def check_dict_entries(main_dict=None, other_dict=None):
'''Check if dictionary entry exists in main dictionary.'''
if 'order' in main_dict.keys():
main_keys = main_dict['order']
else:
main_keys = np.sort(list(main_dict.keys()))
main_entries = np.array([main_dict[main_key] for main_key in main_keys])
if 'order' in other_dict.keys():
other_keys = other_dict['order']
else:
other_keys = np.sort(list(other_dict.keys()))
out_key_order = []
new_dict = other_dict.copy()
replaced_keys = []
for ikey, other_key in enumerate(other_keys):
other_entry = new_dict[other_key]
ind_found = pyres_utils.match_xy(main_entries, np.array(other_entry))
if len(ind_found.squeeze()) > 0:
old_key = new_dict.pop(other_key, None)
replaced_keys.append([other_key, main_keys[ind_found[0]]])
out_key_order.append(main_keys[ind_found[0]])
new_dict[main_keys[ind_found[0]]] = main_dict[main_keys[
ind_found[0]]]
else:
out_key_order.append(other_key)
new_dict.update({'order': out_key_order})
return new_dict, replaced_keys
def quad_mesh_region(mesh_xy=[None, None],
target_xypos=None,
target_res=None,
target_firstnrows=None,
region_elem_list=None,
background_res=None):
"""Define quadrilateral mesh region."""
xx_mesh, yy_mesh = mesh_xy
if len(xx_mesh.shape) == 1:
elem_numbering = np.reshape(np.arange(
xx_mesh.shape[0] * yy_mesh.shape[0]),
(yy_mesh.shape[0], xx_mesh.shape[0]),
order='F') + 1
XX, YY = np.meshgrid(xx_mesh, yy_mesh)
else: # 2d mesh coordinates input
elem_numbering = np.reshape(np.arange(
xx_mesh.shape[0] * xx_mesh.shape[1]),
(xx_mesh.shape[0], xx_mesh.shape[1]),
order='F') + 1
XX, YY = np.array(xx_mesh), np.array(yy_mesh)
fill_cols = None
if target_xypos is not None:
all_xy_pairs = np.hstack([XX.reshape((-1, 1)), YY.reshape((-1, 1))])
matched_inds = pyres_utils.match_xy(
XY=all_xy_pairs,
xy_to_match=np.array(target_xypos).astype(float)).squeeze()
unraveled_inds = np.array(np.unravel_index(matched_inds, XX.shape)).T
unique_cols = np.unique(unraveled_inds[:, 1])
fill_cols = np.arange(
unique_cols[0],
unique_cols[-1]) # can have +1 at end to keep last match.
start_end_rows = []
for unq_col in unique_cols:
rows_found = np.sort(unraveled_inds[unraveled_inds[:,
1] == unq_col,
0])
start_end_rows.append([rows_found[0], rows_found[-1]])
start_end_rows = np.array(start_end_rows)
start_rows_fill = np.round(
np.interp(fill_cols, unique_cols, start_end_rows[:, 0]),
0).astype(int)
end_rows_fill = np.round(
np.interp(fill_cols, unique_cols, start_end_rows[:, 1]),
0).astype(int)
elif target_firstnrows is not None:
fill_cols = np.arange(XX.shape[1])
start_rows_fill = np.zeros(XX.shape[1] - 1)
end_rows_fill = target_firstnrows * np.ones(XX.shape[1] - 1)
# Make background element region first
if region_elem_list is None:
# Initialize list with whole domain
region_elem_list = [[
1, int((XX.shape[0] - 1) * (XX.shape[1] - 1)), background_res
]]
# Add other regions if needed
if fill_cols is not None:
for icol, irowstart, irowend in zip(fill_cols, start_rows_fill,
end_rows_fill):
elems_found = np.sort(elem_numbering[irowstart:irowend + 1, icol])
if len(elems_found) > 1:
region_elem_list.append([
elems_found[0] - icol, elems_found[-1] - icol - 1,
target_res
])
else:
region_elem_list.append(
[elems_found[0] - icol, elems_found[0] - icol, target_res])
return region_elem_list