def test05_plot(self):
path = site.getsitepackages()[0] + '/SPHARM/tests/'
fn = path + 'data/synthetic_cell.txt'
surf = Surface(filename=fn)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
mesh = surf.plot_points()
os.makedirs('data/test_data')
mesh.save('data/test_data/points_3D.png', size=(200, 200))
surf.centrate()
surf.to_spherical()
surf.Rgrid = surf.interpolate(grid_size=100)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
mesh = surf.plot_surface(points=False)
mesh.save('data/test_data/surface_3D.png', size=(200, 200))
with warnings.catch_warnings():
warnings.simplefilter("ignore")
mesh = surf.plot_surface(points=True)
mesh.save('data/test_data/surface_with_points_3D.png',
size=(200, 200))
self.assertEqual(os.path.exists('data/test_data/surface_3D.png'), True)
self.assertEqual(os.path.exists('data/test_data/points_3D.png'), True)
self.assertEqual(
os.path.exists('data/test_data/surface_with_points_3D.png'), True)
shutil.rmtree('data/test_data/')
def plot_3D_surfaces(inputfolder, outputfolder, points=True, gridsize=100):
"""
Plot 3D views of surfaces located in a given directory.
Parameters
----------
inputfolder : str
Input directory with surfaces.
outputfolder : str
Output directory to save the plots.
points : bool, optional
If True, surface points will be displayed.
Default is True.
gridsize : int, optional
Dimension of the square grid to interpolate the surface points.
Default is 100.
"""
files = filelib.list_subfolders(inputfolder, extensions=['csv'])
for fn in files:
s = Surface(filename=inputfolder + fn)
s.centrate()
s.to_spherical()
s.Rgrid = s.interpolate(grid_size=gridsize)
mesh = s.plot_surface(points=points)
mesh.magnification = 3
filelib.make_folders([os.path.dirname(outputfolder + fn[:-4])])
mesh.save(outputfolder + fn[:-4] + '.png', size=(200, 200))
def plot_inverse_shapes(inputfile, outputfolder, group='Group'):
"""
Plot average cells shapes obtained by inverse SPHARM.
Parameters
----------
inputfile : str
Path to the file with spectral data.
outputfolder : str
Directory to save the plotted distributions.
group : str, optional
Column in the input data sheet to use for grouping.
Default is 'Group'.
"""
filelib.make_folders([os.path.dirname(outputfolder)])
stat = pd.read_csv(inputfile, sep='\t', index_col=0)
stat['value'] = stat['real'] + stat['imag']*1j
if 'Group' not in stat.columns:
for name in stat['Name'].unique():
group = name.split('/')[0]
stat = stat.set_value(stat[stat['Name'] == name].index, 'Group', group)
data = stat.groupby(['degree', 'order', 'Group']).mean().reset_index()
groups = data[group].unique()
for gr in groups:
curdata = data[data[group] == gr]
sp = Spectrum()
sp.harmonics_csv = curdata
sp.convert_to_shtools_array()
surf = Surface()
surf.spharm = sp
maxdegree = np.max(sp.harmonics_csv['degree'])
for lmax in np.arange(5, maxdegree + 1, 5):
surf.inverse_spharm(lmax=lmax)
surf.plot_surface(points=False).save(outputfolder + '_' + gr + '_inverse_lmax=' + str(lmax) + '.png',
size=(200, 200))
surf.inverse_spharm(lmax=None)
surf.plot_surface(points=False).save(outputfolder + '_' + gr + '_inverse_full.png',
size=(200, 200))
def test07_spharm_inverse_less(self):
path = site.getsitepackages()[0] + '/SPHARM/tests/'
fn = path + 'data/synthetic_cell.txt'
surf = Surface(filename=fn)
surf.centrate()
surf.to_spherical()
surf.compute_spharm(grid_size=100)
surf.inverse_spharm()
os.makedirs('data/test_data')
with warnings.catch_warnings():
warnings.simplefilter("ignore")
surf.plot_surface(points=True).save(
'data/test_data/surface_inverse_all.png', size=(200, 200))
surf.inverse_spharm(lmax=30)
surf.plot_surface(points=True).save(
'data/test_data/surface_inverse_30.png', size=(200, 200))
surf.inverse_spharm(lmax=10)
surf.plot_surface(points=True).save(
'data/test_data/surface_inverse_10.png', size=(200, 200))
self.assertEqual(
os.path.exists('data/test_data/surface_inverse_all.png'), True)
self.assertEqual(
os.path.exists('data/test_data/surface_inverse_30.png'), True)
self.assertEqual(
os.path.exists('data/test_data/surface_inverse_10.png'), True)
shutil.rmtree('data/test_data/')
files = os.listdir(path + 'surfaces/' + gr + '/')
for fn in files:
stat = pd.read_csv(path + 'surfaces/' + gr + '/' + fn, sep='\t', index_col=0)
t1 = stat['Time'].unique()[0]
stat = stat[stat['Time'] == t1]
print(fn, len(stat))
surface = Surface(data=stat)
mesh = surface.plot_points(scale_factor=0.2)
filelib.make_folders([os.path.dirname(path + 'surface_plots/' + gr + '_' + fn[:-4])])
mesh.save(path + 'surface_plots/' + gr + '_' + fn[:-4] + '_init.png', size=(100, 100))
mlab.clf()
surface.centrate()
surface.to_spherical()
surface.compute_spharm(grid_size=120, normalize=True)
mesh = surface.plot_surface(points=False)
filelib.make_folders([os.path.dirname(path + 'surface_plots/' + gr + '_' + fn[:-4])])
mesh.save(path + 'surface_plots/' + gr + '_' + fn[:-4] + '_grid.png', size=(100, 100))
mlab.clf()
surface.inverse_spharm(lmax=10)
mesh = surface.plot_surface(points=False)
filelib.make_folders([os.path.dirname(path + 'surface_plots/' + gr + '_' + fn[:-4])])
mesh.save(path + 'surface_plots/' + gr + '_' + fn[:-4] + '_inverse_lmax=10.png', size=(100, 100))
mlab.clf()
surface.inverse_spharm(lmax=None)
mesh = surface.plot_surface(points=False)
filelib.make_folders([os.path.dirname(path + 'surface_plots/' + gr + '_' + fn[:-4])])
mesh.save(path + 'surface_plots/' + gr + '_' + fn[:-4] + '_inverse.png', size=(100, 100))
mlab.clf()