%% test_id31_1_metrology.m

%% Clear Workspace and Close figures
clear; close all; clc;

%% Intialize Laplace variable
s = zpk('s');

%% Path for functions, data and scripts
addpath('./mat/'); % Path for Data
addpath('./src/'); % Path for functions
addpath('./STEPS/'); % Path for STEPS
addpath('./subsystems/'); % Path for Subsystems Simulink files

%% Data directory
data_dir = './mat/';

%% Colors for the figures
colors = colororder;

%% Frequency Vector
freqs = logspace(log10(1), log10(2e3), 1000);

%% Sampling Time
Ts = 1e-4;

%% Specifications for Experiments
specs_dz_peak = 50; % [nm]
specs_dy_peak = 100; % [nm]
specs_ry_peak = 0.85; % [urad]
specs_dz_rms = 15; % [nm RMS]
specs_dy_rms = 30; % [nm RMS]
specs_ry_rms = 0.25; % [urad RMS]

%% Geometrical parameters of the metrology system
H = 150e-3;
l1 = (150-48-42)*1e-3;
l2 = (76.2+48+42-150)*1e-3;

% Computation of the Transformation matrix
Hm = [ 0  1  0 -l2  0;
       0  1  0  l1  0;
      -1  0  0  0  -l2;
      -1  0  0  0   l1;
       0  0 -1  0   0];

%% Angular alignment
% Load Data
data_it0 = h5scan(data_dir, 'alignment', 'h1rx_h1ry', 1);
data_it1 = h5scan(data_dir, 'alignment', 'h1rx_h1ry_0002', 3);
data_it2 = h5scan(data_dir, 'alignment', 'h1rx_h1ry_0002', 5);

% Offset wrong points
i_it0 = find(abs(data_it0.Rx_int_filtered(2:end)-data_it0.Rx_int_filtered(1:end-1))>1e-5);
data_it0.Rx_int_filtered(i_it0+1:end) = data_it0.Rx_int_filtered(i_it0+1:end) + data_it0.Rx_int_filtered(i_it0) - data_it0.Rx_int_filtered(i_it0+1);
i_it1 = find(abs(data_it1.Rx_int_filtered(2:end)-data_it1.Rx_int_filtered(1:end-1))>1e-5);
data_it1.Rx_int_filtered(i_it1+1:end) = data_it1.Rx_int_filtered(i_it1+1:end) + data_it1.Rx_int_filtered(i_it1) - data_it1.Rx_int_filtered(i_it1+1);
i_it2 = find(abs(data_it2.Rx_int_filtered(2:end)-data_it2.Rx_int_filtered(1:end-1))>1e-5);
data_it2.Rx_int_filtered(i_it2+1:end) = data_it2.Rx_int_filtered(i_it2+1:end) + data_it2.Rx_int_filtered(i_it2) - data_it2.Rx_int_filtered(i_it2+1);

% Compute circle fit and get radius
[~, ~, R_it0, ~] = circlefit(1e6*data_it0.Rx_int_filtered, 1e6*data_it0.Ry_int_filtered);
[~, ~, R_it1, ~] = circlefit(1e6*data_it1.Rx_int_filtered, 1e6*data_it1.Ry_int_filtered);
[~, ~, R_it2, ~] = circlefit(1e6*data_it2.Rx_int_filtered, 1e6*data_it2.Ry_int_filtered);

%% Rx/Ry alignment of the spheres using the micro-station
figure;
hold on;
plot(1e6*data_it0.Rx_int_filtered, 1e6*data_it0.Ry_int_filtered, '-', ...
     'DisplayName', sprintf('$R_0 = %.0f \\mu$rad', R_it0))
plot(1e6*data_it1.Rx_int_filtered, 1e6*data_it1.Ry_int_filtered, '-', ...
     'DisplayName', sprintf('$R_1 = %.0f \\mu$rad', R_it1))
plot(1e6*data_it2.Rx_int_filtered, 1e6*data_it2.Ry_int_filtered, '-', 'color', colors(5,:), ...
     'DisplayName', sprintf('$R_2 = %.0f \\mu$rad', R_it2))
hold off;
xlabel('$R_x$ [$\mu$rad]'); ylabel('$R_y$ [$\mu$rad]');
axis equal
legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 1);
xlim([-600, 300]);
ylim([-100, 800]);

%% Eccentricity alignment
% Load Data
data_it0 = h5scan(data_dir, 'alignment', 'h1rx_h1ry_0002', 5);
data_it1 = h5scan(data_dir, 'alignment', 'h1dx_h1dy', 1);

% Offset wrong points
i_it0 = find(abs(data_it0.Dy_int_filtered(2:end)-data_it0.Dy_int_filtered(1:end-1))>1e-5);
data_it0.Dy_int_filtered(i_it0+1:end) = data_it0.Dy_int_filtered(i_it0+1:end) + data_it0.Dy_int_filtered(i_it0) - data_it0.Dy_int_filtered(i_it0+1);

% Compute circle fit and get radius
[~, ~, R_it0, ~] = circlefit(1e6*data_it0.Dx_int_filtered, 1e6*data_it0.Dy_int_filtered);
[~, ~, R_it1, ~] = circlefit(1e6*data_it1.Dx_int_filtered, 1e6*data_it1.Dy_int_filtered);

