Add masked operators, remove vanish sd grad

integration_tests/utils/main.jl

@@ -214,7 +214,7 @@ face_aux_vars_edmf(FT, n_up) = (;
         ρ_ae_KH = FT(0),
         ρ_ae_K = FT(0),
         ρ_ae_K∇ϕ = FT(0),
-        en = (; w = FT(0), sat = (; θ_liq_ice = FT(0), q_tot = FT(0)), unsat = (; θ_virt = FT(0))),
+        en = (; w = FT(0)),
         up = ntuple(i -> face_aux_vars_up(FT), n_up),
         massflux_h = FT(0),
         massflux_qt = FT(0),

integration_tests/utils/mse_tables.jl

@@ -5,149 +5,149 @@
 all_best_mse = OrderedCollections.OrderedDict()
 #
 all_best_mse["ARM_SGP"] = OrderedCollections.OrderedDict()
-all_best_mse["ARM_SGP"]["qt_mean"] = 0.22260408607145526
-all_best_mse["ARM_SGP"]["updraft_area"] = 335.3186790824817
-all_best_mse["ARM_SGP"]["updraft_w"] = 142.01229468250628
-all_best_mse["ARM_SGP"]["updraft_qt"] = 27.73127536471595
-all_best_mse["ARM_SGP"]["updraft_thetal"] = 170.9811743126976
+all_best_mse["ARM_SGP"]["qt_mean"] = 0.22286959111173252
+all_best_mse["ARM_SGP"]["updraft_area"] = 335.3378419225924
+all_best_mse["ARM_SGP"]["updraft_w"] = 141.84841956414584
+all_best_mse["ARM_SGP"]["updraft_qt"] = 27.421852759548216
+all_best_mse["ARM_SGP"]["updraft_thetal"] = 170.98083895236377
 all_best_mse["ARM_SGP"]["u_mean"] = 1.3375737467153984e-5
-all_best_mse["ARM_SGP"]["tke_mean"] = 1318.3361036369147
-all_best_mse["ARM_SGP"]["temperature_mean"] = 0.00010914140178692959
-all_best_mse["ARM_SGP"]["ql_mean"] = 174.89754948993047
+all_best_mse["ARM_SGP"]["tke_mean"] = 1318.3154189170075
+all_best_mse["ARM_SGP"]["temperature_mean"] = 0.00010925945966980263
+all_best_mse["ARM_SGP"]["ql_mean"] = 174.380491712554
 all_best_mse["ARM_SGP"]["qi_mean"] = "NA"
-all_best_mse["ARM_SGP"]["thetal_mean"] = 0.00010058065940382863
-all_best_mse["ARM_SGP"]["Hvar_mean"] = 10006.034571429314
-all_best_mse["ARM_SGP"]["QTvar_mean"] = 6375.712096535838
+all_best_mse["ARM_SGP"]["thetal_mean"] = 0.00010068350911718366
+all_best_mse["ARM_SGP"]["Hvar_mean"] = 10272.960793535123
+all_best_mse["ARM_SGP"]["QTvar_mean"] = 6518.918215318262
 #
 all_best_mse["Bomex"] = OrderedCollections.OrderedDict()
-all_best_mse["Bomex"]["qt_mean"] = 0.11516917449744828
-all_best_mse["Bomex"]["updraft_area"] = 129.4490200415662
-all_best_mse["Bomex"]["updraft_w"] = 18.72095900025913
-all_best_mse["Bomex"]["updraft_qt"] = 6.541537482460252
-all_best_mse["Bomex"]["updraft_thetal"] = 69.46315590943559
-all_best_mse["Bomex"]["v_mean"] = 66.93043387413974
-all_best_mse["Bomex"]["u_mean"] = 0.32305284623455727
-all_best_mse["Bomex"]["tke_mean"] = 74.3140355702218
-all_best_mse["Bomex"]["temperature_mean"] = 4.591884954854846e-5
-all_best_mse["Bomex"]["ql_mean"] = 9.279604539199164
+all_best_mse["Bomex"]["qt_mean"] = 0.115170045283136
+all_best_mse["Bomex"]["updraft_area"] = 129.45058117786624
+all_best_mse["Bomex"]["updraft_w"] = 18.370154256735134
+all_best_mse["Bomex"]["updraft_qt"] = 6.306330920610372
+all_best_mse["Bomex"]["updraft_thetal"] = 69.45787769968938
