Default MTtbox interaction function: Difference between revisions
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[[MTtbox documentation#1 C |Return to MTtbox details]]<br><br> | [[MTtbox documentation#1 C |Return to MTtbox details]]<br><br> | ||
Comments are in green - this web version of the matlab file was created using the DArT_Toolbox tool: | |||
webify_interaction_function('MT_Tues_20120501.m') | |||
<br><br> | <br><br> | ||
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MT=data.working.dyn.microtubules.Org(i_MT); | MT=data.working.dyn.microtubules.Org(i_MT); | ||
<span style="color: Green">% MTtbox monitors ...</span> | <span style="color: Green">% MTtbox monitors ...</span> | ||
<span style="color: Green">% MT.Type</span> | |||
<span style="color: Green">% MT.Age</span> | <span style="color: Green">% MT.Age</span> | ||
<span style="color: Green">% MT.PauseDuration</span> | <span style="color: Green">% MT.PauseDuration</span> |
Latest revision as of 05:50, 11 May 2012
Comments are in green - this web version of the matlab file was created using the DArT_Toolbox tool:
webify_interaction_function('MT_Tues_20120501.m')
function data = MT_Tues_20120501( data, before ) if nargin < 1, return; end % % % extract factors from structure for i=1:size( data.factorprops.Concentration,2) factname=lower(data.factorprops.Index2Name{i}); eval([[factname,'_p'],'=reshape(','data.factorprops.Concentration(:,i),[ data.cellprops.cellsize]);']); eval([[factname,'_i'],'=','data.factorprops.Name2Index.(factname);']); end % insert model in here % data=setupDiffusion(data,'Factorname','s_micplm','DiffK',[0.2,0.2],... % 'RegionLists',{{'cytoplasm','vacuole','cell_wall'},{'plasma_membrane','microtubules'}}); % data=setupDiffusion(data,'Factorname','id_micplm','DiffK',[0,0],... % 'RegionLists',{{'cytoplasm','vacuole','cell_wall'},{'plasma_membrane','microtubules'}}); % data.factorprops.DiffusionConst(:,1)=0.1; % This should be superceed by the above % data.factorprops.DiffusionConst(:,2)=0.05;% This should be superceed by the above if data.iterations<0 % insert initialisation code here - use Initialise button to jump to here % modify default cell specifications, etc. to modify how the cell volume is partitioned, e.g. % data.organelleprops.plasma_membrane.size=0.95; % fraction of longest dimension % data.organelleprops.cytoplasm.size=0.80; % data.organelleprops.vacuole.size=0.4; % data.organelleprops.microtubules.nuclspont=0.0012; % observed nucleations per square (cubic) micron per sec elseif data.iterations==0 % insert startup code here - use Restart button to jump to here %% setup MT size %if data.cellprops.cellsize(1)>25 % data=mtSETprops(data,'microtubules','size',0.01,'microtubules','growthrate',0.025); % data=mtSETprops(data,'microtubules','shrinkrate',0.005); %end else %id_micplm_p(:)=0; % clear %id_micplm_p(data.cellprops.Vol==data.organelleprops.cytoplasm.Label)=0.8; % set cytoplasm region to 1 %id_micplm_p(round(data.cellprops.cellsize(1)/3):end,:,:)=0; % then set right hand end back to zero %s_micplm_p(id_micplm_p>0.1)=0.1; %% limit spontaneous nucleation to a region specified by id_micplm_p % data.organelleprops.microtubules.nuclspont=id_micplm_p; %data.cellprops.colourType=0; % set to 1 if colour is to be specified by individual MT property %Work through all the microtubules updating properties depending on flags %Average number of MT's present is observed to be about 80 i.e. 80/300 square microns (say 1 micron thick %so ~0.25 per square (cubic) micron for i_MT=1:length(data.working.dyn.microtubules.Org) MT=data.working.dyn.microtubules.Org(i_MT); % MTtbox monitors ... % MT.Type % MT.Age % MT.PauseDuration % MT.TimeNucleated % MT.Alive=true; % MT.Growing=true; % MT.Shrinking=true; % MT.Catastrophe=false; % MT.BoundPLM=false; % MT.PLMBindVertNums=[]; % MT.BoundMic=false; % MT.MTBindVertNums=[]; % MT.BoundVac=false; % MT.VacBindVertNums=[]; % MT.Hit=struct('Type',,'ID',[]); % MT.HitMe=struct('Type',,'ID',[]); % MT.Props.growthrate % MT.Props.shrinkrate % MT.Props.maxbend % MT.Props.maxAge % MT.Props.nuclspont % MT.Props.nuclonMT % Make changes here, i.e. % diffs=diff(MT.Verts).