15 files changed, 507 insertions, 3 deletions
diff --git a/opa/autotune_preamp.png b/opa/autotune_preamp.png
new file mode 100644
index 0000000..570d4fb
--- /dev/null
+++ b/opa/autotune_preamp.png
diff --git a/opa/c2.png b/opa/c2.png
new file mode 100644
index 0000000..a546d44
--- /dev/null
+++ b/opa/c2.png
diff --git a/opa/chapter.tex b/opa/chapter.tex
index b92f62a..75459b5 100644
--- a/opa/chapter.tex
+++ b/opa/chapter.tex
@@ -1,4 +1,7 @@
-\chapter{A robust, fully automated algorithm to collect high quality OPA tuning curves}
+% TODO: DONALDSON HAS AUTOMATED OPA TUNING DOWN?
+
+\chapter{A robust, fully automated algorithm to collect high quality OPA tuning
+  curves} \label{cha:opa}
 
 \begin{dquote}
   Principle design features of the new EVV 2DIR optical delivery system include the following:
@@ -13,6 +16,138 @@
 
 \clearpage
 
-This chapter pasted from publication...
+In frequency-domain Multi-Resonant Coherent Multidimensional Spectroscopy (MR-CMDS), automated
+Optical Parametric Amplifiers (OPAs) are used to actively scan excitation color axes. %
+To accomplish these experiments, exquisite OPA performance is required. %
+During the experiment, motors inside the OPA move to pre-recorded positions to optimize output at
+the desired color. %
+Parametric conversion (``mixing'') strategies are now readily avalible, extending the 800 nm pumped
+OPA tuning range into the visible, near-infrared, and mid-infrared. %
+
+OPAs are very sensitive to changes in upstream lasers and lab conditions, so OPA tuning is
+regularly required. %
+Manual OPA tuning can easily take a full day. %
+Automated OPA tuning makes OPA upkeep easier, faster and more reproducible, facilitating frequency
+domain experiments. %
+The major challenges in automated OPA tuning are:
+\begin{enumerate}
+  \item Expensive to take high resoltion data.
+  \item Need smooth curves for interpolation, especially at edges where output is low.
+  \item Optimization metrics are not necessarily separable along motor dimensions.
+\end{enumerate}
+
+\section{Introduction}  % =========================================================================
+
+\section{TOPAS-C}  % ==============================================================================
+
+% TODO: introduction to the internal design of the OPA
+
+\section{Preamp}  % ===============================================================================
+
+\begin{figure}
+  \includegraphics[width=\textwidth]{opa/preamp}
+  \caption{
+    CAPTION TODO
+  }
+  \label{opa:fig:preamp}
+\end{figure}
+
+In TOPAS-C OPAs, a small portion of input light is used to generate a signal seed in a BBO crystal
+``C1''.  %
+A motorized delay stage ``D1'' is used to temporally overlap a particular color in chirped white
+light with 800 nm pump.  %
+C1 angle is tuned to optimize phase matching.  %
+Measured seed intensity and color for all combinations of C1 and D1 position are shown in
+\autoref{fig:preamp}.  %
+
+Output color and intensity are not separable along the preamp motor axes.  %
+We therefore use a multidimensional fitting strategy to find the best preamp motor positions, as
+shown below.  %
+
+% TODO: procedure
+
+\begin{figure}
+  \includegraphics[width=\linewidth]{opa/autotune_preamp}
+  \caption{
+    CAPTION TODO
+  }
+  \label{opa:fig:autotune_preamp}
+\end{figure}
+
+A representative preamp tune procedure output image is shown in \autoref{fig:autotune_preamp}.  %
