restore_data refers to P[0] instead of P

[kahilah]

In function restore_data() in onedim.pyx the pressure is restored simply setting
self.P = P[0]

However, prior to that call, P is defined as T, P, Y = states where states is the function argument. If user has created the states by using f.collect_data() function, P is not an array but a float, hence evoking an error TypeError: 'float' object is not subscriptable

Steps to reproduce

import cantera as ct
import numpy as np

# Simulation parameters
p = ct.one_atm  # pressure [Pa]
Tin = 300.0  # unburned gas temperature [K]
reactants = 'H2:1.1, O2:1, AR:5'  # premixed gas composition
width = 0.03  # m
loglevel = 1  # amount of diagnostic output (0 to 8)

# IdealGasMix object used to compute mixture properties, set to the state of the
# upstream fuel-air mixture
gas = ct.Solution('h2o2.xml')
gas.TPX = Tin, p, reactants

# Set up flame object
f = ct.FreeFlame(gas, width=width)
f.set_refine_criteria(ratio=3, slope=0.06, curve=0.12)
f.show_solution()

# Solve with mixture-averaged transport model
f.transport_model = 'Mix'
f.solve(loglevel=loglevel, auto=True)

fdata_tmp = f.collect_data('flame', ['grid'])

f.restore_data('flame', fdata_tmp[0], fdata_tmp[1], fdata_tmp[2])

System information

• Cantera version: development version installed by conda
• OS: Centos 7
• Python 3.8

[ischoegl]

Thanks for this bug report on this recently introduced feature - the main issue is that docstrings are incorrect, i.e. these functions work with tuple arguments, not SolutionArrays; it's certainly true that the observed behavior needs to be fixed also. Overall, these functions are mainly meant as service functions for flame.to_solution_array and flame.from_solution_array. As a work-around, I'd recommend simply using those, i.e.

arr = f.to_solution_array('flame')
f.from_solution_array(arr, 'flame')