From 0e6e21b6662e37d504989369e4d0f0fdff24f95a Mon Sep 17 00:00:00 2001 From: Harrison Nicholls Date: Mon, 9 Sep 2024 13:05:47 +0200 Subject: [PATCH] Hide runtime warnings from bad initial guess --- src/calliope/solve.py | 57 +++++++++++++++++++++++++------------------ tools/SolveVol.ipynb | 34 ++++---------------------- 2 files changed, 38 insertions(+), 53 deletions(-) diff --git a/src/calliope/solve.py b/src/calliope/solve.py index eec9c7f..43038eb 100644 --- a/src/calliope/solve.py +++ b/src/calliope/solve.py @@ -1,6 +1,7 @@ from __future__ import annotations import logging +import warnings import numpy as np from scipy.optimize import fsolve @@ -359,7 +360,7 @@ def get_target_from_pressures(ddict): return target_d -def equilibrium_atmosphere(target_d, ddict): +def equilibrium_atmosphere(target_d, ddict, hide_warnings=True): """Solves for surface partial pressures assuming melt-vapour eqm @@ -378,30 +379,40 @@ def equilibrium_atmosphere(target_d, ddict): log.info("Solving for equilibrium partial pressures at surface") log.debug(" target masses: %s"%str(target_d)) + # solver parameters count = 0 max_attempts = 7000 ier = 0 - # could in principle result in an infinite loop, if randomising - # the ic never finds the physical solution (but in practice, - # this doesn't seem to happen) - while ier != 1: - x0 = get_initial_pressures(target_d) - sol, info, ier, msg = fsolve(func, x0, args=(ddict, target_d), full_output=True) - count += 1 - - # if any negative pressures, report ier!=1 - if any(sol<0): - # sometimes, a solution exists with negative pressures, which is clearly non-physical. Here, assert we must have positive pressures. - ier = 0 - - # check residuals - this_resid = func(sol, ddict, target_d) - if np.amax(np.abs(this_resid)) > 1.0: - ier = 0 - - # give up after a while - if count > max_attempts: - raise Exception("Could not find solution for volatile abundances (max attempts reached)") + + # do calculation + with warnings.catch_warnings(): + # Suppress warnings from solver, since they are triggered when + # the model makes a poor guess for the composition. These are then discarded, + # so the warning should not propagate anywhere. Errors are still printed. + if hide_warnings: + warnings.filterwarnings("ignore", category=RuntimeWarning) + + # could in principle result in an infinite loop, if randomising + # the ic never finds the physical solution (but in practice, + # this doesn't seem to happen) + while ier != 1: + x0 = get_initial_pressures(target_d) + sol, info, ier, msg = fsolve(func, x0, args=(ddict, target_d), full_output=True) + count += 1 + + # if any negative pressures, report ier!=1 + if any(sol<0): + # sometimes, a solution exists with negative pressures, which is clearly non-physical. Here, assert we must have positive pressures. + ier = 0 + + # check residuals + this_resid = func(sol, ddict, target_d) + if np.amax(np.abs(this_resid)) > 1.0: + ier = 0 + + # give up after a while + if count > max_attempts: + raise Exception("Could not find solution for volatile abundances (max attempts reached)") log.debug(" Initial guess attempt number = %d" % count) @@ -442,8 +453,6 @@ def equilibrium_atmosphere(target_d, ddict): outdict[s+"_bar"] = p_d[s] # store as bar outdict["P_surf"] += outdict[s+"_bar"] - # outdict["O2_bar"] = p_d['O2'] - # Store VMRs (=mole fractions) and total atmosphere for s in volatile_species: