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								2018-10-15 - Marc/analysis-marc/IMG_20181015_155505.jpg
									
									
									
									
									
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% Title: id31 microstation in EXP hutch
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% Date: 15 october 2018
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% Description: measure on id31 microstation in exp hutch
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% FS: =256Hz
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%% 15 october 2018 --------------
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% L4-c sensor at 276V/m/s
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% ch1: Tilt frame Z upstream
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% ch2: Tilt frame Z downstream
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% ch3: Ty frame Y
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% TY motor off --> on at ~300sec
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% capt1
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% Tilt OFF --> ON at ~ 326sec
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% capt2
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% ----------------------------
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% ch1: Hexa Z
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% ch2: Tilt frame Z downstream
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% ch3: Ty frame Y
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%
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% Hexa ON --> OFF at ~ 406sec  (tilt ON)
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% capt3
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%
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% Hexa OFF - Slip ring ON at ~ 300sec then spindle ON at ~ 620sec (tilt ON)
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% capt4
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%% Marble measurements ----
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% ch1 floor Z
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% ch2 marble Z
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% ch3 floor Y
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% ch4 marble Y
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% capt5
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%% PARAMETERS
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beamline='ID31 Nanostation ';
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% --------------------------------
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%%----------OROS -----------------
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ch_max=16;
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% --------------------------------
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mult=1e6/276*173;  % --> m/s to micron/s and sensitivity correction
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nyqhp=2.56; % nyquist
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f_cut=0.5; % cut frequency for high pass filter
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t_win=4; % window length in sec
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t_ovlp=3; % overlap window in sec
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d=1; % distance between vertical sensors.
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warning off MATLAB:divideByZero
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% specify capt # for which to run this
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capt=1:5;
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% specify channels for which shut correction must be applied
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% shunt_ch_a=1:3;
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% shunt_ch_b=1:4;
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% in case of hammer inpacts specify capt # where it doesnt occur
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no_hammer=1:5;
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%no_hammer=0;
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% specify hammer channel (or ch to find peak due to impacts)
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shock_ch=1;
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%% main loop --------
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% ------------------
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for i=capt
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    eval(['load Measurement',num2str(i)])
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    freq_max=Track1_TrueBandWidth;
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    dts=1/(freq_max*nyqhp);
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    freq=linspace(0,freq_max,t_win*freq_max);
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    wo=2*pi*freq;
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    for k=1:ch_max
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    vname=['Track',num2str(k)];
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    array_exist(k)=ismember(vname,who);
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    end
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    non_zero=find(array_exist);
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    for z=non_zero(1):length(non_zero)
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    track_nb=['Track',num2str(z)]';
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    eval(['data(:,z)=Track',num2str(z),';']);
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    end
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    c=data*mult;
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    %-------------
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    nbch=size(c,2);
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    %-------------
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    r=length(c);
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    if r/2~=fix(r/2)    % loop to test for odd or even nb of samples
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       c=c(1:r-1,:);   % take only even
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    else
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    end
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    %------------------------------
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    time=linspace(0,length(c)*dts,length(c));
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    for j=nbch %shunt_ch
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        [c(:,j),c_shut]=shut_c(c(:,j),1/dts);   % correct for shunt
