Write STL_File from Matplotlib Mesh - numpy

Question

My program works with matplotlib and calculates envelopes in y-z-section. This can be done for several sections and will be plotted as a 3dplot in a diagram. It is also quite easy to show an envelopes with a wireframe design.
Now i want to write a stl-file. For this i need to have a mesh. I have found a module its named numpy-stl that provides these functionality but i need to create the mesh.
Now i have found out that matplotlib has already included the functionality of creation a mesh.
Has someone experiences with this? Here is my code so far. Data comes from dictionary in the form: {'X' : {'Y' : [], 'Z' : []}}.
def lines_draw(self):
self.plot_data.clear()
self.plot_data = publish('3D_DATA_PLOT')
self.plot_Handling = []
a = []
x_keys = []
x_keys_collect1 = []
x_keys_collect2 = []
#print(self.plot_data)
_big_list_X = []
_big_list_Y = []
_big_list_Z = []
big_list_X = []
big_list_Y = []
big_list_Z = []
# Draw the section-lines
for key,val in self.plot_data.items():
a.clear()
for i in range(len(self.plot_data[key]['Y'])):
a.append(key)
x = np.array(a)
y = np.array(self.plot_data[key]['Y'])
z = np.array(self.plot_data[key]['Z'])
x = x.astype(np.float)
y = y.astype(np.float)
z = z.astype(np.float)
linesdraw, = self.ax.plot(x,y,z)
self.plot_Handling.append(linesdraw)
x_keys = list(self.plot_data)
dict_length = len(x_keys)
a=1
# Draw the wireframes
for i in range(dict_length-1):
x_keys_collect1.clear()
x_keys_collect2.clear()
for xi in self.plot_data[x_keys[i]]['Y']:
x_keys_collect1.append(x_keys[i])
a = a + 1
for xi in self.plot_data[x_keys[i+1]]['Y']:
x_keys_collect2.append(x_keys[i+1])
x1 = np.array(x_keys_collect1)
y1 = np.array(self.plot_data[x_keys[i]]['Y'])
z1 = np.array(self.plot_data[x_keys[i]]['Z'])
x2 = np.array(x_keys_collect2)
y2 = np.array(self.plot_data[x_keys[i+1]]['Y'])
z2 = np.array(self.plot_data[x_keys[i+1]]['Z'])
x1 = x1.astype(np.float)
y1 = y1.astype(np.float)
z1 = z1.astype(np.float)
x2 = x2.astype(np.float)
y2 = y2.astype(np.float)
z2 = z2.astype(np.float)
# i1, h1 = np.meshgrid(np.arange(a-1), np.linspace(x1[0],x2[0],5))
# print(np.linspace(x1[0],x2[0],5))
# i1 = i1.astype(np.int)
# h1 = h1.astype(np.int)
# X = (y2[i1] - y1[i1]) / (x2 - x1) * (h1 - x1) + y1[i1]
# Y = (z2[i1] - z1[i1]) / (x2 - x1) * (h1 - x1) + z1[i1]
# self.ax.plot_surface(h1,X, Y, color='m', alpha=0.3, linewidth=0)
# y1 = -y1.astype(np.float)
# y2 = -y2.astype(np.float)
# i1, h1 = np.meshgrid(np.arange(a-1), np.linspace(x1[0],x2[0],5))
# i1 = i1.astype(np.int)
# h1 = h1.astype(np.int)
# X = (y2[i1] - y1[i1]) / (x2 - x1) * (h1 - x1) + y1[i1]
# Y = (z2[i1] - z1[i1]) / (x2 - x1) * (h1 - x1) + z1[i1]
# self.ax.plot_surface(h1,X, Y, color='m', alpha=0.3, linewidth=0)
big_list_X = np.array(x_keys_collect1 + x_keys_collect2)
big_list_Y = np.array(self.plot_data[x_keys[i]]['Y'] + self.plot_data[x_keys[i+1]]['Y'])
big_list_Z = np.array(self.plot_data[x_keys[i]]['Z'] + self.plot_data[x_keys[i+1]]['Z'])
big_list_X = big_list_X.astype(np.float)
big_list_Y = big_list_Y.astype(np.float)
big_list_Z = big_list_Z.astype(np.float)
print(big_list_X)
# print(big_list_Y)
# print(big_list_Z)
# big_list_X, big_list_Z = np.meshgrid(big_list_X,big_list_Z)
# big_list_X, big_list_Z = big_list_X.flatten(), big_list_Z.flatten()
# tri = mtri.Triangulation(_big_list_X,_big_list_Z)
print(big_list_X)
# print(big_list_Y)
# print(big_list_Z)
self.ax.plot_trisurf(big_list_X,big_list_Y,big_list_Z, cmap=cm.jet, linewidth=0)#,triangles=tri.triangles)#,cmap=plt.cm.Spectral)
a = 1
# tri = mtri.Triangulation(X,Y)
# self.ax.plot_trisurf(h1,X,Y,triangles=tri.triangles,cmap=plt.cm.Spectral)
self.canvas.draw()