Error “The linesearch algorithm failed with too small a step.” in sensitivitiy analysis. #4678
Comments
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I also tried the .factory function of casadi to calculate the sensitivity, similar to casadi/casadi#2517. Briefly integrator_fwd_p = integrator.factory("F_fwd", ['x0', 'z0', 'p', 'fwd:p'], ['fwd:xf'])
casadi_sol_fwd_p = integrator_fwd_p(x0=y0_diff, z0=y0_alg, p=inputs_with_tmin, fwd_p=[1, 0, 0])Similar error "The linesearch algorithm failed with too small a step." and another "Newton/Linesearch algorithm failed to converge." raised for "safe" and "fast" mode. Following is the error when "fast" mode set. F:\Anaconda\envs\PyBaMM_env\python.exe F:\PyBaMM\experiment.py
Newton/Linesearch algorithm failed to converge.
Function fsens1_F (0x20926946a60)
Input 0 (x0):
[[0, 0],
[0, 0],
[0.81, 0],
...,
[0.426, 0],
[0.426, 0],
[0.426, 0]]
Input 1 (z0):
[[-9.86656e-08, 0],
[-2.86168e-07, 0],
[-4.6384e-07, 0],
[-6.31682e-07, 0],
[-7.89691e-07, 0],
[-9.37865e-07, 0],
[-1.0762e-06, 0],
[-1.2047e-06, 0],
[-1.32335e-06, 0],
[-1.43215e-06, 0],
[-1.5311e-06, 0],
[-1.62019e-06, 0],
[-1.69941e-06, 0],
[-1.76876e-06, 0],
[-1.82823e-06, 0],
[-1.87781e-06, 0],
[-1.91749e-06, 0],
[-1.94727e-06, 0],
[-1.96713e-06, 0],
[-1.97707e-06, 0],
[-0.08144, 0],
[-0.0814562, 0],
[-0.0814883, 0],
[-0.0815361, 0],
[-0.0815997, 0],
[-0.0816789, 0],
[-0.0817738, 0],
[-0.0818844, 0],
[-0.0820108, 0],
[-0.0821533, 0],
[-0.082312, 0],
[-0.0824873, 0],
[-0.0826795, 0],
[-0.082889, 0],
[-0.0831164, 0],
[-0.083362, 0],
[-0.0836266, 0],
[-0.0839108, 0],
[-0.0842154, 0],
[-0.0845411, 0],
[-0.0744532, 0],
[-0.0744559, 0],
[-0.0744612, 0],
[-0.0744691, 0],
[-0.0744796, 0],
[-0.0744928, 0],
[-0.0745087, 0],
[-0.0745271, 0],
[-0.0745483, 0],
[-0.074572, 0],
[-0.0745984, 0],
[-0.0746275, 0],
[-0.0746592, 0],
[-0.0746935, 0],
[-0.0747306, 0],
[-0.0747702, 0],
[-0.0748125, 0],
[-0.0748575, 0],
[-0.0749052, 0],
[-0.0749555, 0],
[-0.0749938, 0],
[-0.0750217, 0],
[-0.0750495, 0],
[-0.0750774, 0],
[-0.0751053, 0],
[-0.0751331, 0],
[-0.075161, 0],
[-0.0751889, 0],
[-0.0752168, 0],
[-0.0752446, 0],
[-0.0752725, 0],
[-0.0753004, 0],
[-0.0753282, 0],
[-0.0753561, 0],
[-0.075384, 0],
[-0.0754118, 0],
[-0.0754397, 0],
[-0.0754676, 0],
[-0.0754955, 0],
[-0.0755233, 0],
[-0.0755843, 0],
[-0.0756766, 0],
[-0.0757645, 0],
[-0.075848, 0],
[-0.0759271, 0],
[-0.0760019, 0],
[-0.0760723, 0],
[-0.0761383, 0],
[-0.0761999, 0],
[-0.0762571, 0],
[-0.0763097, 0],
[-0.0763578, 0],
[-0.0764011, 0],
[-0.0764396, 0],
[-0.0764731, 0],
[-0.0765015, 0],
[-0.0765247, 0],
[-0.0765424, 0],
[-0.0765544, 0],
[-0.0765606, 0]]
Input 2 (p):
[[3e-15, 1],
[5.9e-13, 0],
[0, 0]]
Input 3 (u): 0x2
Input 4 (adj_xf): 0x0
Input 5 (adj_zf): 0x0
Input 6 (adj_qf): 0x0
Function fwd1_F (0x20926a68db0)
