Hloop

[ ]:

# Important to find data directory
import os
os.chdir('/notebooks/ana')

[2]:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import pandas as pd
import seaborn as sns
import scipy
from scipy import constants
import os, sys, time, re # System Modules
from glob import glob # Readout Files in Directories

import ana
%matplotlib inline


[3]:

matplotlib.rcParams['text.latex.preamble'] = r'\usepackage[utf8]{inputenc}\DeclareUnicodeCharacter{2212}{-}'

Calculate carrier concentration

\[n = \frac{I}{e \cdot V_H}\]
[4]:

test_meas = ana.Hloop(56)
test_meas.set_factor(1)
test_meas.up.B /= 1e3
test_meas.down.B /= 1e3
x = test_meas.up.B[test_meas.up.B > -.950][test_meas.up.B < .950]
y = test_meas.up.Vx8[test_meas.up.B > -.950][test_meas.up.B < .950]
fit = scipy.stats.linregress(x,y)

x2 = test_meas.down.B[test_meas.down.B > -.950][test_meas.down.B < .950]
y2 = test_meas.down.Vx8[test_meas.down.B > -.950][test_meas.down.B < .950]
fit2 = scipy.stats.linregress(x2,y2)
e = constants.physical_constants['electron volt'][0]
slope = np.mean([fit.slope, fit2.slope])
I = 2.5e-6
n = I/(slope*e)
print("Carrier concentration n = %f 1/m^2= %e 1/m^2 = %e 1/cm^2" % (n,n, n*1e-4))

test_meas.set_factor(1e3)
ax = plt.figure(figsize=(12,9)).gca()
test_meas.plot_hloop(ax, show_fitted=False, show_original=True)

Carrier concentration n = 1369288437038225.250000 1/m^2= 1.369288e+15 1/m^2 = 1.369288e+11 1/cm^2
../_images/notebooks_01_Hloop_5_1.png

Load Measurement Info (Angles)

[5]:

df_pos2 = pd.read_csv('data/angles_info.csv', index_col=0)
df_parallel2 = pd.read_csv('data/parallel_info.csv', index_col=0)


df_together2 = pd.concat([df_pos2, df_parallel2], axis=1)
df_together2.columns = ['Plusses', 'Crosses', 'Parallel']
df_together2

[5]:
Plusses Crosses Parallel
-90.0 155.0 0.0 NaN
-85.0 152.0 153.0 NaN
-80.0 148.0 149.0 NaN
-75.0 138.0 139.0 NaN
-70.0 134.0 136.0 NaN
-65.0 131.0 132.0 NaN
-60.0 128.0 129.0 NaN
-55.0 125.0 126.0 NaN
-50.0 122.0 123.0 NaN
-45.0 119.0 120.0 NaN
-40.0 143.0 144.0 NaN
-35.0 113.0 114.0 NaN
-30.0 110.0 111.0 NaN
-25.0 107.0 108.0 NaN
-20.0 104.0 105.0 NaN
-15.0 101.0 102.0 NaN
-10.0 98.0 99.0 NaN
-5.0 95.0 96.0 NaN
0.0 54.0 55.0 56.0
5.0 51.0 52.0 53.0
10.0 48.0 49.0 50.0
15.0 45.0 46.0 47.0
20.0 42.0 43.0 44.0
25.0 39.0 40.0 41.0
30.0 36.0 37.0 38.0
35.0 32.0 34.0 35.0
40.0 29.0 30.0 31.0
42.5 NaN NaN 28.0
45.0 23.0 22.0 24.0
50.0 79.0 80.0 NaN
55.0 76.0 77.0 NaN
60.0 73.0 74.0 NaN
65.0 70.0 71.0 72.0
70.0 67.0 68.0 69.0
75.0 64.0 65.0 66.0
80.0 61.0 62.0 63.0
85.0 58.0 59.0 60.0
90.0 57.0 0.0 57.0
95.0 82.0 83.0 NaN
100.0 85.0 86.0 NaN
105.0 88.0 89.0 NaN
110.0 91.0 93.0 NaN

Plot Strayfield

[6]:

def set_size(width_pt, fraction=1, subplots=(1, 1)):
    """Set figure dimensions to sit nicely in our document.

