update 20180605 1200

.gitignore

@@ -33,3 +33,4 @@ data/raspi-i2c/i2c
 data/m03_poticalib/poticalib_ana.py
 data/m02_adccalib_48/adccalib_48.py
 data/m04_cycledepends/cycledepends.csv
+data/m04_cycledepends/cycledepends.py

README.md

@@ -28,22 +28,38 @@
 - Calibration
     - [x] characterize adcbehaviour
         - [x] plot resulting fitted incline of $\Delta $V vs. num. of readcycles
-        - [ ] write reasoning for using a given `sampleTicks` value
-            - smallest gain error
-            - smallest offset
-            - hightst samplerate
+        - [x] see if v_pin same as v_keith_pin
+            - on dV of **small enough** -> adc circuit working correctly -> calib
+        - [ ] reasoning for using a given `sampleTicks` value
+            - smallest gain error -> inconsistent
+            - smallest offset -> inconsistent
+            - hightst samplerate -> `sampleTicks = 1`
+            - pin plot -> `sampleTicks = 0` is no go
+            - pin plot -> `sampleTicks` in `1-7`
     - [x] polynomials
         - [x] polynomials rw-able
     - [x] 10I calc
-    - ADC vs. Keithley
-        - [ ] 48V
-            - redo after selection of `sampleTicks` value
-        - [ ] 10V
-        - [x] 1.8V
+    - [ ] differences between PIts?
+        - if yes then we need a `PITDB`
+        - if not then we can hardset those values
+    - [ ] ADC vs. Keithley
+        - [ ] redo after selection of `sampleTicks` value
+            - [ ] 48V
+            - [ ] 10V
+            - [ ] 1.8V
+        - [ ] calibrate based on fit
+            - [ ] 48V
+            - [ ] 10V
+            - [ ] 1.8V
     - ADC vs. EL
-        - [ ] 48I
-        - [ ] 10I
-        - [ ] 1.8I
+        - [ ] without calib
+            - [ ] 48I
+            - [ ] 10I
+            - [ ] 1.8I
+        - [ ] with calib
+            - [ ] 48I
+            - [ ] 10I
+            - [ ] 1.8I
     - Temp
         - [ ] accuracy
         - [ ] position in system

data/m04_cycledepends/cycledepends_20180529.csv

@@ -1,4 +1,4 @@
-time/s,v_ps/v,dv_ps/v,v_pit48/v,dv_pit48/v,v_keith/v,v_set/v,cycles
+time,v_ps,dv_ps,v_pit48,dv_pit48,v_keith,v_set,cycles
 14.897,43.034,0.011,38.931,0.243,43.112,43.000,000
 18.963,43.038,0.008,42.409,0.084,43.112,43.000,001
 23.282,43.032,0.005,42.156,0.074,43.113,43.000,002

data/m04_cycledepends/cycledepends_20180530.csv

@@ -0,0 +1,170 @@
+#cycledepends, generated: May 30 2018 13:11:39
+time,v_ps,dv_ps,v_pit48,dv_pit48,v_keith,v_set,cycles
+15.329,43.039,0.012,38.964,0.025,43.115,43.000,000
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+31.547,43.047,0.009,41.822,0.099,43.115,43.000,004
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+41.045,43.045,0.009,41.753,0.164,43.113,43.000,006
+45.096,43.045,0.007,41.938,0.161,43.114,43.000,007
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data/m04_cycledepends/cycledepends_20180605.csv

@@ -0,0 +1,170 @@
+# cycledepends, v48[1]=1, generated: Jun 05 2018 11:05:19
+time,t_core,v_ps,dv_ps,v_pit48,dv_pit48,v_keith,v_set,cycles
+15.051,28.8,43.035,0.007,1.465,0.014,1.523,43.000,000
+19.201,29.2,43.041,0.009,1.524,0.001,1.524,43.000,001
+23.602,30.1,43.035,0.007,1.521,0.012,1.523,43.000,002
+28.001,30.1,43.037,0.003,1.538,0.009,1.524,43.000,003
+32.402,30.1,43.037,0.013,1.531,0.002,1.523,43.000,004
+37.012,30.5,43.039,0.008,1.529,0.003,1.524,43.000,005
+43.612,29.2,43.034,0.006,1.527,0.003,1.524,43.000,006
+48.013,29.5,43.036,0.006,1.524,0.004,1.524,43.000,007
+63.441,27.9,43.519,0.007,1.476,0.012,1.540,43.500,000
+67.607,29.5,43.521,0.003,1.547,0.014,1.540,43.500,001
+72.003,30.1,43.514,0.004,1.543,0.008,1.541,43.500,002
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+128.268,28.8,43.999,0.009,1.493,0.005,1.558,44.000,000
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+246.908,30.5,45.001,0.006,1.599,0.004,1.593,45.000,005
+252.408,29.8,44.995,0.004,1.598,0.005,1.593,45.000,006
+257.020,29.2,44.994,0.005,1.594,0.006,1.593,45.000,007
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data/m04_cycledepends/out.tex