outdict[s+"_vmr"] = outdict[s+"_bar"]/outdict["P_surf"] diff --git a/tools/SolveVol.ipynb b/tools/SolveVol.ipynb index 962804e..7022cbf 100644 --- a/tools/SolveVol.ipynb +++ b/tools/SolveVol.ipynb @@ -138,7 +138,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "{'M_atm': np.float64(2.0991678467167884e+21), 'P_surf': np.float64(267.17533370402055), 'H2O_bar': np.float64(0.3077422844774362), 'H2O_kg_atm': np.float64(1.4986163489058386e+18), 'H2O_kg_liquid': np.float64(1.1076302538596967e+22), 'H2O_kg_solid': 0.0, 'H2O_kg_total': np.float64(1.1077801154945873e+22), 'CO2_bar': np.float64(18.829597282309976), 'CO2_kg_atm': np.float64(2.2400343417499815e+20), 'CO2_kg_liquid': np.float64(3.271245505857492e+20), 'CO2_kg_solid': 0.0, 'CO2_kg_total': np.float64(5.511279847607473e+20), 'H2_bar': np.float64(0.6213549317124336), 'H2_kg_atm': np.float64(3.3858421107090234e+17), 'H2_kg_liquid': 0.0, 'H2_kg_solid': 0.0, 'H2_kg_total': np.float64(3.3858421107090234e+17), 'CH4_bar': np.float64(8.559238758232162e-07), 'CH4_kg_atm': np.float64(3711092516717.1055), 'CH4_kg_liquid': np.float64(451309664086.35474), 'CH4_kg_solid': 0.0, 'CH4_kg_total': np.float64(4162402180803.46), 'CO_bar': np.float64(230.95600036737125), 'CO_kg_atm': np.float64(1.7486570174289632e+21), 'CO_kg_liquid': np.float64(7.922955564585293e+20), 'CO_kg_solid': 0.0, 'CO_kg_total': np.float64(2.5409525738874927e+21), 'N2_bar': np.float64(16.4583241513067), 'N2_kg_atm': np.float64(1.2463011972890077e+20), 'N2_kg_liquid': np.float64(2.778565825955145e+19), 'N2_kg_solid': 0.0, 'N2_kg_total': np.float64(1.5241577798845222e+20), 'S2_bar': np.float64(9.936902590352362e-05), 'S2_kg_atm': np.float64(1721754942485320.8), 'S2_kg_liquid': np.float64(1.1431163297103474e+22), 'S2_kg_solid': 0.0, 'S2_kg_total': np.float64(1.1431165018858416e+22), 'SO2_bar': np.float64(0.0022144618929678356), 'SO2_kg_atm': np.float64(3.834935791448404e+16), 'SO2_kg_liquid': 0.0, 'SO2_kg_solid': 0.0, 'SO2_kg_total': np.float64(3.834935791448404e+16), 'H2O_vmr': np.float64(0.0011518364371853134), 'CO2_vmr': np.float64(0.07047655568073356), 'H2_vmr': np.float64(0.0023256448231885685), 'CH4_vmr': np.float64(3.203603655910156e-09), 'CO_vmr': np.float64(0.8644360883375056), 'N2_vmr': np.float64(0.06160121117146014), 'S2_vmr': np.float64(3.719244008266332e-07), 'SO2_vmr': np.float64(8.288421922291068e-06), 'H_kg_atm': np.float64(5.0630796909998144e+17), 'H_kg_liquid': np.float64(1.2394936920134047e+21), 'H_kg_solid': 0.0, 'H_kg_total': np.float64(1.2399999999825048e+21), 'C_kg_atm': np.float64(8.109775623938723e+20), 'C_kg_liquid': np.float64(4.2902243760239935e+20), 'C_kg_solid': 0.0, 'C_kg_total': np.float64(1.2399999999962718e+21), 'N_kg_atm': np.float64(1.2463011972890077e+20), 'N_kg_liquid': np.float64(2.778565825955145e+19), 'N_kg_solid': 0.0, 'N_kg_total': np.float64(1.5241577798845222e+20), 'S_kg_atm': np.float64(2.0051987001340212e+16), 'S_kg_liquid': np.float64(1.1431163297103474e+22), 'S_kg_solid': 0.0, 'S_kg_total': np.float64(1.1431183349090475e+22), 'O_kg_atm': np.float64(1.1630278462736336e+21), 'O_kg_liquid': np.float64(1.0527026931615612e+22), 'O_kg_solid': 0.0, 'O_kg_total': np.float64(1.1690054777889245e+22), 'atm_kg_per_mol': np.float64(0.029066218154194936), 'H2O_mol_atm': np.float64(8.318584828577954e+19), 'H2O_mol_solid': 0.0, 'H2O_mol_liquid': np.float64(6.148282201884714e+23), 