def angle_dd2dcm(angle):
diff = np.append(np.diff(angle), 0)
movement = (np.empty_like(angle)).astype(str)
movement[diff > 0] = "CW"
movement[diff < 0] = "CC"
movement[diff == 0] = "NONE"
converted_angle = np.array(angle, copy=False)
converted_angle[
converted_angle < 0] = converted_angle[converted_angle < 0] + 360
converted_angle = converted_angle.astype(str).tolist()
return converted_angle, movement
def convert_numbers_to_string(name, lookup, column):
dtype = np.array([item for _, item in lookup.items()]).dtype
result = np.empty_like(column).astype(dtype)
result[:] = ""
for i, item in lookup.items():
result[column.values == int(i)] = item
if np.any(result == ""):
print(lookup)
print(np.where(result == ""))
print(column[result == ""].values)
unconverted_entries = np.unique(column[result == ""])
raise Exception(
"The conversion lookup list for converting {} is incomplete. "
"The following data numbers were not converted:\n"
"{}\n"
"Please update the trf2csv conversion script to include these "
"in its definitions.".format(name, unconverted_entries))
return result
def find_relevant_control_points(mu):
"""Returns that control points that had an MU difference either side.
"""
mu_diff = np.diff(mu)
no_change = mu_diff == 0
try:
start = no_change[0]
end = no_change[-1]
except IndexError:
all_true = np.empty_like(mu).astype(bool)
all_true.fill(True)
return all_true
no_change_before = no_change[0:-1]
no_change_after = no_change[1::]
no_change_before_and_after = no_change_before & no_change_after
irrelevant_control_point = np.hstack(
[start, no_change_before_and_after, end])
relevant_control_points = np.invert(irrelevant_control_point)
return relevant_control_points