Input 0 (x0): [0, 0, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 0.81, 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0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.0038, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.36, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426, 0.426]
Input 1 (z0): [-9.86656e-08, -2.86168e-07, -4.6384e-07, -6.31682e-07, -7.89691e-07, -9.37865e-07, -1.0762e-06, -1.2047e-06, -1.32335e-06, -1.43215e-06, -1.5311e-06, -1.62019e-06, -1.69941e-06, -1.76876e-06, -1.82823e-06, -1.87781e-06, -1.91749e-06, -1.94727e-06, -1.96713e-06, -1.97707e-06, -0.08144, -0.0814562, -0.0814883, -0.0815361, -0.0815997, -0.0816789, -0.0817738, -0.0818844, -0.0820108, -0.0821533, -0.082312, -0.0824873, -0.0826795, -0.082889, -0.0831164, -0.083362, -0.0836266, -0.0839108, -0.0842154, -0.0845411, -0.0744532, -0.0744559, -0.0744612, -0.0744691, -0.0744796, -0.0744928, -0.0745087, -0.0745271, -0.0745483, -0.074572, -0.0745984, -0.0746275, -0.0746592, -0.0746935, -0.0747306, -0.0747702, -0.0748125, -0.0748575, -0.0749052, -0.0749555, -0.0749938, -0.0750217, -0.0750495, -0.0750774, -0.0751053, -0.0751331, -0.075161, -0.0751889, -0.0752168, -0.0752446, -0.0752725, -0.0753004, -0.0753282, -0.0753561, -0.075384, -0.0754118, -0.0754397, -0.0754676, -0.0754955, -0.0755233, -0.0755843, -0.0756766, -0.0757645, -0.075848, -0.0759271, -0.0760019, -0.0760723, -0.0761383, -0.0761999, -0.0762571, -0.0763097, -0.0763578, -0.0764011, -0.0764396, -0.0764731, -0.0765015, -0.0765247, -0.0765424, -0.0765544, -0.0765606]
Input 2 (p): [3e-15, 5.9e-13, 0]
Input 3 (u): 0x1
Input 4 (adj_xf): 0x0
Input 5 (adj_zf): 0x0
Input 6 (adj_qf): 0x0
Input 7 (out_xf): [00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00]
Input 8 (out_zf): [00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00, 00]
Input 9 (out_qf): 0x1
Input 10 (out_adj_x0): 0x0
Input 11 (out_adj_z0): 0x0
Input 12 (out_adj_p): 0x0
Input 13 (out_adj_u): 0x0
Input 14 (fwd_x0): [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
Input 15 (fwd_z0): [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
Input 16 (fwd_p): [1, 0, 0]
Input 17 (fwd_u): 0x1
Input 18 (fwd_adj_xf): 0x0
Input 19 (fwd_adj_zf): 0x0
Input 20 (fwd_adj_qf): 0x0
2024-12-16 00:56:46.732 - [ERROR] callbacks.on_experiment_error(233): Simulation error: Error in Function::call for 'F_fwd' [MXFunction] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F_fwd' [MXFunction] at .../casadi/core/function.cpp:361:
Error in Function::operator() for 'fwd1_F' [MXFunction] at .../casadi/core/function.cpp:1513:
Error in Function::operator() for 'fsens1_F' [IdasInterface] at .../casadi/core/function.cpp:1513:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_CONV_FAIL". Consult IDAS documentation.