'H2O_mol_total': np.float64(6.149114060367572e+23), 'CO2_mol_atm': np.float64(5.089830360713432e+21), 'CO2_mol_solid': 0.0, 'CO2_mol_liquid': np.float64(7.432959567956128e+21), 'CO2_mol_total': np.float64(1.2522789928669561e+22), 'H2_mol_atm': np.float64(1.6795851492693135e+20), 'H2_mol_solid': 0.0, 'H2_mol_liquid': 0.0, 'H2_mol_total': np.float64(1.6795851492693135e+20), 'CH4_mol_atm': np.float64(231364870119520.3), 'CH4_mol_solid': 0.0, 'CH4_mol_liquid': np.float64(28136512723588.203), 'CH4_mol_total': np.float64(259501382843108.5), 'CO_mol_atm': np.float64(6.242974000103403e+22), 'CO_mol_solid': 0.0, 'CO_mol_liquid': np.float64(2.828616767077934e+22), 'CO_mol_total': np.float64(9.071590767181337e+22), 'N2_mol_atm': np.float64(4.4488512789641167e+21), 'N2_mol_solid': 0.0, 'N2_mol_liquid': np.float64(9.918490133344559e+20), 'N2_mol_total': np.float64(5.440700292298573e+21), 'S2_mol_atm': np.float64(2.6860451520831836e+16), 'S2_mol_solid': 0.0, 'S2_mol_liquid': np.float64(1.783332807660448e+23), 'S2_mol_total': np.float64(1.7833330762649634e+23), 'SO2_mol_atm': np.float64(5.985914200119259e+17), 'SO2_mol_solid': 0.0, 'SO2_mol_liquid': 0.0, 'SO2_mol_total': np.float64(5.985914200119259e+17), 'H/O_atm': np.float64(0.0004353360675947727), 'H/C_atm': np.float64(0.000624318097784905), 'H/N_atm': np.float64(0.0040624848166825), 'H/S_atm': np.float64(25.249765475418542), 'O/H_atm': np.float64(2297.075924641369), 'O/C_atm': np.float64(1.4341060717396013), 'O/N_atm': np.float64(9.331836066622476), 'O/S_atm': np.float64(58000.628376424764), 'C/H_atm': np.float64(1601.7475763525406), 'C/O_atm': np.float64(0.697298491168773), 'C/N_atm': np.float64(6.507075209090189), 'C/S_atm': np.float64(40443.750653721705), 'N/H_atm': np.float64(246.1547661405461), 'N/O_atm': np.float64(0.10716004791133624), 'N/C_atm': np.float64(0.15367887535755387), 'N/S_atm': np.float64(6215.350115705285), 'S/H_atm': np.float64(0.03960432824508933), 'S/O_atm': np.float64(1.7241192517949773e-05), 'S/C_atm': np.float64(2.4725698874023155e-05), 'S/N_atm': np.float64(0.0001608919821705853), 'H_res': np.float64(-1.4109055174193549e-11), 'C_res': np.float64(-3.0066225548387095e-12), 'N_res': np.float64(6.802095988288044e-12), 'S_res': np.float64(3.0017540595946413e-12)}\n", + "{'M_atm': np.float64(2.0991678467196825e+21), 'P_surf': np.float64(267.1753337043889), 'H2O_bar': np.float64(0.30774228445751334), 'H2O_kg_atm': np.float64(1.498616348808447e+18), 'H2O_kg_liquid': np.float64(1.1076302538238434e+22), 'H2O_kg_solid': 0.0, 'H2O_kg_total': np.float64(1.1077801154587243e+22), 'CO2_bar': np.float64(18.829597282349553), 'CO2_kg_atm': np.float64(2.2400343417541313e+20), 'CO2_kg_liquid': np.float64(3.271245505864353e+20), 'CO2_kg_solid': 0.0, 'CO2_kg_total': np.float64(5.5112798476184846e+20), 'H2_bar': np.float64(0.6213549316722079), 'H2_kg_atm': np.float64(3.385842110488984e+17), 'H2_kg_liquid': 0.0, 'H2_kg_solid': 0.0, 'H2_kg_total': np.float64(3.385842110488984e+17), 'CH4_bar': np.float64(8.559238757141924e-07), 'CH4_kg_atm': np.float64(3711092516243.4775), 'CH4_kg_liquid': np.float64(451309664028.8689), 'CH4_kg_solid': 0.0, 'CH4_kg_total': np.float64(4162402180272.3467), 'CO_bar': np.float64(230.9560003678567), 'CO_kg_atm': np.float64(1.748657017432203e+21), 'CO_kg_liquid': np.float64(7.92295556459952e+20), 'CO_kg_solid': 0.0, 'CO_kg_total': np.float64(2.540952573892155e+21), 