+all_best_mse["Bomex"]["v_mean"] = 66.9363180496193
+all_best_mse["Bomex"]["u_mean"] = 0.3230987236309413
+all_best_mse["Bomex"]["tke_mean"] = 74.29246691414228
+all_best_mse["Bomex"]["temperature_mean"] = 4.591826060245829e-5
+all_best_mse["Bomex"]["ql_mean"] = 8.909573333964328
 all_best_mse["Bomex"]["qi_mean"] = "NA"
-all_best_mse["Bomex"]["thetal_mean"] = 4.6675976163615926e-5
-all_best_mse["Bomex"]["Hvar_mean"] = 3788.9644749083805
-all_best_mse["Bomex"]["QTvar_mean"] = 1420.5895981298102
+all_best_mse["Bomex"]["thetal_mean"] = 4.666238445127772e-5
+all_best_mse["Bomex"]["Hvar_mean"] = 3822.8747397715383
+all_best_mse["Bomex"]["QTvar_mean"] = 1433.09548125117
 #
 all_best_mse["DryBubble"] = OrderedCollections.OrderedDict()
 all_best_mse["DryBubble"]["updraft_area"] = 0.0
 all_best_mse["DryBubble"]["updraft_w"] = 0.0
 all_best_mse["DryBubble"]["updraft_thetal"] = 0.0
 all_best_mse["DryBubble"]["u_mean"] = 0.0
-all_best_mse["DryBubble"]["tke_mean"] = 0.0
+all_best_mse["DryBubble"]["tke_mean"] = 2.3501977062566578e-40
 all_best_mse["DryBubble"]["temperature_mean"] = 0.0
 all_best_mse["DryBubble"]["thetal_mean"] = 0.0
-all_best_mse["DryBubble"]["Hvar_mean"] = 0.0
+all_best_mse["DryBubble"]["Hvar_mean"] = 3.4874726372288367e-43
 #
 all_best_mse["DYCOMS_RF01"] = OrderedCollections.OrderedDict()
-all_best_mse["DYCOMS_RF01"]["qt_mean"] = 0.022666124107562857
-all_best_mse["DYCOMS_RF01"]["ql_mean"] = 10.29424580304818
-all_best_mse["DYCOMS_RF01"]["updraft_area"] = 30.546869712149793
-all_best_mse["DYCOMS_RF01"]["updraft_w"] = 4.13826148825719
-all_best_mse["DYCOMS_RF01"]["updraft_qt"] = 2.1512919048813117
-all_best_mse["DYCOMS_RF01"]["updraft_thetal"] = 46.18689371056969
-all_best_mse["DYCOMS_RF01"]["v_mean"] = 0.0030072605135407506
-all_best_mse["DYCOMS_RF01"]["u_mean"] = 0.07908969038954133
-all_best_mse["DYCOMS_RF01"]["tke_mean"] = 21.342247470474888
-all_best_mse["DYCOMS_RF01"]["temperature_mean"] = 8.099236820043368e-5
-all_best_mse["DYCOMS_RF01"]["thetal_mean"] = 8.159657479729185e-5
-all_best_mse["DYCOMS_RF01"]["Hvar_mean"] = 1243.0763870118528
-all_best_mse["DYCOMS_RF01"]["QTvar_mean"] = 483.91315327538
+all_best_mse["DYCOMS_RF01"]["qt_mean"] = 0.022666124109793833
+all_best_mse["DYCOMS_RF01"]["ql_mean"] = 10.29424581361349
+all_best_mse["DYCOMS_RF01"]["updraft_area"] = 30.54686971359306
+all_best_mse["DYCOMS_RF01"]["updraft_w"] = 4.138261488244225
+all_best_mse["DYCOMS_RF01"]["updraft_qt"] = 2.1512919048289247
+all_best_mse["DYCOMS_RF01"]["updraft_thetal"] = 46.18689371056938
+all_best_mse["DYCOMS_RF01"]["v_mean"] = 0.0030072605138559954
+all_best_mse["DYCOMS_RF01"]["u_mean"] = 0.07908969038701516
+all_best_mse["DYCOMS_RF01"]["tke_mean"] = 21.342247465667818
+all_best_mse["DYCOMS_RF01"]["temperature_mean"] = 8.099236822693791e-5
+all_best_mse["DYCOMS_RF01"]["thetal_mean"] = 8.159657482364597e-5
+all_best_mse["DYCOMS_RF01"]["Hvar_mean"] = 1243.0763870159726
