def process(self, timestep=1):
'''
Processes the surface depending whether par.ETCHING is set or not.
When the initialTime is specified
par.ETCHING = True -> etching
par.ETCHING = False-> Sputtern
When a file is specified, the process is written to a file after each step.
>>>surface.process(time, step)
'''
if par.ETCHING:
vn = par.ETCH_RATE
else:
vn = sputterVelocity(self)
assert len(vn) > 0, 'Error: vn could not be calculated!'
self.movePointsByDirection(vn*timestep)
if not par.NUMPY:
#Umwandlung da delopping ein Liste für korrekte Funktion braucht, wenn par.NUMPY=False
self.xvals, self.yvals = np.array(deloop(list(self.xvals), list(self.yvals)))
else:
self.xvals, self.yvals = deloop(self.xvals, self.yvals)
#Berechne neue Winkelsymmetralen für die neuen x & y werte
self.xs, self.ys = anglebisect(self.xvals, self.yvals)
#Falls die Funktion Adaptive Gitter erwünscht ist, passe Knoten (und Winkelsymmetralen) an
if par.ADAPTIVE_GRID:
adapt(self)
def __init__(self):
interval_start = par.XMIN
interval_end = par.XMAX
period = interval_start - interval_end
assert period != 0, 'Error period is 0.'
interval_step = par.DELTA_X
amplitudePP = par.FUN_PEAK_TO_PEAK
self.surfaceType = par.INITIAL_SURFACE_TYPE
self.surfaceFile = par.INITIAL_SURFACE_FILE
#arange() creates a half-open interval, which excludes the endpoint
self.xvals = np.arange(interval_start, interval_end + interval_step, interval_step)
self.yvals = np.zeros_like(self.xvals)
func = functions.default
if par.INITIAL_SURFACE_TYPE == 'Cosine':
func = functions.cosine
elif par.INITIAL_SURFACE_TYPE == 'DoubleCosine':
func = functions.doubleCosine
elif par.INITIAL_SURFACE_TYPE == 'Step':
func = functions.step
elif par.INITIAL_SURFACE_TYPE == 'V-Shape':
func = functions.vShape
for i, x in enumerate(self.xvals):
self.yvals[i] = amplitudePP * (1 + func(x * 2*pi / period) )
#Berechne Winkelsymmetralen
self.xs, self.ys = anglebisect(self.xvals, self.yvals)
#Falls Adaptives Grid gewünscht, passe Werte an
if par.ADAPTIVE_GRID:
adapt(self)
def adapt_grid(self, method='linear'):
"""Adapts surface so that the distance of adjacent points is not too
large or too small (as defined by MAX_SEGLEN) and angles between normal
vectors of adjacent knots do not exceed MAX_ANGLE.
method : str, optional
Method of
Possible values are 'linear', 'quadratic'. 'cubic' """
x, y = self.vertices
# Check if x-values are monotonically increasing
if np.any(x[1:] - x[:-1] < 0):
print('Error: X-Values are not monotonically increasing!')
sys.exit()
# Check if the segments are too short and remove knot if so
max_angle = np.deg2rad(par.MAX_ANGLE)
status = True
while (status):
dx = x[2:] - x[:-2]
dy = y[2:] - y[:-2]
double_seglen = np.hypot(dx, dy)
remove_indices, = np.where(double_seglen < par.MAX_SEGLEN)
if remove_indices.size == 0:
break
for remove_index in remove_indices:
if abs(self.angles[remove_index + 2] -
self.angles[remove_index]) < max_angle:
x = np.delete(x, remove_index + 1)
y = np.delete(y, remove_index + 1)
self.vertices = np.array((x, y))
self.__directions()
break
else:
status = False
plt.plot(x, y, 'b+')
# Check if the segments are too long and insert knot if so
dx = x[1:] - x[:-1]
dy = y[1:] - y[:-1]
seglen = np.hypot(dx, dy)
long_seg_index, = np.where(seglen > par.MAX_SEGLEN)
if long_seg_index.size > 0:
split_value = seglen[long_seg_index] / par.MAX_SEGLEN
split_value = np.ceil(split_value)
f = interpolate.interp1d(x, y, method)
index_insert = list()
x_insert = list()
for i in range(long_seg_index.size):
index_local = long_seg_index[i]
index_new = np.ones(split_value[i] - 1) * (index_local + 1)
index_insert.append(index_new)
x_new = np.linspace(x[index_local],
x[index_local + 1],
num=split_value[i],
endpoint=False)
x_insert.append(x_new[1:])
x_insert = np.hstack(x_insert)
y_insert = f(x_insert)
index_insert = np.hstack(index_insert)
x = np.insert(x, index_insert, x_insert)
y = np.insert(y, index_insert, y_insert)
self.vertices = np.array((x, y))
self.__directions()
# Check if angle between normal vectors of adjacent knots is too large
# and insert additional knots (same coordinates, different normal vec)
x, y = self.vertices
nvx, nvy = self.directions
# Calculate angles between segments
dx = x[1:] - x[:-1]
dy = y[1:] - y[:-1]
seglen = np.hypot(dx, dy)
seg_angles_diff = dx[:-1] * dx[1:] + dy[:-1] * dy[1:]
seg_angles_diff /= (seglen[:-1] * seglen[1:])
seg_angles_diff = np.clip(seg_angles_diff, -1., 1.)