+The thick black line is the final output curve.  %
+The dark grey lines are the contours of constant color.  %
+The colorbar shows the Delaunay-interpolated intensity values for each motor position.  %
+
+Preamp tuning takes less than 20 minutes, in large part due to a NIR array detector which collects
+the full spectrum at each motor position.  %
+
+\section{Poweramp}  % =============================================================================
+
+\begin{figure}
+  \includegraphics[width=\linewidth]{opa/poweramp}
+  \caption{
+    CAPTION TODO
+  }
+  \label{opa:fig:poweramp}
+\end{figure}
+
+Once generated, the seed goes on to be amplified in a second BBO crystal ``C2'' with the rest of
+the 800 nm pump.  %
+Optimizing this amplification step is primarily a matter of setting C2 angle.  %
+A small delay correction ``D2'' is necessary to account for dispersion in the seed optics.  %
+To fully explore poweramp behavior, we need to tak a C2-D23 scan for each seed color.  %
+Measured output intensity and color in this 3D space is represented in \autoref{fig:poweramp}.  %
+Note that the motor axes are scans about the previously recorded tuning curve value.  %
+
+The best position (zero displacement along both axes) is chosen to maximize output intensity while
+keeping the output color identical to the seed color.  %
+Optimizing for zero detuining rather than simply for output intensity has led to better OPA
+performance and stability.  %
+Like in the preamp case, color and intensity are not fully separable along the poweramp motor
+dimensions (this is especially true at the edge output colors).  %
+In the poweramp, the increased dimensionaity makes it too expensive to do a full multidimensional
+tuning procedure.  %
+Instead we emply an iterative procedure as diagrammed below.  %
+
+% TODO: procedure
+
+We always end the iteration(s) with C2 so that the OPA's color calibration is as good as
+possible.  %
+Typically only one iteration is required but multiple iterations may be necessary if dramatic OPA
+realignment has occurred.  %
+In total, poweramp tuning typically takes less than 1 hour. %
+Representative procedure output images for D2 (\autoref{op:fig:d2}) and C2 (\autoref{opa:fig:c2})
+are shown.  %
+
+\begin{figure}
+  \includegraphics[width=\textwidth]{opa/d2}
+  \caption{
+    CAPTION TODO
+  }
+  \label{opa:fig:d2}
+\end{figure}
+
+\begin{figure}
+  \includegraphics[width=\textwidth]{opa/c2}}
+  \caption{
+    CAPTION TODO
+  }
+  \label{opa:fig:c2}
+\end{figure}
+
+For the D2 figure, the lower panel shows the intensity of the data taken.  %
+Note the thick grey line, which represents the chosen points before the final spline step.  %
+The top panel compares the old tuning curve (thin) with the output tuning curve (thick).  %
+For the C2 image, the bottom panel represents the color of each fit mapped onto detuning.  %
+Each separate marker color represents a different setpoint.  %
+As with D2, the C2 upper panel compares the old tuning curve (thin black) with the output tuning
+curve (colored X's).  %
+
+\section{Mixers}  % ===============================================================================
+
+\section{Generalizability}  % =====================================================================
+
+\section{Future directions}  % ====================================================================
 
-% DONALDSON HAS AUTOMATED OPA TUNING DOWN?