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    end
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    % compute differential level when necessary and store it as 4th column
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    if i<3
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    c(:,4)=(c(:,2)-c(:,1))/d; % divide by d to obtain Theta Y angle
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    end
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     b=find(no_hammer==i); %      if i==1 | i==2 | i==6
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     if b~=0
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         [psd_v,integ_v,psd_d,integ_d]=integrated_psd(c,t_win,t_ovlp,nyqhp,dts);
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         [frz_cut,crsp,pwsp,coherz,nsp]=fqresp(c,1,t_win,t_ovlp,nyqhp,dts);
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         [frh_cut,crsp,pwsp,coherz,nsp]=fqresp(c,3,t_win,t_ovlp,nyqhp,dts);
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     else
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        thresh=0.5;  % threshold of max value
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        sep=2.5;  % separation minimum of peaks in sec
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        pre_ev=2; % pre event delay in sec
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        pos_ev=2; % post event delay in sec
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        [ti,t_impact]=findpeaks(c(:,shock_ch),'minpeakheight',max(c(:,shock_ch))*thresh,'minpeakdistance',ceil(sep/dts));
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        % find times at which there are impacts (threshold of max and separated by sep sec)
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        psd_v=zeros((pre_ev+pos_ev)/dts/nyqhp,nbch);
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        psd_d=zeros((pre_ev+pos_ev)/dts/nyqhp,nbch);
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        frz_cut=zeros((pre_ev+pos_ev)/dts/nyqhp,nbch);
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        for k=1:length(t_impact)
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            ibeg=fix(t_impact(k)-(pre_ev/dts));
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            iend=fix(t_impact(k)+(pos_ev/dts));
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            freq_s=linspace(0,freq_max,t_win/2*freq_max);
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            if ibeg>1 && iend<length(c)        % eliminate indexes outside data range
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                [psd,integ_v,psd_int,integ_d]=integrated_psd(c(ibeg:iend,:),t_win,t_ovlp,nyqhp,dts);
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                psd_v=psd+psd_v;
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                psd_d=psd_int+psd_d;
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                [frz,crsp,pwsp,coherz,nsp]=fqresp(c(ibeg:iend,:),shock_ch,t_win,t_ovlp,nyqhp,dts);
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                frz_cut=frz+frz_cut;
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            end
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        end
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        psd_v=psd_v/length(t_impact);
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        psd_d=psd_d/length(t_impact);
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        frz_cut=frz_cut/length(t_impact);
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     end
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    drms=max(integ_d);  % compute rms level
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    dc=hpfint(c,f_cut,dts);    % filter and integrate in time domain
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    dppc=hpdpp(dc,t_win,t_ovlp,1,dts);  % compute peak to peak level
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   % tranfer function, cross spectrum, power spectr. and coherence w.r.t. ch1
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    %----------------------------------------------------------------------------------------------------
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   eval(['c',num2str(i),'=c;'])
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   eval(['dc',num2str(i),'=dc;'])
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   eval(['dppc',num2str(i),'=dppc;'])
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   eval(['drms',num2str(i),'=drms;'])
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   eval(['psd_v',num2str(i),'=psd_v;'])  % already integrated in OROS
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   eval(['psd_d',num2str(i),'=psd_d;'])
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   eval(['integ_v',num2str(i),'=integ_v;'])
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   eval(['integ_d',num2str(i),'=integ_d;'])
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   eval(['frz',num2str(i),'=frz_cut;'])
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   eval(['frh',num2str(i),'=frh_cut;'])
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%    eval(['frx',num2str(i),'=frx;'])
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%    eval(['coherz',num2str(i),'=coherz;'])
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   eval(['time',num2str(i),'=time;'])
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   clear data c dc psd psd_v psd_d time c_shut % clean up the mess
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end
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%% Plot settings for colors and linewidth----
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proname(1)={'LineWidth'};
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proname(2)={'Color'};
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proname(3)={'LineStyle'};
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val(1,1) = {.5}   ;val(1,2) = {[0.6 0.2 1]}     ;val(1,3) = {'-'};
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val(2,1) = {2}    ;val(2,2) = {[0 0 1]}         ;val(2,3) = {'-'};
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val(3,1) = {2}    ;val(3,2) = {[0.25 0.9 0.65]} ;val(3,3) = {'-'};
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val(4,1) = {2}    ;val(4,2) = {[0 1 0]}         ;val(4,3) = {'-'};
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val(5,1) = {0.5}  ;val(5,2) = {[1 0.4 0.4]}     ;val(5,3) = {'-'};
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val(6,1) = {2}    ;val(6,2) = {[1 0 0]}         ;val(6,3) = {'-'};
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val(7,1) = {1}    ;val(7,2) = {[0.8 0.8 0.8]}   ;val(7,3) = {'-'};