%% Dx/Dy alignment of the spheres using the micro-station
figure;
hold on;
plot(1e6*data_it0.Dx_int_filtered, 1e6*data_it0.Dy_int_filtered, '-', ...
     'DisplayName', sprintf('$R_0 = %.0f \\mu$m', R_it0))
plot(1e6*data_it1.Dx_int_filtered, 1e6*data_it1.Dy_int_filtered, '-', ...
     'DisplayName', sprintf('$R_1 = %.0f \\mu$m', R_it1))
hold off;
xlabel('$D_x$ [$\mu$m]'); ylabel('$D_y$ [$\mu$m]');
axis equal
legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 1);
xlim([-1, 21]);
ylim([-8, 14]);

%% Estimated acceptance of the metrology
% This is estimated by moving the spheres using the micro-hexapod

% Dx
data_dx = h5scan(data_dir, 'metrology_acceptance_new_align', 'dx', 1);

dx_acceptance = zeros(5,1);

for i = [1:size(dx_acceptance, 1)]
    % Find range in which the interferometers are measuring displacement
    dx_di = diff(data_dx.(sprintf('d%i', i))) == 0;
    if sum(dx_di) > 0
        dx_acceptance(i) = data_dx.h1tx(find(dx_di(501:end), 1) + 500) - ...
                           data_dx.h1tx(find(flip(dx_di(1:500)), 1));
    else
        dx_acceptance(i) = data_dx.h1tx(end) - data_dx.h1tx(1);
    end
end

% Dy
data_dy = h5scan(data_dir, 'metrology_acceptance_new_align', 'dy', 1);

dy_acceptance = zeros(5,1);

for i = [1:size(dy_acceptance, 1)]
    % Find range in which the interferometers are measuring displacement
    dy_di = diff(data_dy.(sprintf('d%i', i))) == 0;
    if sum(dy_di) > 0
        dy_acceptance(i) = data_dy.h1ty(find(dy_di(501:end), 1) + 500) - ...
                           data_dy.h1ty(find(flip(dy_di(1:500)), 1));
    else
        dy_acceptance(i) = data_dy.h1ty(end) - data_dy.h1ty(1);
    end
end

% Dz
data_dz = h5scan(data_dir, 'metrology_acceptance_new_align', 'dz', 1);

dz_acceptance = zeros(5,1);

for i = [1:size(dz_acceptance, 1)]
    % Find range in which the interferometers are measuring displacement
    dz_di = diff(data_dz.(sprintf('d%i', i))) == 0;
    if sum(dz_di) > 0
        dz_acceptance(i) = data_dz.h1tz(find(dz_di(501:end), 1) + 500) - ...
                           data_dz.h1tz(find(flip(dz_di(1:500)), 1));
    else
        dz_acceptance(i) = data_dz.h1tz(end) - data_dz.h1tz(1);
    end
end

%% Interferometer noise estimation
data = load("test_id31_interf_noise.mat");

Ts = 1e-4;
Nfft = floor(5/Ts);
win = hanning(Nfft);
Noverlap = floor(Nfft/2);

[pxx_int, f] = pwelch(detrend(data.d, 0), win, Noverlap, Nfft, 1/Ts);

% Uncorrelated noise: square root of the sum of the squares
pxx_cart = pxx_int*sum(inv(Hm).^2, 2)';

rms_dxy = sqrt(trapz(f(f>1), pxx_cart((f>1),1))); % < 0.3 nm RMS
rms_dz  = sqrt(trapz(f(f>1), pxx_cart((f>1),3))); % < 0.3 nm RMS
rms_rxy = sqrt(trapz(f(f>1), pxx_cart((f>1),4))); % 5 nrad RMS

figure;
hold on;
plot(f, sqrt(pxx_cart(:,1)), 'DisplayName', sprintf('$D_{x,y}$, %.1f nmRMS', rms_dxy));
plot(f, sqrt(pxx_cart(:,3)), 'DisplayName', sprintf('$D_{z}$, %.1f nmRMS', rms_dz));
plot(f, sqrt(pxx_cart(:,4)), 'DisplayName', sprintf('$R_{x,y}$, %.1f nradRMS', rms_rxy));
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
xlabel('Frequency [Hz]'); ylabel('ASD $\left[\frac{nm,\ nrad}{\sqrt{Hz}}\right]$')
xlim([1, 1e3]); ylim([1e-3, 1]);
leg = legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 1);
leg.ItemTokenSize(1) = 15;

%% X-Y scan with the micro-hexapod, and record of the vertical interferometer
data = h5scan(data_dir, 'metrology_acceptance', 'after_int_align_meshXY', 1);

x = 1e3*detrend(data.h1tx, 0); % [um]
y = 1e3*detrend(data.h1ty, 0); % [um]
z = 1e6*data.Dz_int_filtered - max(data.Dz_int_filtered); % [um]

mdl = scatteredInterpolant(x, y, z);
[xg, yg] = meshgrid(unique(x), unique(y));
zg = mdl(xg, yg);

% Fit a sphere to the data
[sphere_center,sphere_radius] = sphereFit(1e-3*[x, y, z]);

%% XY mapping of the Z measurement by the interferometer
figure;
[~,c] = contour3(xg,yg,zg,30);
c.LineWidth = 3;
xlabel('$D_x$ [$\mu$m]');
ylabel('$D_y$ [$\mu$m]');
zlabel('$D_z$ [$\mu$m]');
zlim([-1, 0]);
xticks(-100:50:100); yticks(-100:50:100); zticks(-1:0.2:0);