-\ No newline at end of file
+% TODO: discuss Attune
+\ No newline at end of file
diff --git a/opa/curve.png b/opa/curve.png
new file mode 100644
index 0000000..6290ce0
--- /dev/null
+++ b/opa/curve.png
diff --git a/opa/d2.png b/opa/d2.png
new file mode 100644
index 0000000..3c1cf87
--- /dev/null
+++ b/opa/d2.png
diff --git a/opa/figures.py b/opa/figures.py
new file mode 100644
index 0000000..efc8d45
--- /dev/null
+++ b/opa/figures.py
@@ -0,0 +1,369 @@
+### import ####################################################################
+
+
+import os
+import collections
+
+import numpy as np
+
+import matplotlib
+import matplotlib.pyplot as plt
+matplotlib.rcParams['font.size'] = 14
+
+import WrightTools as wt
+import WrightData as wd
+
+
+### define ####################################################################
+
+
+width = 14
+
+gd_path = wt.kit.get_path_matching('Google Drive')
+
+data_path = os.path.join(gd_path, 'Blaise', 'unpublished Thompson - Automated OPA Tuning')
+
+
+### recent examples ###########################################################
+
+
+if False:
+    # prepare figure
+    wf = 0.01
+    cols = ['cbar', 1, 1, 'cbar']
+    aspects = [[[0, 1], 0.5]]
+    fig, gs = wt.artists.create_figure(width=width/2., nrows=2, cols=cols, hspace=0.5, wspace=0.5, aspects=aspects)
+    # dOD colorbar
+    cax = plt.subplot(gs[:, 0])
+    limit = 0.05
+    ticks = np.linspace(-limit, limit, 5)
+    wt.artists.plot_colorbar(cax=cax, cmap='signed', label='dOD', ticklocation='left', ticks=ticks)
+    # example 1 (MoS2 TA)
+    ax = plt.subplot(gs[0, 1])
+    p = os.path.join(gd_path, 'MX2', 'CMDS', '2016.05.26', 'SCAN [w2, wmw1, d2] 2016.05.30 18_17_55 TA', 'SCAN [w2, wmw1, d2] 2016.05.30 18_17_55 TA.data')
+    data = wt.data.from_PyCMDS(p, verbose=False)
+    data = data.chop('w2', 'wmw1', verbose=False)[11]
+    data = data.split('wmw1', 13250, verbose=False)[1]
+    data.smooth(2)
+    data.dOD('dI', 'I')
+    data.dI.clip(-limit, limit)
+    xi = data.axes[1].points
+    yi = data.axes[0].points
+    zi = data.channels[0].values
+    X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+    ax.pcolor(X, Y, Z, vmin=-limit, vmax=limit, cmap=wt.artists.colormaps['signed'])
+    wt.artists.diagonal_line(xi, yi)
+    ax.grid()
+    plt.setp(ax.get_xticklabels(), visible=False)
+    plt.setp(ax.get_yticklabels(), visible=False)
+    ax.set_xlabel('$\\mathsf{\\bar\\nu_{probe}=\\bar\\nu_{m}}$', fontsize=18)
+    ax.set_ylabel('$\\mathsf{\\bar\\nu_{pump}}$', fontsize=18)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_ylim(yi.min(), yi.max())
+    # example 2 (MoS2 TrEE)
+    ax = plt.subplot(gs[0, 2])
+    data = wd.get('2015.12 Czech', check_remote=False)['movie']
+    data = data.chop('w1', 'd2')[29]
+    data.transpose()
+    xi = data.axes[1].points
+    yi = data.axes[0].points
+    zi = data.channels[0].values
+    X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+    ax.pcolor(X, Y, Z, cmap=wt.artists.colormaps['default'])
+    ax.grid()
+    ax.axhline(0, c='k', lw=1)
+    ax.axvline(data.w2.points, c='k', lw=4, alpha=0.25)
+    plt.setp(ax.get_xticklabels(), visible=False)