Traceback (most recent call last):
File "F:\PyBaMM\pybamm\solvers\casadi_solver.py", line 686, in _run_integrator
casadi_sol_fwd_p = integrator_fwd_p(x0=y0_diff, z0=y0_alg, p=inputs_with_tmin, fwd_p=[1, 0, 0])
File "F:\Anaconda\envs\PyBaMM_env\lib\site-packages\casadi\casadi.py", line 23531, in __call__
return self.call(kwargs)
File "F:\Anaconda\envs\PyBaMM_env\lib\site-packages\casadi\casadi.py", line 20180, in call
return _casadi.Function_call(self, *args)
RuntimeError: Error in Function::call for 'F_fwd' [MXFunction] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F_fwd' [MXFunction] at .../casadi/core/function.cpp:361:
Error in Function::operator() for 'fwd1_F' [MXFunction] at .../casadi/core/function.cpp:1513:
Error in Function::operator() for 'fsens1_F' [IdasInterface] at .../casadi/core/function.cpp:1513:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_CONV_FAIL". Consult IDAS documentation.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "F:\PyBaMM\experiment.py", line 40, in <module>
solution = sim.solve(inputs=inputs)
File "F:\PyBaMM\pybamm\simulation.py", line 778, in solve
raise error
File "F:\PyBaMM\pybamm\simulation.py", line 754, in solve
step_solution = solver.step(
File "F:\PyBaMM\pybamm\solvers\base_solver.py", line 1374, in step
solution = self._integrate(model, t_eval, model_inputs, t_interp)
File "F:\PyBaMM\pybamm\solvers\casadi_solver.py", line 169, in _integrate
solution = self._run_integrator(model, model.y0, inputs_dict, inputs, t_eval)
File "F:\PyBaMM\pybamm\solvers\casadi_solver.py", line 692, in _run_integrator
raise pybamm.SolverError(error.args[0]) from error
pybamm.expression_tree.exceptions.SolverError: Error in Function::call for 'F_fwd' [MXFunction] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F_fwd' [MXFunction] at .../casadi/core/function.cpp:361:
Error in Function::operator() for 'fwd1_F' [MXFunction] at .../casadi/core/function.cpp:1513:
Error in Function::operator() for 'fsens1_F' [IdasInterface] at .../casadi/core/function.cpp:1513:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_CONV_FAIL". Consult IDAS documentation.
Process finished with exit code 1 |
Azure-Dreamer
changed the title
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There is no problem when regular solving without sensitivity. |
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Hi @Azure-Dreamer, I'm unsure exactly what you are trying to do, can you please post a MRE or small script that produces the error, so that I can run this locally and see what the problem is? |
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@martinjrobins Thank you for your reply. A simple example for the first situation is like this: import pybamm
import numpy as np
experiment = pybamm.Experiment(["Discharge at 1 C for 10 seconds",])
parameter_values = pybamm.ParameterValues('Prada2013')
parameter_values["Negative electrode diffusivity [m2.s-1]"] = "[input]"
options = {}
model = pybamm.lithium_ion.DFN(options=options)
solver = pybamm.CasadiSolver()
sim = pybamm.Simulation(model, experiment=experiment, parameter_values=parameter_values, solver=solver)
inputs = {"Negative electrode diffusivity [m2.s-1]": 3e-15,}
t_eval = np.linspace(0, 30, 1000)
sim.solve(t_eval=t_eval, inputs=inputs, calculate_sensitivities=True)which outputs F:\Anaconda\envs\PyBaMM_env\python.exe F:\PyBaMM_2\experiment.py
2024-12-18 00:11:13.787 - [WARNING] simulation.solve(556): Ignoring t_eval as solution times are specified by the experiment
The linesearch algorithm failed with too small a step.
The linesearch algorithm failed with too small a step.
The linesearch algorithm failed with too small a step.
The linesearch algorithm failed with too small a step.
The linesearch algorithm failed with too small a step.
The linesearch algorithm failed with too small a step.
2024-12-18 00:11:16.296 - [ERROR] callbacks.on_experiment_error(233): Simulation error: Maximum number of decreased steps occurred at t=0.0 (final SolverError: 'Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:361:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_LINESEARCH_FAIL". Consult IDAS documentation.'). For a full solution try reducing dt_max (currently, dt_max=600) and/or reducing the size of the time steps or period of the experiment. Set `return_solution_if_failed_early=True` to return the solution object up to the point where failure occured.