'N2_bar': np.float64(16.458324151197715), 'N2_kg_atm': np.float64(1.2463011972804441e+20), 'N2_kg_liquid': np.float64(2.778565825937559e+19), 'N2_kg_solid': 0.0, 'N2_kg_total': np.float64(1.5241577798742e+20), 'S2_bar': np.float64(9.936902692695684e-05), 'S2_kg_atm': np.float64(1721754960217793.8), 'S2_kg_liquid': np.float64(1.1431163355970058e+22), 'S2_kg_solid': 0.0, 'S2_kg_total': np.float64(1.1431165077725018e+22), 'SO2_bar': np.float64(0.0022144619043715594), 'SO2_kg_atm': np.float64(3.834935811196061e+16), 'SO2_kg_liquid': 0.0, 'SO2_kg_solid': 0.0, 'SO2_kg_total': np.float64(3.834935811196061e+16), 'H2O_vmr': np.float64(0.0011518364371091569), 'CO2_vmr': np.float64(0.07047655568078454), 'H2_vmr': np.float64(0.002325644823034803), 'CH4_vmr': np.float64(3.2036036554976784e-09), 'CO_vmr': np.float64(0.8644360883381308), 'N2_vmr': np.float64(0.06160121117096729), 'S2_vmr': np.float64(3.7192440465668823e-07), 'SO2_vmr': np.float64(8.28842196496219e-06), 'H_kg_atm': np.float64(5.063079690670775e+17), 'H_kg_liquid': np.float64(1.2394936919732833e+21), 'H_kg_solid': 0.0, 'H_kg_total': np.float64(1.2399999999423503e+21), 'C_kg_atm': np.float64(8.109775623953749e+20), 'C_kg_liquid': np.float64(4.2902243760319667e+20), 'C_kg_solid': 0.0, 'C_kg_total': np.float64(1.2399999999985716e+21), 'N_kg_atm': np.float64(1.2463011972804441e+20), 'N_kg_liquid': np.float64(2.778565825937559e+19), 'N_kg_solid': 0.0, 'N_kg_total': np.float64(1.5241577798742e+20), 'S_kg_atm': np.float64(2.005198710903072e+16), 'S_kg_liquid': np.float64(1.1431163355970058e+22), 'S_kg_solid': 0.0, 'S_kg_total': np.float64(1.1431183407957167e+22), 'O_kg_atm': np.float64(1.163027846275798e+21), 'O_kg_liquid': np.float64(1.052702693129852e+22), 'O_kg_solid': 0.0, 'O_kg_total': np.float64(1.1690054777574317e+22), 'atm_kg_per_mol': np.float64(0.02906621815420218), 'H2O_mol_atm': np.float64(8.318584828037348e+19), 'H2O_mol_solid': 0.0, 'H2O_mol_liquid': np.float64(6.148282201685699e+23), 'H2O_mol_total': np.float64(6.149114060168502e+23), 'CO2_mol_atm': np.float64(5.089830360722862e+21), 'CO2_mol_solid': 0.0, 'CO2_mol_liquid': np.float64(7.432959567971717e+21), 'CO2_mol_total': np.float64(1.252278992869458e+22), 'H2_mol_atm': np.float64(1.6795851491601606e+20), 'H2_mol_solid': 0.0, 'H2_mol_liquid': 0.0, 'H2_mol_total': np.float64(1.6795851491601606e+20), 'CH4_mol_atm': np.float64(231364870089992.38), 'CH4_mol_solid': 0.0, 'CH4_mol_liquid': np.float64(28136512720004.297), 'CH4_mol_total': np.float64(259501382809996.7), 'CO_mol_atm': np.float64(6.24297400011497e+22), 'CO_mol_solid': 0.0, 'CO_mol_liquid': np.float64(2.828616767083013e+22), 'CO_mol_total': np.float64(9.071590767197983e+22), 'N2_mol_atm': np.float64(4.4488512789335475e+21), 'N2_mol_solid': 0.0, 'N2_mol_liquid': np.float64(9.918490133281784e+20), 'N2_mol_total': np.float64(5.440700292261726e+21), 'S2_mol_atm': np.float64(2.686045179746948e+16), 'S2_mol_solid': 0.0, 'S2_mol_liquid': np.float64(1.783332816844003e+23), 'S2_mol_total': np.float64(1.7833330854485208e+23), 'SO2_mol_atm': np.float64(5.985914230943185e+17), 'SO2_mol_solid': 0.0, 'SO2_mol_liquid': 0.0, 'SO2_mol_total': np.float64(5.985914230943185e+17), 'H/O_atm': np.float64(0.0004353360675656709), 'H/C_atm': np.float64(0.000624318097743175), 'H/N_atm': np.float64(0.004062484816446402), 'H/S_atm': np.float64(25.249765338172093), 'O/H_atm': np.float64(2297.0759247949263), 