+    plt.setp(ax.get_yticklabels(), visible=False)
+    ax.set_xlabel('$\\mathsf{\\bar\\nu_{1}=\\bar\\nu_{m}}$', fontsize=18)
+    ax.set_ylabel('$\\mathsf{\\tau_{21}}$', fontsize=18)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_ylim(yi.min(), yi.max())
+    # example 3 (PbSe TrEE)
+    ax = plt.subplot(gs[1, 1])
+    data = wt.data.from_pickle('PbSe.p')
+    data = data.chop('w2', 'w1')[12]
+    xi = data.axes[1].points
+    yi = data.axes[0].points
+    zi = data.channels[0].values
+    zi -= zi.min()
+    zi += 0.001
+    zi /= zi.max()
+    zi **= 0.5
+    X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+    ax.pcolor(X, Y, Z, cmap=wt.artists.colormaps['default'])
+    wt.artists.diagonal_line(xi, yi)
+    ax.grid()
+    plt.setp(ax.get_xticklabels(), visible=False)
+    plt.setp(ax.get_yticklabels(), visible=False)
+    ax.set_xlabel('$\\mathsf{\\bar\\nu_{1}=\\bar\\nu_{m}}$', fontsize=18)
+    ax.set_ylabel('$\\mathsf{\\bar\\nu_{2}}$', fontsize=18)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_ylim(yi.min(), yi.max())
+    # example 4 (TRSF)
+    ax = plt.subplot(gs[1, 2])
+    data = wd.get('2013.10 Boyle', check_remote=False)['full 2D TRSF']
+    xi = data.axes[1].points
+    yi = data.axes[0].points
+    zi = data.channels[0].values
+    X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+    ax.pcolor(X, Y, Z, cmap=wt.artists.colormaps['default'])
+    wt.artists.diagonal_line(xi, yi)
+    ax.grid()
+    plt.setp(ax.get_xticklabels(), visible=False)
+    plt.setp(ax.get_yticklabels(), visible=False)
+    ax.set_xlabel('$\\mathsf{\\bar\\nu_{1}}$', fontsize=18)
+    ax.set_ylabel('$\\mathsf{\\bar\\nu_{2}}$', fontsize=18)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_ylim(yi.min(), yi.max())
+    # homodyne colorbar
+    cax = plt.subplot(gs[:, -1])
+    wt.artists.plot_colorbar(cax=cax, label='amplitude')
+    # finish
+    plt.savefig('frequency domain examples.png', dpi=300, transparent=True, pad_inches=1)
+    plt.close(fig)
+
+    
+### curve #####################################################################
+
+
+if False:
+    # prepare figure
+    fig, gs = wt.artists.create_figure(width=width/2., nrows=2, cols=[1],
+                                       default_aspect=0.3)
+    # get curve
+    d = os.path.join(gd_path, 'Development', 'OPA tuning', 'tuning records', 'TOPAS-C 10743', 'signal', '2016.05.28', 'OPA1 (10743) curves')
+    curves = [os.path.join(d, 'OPA1 (10743) base - 2016.05.28 12_56_14.crv'),
+              os.path.join(d, 'OPA1 (10743) mixer1 - 2015.11.09'),
+              os.path.join(d, 'OPA1 (10743) mixer2 - 2016.05.15 10_23_48'),
+              os.path.join(d, 'OPA1 (10743) mixer3 - 2013.06.01'),]
+    curve = wt.tuning.curve.from_TOPAS_crvs(curves, 'TOPAS-C', 'NON-NON-NON-Sig')
+    # preamp
+    ax = plt.subplot(gs[0, 0])
+    plt.setp(ax.get_xticklabels(), visible=False)
+    ax.grid()
+    ax.set_xticks([1200, 1400, 1600])
+    # C1
+    ax.scatter(curve.colors, curve.motors[0].positions, c='b', edgecolor='none')
+    ax.plot(curve.colors, curve.motors[0].positions, c='b', lw=2)
+    gone = [0, 7]
+    for i, tl in enumerate(ax.get_yticklabels()):
