update 20180601

data/m04_cycledepends/processing_cycledepends.py

@@ -5,11 +5,22 @@ import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
 import VisTools.plotting as vt
+import uncertainties as unc
+import uncertainties.unumpy as unp
+
+import statsmodels.api as sm
+from statsmodels.stats.outliers_influence import summary_table as st
 
 plt.ioff()
 plt.style.use('bmh')
-fig, axarr = plt.subplots(2,1,figsize=(11.88, 8.4))
+fig, axarr = plt.subplots(
-data = pd.read_csv("./" + __file__[:-3].split("_")[1] + ".csv")
+    2,
+    1,
+    figsize=(9, 8),
+    gridspec_kw = {'height_ratios':[4,1]}
+)
+plt.subplots_adjust(hspace=.5)
+data = pd.read_csv("./" + __file__[:-3].split("_")[1] + ".csv", comment="#")
 
 fits = np.array([])
 errs = np.array([])
@@ -21,73 +32,59 @@ print(data)
 # fit to abs dist
 linfnc = lambda x,m,c: x*m+c
 
+def plot_and_linfit(col: str,fil, l: str):
     p = axarr[0].errorbar(
-    data[data.cycles == 0]['v_set/v'],
+        data[fil]['v_set/v'],
-    data[data.cycles == 0]['Dvk'],
+        data[fil][col],
-    label="relative Error of ADC, keith",
+        alpha = 0,
-    fmt='.'
+        label=None,
+    #    fmt='.',
+    #    antialiased=True
     )
 
-pfinal, pcov = opt.curve_fit(
+    vals = vt.lm_plot(
-    linfnc,
+        data[fil],
-    data[data.cycles == 0]['v_set/v'],
+        'v_set/v',
-    data[data.cycles == 0]['Dvk'],
+        col,
-    p0=(.1,2.6),
+        None,
-    sigma=[.5 for e in range(data[data.cycles == 0]['Dv'].size)]
+        'dv_pit48/v',
-)
+        l,
-
+        fig=axarr[0],
-axarr[0].plot(
-    data[data.cycles == 0]['v_set/v'],
-    data[data.cycles == 0]['v_set/v']*pfinal[0]+pfinal[1],
-    label="fitted, keith",
         color = p[0].get_color()
     )
+
+    return vals, p
+
+plot_and_linfit('Dvk', data.cycles == 0, 'ref')
 for i in range(8):
-    p = axarr[0].errorbar(
+    val, p = plot_and_linfit('Dv', data.cycles == i, 'scaler: {}'.format(i))
-        data[data.cycles == i]['v_set/v'],
+    fits = np.append(fits, val[0])
-        data[data.cycles == i]['Dv'],
+    #errs = np.append(errs, np.sqrt(pcov[0][0]))
-        yerr=data[data.cycles == i]['dv_pit48/v'],
+    #colors = np.append(colors, p[0].get_color() )
-        label="relative Error of ADC, scaler: "+str(i),
-        fmt='.'
-    )
 
-    pfinal, pcov = opt.curve_fit(
-        linfnc,
-        data[data.cycles == i]['v_set/v'],
-        data[data.cycles == i]['Dv'],
-        p0=(.1,2.6),
-        sigma=[.5 for e in range(data[data.cycles == i]['Dv'].size)]
-    )
 
-    axarr[0].plot(
+print(fits[0].n)
-        data[data.cycles == i]['v_set/v'],
-        data[data.cycles == i]['v_set/v']*pfinal[0]+pfinal[1],
-        label="fitted, scaler: "+str(i),
-        color = p[0].get_color()
-    )
-
-    fits = np.append(fits, pfinal[0])
-    errs = np.append(errs, np.sqrt(pcov[0][0]))
-    colors = np.append(colors, p[0].get_color() )
-
-#vt.annotate_val(plt, pfinal[0], np.sqrt(pcov[0][0]), name="V48[2]", data_pos=(44, 3))
-
-print(fits)
 for i in range(8):
     axarr[1].errorbar(
         i,
-        fits[i],
+        fits[i].n,
-        yerr = errs[i],
+        yerr = fits[i].s,
         fmt='.',
-        c = colors[i]
+        #c = colors[i],
     )
 
 axarr[0].set_xlabel('V$_{set}$/V')
-axarr[0].set_title("PowerIt ADC Calibration: dependency on measurement cycles")
+#axarr[0].set_title("PowerIt ADC Calibration: dependency on measurement cycles")
 axarr[0].set_ylabel('$\Delta$V$_{IN}$ / V')
 
 axarr[1].set_xlabel('sampleTicks scaler')
 axarr[1].set_ylabel('$\Delta(\Delta$V$_{IN})$')
+axarr[0].legend(bbox_to_anchor=(0, -.28,1, 1), loc="lower left",
+                mode="expand", borderaxespad=0, ncol=5)
+#plt.tight_layout()
+plt.savefig("./" + __file__[:-3].split("_")[1] + ".pdf", dpi=1000, bbox_inches='tight')
 
-plt.tight_layout()
+
-plt.savefig("./" + __file__[:-3].split("_")[1] + ".eps", format='eps', dpi=1000)
+ss, d, ss2 = st(sm.OLS(data[data.cycles == 0]['v_pit48/v'], data[data.cycles == 0]['v_set/v']).fit(), alpha=.05)
+
+low_ci, high_ci = d[:,4:6].T

parts/intro.tex

@@ -2,9 +2,25 @@
 
 \chapter{Intro}
 
-\section{The Hardware}
+\section{Premise}
 
-The hardware used in this thesis is a PowerIt board, developed in the electronic visions group. It functions as power supply inside of the Waferscale System\footnote{
+\section{Hardware Overview}
+
+The hardware used in this thesis is a PowerIt board, developed in the electronic visions group\footnote{
     %TODO    
-}. In which it iis providing the HICANN Chips with ~1.8V and the FPGAs with 9.6V.
+}. It functions as power supply inside of the Waferscale System\footnote{
+    %TODO
+} (fig. \ref{wss}). 
+\begin{figure}[h]
+    \centering
+    \includegraphics[width=.9\textwidth]{../InternReport/img/waferscale_system.png}
+    \caption{WSS}
+    \label{wss}
+\end{figure}
+In which it is providing the Wafer with 1.8V and the FPGAs with 9.6V. Its maximum rated Pwerdraw is 2kW. 
+
 <containing intro to system and board>
+
+\section{Measurement Hardware}
+
+<contains circuits to all measureing adcs, and description of the measureing process>

preamble.tex

@@ -7,6 +7,8 @@
 \usepackage{hyperref}
 \usepackage{tcolorbox}
 \usepackage{enumitem,amssymb}
+\usepackage{graphicx}
+\usepackage{svg}
 
 \definecolor{myteal}{HTML}{228c9c}
 %\DeclareTColorBox{blockbox}{ O{width=\textwidth} }{boxrule=0mm, colframe=myteal, valign lower=bottom, on line, lower separated=false, height=.6\textheight, #1} 

thesis.tex

@@ -20,7 +20,12 @@
 
     \tableofcontents
     \include{./tabs/registerbuffer}
-    %\include{parts/intro}
+    \begin{figure}
+        \centering
+        \hspace*{-.16\columnwidth}
+        \includegraphics[width=1.3\columnwidth]{./data/m04_cycledepends/cycledepends.pdf}
+    \end{figure}
+    \include{parts/intro}
     %\include{parts/tasks}
     %\include{parts/theory} 
     %\include{parts/experiments}