    Source: https://jwalton.info/Matplotlib-latex-PGF/

    Parameters
    ----------
    width_pt: float
            Document width in points
    fraction: float, optional
            Fraction of the width which you wish the figure to occupy
    subplots: array-like, optional
            The number of rows and columns of subplots.
    Returns
    -------
    fig_dim: tuple
            Dimensions of figure in inches
    """
    # Width of figure (in pts)
    fig_width_pt = width_pt * fraction
    # Convert from pt to inches
    inches_per_pt = 1 / 72.27

    # Golden ratio to set aesthetic figure height
    golden_ratio = (5**.5 - 1) / 2

    # Figure width in inches
    fig_width_in = fig_width_pt * inches_per_pt
    # Figure height in inches
    fig_height_in = fig_width_in * golden_ratio * (subplots[0] / subplots[1])

    return (fig_width_in, fig_height_in)


[7]:

m = ana.Hloop(57)
m.style.set_style(default=True, size="paper")
fig, ax = plt.subplots(figsize=set_size(426))
m.plot_strayfield(ax, 'm57: Strayfield ($90^\\circ$)')
plt.savefig('90deg-stray.pgf', format='pgf')
../_images/notebooks_01_Hloop_10_0.png

Measurement Plan (90deg, Noise)

[8]:

# Set Plot Style
sns.set(context="notebook", style="ticks", palette="deep")
plt.style.use(['science', 'notebook'])


# Save figures?
save_figures = True

# Global information
figsize = (16,10) # set_size(426)
x1, x2 = -750, 750
y1, y2 = -1.5, .5
main_color = '#CCCCFF'
#m.style.set_style(size="paper")

# Inset position and limits
## Position = x_pos, y_pos, width, height
## unit of positions are in % of frame
## x_pos, ypos points to lower left corner of inset
i1pos = .69, .3, .3, .3
i1x1, i1x2 = -100, 100
i2pos = .65, .8, .34, .2
i2x1, i2x2 = 530, 620
i2y1, i2y2 = -.175, 0.05
i3pos = .055, .65, .25, .3
i3x1, i3x2 = -650, -250
i3y1, i3y2 = -.05, .125
i4pos = .06, .03, .3, .25
i4x1, i4x2 = -100, 0
i4y1, i4y2 = -1.35, -.75
i5pos = .07, .36, .4, .28
i5x1, i5x2 = -300, 50
i5y1, i5y2 = -.7, .45

# Highlighting limits
h0range, h0color, h0alpha = 25, 'blue', .1
h1x1, h1x2, h1color, h1alpha = -611, -443, 'orange', .1
h2x1, h2x2, h2color, h2alpha = -291, -443, 'red', .1
h3x1, h3x2, h3color, h3alpha = -291.13, 36.56, 'green', .1

# Create Plot
fig, ax = plt.subplots(figsize=figsize)

# Plot hysetersis
m.plot_strayfield(ax, 'm57: Strayfield ($90^\\circ$)')

# Draw Inset 1
inset = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=i1pos,
                       bbox_transform=ax.transAxes)
# Highlight 0 / 3
inset.fill([-h0range, -h0range, h0range, h0range], [y2, y1, y1, y2], h0color, alpha=h0alpha)
inset.fill([h3x1, h3x1, h3x2, h3x2], [y2, y1, y1, y2], h3color, alpha=h3alpha)

# Highlight tertiary range
i1tert = h0range/3 # Tertiary range
inset.plot([i1tert, i1tert], [y1, y2], 'b--', alpha=.5)
inset.plot([-i1tert, -i1tert], [y1, y2], 'b--', alpha=.5)

m.plot_strayfield(inset, '$B \\in (-100, 100)$ mT', nolegend=True)
inset.set_xlim(i1x1, i1x2)
inset.set_ylim(y1, y2)