+        tl.set_color('b')
+        if i in gone:
+            tl.set_visible(False)
+    ax.set_ylabel('C1 (deg)', color='b', fontsize=18)
+    # D1
+    ax = ax.twinx()
+    ax.scatter(curve.colors, curve.motors[1].positions, c='r', edgecolor='none')
+    ax.plot(curve.colors, curve.motors[1].positions, c='r', lw=2)
+    gone = [5]
+    for i, tl in enumerate(ax.get_yticklabels()):
+        tl.set_color('r')
+        if i in gone:
+            tl.set_visible(False)
+    ax.set_ylabel('D1 (mm)', color='r', fontsize=18)
+    # poweramp
+    ax = plt.subplot(gs[1, 0])
+    ax.grid()
+    xi = np.linspace(1100, 1700, 4)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_xticks([1200, 1400, 1600])
+    ax.set_xlabel('setpoint (nm)', fontsize=18)
+    # C2
+    ax.scatter(curve.colors, curve.motors[2].positions, c='b', edgecolor='none')
+    ax.plot(curve.colors, curve.motors[2].positions, c='b', lw=2)
+    gone = [0, 9]
+    for i, tl in enumerate(ax.get_yticklabels()):
+        tl.set_color('b')
+        if i in gone:
+            tl.set_visible(False)
+    ax.set_ylabel('C2 (deg)', color='b', fontsize=18)
+    # D2
+    ax = ax.twinx()
+    ax.scatter(curve.colors, curve.motors[3].positions, c='r', edgecolor='none')
+    ax.plot(curve.colors, curve.motors[3].positions, c='r', lw=2)
+    gone = [0, 5]
+    for i, tl in enumerate(ax.get_yticklabels()):
+        tl.set_color('r')
+        if i in gone:
+            tl.set_visible(False)
+    ax.set_ylabel('D2 (deg)', color='r', fontsize=18)
+    yticks = ax.yaxis.get_major_ticks()
+    # finish
+    plt.savefig('curve.png', dpi=300, transparent=True, pad_inches=1)
+    plt.close(fig)
+
+
+### tuning range ##############################################################
+
+
+if False:
+    # prepare figure
+    fig, gs = wt.artists.create_figure(width=width, nrows=1, cols=[1],
+                                       default_aspect=0.15)
+    # populate
+    ax = plt.subplot(gs[0, 0])
+    cs = ['k', 'grey', 'orange', 'r', 'c', 'm', 'g', 'b', 'k']
+    ranges = collections.OrderedDict()
+    ranges['Idler'] = [2600, 1600]
+    ranges['Signal'] = [1600, 1150]
+    ranges['SHI'] = [800, 1200]
+    ranges['SHS'] = [800, 580]
+    ranges['SFI'] = [600, 533]
+    ranges['SFS'] = [533, 480]
+    ranges['4HI'] = [590, 400]
+    ranges['4HS'] = [400, 290]
+    height = 0
+    for name, limits in ranges.items():
+        ax.plot(limits, [height, height], lw=10, label=name, c=cs[height+1])
+        height += 1
+    labels = [''] + ranges.keys() + ['']
+    [i.set_color(c) for i, c in zip(plt.gca().get_yticklabels(), cs)]
+    ax.set_yticklabels(labels)
+    ax.set_xlim(290, 2000)
+    ax.set_ylim(-1, len(ranges))
+    ax.set_xlabel('OPA output (nm)', fontsize=18)
+    ax.grid()
+    # finish
+    plt.savefig('ranges.png', dpi=300, transparent=True, pad_inches=1)
+    plt.close(fig)
+
+
+### huge preamp ###############################################################
+
+
+if False:
+    # prepare figure
+    fig, gs = wt.artists.create_figure(width=width, nrows=1, hspace=1,
+                                       cols=[ 1, 'cbar', 0.1, 1, 'cbar'],