+all_best_mse["DYCOMS_RF01"]["QTvar_mean"] = 483.91315327820047
 #
 all_best_mse["GABLS"] = OrderedCollections.OrderedDict()
-all_best_mse["GABLS"]["updraft_thetal"] = 0.0
-all_best_mse["GABLS"]["v_mean"] = 0.0
-all_best_mse["GABLS"]["u_mean"] = 0.0
-all_best_mse["GABLS"]["tke_mean"] = 0.0
-all_best_mse["GABLS"]["temperature_mean"] = 0.0
-all_best_mse["GABLS"]["thetal_mean"] = 0.0
-all_best_mse["GABLS"]["Hvar_mean"] = 0.0
-all_best_mse["GABLS"]["QTvar_mean"] = 0.0
-all_best_mse["GABLS"]["qt_mean"] = 0.0
+all_best_mse["GABLS"]["updraft_thetal"] = 4.5904248400012984e-32
+all_best_mse["GABLS"]["v_mean"] = 2.9863510775758257e-26
+all_best_mse["GABLS"]["u_mean"] = 3.5653565343617814e-28
+all_best_mse["GABLS"]["tke_mean"] = 2.5532594247952552e-27
+all_best_mse["GABLS"]["temperature_mean"] = 2.3209177991607466e-31
+all_best_mse["GABLS"]["thetal_mean"] = 4.573449792507506e-32
+all_best_mse["GABLS"]["Hvar_mean"] = 1.204603534644079e-25
+all_best_mse["GABLS"]["QTvar_mean"] = 8.712740863504478e-27
+all_best_mse["GABLS"]["qt_mean"] = 4.22896437880345e-27
 #
 all_best_mse["life_cycle_Tan2018"] = OrderedCollections.OrderedDict()
-all_best_mse["life_cycle_Tan2018"]["qt_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["ql_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["updraft_area"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["updraft_w"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["updraft_qt"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["updraft_thetal"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["v_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["u_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["tke_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["temperature_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["thetal_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["Hvar_mean"] = 0.0
-all_best_mse["life_cycle_Tan2018"]["QTvar_mean"] = 0.0
+all_best_mse["life_cycle_Tan2018"]["qt_mean"] = 4.870949616027259e-12
+all_best_mse["life_cycle_Tan2018"]["ql_mean"] = 2.9408095702689907e-9
+all_best_mse["life_cycle_Tan2018"]["updraft_area"] = 4.5181722030838177e-11
+all_best_mse["life_cycle_Tan2018"]["updraft_w"] = 1.8706227853888109e-10
+all_best_mse["life_cycle_Tan2018"]["updraft_qt"] = 8.921538771643461e-13
+all_best_mse["life_cycle_Tan2018"]["updraft_thetal"] = 5.269381089837162e-16
+all_best_mse["life_cycle_Tan2018"]["v_mean"] = 1.526604656383764e-11
+all_best_mse["life_cycle_Tan2018"]["u_mean"] = 5.741146289594956e-14
+all_best_mse["life_cycle_Tan2018"]["tke_mean"] = 1.7229389950750602e-11
+all_best_mse["life_cycle_Tan2018"]["temperature_mean"] = 2.3695737488566606e-15
+all_best_mse["life_cycle_Tan2018"]["thetal_mean"] = 2.3296538264903215e-15
+all_best_mse["life_cycle_Tan2018"]["Hvar_mean"] = 3.110057054481711e-5
+all_best_mse["life_cycle_Tan2018"]["QTvar_mean"] = 2.631979354952001e-5
 #
 all_best_mse["Nieuwstadt"] = OrderedCollections.OrderedDict()