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val(8,1) = {2}    ;val(8,2) = {[0.1 0.1 0.2]}   ;val(8,3) = {'-'};
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val(9,1) = {1}    ;val(9,2) = {[0.7 0.8 0.4]}   ;val(9,3) = {'-'};
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val(10,1) = {2}   ;val(10,2) = {[0.7 0.8 0.2]}  ;val(10,3) = {'-'};
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val(11,1) = {1}   ;val(11,2) = {[0.9 0.7 0.35]} ;val(11,3) = {'-'};
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val(12,1) = {2}   ;val(12,2) = {[1 0.8 0.3]}    ;val(12,3) = {'-'};
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val(13,1) = {1}   ;val(13,2) = {[0.5 0.4 0.3]}  ;val(13,3) = {'-'};
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val(14,1) = {2}   ;val(14,2) = {[0.5 0.3 0.2]}  ;val(14,3) = {'-'};
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%% PLOT legends, titles,...
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xlab1='Frequency in Hz';
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xlab2='Time in sec';
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ylab1='Amplification';
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ylab2='PSD in $\frac{\mu{}m^{2}}{Hz}$';
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ylab3='PSD in $\frac{\mu{}m s)^{2}/Hz';
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ylab4='Displacement in ${\mu{}m}$';
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ylab5='Displacement in \mum';
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ylab7='Coherence';
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font_s=14;
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% ---------------------------------
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% tit_1=[beamline,' - Amplification wrt Floor (Z)'];
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% tit_2=[beamline,' - Amplification wrt Floor (Y)'];
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% tit_3=[beamline,' - Amplification wrt Floor (X)'];
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tit_4=[beamline,' - Vertical (Z) PSD'];
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tit_7=[beamline,' - Horizontal (X) PSD'];
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tit_6=[beamline,' - Horizontal (Y) PSD'];
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legend1=['Floor','Marble','Location','NorthEast'];
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% legend2=['''Floor OFF'',''Frame EM OFF'',''Floor ON'',''Frame EM ON'',''Location'',''NorthEast'''];
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% legend3=['''EM ON'',''EM OFF'',''Location'',''NorthWest'''];
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%% Response of Marble - Y
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h1 = newFigure(16,12);
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h=semilogy(freq,abs([psd_d5(:,[3 4])]));
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set(h,proname,val([1 6],1:3))
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eval(['leg1 = legend(',legend1,'); set(leg1, ''Interpreter'', ''latex'')'])
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titlabel_font(tit_6,xlab1,ylab2,font_s);
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axis([0 100 1e-11 1e-1])
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grid
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saveas(gcf,'psd_marble_y','fig')
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print -dpng psd_marble_y
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exportFigure(h1,'psd_marble_y', 'pdf')
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%% Response of Marble - Z
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h1 = newFigure(16,12);
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h=semilogy(freq,abs([psd_d5(:,[1 2])]));
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set(h,proname,val([1 6],1:3))
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eval(['leg1 = legend(',legend1,'); set(leg1, ''Interpreter'', ''latex'')'])
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titlabel_font(tit_4,xlab1,ylab2,font_s);
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axis([0 100 1e-11 1e-1])
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grid
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saveas(gcf,'psd_marble_z','fig')
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print -dpng psd_marble_z
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exportFigure(h1,'psd_marble_z', 'pdf')
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%% spectrograms
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spt = strogram_h(c1(:,3),4,3,1/256,2.56,'ID31 nanostation Ty Y - Ty ON @ 300s',1,30,4,12,'egend1','legend2');
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exportFigure(h1,'spectrogram_Ty_y', 'pdf')
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spt = strogram_h(c2(:,1),4,3,1/256,2.56,'ID31 nanostation Tilt Z - Tilt ON @ 320s',1,30,4,12,'egend1','legend2');
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exportFigure(h1,'spectrogram_Tilt_z', 'pdf')
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spt = strogram_h(c3(:,1),4,3,1/256,2.56,'ID31 nanostation Hexa Z - Hexa OFF @ 410s',1,30,4,12,'egend1','legend2');
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exportFigure(h1,'spectrogram_hexa_y', 'pdf')
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spt = strogram_h(c4(:,1),4,3,1/256,2.56,'ID31 nanostation Hexa Z - SlipRing ON @ 300s; Spindle ON @ 620s',1,30,4,12,'egend1','legend2');
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exportFigure(h1,'spectrogram_slip_spindle_y', 'pdf')
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								2018-10-15 - Marc/analysis-marc/info.txt
									
									
									
									
									
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contient les mesures de l'effet des diff<66>rents moteurs ON/OFF, j'ai sorti qq spectrogrammes qui montrent bien que c'est la spindle qui a le plus d'effet
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+ une mesure de la r<>ponse du marbre sans excitation.
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Le capteur Y sur le marbre semble faible en basse fr<66>quence (marbre pas de niveau peut <20>tre) 
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								2018-10-15 - Marc/analysis-marc/spectrogram_hexa_y.pdf
									
									
									
									
									
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								2018-10-15 - Marc/analysis-marc/spectrogram_slip_spindle_y.pdf
									
									
									
									
									
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