Traceback (most recent call last):
File "F:\PyBaMM_2\pybamm\solvers\casadi_solver.py", line 678, in _run_integrator
casadi_sol = integrator(
File "F:\Anaconda\envs\PyBaMM_env\lib\site-packages\casadi\casadi.py", line 23531, in __call__
return self.call(kwargs)
File "F:\Anaconda\envs\PyBaMM_env\lib\site-packages\casadi\casadi.py", line 20180, in call
return _casadi.Function_call(self, *args)
RuntimeError: Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:361:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_LINESEARCH_FAIL". Consult IDAS documentation.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "F:\PyBaMM_2\pybamm\solvers\casadi_solver.py", line 245, in _integrate
current_step_sol = self._run_integrator(
File "F:\PyBaMM_2\pybamm\solvers\casadi_solver.py", line 684, in _run_integrator
raise pybamm.SolverError(error.args[0]) from error
pybamm.expression_tree.exceptions.SolverError: Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:361:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_LINESEARCH_FAIL". Consult IDAS documentation.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "F:\PyBaMM_2\experiment.py", line 70, in <module>
sim.solve(t_eval=t_eval, inputs=inputs, calculate_sensitivities=True)
File "F:\PyBaMM_2\pybamm\simulation.py", line 779, in solve
raise error
File "F:\PyBaMM_2\pybamm\simulation.py", line 755, in solve
step_solution = solver.step(
File "F:\PyBaMM_2\pybamm\solvers\base_solver.py", line 1364, in step
solution = self._integrate(model, t_eval, model_inputs, t_interp)
File "F:\PyBaMM_2\pybamm\solvers\casadi_solver.py", line 282, in _integrate
raise pybamm.SolverError(
pybamm.expression_tree.exceptions.SolverError: Maximum number of decreased steps occurred at t=0.0 (final SolverError: 'Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:1432:
Error in Function::call for 'F' [IdasInterface] at .../casadi/core/function.cpp:361:
.../casadi/interfaces/sundials/idas_interface.cpp:596: IDACalcIC returned "IDA_LINESEARCH_FAIL". Consult IDAS documentation.'). For a full solution try reducing dt_max (currently, dt_max=600) and/or reducing the size of the time steps or period of the experiment. Set `return_solution_if_failed_early=True` to return the solution object up to the point where failure occured.
Process finished with exit code 1 |
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thanks @Azure-Dreamer. I would use the IDAKLU solver for this, I've tried this and it seemed to work. The sensitivity implementation for the IDAKLU solver uses the sundials library directly and is more reliable and faster than the casadi solver. |
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I'm sorry that I failed with IDAKLU solver. solver = pybamm.CasadiSolver()with solver = pybamm.IDAKLUSolver()and ouput is F:\Anaconda\envs\PyBaMM_env\python.exe F:\PyBaMM_2\experiment_1.py
Traceback (most recent call last):
File "F:\PyBaMM_2\experiment_1.py", line 26, in <module>
solver = pybamm.IDAKLUSolver()
File "F:\PyBaMM_2\pybamm\solvers\idaklu_solver.py", line 236, in __init__
raise ImportError("KLU is not installed")
ImportError: KLU is not installed
Process finished with exit code 1Seems idaklu_spec = importlib.util.find_spec("pybamm.solvers.idaklu")is none. I found Saransh-cpp may have noticed this #4630 and done something, and already uninstalled and installed the PyBaMM package (now version 24.11.2). I'm still working on this to find what I missed. |
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Yes, the IDAKLU solver is not yet available with our conda-forge distribution. We do have plans to include it soon enough (please see conda-forge/pybamm-feedstock#65). |
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@Azure-Dreamer The idaklu solver comes with the pypi installation. You can use a virtual environment to install pybamm: Linux/Mac virtualenv .venv
source .venv/bin/activate
pip install pybammThat should let you use |
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Thank you pybamm team for your great work, and I would be grateful if you can provide some help with the following problem.
I tried to calculate the sensitivity applying the "explicit sensitivity calculation" function.
I created a new parameter class and put both negative and positive particle diffusivities into it, then processed it into InputParameter class during discretization. Everything is fine until solving. The solver usually raised error “The linesearch algorithm failed with too small a step.” when I chose "fast", "fast with events" and "safe" as the casadisolve "mode" argument. I tried
At present the only situation that solver didn't raise the error "The linesearch ..." is only sensitivity of Negative particle diffusivity is calculated and the simulation time is set as 0.1s. However, another error raised which seems not by solver:
I will post the error in the last of this issue, and thank you team for your work. If possible, please help me with it. I will also post it in PyBaMM Discourse.
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