+                                       aspects=[[[0, 0], 1]])
+    # get data
+    p = 'TOPAS_C_full_preamp.p'
+    data = wt.data.from_pickle(p)
+    #data.transpose()
+    # clip based on intensity
+    data.amplitude.clip(zmin=0.1, zmax=5)
+    # clip based on width
+    data.width.clip(zmin=10, zmax=100)
+    # clip based on center
+    data.center.clip(zmin=1140, zmax=1620)
+    # share NaNs
+    data.share_nans()
+    data.heal('center')
+    data.heal('amplitude')
+    # intensity
+    ax = plt.subplot(gs[0, 0])
+    cax = plt.subplot(gs[0, 1])
+    xi = data.c1.points
+    yi = data.d1.points
+    zi = data.amplitude.values
+    zi /= np.nanmax(zi)
+    X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+    cmap=wt.artists.colormaps['default']
+    cmap.set_under([0.75]*3, 1)
+    mappable = ax.pcolor(X, Y, Z, vmin=0, vmax=1, cmap=cmap)
+    plt.colorbar(mappable=mappable, cax=cax, ticklocation='right')
+    cax.set_ylabel('intensity', fontsize=18)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_ylim(1.35, 1.8)
+    ax.contour(xi, yi, zi, 5, colors='k')
+    ax.set_xlabel('C1 (deg)', fontsize=18)
+    ax.set_ylabel('D1 (mm)', fontsize=18)
+    ax.grid()
+    # color
+    ax = plt.subplot(gs[0, 3])
+    cax = plt.subplot(gs[0, 4])
+    xi = data.c1.points
+    yi = data.d1.points
+    zi = data.center.values
+    X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+    cmap=wt.artists.colormaps['rainbow']
+    cmap.set_under([0.75]*3, 1)
+    mappable = ax.pcolor(X, Y, Z, vmin=np.nanmin(Z), vmax=np.nanmax(Z), cmap=cmap)
+    plt.colorbar(mappable=mappable, cax=cax)
+    cax.set_ylabel('color (nm)', fontsize=18)
+    ax.set_xlim(xi.min(), xi.max())
+    ax.set_ylim(1.35, 1.8)   
+    ax.contour(xi, yi, zi, 25, colors='k')
+    ax.set_xlabel('C1 (deg)', fontsize=18)
+    plt.setp(ax.get_yticklabels(), visible=False)
+    ax.grid()
+    # finish
+    plt.savefig('preamp.png', dpi=300, transparent=True, pad_inches=1)
+    plt.close(fig)
+
+
+### actual preamp #############################################################
+
+
+if False:
+    p = os.path.join(gd_path, 'Development', 'OPA tuning', 'tuning records', 'TOPAS-C 10743', 'signal', '2016.05.14', 'TOPAS-C AUTOTUNE [w1, w1_Delay_1, wa] 2016.05.14 20_25_26', 'TOPAS-C AUTOTUNE [w1, w1_Delay_1, wa] 2016.05.14 20_25_26.data')
+    d = r'C:\Users\blais\Google Drive\Development\OPA tuning\tuning records\TOPAS-C 10743\signal\2016.04.25\OPA1 (10743) curves'    
+    curves = [os.path.join(d, 'OPA1 (10743) base - 2016.04.25 22_46_02.crv'),
+              os.path.join(d, 'OPA1 (10743) mixer1 - 2015.11.09'),
+              os.path.join(d, 'OPA1 (10743) mixer2 - 2016.03.22 23_31_12'),
+              os.path.join(d, 'OPA1 (10743) mixer3 - 2013.06.01'),]
+    wt.tuning.TOPAS_C.process_preamp_motortune(1, p, curves, save=True)
+
+
+### huge poweramp #############################################################
+
+
+if False:
+    # prepare figure
+    fig, gs = wt.artists.create_figure(width=width, nrows=1, hspace=1,
+                                       cols=[ 1, 'cbar', 0.1, 1, 'cbar'],
+                                       aspects=[[[0, 0], 4/3.]])