@@ -0,0 +1,5 @@
+\newcommand{\val}[2]{%
+	\IfEqCase{#1}{%
+		{ 0 }{  \SI{ -0.0016790748810628826+-7.332339429588327e-05 }{  }}
+	}[\PackageError{unc_tolatex}{undefinded value: #1}{}]%
+}

data/m04_cycledepends/processing_cycledepends.py

@@ -1,12 +1,15 @@
-#! /Usr/bin/python3
+#! /usr/bin/python4
 
-import scipy.optimize as opt
+#import scipy.optimize as opt
 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 VisTools.tex as vtt
+#import uncertainties as unc
+#import uncertainties.unumpy as unp
+
+append = "_20180605"
 
 plt.ioff()
 plt.style.use('bmh')
@@ -14,27 +17,27 @@ fig, axarr = plt.subplots(
     2,
     1,
     figsize=(10, 8),
-    gridspec_kw = {'height_ratios':[4,1]}
+    gridspec_kw={'height_ratios':[4, 1]},
+    sharex="col"
 )
-plt.subplots_adjust(hspace=.5)
-data = pd.read_csv("./" + __file__[:-3].split("_")[1] + ".csv", comment="#")
+plt.subplots_adjust(hspace=.1)
+data = pd.read_csv("./" + __file__[:-3].split("_")[1] + append + ".csv", comment="#")
 
 fits = np.array([])
 errs = np.array([])
 colors = np.array([])
 
-data['dv_pit48/v'] /= 2
-data['Dv'] = data['v_pit48/v'] - data['v_set/v']
-data['Dvk'] = data['v_keith/v'] - data['v_set/v']
+data['dv_pit48'] /= 2
+data['Dv'] = data['v_pit48'] - data['v_keith']
 print(data)
 # fit to abs dist
-linfnc = lambda x,m,c: x*m+c
+linfnc = lambda x, m, c: x*m+c
 
-def plot_and_linfit(col: str,fil, l: str):
-    p = axarr[0].errorbar(
-        data[fil]['v_set/v'],
+def plot_and_linfit(col: str, fil, l: str):
+    plot = axarr[0].errorbar(
+        data[fil]['v_set'],
         data[fil][col],
-        alpha = 0.3,
+        alpha=0.3,
         label=None,
         fmt='.',
         antialiased=True
@@ -42,52 +45,51 @@ def plot_and_linfit(col: str,fil, l: str):
 
     vals = vt.lm_plot(
         data[fil],
-        'v_set/v',
+        'v_set',
         col,
         None,
-        'dv_pit48/v',
+        'dv_pit48',
         l,
         fig=axarr[0],
-        color = p[0].get_color()
+        color=plot[0].get_color()
     )
 
-    return vals, p
+    return vals, plot
 
 for i in range(8):
     val, p = plot_and_linfit(
-        'Dv', 
-        data.cycles == i, 
-        '$f_{}={{m:.3f}}\\cdot x{{c:+.3f}}V$'.format(i))
+        'Dv',
+        data.cycles == i,
+        '$f_{}={{m:.5f}}\\cdot x{{c:+.5f}}V$'.format(i))
     fits = np.append(fits, val[0])
     #errs = np.append(errs, np.sqrt(pcov[0][0]))
-    #colors = np.append(colors, p[0].get_color() )
+    colors = np.append(colors, p[0].get_color() )
 
-plot_and_linfit('Dvk', data.cycles == 0, 'reference measurement')
+#plot_and_linfit('Dvk', data.cycles == 0, 'reference measurement')
 
 print(fits[0].n)
 for i in range(8):
     axarr[1].errorbar(
-        i,
-        fits[i].n,
-        yerr = fits[i].s,
-        fmt='.',
-        #c = colors[i],
+        data[data.cycles==i]['v_set'],
+        data[data.cycles==i]['t_core'],
+        #fmt='.',
+        alpha=.3,
+        c = colors[i],
+        label="$f_{}: T_{{mean}}={:.1f}$".format(i, np.mean(data[data.cycles==i]['t_core']))
     )
 
-axarr[0].set_xlabel('V$_{set}$/V')
+axarr[1].set_xlabel('V$_{set}$')
 #axarr[0].set_title("PowerIt ADC Calibration: dependency on measurement cycles")
-axarr[0].set_ylabel('$\Delta$V$_{IN}$ / V')
+axarr[0].set_ylabel(r'$\Delta$V$_{IN}$ / V')
 