-all_best_mse["Nieuwstadt"]["updraft_area"] = 98.77517014009693
-all_best_mse["Nieuwstadt"]["updraft_w"] = 12.495642974390554
+all_best_mse["Nieuwstadt"]["updraft_area"] = 98.77517013992535
+all_best_mse["Nieuwstadt"]["updraft_w"] = 12.495642974380058
 all_best_mse["Nieuwstadt"]["updraft_thetal"] = 117.36697373364835
-all_best_mse["Nieuwstadt"]["u_mean"] = 14.602386345210054
-all_best_mse["Nieuwstadt"]["tke_mean"] = 313.2319990260036
-all_best_mse["Nieuwstadt"]["temperature_mean"] = 9.723169961494773e-6
-all_best_mse["Nieuwstadt"]["thetal_mean"] = 1.003536628584033e-5
-all_best_mse["Nieuwstadt"]["Hvar_mean"] = 1277.7564627156673
+all_best_mse["Nieuwstadt"]["u_mean"] = 14.602386345210023
+all_best_mse["Nieuwstadt"]["tke_mean"] = 313.23199902597605
+all_best_mse["Nieuwstadt"]["temperature_mean"] = 9.7231699614854e-6
+all_best_mse["Nieuwstadt"]["thetal_mean"] = 1.0035366285832543e-5
+all_best_mse["Nieuwstadt"]["Hvar_mean"] = 1277.7564627153547
 #
 all_best_mse["Rico"] = OrderedCollections.OrderedDict()
-all_best_mse["Rico"]["qt_mean"] = 1.2348356677520063
-all_best_mse["Rico"]["updraft_area"] = 477.46259802428483
-all_best_mse["Rico"]["updraft_w"] = 108.123453851901
-all_best_mse["Rico"]["updraft_qt"] = 12.128215447543258
-all_best_mse["Rico"]["updraft_thetal"] = 133.3615630817877
-all_best_mse["Rico"]["v_mean"] = 0.611195500426451
-all_best_mse["Rico"]["u_mean"] = 0.6932437970565734
-all_best_mse["Rico"]["tke_mean"] = 82.26809010566267
-all_best_mse["Rico"]["temperature_mean"] = 0.0005721060978593456
-all_best_mse["Rico"]["ql_mean"] = 63.57516679609136
+all_best_mse["Rico"]["qt_mean"] = 1.2368324954575274
+all_best_mse["Rico"]["updraft_area"] = 477.4540646477023
+all_best_mse["Rico"]["updraft_w"] = 107.93534078910224
+all_best_mse["Rico"]["updraft_qt"] = 12.106416673863404
+all_best_mse["Rico"]["updraft_thetal"] = 133.36104664499535
+all_best_mse["Rico"]["v_mean"] = 0.6116450245539317
+all_best_mse["Rico"]["u_mean"] = 0.695169541619883
+all_best_mse["Rico"]["tke_mean"] = 82.35898449028875
+all_best_mse["Rico"]["temperature_mean"] = 0.0005727120565407745
+all_best_mse["Rico"]["ql_mean"] = 63.507574798525205
 all_best_mse["Rico"]["qi_mean"] = "NA"
-all_best_mse["Rico"]["qr_mean"] = 760.7832680331468
-all_best_mse["Rico"]["thetal_mean"] = 0.0005644774398077206
-all_best_mse["Rico"]["Hvar_mean"] = 168760.41387534072
-all_best_mse["Rico"]["QTvar_mean"] = 37889.64625145492
+all_best_mse["Rico"]["qr_mean"] = 760.8475924163045
+all_best_mse["Rico"]["thetal_mean"] = 0.0005650860400845547
+all_best_mse["Rico"]["Hvar_mean"] = 173935.8383250262
+all_best_mse["Rico"]["QTvar_mean"] = 39053.357708784606
 #
 all_best_mse["Soares"] = OrderedCollections.OrderedDict()
-all_best_mse["Soares"]["qt_mean"] = 0.12605920198643053
-all_best_mse["Soares"]["updraft_area"] = 98.11492529621005
-all_best_mse["Soares"]["updraft_w"] = 11.391215812361056
-all_best_mse["Soares"]["updraft_qt"] = 23.08519167889173
-all_best_mse["Soares"]["updraft_thetal"] = 65.25330158630689