seg_angles_diff = np.arccos(seg_angles_diff)
max_angle = np.deg2rad(par.MAX_ANGLE)
large_angles, = np.where(seg_angles_diff > max_angle)
if large_angles.size > 0:
index_insert = list()
x_insert = list()
y_insert = list()
nvx_insert = list()
nvy_insert = list()
for i in range(large_angles.size):
index_local = large_angles[i]
delta_angle_left = self.angles[index_local +
1] - self.angles[index_local]
local_split = np.ceil(abs(delta_angle_left / max_angle))
local_split = int(local_split)
rot_angle = delta_angle_left / local_split
nvx_new = list()
nvy_new = list()
for k in range(local_split):
nvx_local = nvx[index_local] * np.cos(k * rot_angle)
nvx_local -= nvy[index_local] * np.sin(k * rot_angle)
nvy_local = nvx[index_local] * np.sin(k * rot_angle)
nvy_local += nvy[index_local] * np.cos(k * rot_angle)
nvx_new.append(nvx_local)
nvy_new.append(nvy_local)
index_new = np.array(np.ones(local_split) * index_local + 1,
dtype=int)
index_insert.append(index_new)
x_new = np.ones(local_split) * x[index_local + 1]
x_insert.append(x_new)
y_new = np.ones(local_split) * y[index_local + 1]
y_insert.append(y_new)
nvx_insert.append(nvx_new)
nvy_insert.append(nvy_new)
delta_angle_right = self.angles[index_local +
2] - self.angles[index_local + 1]
local_split = np.ceil(abs(delta_angle_right / max_angle))
local_split = int(local_split)
rot_angle = delta_angle_right / local_split
nvx_new = list()
nvy_new = list()
for k in range(1, local_split + 1):
nvx_local = nvx[index_local + 1] * np.cos(k * rot_angle)
nvx_local -= nvy[index_local + 1] * np.sin(k * rot_angle)
nvy_local = nvx[index_local + 1] * np.sin(k * rot_angle)
nvy_local += nvy[index_local + 1] * np.cos(k * rot_angle)
nvx_new.append(nvx_local)
nvy_new.append(nvy_local)
index_new = np.array(np.ones(local_split) * index_local + 2,
dtype=int)
index_insert.append(index_new)
x_new = np.ones(local_split) * x[index_local + 1]
x_insert.append(x_new)
y_new = np.ones(local_split) * y[index_local + 1]
y_insert.append(y_new)
nvx_insert.append(nvx_new)
nvy_insert.append(nvy_new)
x_insert = np.hstack(x_insert)
y_insert = np.hstack(y_insert)
nvx_insert = np.hstack(nvx_insert)
nvy_insert = np.hstack(nvy_insert)
index_insert = np.hstack(index_insert)
x = np.insert(x, index_insert, x_insert)
y = np.insert(y, index_insert, y_insert)
nvx = np.insert(nvx, index_insert, nvx_insert)
nvy = np.insert(nvy, index_insert, nvy_insert)
self.vertices = np.array((x, y))
self.directions = np.array((nvx, nvy))
self.angles = np.arctan(
(self.directions[0] / (-1 * self.directions[1])))
#Berechne Winkelsymmetralen
self.xs, self.ys = anglebisect(self.xvals, self.yvals)
#Falls Adaptives Grid gewünscht, passe Werte an
if par.ADAPTIVE_GRID:
adapt(self)
#Berechne neue Winkelsymmetralen für die neuen x & y werte
self.xs, self.ys = anglebisect(self.xvals, self.yvals)
#Falls die Funktion Adaptive Gitter erwünscht ist, passe Knoten (und Winkelsymmetralen) an
if par.ADAPTIVE_GRID:
adapt(self)