^2; % calculate length of MT % MTlength=sum(sqrt(sum(diffs')'))*data.cellprops.micronsPerVoxelEdge; % microns % if MTlength>0.5 % MT.Props.nuclonMT=min(1,0.4*MTlength); % observed approx. 0.007 per micron per sec % else % MT.Props.nuclonMT=0; % end %ageMT=data.working.CellAge;% seconds %maxAgeColour=20; %MT.Props.FaceColor=[max(0,min(1,1-ageMT/maxAgeColour)), 0.5, max(0,min(1,ageMT/maxAgeColour))]; %if MT.BoundPLM && MT.Growing % hit plasma_membrane and aligned %elseif MT.BoundPLM && ~MT.Growing % hit plasma_membrane and NOT aligned %end %if MT.BoundMic && MT.Growing % hit another microtubule and aligned %elseif MT.BoundMic && ~MT.Growing % hit another microtubule and NOT aligned %end %if MT.BoundVac && MT.Growing % hit vacuole membrane and aligned %elseif MT.BoundVac && ~MT.Growing % hit vacuole membrane and NOT aligned %end % Keep the following % Clear flags from collision detector MT.BoundPLM=false; MT.BoundMic=false; MT.BoundVac=false; data.working.dyn.microtubules.Org(i_MT)=MT; end end % put factors back into structure for i=1:size( data.factorprops.Concentration,2) factname=lower(data.factorprops.Index2Name{i}); eval(['data.factorprops.Concentration(:,i)=',[factname,'_p(:);']]); end end % This space intentionally left blank. % Default factor parameters % Default organelle parameters % cell_wall.size =0.000000 % cell_wall.offset =0.500000 % cell_wall.micronthick =0.100000 % cell_wall.minvox =1.000000 % cell_wall.FaceColor =[1.000000,0.000000,1.000000,] % cell_wall.FaceAlpha =0.010000 % cell_wall.Label =-5.000000 % cell_wall.isLayer =1.000000 % cell_wall.Static =1.000000 % cell_wall.InUse =1.000000 %plasma_membrane.size =0.000000 %plasma_membrane.offset =0.500000 %plasma_membrane.micronthick =0.010000 %plasma_membrane.minvox =3.000000 %plasma_membrane.FaceColor =[1.000000,1.000000,0.000000,] %plasma_membrane.FaceAlpha =0.020000 %plasma_membrane.Label =-4.000000 %plasma_membrane.isLayer =1.000000 %plasma_membrane.Static =1.000000 %plasma_membrane.InUse =1.000000 % cytoplasm.size =0.000000 % cytoplasm.offset =0.500000 % cytoplasm.micronthick =1.000000 % cytoplasm.minvox =5.000000 % cytoplasm.FaceColor =[0.000000,1.000000,0.000000,] % cytoplasm.FaceAlpha =0.020000 % cytoplasm.Label =0.000000 % cytoplasm.isLayer =1.000000 % cytoplasm.Static =1.000000 % cytoplasm.InUse =1.000000 % microtubules.size =0.025000 % microtubules.minvoxel =3.000000 % microtubules.growthrate =0.100000 % microtubules.shrinkrate =0.010000 % microtubules.maxbend =40.000000 % microtubules.MaxAngle =20.000000 % microtubules.maxAge =0.000000 % microtubules.nuclspont =0.050000 % microtubules.nuclonMT =0.090000 % microtubules.probCatastrophe=0.300000 % microtubules.FaceColor =[0.000000,0.000000,1.000000,] % microtubules.FaceAlpha =0.400000 % microtubules.Label =-6.000000 % microtubules.isLayer =0.000000 % microtubules.Static =0.000000 % microtubules.InUse =1.000000 % vacuole.size =0.200000 % vacuole.offset =0.500000 % vacuole.micronthick =1.000000 % vacuole.minvox =0.000000 % vacuole.FaceColor =[1.000000,1.000000,0.000000,] % vacuole.FaceAlpha =0.300000 % vacuole.Label =-3.000000 % vacuole.isLayer =0.000000 % vacuole.Static =1.000000 % vacuole.InUse =1.000000 % Default cell parameters % cellprops.shape ='Rect:1:1:1' % cellprops.sheetmodel =0 % cellprops.maxLengthMicrons=10 % cellprops.secondsPerStep =1 % cellprops.micronsPerVoxelEdge=0.400000 % cellprops.cubicMicronsPerVoxel=0.064000 % cellprops.cellsize =[25,25,25,] % cellprops.colourType =1 % cellprops.Vol =[-1,-1,-1,-1, ... ] % cellprops.Smooth ='None' % cellprops.dynamic ='microtubules' % cellprops.bound_distance =5 % cellprops.collide_distance=10 % cellprops.% vacuole.Vol=struct % vacuole.EdgeVol=struct % cellprops.% cell_wall.Vol=struct % cell_wall.EdgeVol=struct % cellprops.% plasma_membrane.Vol=struct % plasma_membrane.EdgeVol=struct % cellprops.% cytoplasm.Vol=struct % cytoplasm.EdgeVol=struct % cytoplasm.Indexes=struct % cellprops.% Diameter.microtubules=struct % cellprops.% microtubules.Vol=struct % microtubules.Offsets=struct