'O/C_atm': np.float64(1.434106071739613), 'O/N_atm': np.float64(9.331836066703964), 'O/S_atm': np.float64(58000.62806503654), 'C/H_atm': np.float64(1601.7475764596027), 'C/O_atm': np.float64(0.6972984911687672), 'C/N_atm': np.float64(6.507075209146957), 'C/S_atm': np.float64(40443.75043659083), 'N/H_atm': np.float64(246.1547661548518), 'N/O_atm': np.float64(0.10716004791040049), 'N/C_atm': np.float64(0.15367887535621316), 'N/S_atm': np.float64(6215.3500822826345), 'S/H_atm': np.float64(0.03960432846036077), 'S/O_atm': np.float64(1.724119261051264e-05), 'S/C_atm': np.float64(2.4725699006768325e-05), 'S/N_atm': np.float64(0.00016089198303577174), 'H_res': np.float64(-4.6491661212903224e-11), 'C_res': np.float64(-1.1519537548387096e-12), 'N_res': np.float64(2.966873941602927e-14), 'S_res': np.float64(5.1526603622746795e-09)}\n", "Partial pressures\n", " H2O : 0.308 bar\n", " CO2 : 18.830 bar\n", @@ -148,21 +148,11 @@ " CH4 : 0.000 bar\n", " S2 : 0.000 bar\n", " SO2 : 0.002 bar\n", - "mubar = 0.029066218154194936\n", + "mubar = 0.02906621815420218\n", "ptot = 267.175 bar\n", " \n", - "{'H2O': np.float64(1.4978566192661673e+18), 'CO2': np.float64(2.2388987472500602e+20), 'N2': np.float64(1.2456693798393779e+20), 'H2': np.float64(3.38412564431078e+17), 'CO': np.float64(1.747770528657684e+21), 'CH4': np.float64(3709211163305.6245), 'S2': np.float64(1720882091830106.2), 'SO2': np.float64(3.832991655186226e+16)}\n", - "5.06051294220378e+17 8.10566434027557e+20 1.2456693798393779e+20 1720882091830106.2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/dataserver/users/formingworlds/nicholls/CALLIOPE/src/calliope/surface_gases.py:91: RuntimeWarning: invalid value encountered in scalar power\n", - " p_d['SO2'] = (gamma*pin['S2']*p_d['O2']**2)**0.5\n", - "/dataserver/users/formingworlds/nicholls/CALLIOPE/src/calliope/solubility.py:151: RuntimeWarning: invalid value encountered in log10\n", - " ppmw = 10 ** (-0.738 + 0.876 * np.log10(p) - 5.44e-5 * p_total)\n" + "{'H2O': np.float64(1.497856619168824e+18), 'CO2': np.float64(2.2388987472542073e+20), 'N2': np.float64(1.2456693798308186e+20), 'H2': np.float64(3.3841256440908525e+17), 'CO': np.float64(1.7477705286609218e+21), 'CH4': np.float64(3709211162832.2363), 'S2': np.float64(1720882109553589.5), 'SO2': np.float64(3.83299167492387e+16)}\n", + "5.060512941874906e+17 8.105664340290585e+20 1.2456693798308186e+20 1720882109553589.5\n" ] } ], @@ -242,23 +232,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/dataserver/users/formingworlds/nicholls/CALLIOPE/src/calliope/solubility.py:124: RuntimeWarning: overflow encountered in exp\n", - " ppmw = pb_N2**0.5 * np.exp(5908.0 * pb_tot**0.5/temp - 1.6*fO2_shift)\n", - "/dataserver/users/formingworlds/nicholls/CALLIOPE/src/calliope/solubility.py:124: RuntimeWarning: invalid value encountered in scalar power\n", - " ppmw = pb_N2**0.5 * np.exp(5908.0 * pb_tot**0.5/temp - 1.6*fO2_shift)\n", - "/dataserver/users/formingworlds/nicholls/CALLIOPE/src/calliope/solubility.py:19: RuntimeWarning: invalid value encountered in scalar power\n", - " return const*p**exponent\n", - "/dataserver/users/formingworlds/nicholls/CALLIOPE/src/calliope/solubility.py:139: RuntimeWarning: overflow encountered in exp\n", - " ppmw = p*np.exp(4.93 - (0.000193 * p_total))\n" - ] - }, { "data": { "image/png": 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",