences
def test_get_branch_index_sub_divide_3d_no_box_size():
x = np.random.random_sample(50)
y = np.random.random_sample(50)
z = np.random.random_sample(50)
mst = mist.GetMST(x=x, y=y, z=z)
mst.construct_mst()
mst.get_degree()
mst.get_degree_for_edges()
branch_index, branch_index_rej = mist.get_branch_index(mst.edge_index, mst.edge_degree)
branch_index_sub, branch_index_sub_rej = mist.get_branch_index_sub_divide(2, mst.edge_index, mst.edge_degree,
edge_x=mst.edge_x, edge_y=mst.edge_y, edge_z=mst.edge_z)
assert len(branch_index_sub_rej) == 0
count = 0
for i in range(0, len(branch_index)):
for j in range(0, len(branch_index_sub)):
if np.array_equal(np.array(sorted(branch_index[i])), np.array(sorted(branch_index_sub[j]))) == True:
count += 1
else:
pass
assert count == len(branch_index)
def test_GetMST_init():
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
assert mst._mode == '2D'
z = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y, z=z)
assert mst._mode == '3D'
mst = mist.GetMST(phi=x, theta=y)
assert mst._mode == 'tomographic'
mst = mist.GetMST(phi=x, theta=y, r=z)
assert mst._mode == 'spherical polar'
mst = mist.GetMST(ra=x, dec=y)
assert mst._mode == 'tomographic celestial'
mst = mist.GetMST(ra=x, dec=y, r=z)
assert mst._mode == 'spherical polar celestial'
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 test_GetMST_scal_cut():
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
mst.scale_cut(0.2)
assert mst.scale_cut_length == 0.2
def test_GetMST_branch_edge_count():
mst = mist.GetMST()
mst.branch_index = [[1, 2, 3], [1, 2], [3, 4, 5, 6, 6]]
mst.get_branch_edge_count()
condition = np.where(mst.branch_edge_count == np.array([3, 2, 5]))[0]
assert len(condition) == 3
def test_GetMST_knn():
x = np.random.random_sample(100)
y = np.random.random_sample(100)
mst = mist.GetMST(x=x, y=y)
mst.define_k_neighbours(10)
assert mst.k_neighbours == 10
t = data[:, 3] xmin = x > 6000 xmax = x < 9000 ymin = y > -6000 ymax = y < -3000 zmin = z > 1500 zmax = z < 5000 selection = zmin * zmax * ymin * ymax * xmin * xmax xcut = x[selection] ycut = y[selection] zcut = z[selection] tcut = t[selection] mst = mist.GetMST(x=xcut, y=ycut, z=zcut) d, l, b, s = mst.get_stats() l_index = mst.edge_index b_index = mst.branch_index fig = plt.figure(figsize=(7., 7.)) ax1 = fig.add_subplot(111, projection='3d') # plotting nodes: ax1.scatter(xcut, ycut, zcut, s=10, color='r') # plotting branches: ''' for i in range(len(b_index)):