def _getFitParameters(list_of_dicts, key):
# Load rows of data
x = _loadRow('doublingTime', list_of_dicts)
y = _loadRow(key, list_of_dicts)
# Save and strip units
y_units = 1
x_units = 1
if units.hasUnit(y):
y_units = units.getUnit(y)
y = y.asNumber(y_units)
if units.hasUnit(x):
x_units = units.getUnit(x)
x = x.asNumber(x_units)
# Sort data for spine fitting (must be ascending order)
idx_order = x.argsort()
x = x[idx_order]
y = y[idx_order]
# Generate fit
parameters = interpolate.splrep(x, y)
if np.sum(np.absolute(interpolate.splev(x, parameters) - y)) / y.size > 1.:
raise Exception(
"Fitting {} with 3d spline, residuals are huge!".format(key))
return {
'parameters': parameters,
'x_units': x_units,
'y_units': y_units,
'dtype': y.dtype
}
def _loadRow(key, list_of_dicts):
if units.hasUnit(list_of_dicts[0][key]):
row_units = units.getUnit(list_of_dicts[0][key])
return row_units * np.array(
[x[key].asNumber(row_units) for x in list_of_dicts])
else:
return np.array([x[key] for x in list_of_dicts])
def _useFitParameters(x_new, parameters, x_units, y_units, dtype):
# Convert to same unit base
if units.hasUnit(x_units):
x_new = x_new.asNumber(x_units)
elif units.hasUnit(x_new):
raise Exception("New x value has units but fit does not!")
# Calculate new interpolated y value
y_new = interpolate.splev(x_new, parameters)
# If value should be an integer (i.e. an elongation rate)
# round to the nearest integer
if dtype == np.int:
y_new = int(np.round(y_new))
return y_units * y_new
def _field(self, fieldname):
if not units_pkg.hasUnit(self.units[fieldname]):
if self.units[fieldname] == None:
return self.struct_array[fieldname]
else:
raise Exception, 'Field has incorrect units or unitless designation!\n'
else:
return self.units[fieldname] * self.struct_array[fieldname]
def __setitem__(self, key, value):
if units_pkg.hasUnit(value):
try:
self.units[key].matchUnits(value)
except unum.IncompatibleUnitsError:
raise Exception, 'Units do not match!\n'
self.struct_array[key] = value.asNumber()
self.units[key] = units_pkg.getUnit(value)
elif type(value) == list or type(value) == np.ndarray:
if units_pkg.hasUnit(self.units[key]):
raise Exception, 'Units do not match! Quantity has units your input does not!\n'
self.struct_array[key] = value
self.units[key] = None
else:
raise Exception, 'Cant assign data-type other than unum datatype or list/numpy array!\n'