+    # get data
+    p = 'TOPAS_C_full_poweramp_moments.p'
+    data = wt.data.from_pickle(p, verbose=False)
+    setpoints = np.linspace(1160, 1600, 12)
+    # clip, share NaNs
+    data.integral.clip(zmin=0.1, zmax=500)
+    data.one.clip(zmin=1140, zmax=1620)
+    # plot method
+    def plot(subplot_spec, cax, channel_index, cmap, yticklabels=False):
+        inner_gs = matplotlib.gridspec.GridSpecFromSubplotSpec(4, 3, subplot_spec=subplot_spec, wspace=0.0, hspace=0.0)
+        # fill in
+        for i, g in enumerate(inner_gs):
+            ax = plt.subplot(g)
+            if not ax.is_last_row():
+                plt.setp(ax.get_xticklabels(), visible=False)
+            if not ax.is_first_col():
+                plt.setp(ax.get_yticklabels(), visible=False)
+            if not yticklabels:
+                plt.setp(ax.get_yticklabels(), visible=False)
+            ax.grid()
+            if i == 10:
+                ax.set_xlabel('$\mathsf{\Delta}$C2 (deg)', fontsize=18)
+            cm = wt.artists.colormaps[cmap]
+            cm.set_under([0.75]*3)
+            setpoint = setpoints[i]
+            d = data.chop('d2', 'c2', {'w1': [setpoint, 'nm']})[0]
+            xi = d.c2.points
+            yi = d.d2.points
+            zi = d.channels[channel_index].values
+            vmin = data.channels[channel_index].min()
+            vmax = data.channels[channel_index].max()
+            X, Y, Z = wt.artists.pcolor_helper(xi, yi, zi)
+            ax.pcolor(X, Y, Z, vmin=vmin, vmax=vmax, cmap=cm)
+            ax.set_xlim(xi.min(), xi.max())
+            ax.set_ylim(yi.min(), yi.max())
+            wt.artists.corner_text(int(setpoint), fontsize=18, background_alpha=0.33)
+            ax.grid()
+    # intensity
+    subplot_spec = gs[0, 0]
+    cax = plt.subplot(gs[0, 1])
+    plot(subplot_spec, cax, 0, 'default', yticklabels=True)
+    wt.artists.plot_colorbar(cax=cax, cmap='default', label='intensity')
+    # color
+    subplot_spec = gs[0, 3]
+    cax = plt.subplot(gs[0, 4])
+    plot(subplot_spec, cax, 1, 'rainbow')
+    ticks = np.linspace(1140, 1620, 9)
+    wt.artists.plot_colorbar(cax=cax, cmap='rainbow', label='color (nm)', ticks=ticks)
+    # y label
+    fig.text(0.01, 0.55, '$\mathsf{\Delta}$D2 (deg)', fontsize=18, rotation=90)
+    # finish
+    plt.savefig('poweramp.png', dpi=300, transparent=True, pad_inches=1)
+    plt.close(fig)
diff --git a/opa/frequency domain examples.png b/opa/frequency domain examples.png
new file mode 100644
index 0000000..c86bb8f
--- /dev/null
+++ b/opa/frequency domain examples.png
diff --git a/opa/introduction.png b/opa/introduction.png
new file mode 100644
index 0000000..869c073
--- /dev/null
+++ b/opa/introduction.png
diff --git a/opa/poweramp flowchart.png b/opa/poweramp flowchart.png
new file mode 100644
index 0000000..7ab1dc4
--- /dev/null
+++ b/opa/poweramp flowchart.png
diff --git a/opa/poweramp.png b/opa/poweramp.png
new file mode 100644
index 0000000..3f0fdb7
--- /dev/null
+++ b/opa/poweramp.png
diff --git a/opa/preamp flowchart.png b/opa/preamp flowchart.png
new file mode 100644
index 0000000..01b04f1
--- /dev/null
+++ b/opa/preamp flowchart.png
diff --git a/opa/preamp.png b/opa/preamp.png
new file mode 100644
index 0000000..abf3a24
--- /dev/null
+++ b/opa/preamp.png
diff --git a/opa/ranges.png b/opa/ranges.png
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index 0000000..07bbbcb
--- /dev/null
+++ b/opa/ranges.png
diff --git a/opa/reproducability.png b/opa/reproducability.png
new file mode 100644
index 0000000..83ad67f
--- /dev/null
+++ b/opa/reproducability.png
diff --git a/opa/signal_and_idler_motortune.png b/opa/signal_and_idler_motortune.png
new file mode 100644
index 0000000..092eb72
--- /dev/null
+++ b/opa/signal_and_idler_motortune.png