def _grow(self, tolerance=0.2):
"""
A single grid is iteratively inflated, and the top 20% of neighbouring grid points added until the volume
is with the tolerance of the target volume.
:param float tolerance: allowable error in volume extraction
:return float: threshold
"""
self.best_island = self._single_grid.common_boundaries(
self.best_island)
current_num_gp = self.best_island.count_grid()
f = 0
while f < 100 and abs(
((self.settings._num_gp - current_num_gp) / self.settings._num_gp
)) > tolerance and self.settings._num_gp >= current_num_gp:
grown = Grid.grow(self.best_island, self.single_grid)
self.best_island = grown
current_num_gp = self.best_island.count_grid()
print(current_num_gp, 'out of', self.settings._num_gp)
f += 1
tmp_best_island = self.best_island * self.single_grid
g_vals = tmp_best_island.grid_values()
g_vals[::-1].sort()
try:
threshold = g_vals[self.settings._num_gp]
except IndexError:
threshold = min(g_vals)
# assert abs(((self.settings._num_gp - current_num_gp) / self.settings._num_gp)) < tolerance
return threshold
def _grow(self):
"""
A single grid is iteratively inflated, and the top 20% of neighbouring grid points added until the volume
is with the tolerance of the target volume.
:param float tolerance: allowable error in volume extraction
:return float: threshold
"""
self.best_island = self._single_grid.common_boundaries(
self.best_island)
self.second_best_island = self._single_grid.common_boundaries(
self.second_best_island)
current_num_gp = self.best_island.count_grid()
f = 0
for f in range(0, 10):
if self.settings._num_gp <= current_num_gp:
break
grown = Grid.grow(self.best_island, self.second_best_island)
self.best_island = self._remove_protein_vol(grown)
old_num_gp = current_num_gp
current_num_gp = self.best_island.count_grid()
print(current_num_gp, 'out of', self.settings._num_gp)
growth = current_num_gp - old_num_gp
if growth == 0:
break
tmp_best_island = (self.best_island > 0.5) * (self._single_grid)
g_vals = tmp_best_island.grid_values()
g_vals[::-1].sort()
print(len(g_vals))
print(self.settings._num_gp)
try:
threshold = g_vals[self.settings._num_gp]
except IndexError:
threshold = min(g_vals)
return threshold