-axarr[1].set_xlabel('scaler value')
-axarr[1].set_ylabel('$m = \Delta$Gain')
+#axarr[1].set_xlabel('scaler value')
+axarr[1].set_ylabel(r'$T / \degree C$')
 axarr[0].legend(
-    bbox_to_anchor=(0, -.29,1, 1), 
-    loc="lower left",
-    mode="expand", 
-    borderaxespad=0, 
-    ncol=3)
+    bbox_to_anchor=(.3, -.29, 1, 1),
+    ncol=1)
 plt.savefig(
-    "./" + __file__[:-3].split("_")[1] + ".pdf", 
-    dpi=1000, 
+    "./" + __file__[:-3].split("_")[1] + append + ".pdf",
+    dpi=1000,
     bbox_inches='tight')
 
+vtt.unc_tolatex(fits[0], "0")

data/m04_cycledepends/processing_cycledepends_raw.py

@@ -0,0 +1,97 @@
+#! /usr/bin/python4
+
+#import scipy.optimize as opt
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+import VisTools.plotting as vt
+import VisTools.tex as vtt
+#import uncertainties as unc
+#import uncertainties.unumpy as unp
+
+append = ""#"_20180529"
+
+plt.ioff()
+plt.style.use('bmh')
+fig, axarr = plt.subplots(
+    2,
+    1,
+    figsize=(10, 8),
+    gridspec_kw={'height_ratios':[4, 1]}
+)
+plt.subplots_adjust(hspace=.5)
+data = pd.read_csv("./" + __file__[:-3].split("_")[1] + append + ".csv", comment="#")
+
+fits = np.array([])
+errs = np.array([])
+colors = np.array([])
+
+data['dv_pit48'] /= 2
+data['Dv'] = data['v_pit48'] - data['v_set']
+data['Dvk'] = data['v_keith'] - data['v_set']
+print(data)
+# fit to abs dist
+linfnc = lambda x, m, c: x*m+c
+
+def plot_and_linfit(col: str, fil, l: str):
+    plot = axarr[0].errorbar(
+        data[fil]['v_set'],
+        data[fil][col],
+        alpha=0.3,
+        label=None,
+        fmt='.',
+        antialiased=True
+    )
+
+    vals = vt.lm_plot(
+        data[fil],
+        'v_set',
+        col,
+        None,
+        'dv_pit48',
+        l,
+        fig=axarr[0],
+        color=plot[0].get_color()
+    )
+
+    return vals, plot
+
+for i in range(8):
+    val, p = plot_and_linfit(
+        'Dv',
+        data.cycles == i,
+        '$f_{}={{m:.3f}}\\cdot x{{c:+.3f}}V$'.format(i))
+    fits = np.append(fits, val[0])
+    #errs = np.append(errs, np.sqrt(pcov[0][0]))
+    colors = np.append(colors, p[0].get_color() )
+
+plot_and_linfit('Dvk', data.cycles == 0, 'reference measurement')
+
+print(fits[0].n)
+for i in range(8):
+    axarr[1].errorbar(
+        i,
+        fits[i].n,
+        yerr=fits[i].s,
+        fmt='.',
+        #c = colors[i],
+    )
+
+axarr[0].set_xlabel('V$_{set}$')
+#axarr[0].set_title("PowerIt ADC Calibration: dependency on measurement cycles")
+axarr[0].set_ylabel(r'$\Delta$V$_{IN}$ / V')
+
+axarr[1].set_xlabel('scaler value')
+axarr[1].set_ylabel(r'$m = \Delta$Gain')
+axarr[0].legend(
+    bbox_to_anchor=(0, -.29, 1, 1),
+    loc="lower left",
+    mode="expand",
+    borderaxespad=0,
+    ncol=3)
+plt.savefig(
+    "./" + __file__[:-3].split("_")[1] + append + ".pdf",
+    dpi=1000,
+    bbox_inches='tight')
+
+vtt.unc_tolatex(fits[0], "0")

preamble.tex

@@ -9,6 +9,7 @@
 \usepackage{enumitem,amssymb}
 \usepackage{graphicx}
 \usepackage{svg}
+\usepackage{pdflscape}
 
 \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

@@ -1,4 +1,4 @@
-\documentclass[notitlepage]{scrreprt}
+\documentclass[notitlepage, a4]{scrreprt}
 \input{preamble}
 
 \pretitle{\begin{center}\huge\bfseries}
@@ -20,10 +20,17 @@
 
     \tableofcontents
     \include{./tabs/registerbuffer}
+    \begin{figure}
+        \centering
+        \hspace*{-.16\columnwidth}
+        \includegraphics[width=1.3\columnwidth]{./data/m04_cycledepends/cycledepends_20180529.pdf}
+        \caption{plotted difference from set input voltage, and fitted linearly, May 29th 2018, $\approx$32\si\degree C}
+    \end{figure}
     \begin{figure}
         \centering
         \hspace*{-.16\columnwidth}
         \includegraphics[width=1.3\columnwidth]{./data/m04_cycledepends/cycledepends.pdf}
+        \caption{plotted difference from set input voltage, and fitted linearly, May 30th 2018, $\approx$25\si\degree C}
     \end{figure}
     \include{parts/intro}
     %\include{parts/tasks}