-all_best_mse["Soares"]["u_mean"] = 96.34580613148802
-all_best_mse["Soares"]["tke_mean"] = 241.30242939684976
-all_best_mse["Soares"]["temperature_mean"] = 1.0979451729133836e-5
-all_best_mse["Soares"]["thetal_mean"] = 1.040799929860969e-5
-all_best_mse["Soares"]["Hvar_mean"] = 1124.1641081242815
+all_best_mse["Soares"]["qt_mean"] = 0.12631256600224
+all_best_mse["Soares"]["updraft_area"] = 96.19157396759499
+all_best_mse["Soares"]["updraft_w"] = 11.391626503785842
+all_best_mse["Soares"]["updraft_qt"] = 23.081037927314153
+all_best_mse["Soares"]["updraft_thetal"] = 65.25330113168873
+all_best_mse["Soares"]["u_mean"] = 96.34646256855906
+all_best_mse["Soares"]["tke_mean"] = 241.36263695867387
+all_best_mse["Soares"]["temperature_mean"] = 1.0985075298440972e-5
+all_best_mse["Soares"]["thetal_mean"] = 1.0414382065295909e-5
+all_best_mse["Soares"]["Hvar_mean"] = 1121.2519631022305
 #
 all_best_mse["TRMM_LBA"] = OrderedCollections.OrderedDict()
-all_best_mse["TRMM_LBA"]["qt_mean"] = 3.9659428453652863
-all_best_mse["TRMM_LBA"]["updraft_area"] = 7590.521944576046
-all_best_mse["TRMM_LBA"]["updraft_w"] = 29147.73666793535
-all_best_mse["TRMM_LBA"]["updraft_qt"] = 264.40322006294645
-all_best_mse["TRMM_LBA"]["updraft_thetal"] = 1962.1800212491873
-all_best_mse["TRMM_LBA"]["v_mean"] = 286.6313055852003
-all_best_mse["TRMM_LBA"]["u_mean"] = 113.7950533341916
-all_best_mse["TRMM_LBA"]["tke_mean"] = 25980.79441823836
-all_best_mse["TRMM_LBA"]["temperature_mean"] = 0.0011280565198651163
-all_best_mse["TRMM_LBA"]["ql_mean"] = 11329.91935493494
+all_best_mse["TRMM_LBA"]["qt_mean"] = 3.9659428453653844
+all_best_mse["TRMM_LBA"]["updraft_area"] = 7590.521944576031
+all_best_mse["TRMM_LBA"]["updraft_w"] = 29147.7366679372
+all_best_mse["TRMM_LBA"]["updraft_qt"] = 264.4032200629445
+all_best_mse["TRMM_LBA"]["updraft_thetal"] = 1962.1800212491878
+all_best_mse["TRMM_LBA"]["v_mean"] = 286.63130558520237
+all_best_mse["TRMM_LBA"]["u_mean"] = 113.79505333419178
+all_best_mse["TRMM_LBA"]["tke_mean"] = 25980.794418238478
+all_best_mse["TRMM_LBA"]["temperature_mean"] = 0.0011280565198652176
+all_best_mse["TRMM_LBA"]["ql_mean"] = 11329.919354934302
 all_best_mse["TRMM_LBA"]["qi_mean"] = "NA"
-all_best_mse["TRMM_LBA"]["thetal_mean"] = 0.021118734698942345
-all_best_mse["TRMM_LBA"]["Hvar_mean"] = 4347.874034179393
-all_best_mse["TRMM_LBA"]["QTvar_mean"] = 2834.63299032306
+all_best_mse["TRMM_LBA"]["thetal_mean"] = 0.021118734698942185
+all_best_mse["TRMM_LBA"]["Hvar_mean"] = 4347.874034178831
+all_best_mse["TRMM_LBA"]["QTvar_mean"] = 2834.632990322874
 #
 all_best_mse["LES_driven_SCM"] = OrderedCollections.OrderedDict()
-all_best_mse["LES_driven_SCM"]["qt_mean"] = 8.398966774944043
-all_best_mse["LES_driven_SCM"]["v_mean"] = 3.2126761915549915
-all_best_mse["LES_driven_SCM"]["u_mean"] = 1.1346893323826517
-all_best_mse["LES_driven_SCM"]["temperature_mean"] = 0.003350514968624466
-all_best_mse["LES_driven_SCM"]["ql_mean"] = 258.08240248588
-all_best_mse["LES_driven_SCM"]["thetal_mean"] = 0.0036460773607307224
+all_best_mse["LES_driven_SCM"]["qt_mean"] = 8.406564053715782
+all_best_mse["LES_driven_SCM"]["v_mean"] = 3.2040337013230182
+all_best_mse["LES_driven_SCM"]["u_mean"] = 1.1315506153907806
+all_best_mse["LES_driven_SCM"]["temperature_mean"] = 0.0033521173395760517
+all_best_mse["LES_driven_SCM"]["ql_mean"] = 250.69314421158143
+all_best_mse["LES_driven_SCM"]["thetal_mean"] = 0.0036475573789737916
 #
 #################################
 #################################

src/Operators.jl

@@ -218,54 +218,6 @@ function c∇(f::SA.SVector, grid::Grid, ::BottomBCTag, ::Extrapolate)
     return (∇_staggered(f_dual⁺, grid) + ∇_staggered(f_dual⁻, grid)) / 2
 end
 
-# ∇(center data) for possibly vanishing subdomains.
-
-"""
-    c∇_vanishing_subdomain
-
-Used when the vertical gradient of a field must be computed over a conditional subdomain which may vanish
-below or above the current cell. If the subdomains vanishes, a default user-defined gradient is returned.
-
-Inputs:
- - f_cut: Slice of field.
- - sd_cut: Slice of subdomain volume fraction.
- - default∇: Gradient used in vanishing subdomains.
-"""
-function c∇_vanishing_subdomain(
-    f_cut::SA.SVector,
-    sd_cut::SA.SVector,
-    default∇::FT,
-    grid::Grid,
-    k;
-    bottom = NoBCGivenError(),
-    top = NoBCGivenError(),
-) where {FT <: Real}
-    if is_surface_center(grid, k)
-        return c∇(f_cut, grid, BottomBCTag(), bottom)
-    elseif is_toa_center(grid, k)
-        return c∇(f_cut, grid, TopBCTag(), top)
-    else
-        return c∇_vanishing_subdomain(f_cut, sd_cut, default∇, grid, InteriorTag())
-    end
-end
-function c∇_vanishing_subdomain(
-    f::SA.SVector,
-    sd::SA.SVector,
-    default∇::FT,
-    grid::Grid,
-    ::InteriorTag,
-) where {FT <: Real}
-    @assert length(f) == 3
-    @assert length(sd) == 3
-    if sd[1] * sd[3] ≈ FT(0)
-        return default∇
-    else
-        f_dual⁺ = SA.SVector(f[2], f[3])
-        f_dual⁻ = SA.SVector(f[1], f[2])
-        return (∇_staggered(f_dual⁺, grid) + ∇_staggered(f_dual⁻, grid)) / 2
-    end
-end
-
 #####
 ##### ∇(face data)
 #####
@@ -492,3 +444,36 @@ function dual_centers(f, grid, k::CCO.PlusHalf, i_up::Int)
         return SA.SVector(f[i_up, Cent(k.i - 1)], f[i_up, Cent(k.i)])
     end
 end
+
+
+#####
+##### Helpers for masked operators
+#####
+
+"""
+    shrink_mask(mask)
+
+Shrinks the subdomains where `mask == 1`.
+
+Example:
+
+```julia
+using Test
+mask = Bool[0, 0, 0, 1, 1, 1, 0, 0, 1, 1]
+shrunken_mask = Bool[0, 0, 0, 0, 1, 0, 0, 0, 0, 1]
+@test shrink_mask(mask) == shrunken_mask
+```
+"""
+function shrink_mask(mask)
+    return map(enumerate(mask)) do (i, m)
+        if i == 1 || i == length(mask)
+            m
+        elseif m == 1 && mask[i - 1] == 0
+            m = 0
+        elseif m == 1 && mask[i + 1] == 0
+            m = 0
+        else
+            m
+        end
+    end
+end