# Draw Inset 2
inset2 = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=i2pos,
                       bbox_transform=ax.transAxes)
m.plot_strayfield(inset2, '$B \\in (500, 600)$ mT', nolegend=True)
inset2.set_xlim(i2x1, i2x2)
inset2.set_ylim(i2y1, i2y2)

# Draw Inset 3
inset3 = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=i3pos,
                       bbox_transform=ax.transAxes)
m.plot_strayfield(inset3, '$B \\in (%s, %s)$ mT' % (i3x1, i3x2), nolegend=True)
inset3.set_xlim(i3x1, i3x2)
inset3.set_ylim(i3y1, i3y2)
# Highlight 1 / 2
inset3.fill([h1x1, h1x1, h1x2, h1x2], [i3y1, i3y2, i3y2, i3y1], h1color, alpha=h1alpha)
inset3.fill([h2x1, h2x1, h2x2, h2x2], [i3y1, i3y2, i3y2, i3y1], h2color, alpha=h2alpha)

# Draw Inset 4
inset4 = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=i4pos,
                       bbox_transform=ax.transAxes)
m.plot_strayfield(inset4, '$B \\in (%s, %s)$ mT' % (i4x1, i4x2), nolegend=True)
inset4.set_xlim(i4x1, i4x2)
inset4.set_ylim(i4y1, i4y2)

# Draw Inset 5
inset5 = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=i5pos,
                       bbox_transform=ax.transAxes)
m.plot_strayfield(inset5, '$B \\in (%s, %s)$ mT' % (i5x1, i5x2), nolegend=True)
inset5.set_xlim(i5x1, i5x2)
inset5.set_ylim(i5y1, i5y2)
inset5.fill([h3x1, h3x1, h3x2, h3x2], [i5y2, i5y1, i5y1, i5y2], h3color, alpha=h3alpha)

# Main Plot limits
ax.set_xlim(x1, x2)
ax.set_ylim(y1, y2)

# Highlight in main plot
ax.fill([-h0range, -h0range, h0range, h0range], [y1, y2, y2, y1], h0color, alpha=h0alpha)
ax.fill([h1x1, h1x1, h1x2, h1x2], [y1, y2, y2, y1], h1color, alpha=h1alpha)
ax.fill([h2x1, h2x1, h2x2, h2x2], [y1, y2, y2, y1], h2color, alpha=h2alpha)
ax.fill([h3x1, h3x1, h3x2, h3x2], [y1, y2, y2, y1], h3color, alpha=h3alpha)

# Remove x and y labels
for i, inset_ax in enumerate([inset3, inset2, inset5, inset, inset4]):
    inset_ax.set_xlabel('')
    inset_ax.set_ylabel('')
    inset_ax.set_title('')
    ann_x, ann_xx = inset_ax.get_xlim()
    ann_x += (ann_xx - ann_x)*.05
    ann_yy, ann_y = inset_ax.get_ylim()
    ann_y -= (ann_y - ann_yy)*.20
    inset_ax.text(x=ann_x, y=ann_y, s=chr(i+97) + ')',
                  fontdict=dict(fontweight='bold', fontsize=10),
                  bbox=dict(boxstyle="round,pad=0.1", fc=main_color, ec="b", lw=1))

# Save as image (if needed)
if save_figures:
    m.style.save_plot('m57_zoomed', 'png')
../_images/notebooks_01_Hloop_12_0.png 
<Figure size 576x432 with 0 Axes>

Plot All measurements

Compact (4 in One)

[9]:

def get_measurement(meas, all_angles):
    for i, nr in enumerate(map(int, all_angles)):
        meas[nr] = ana.Hloop(nr)
    return meas

all_angles = df_together2.query('Crosses > 0')[['Plusses', 'Crosses']].dropna().to_numpy().ravel()
all_angles

meas = {}
meas = get_measurement(meas, all_angles)


[11]:

def plot_four_measurement(meas, all_angles, axes):
    global style
    for i, nr in enumerate(map(int, all_angles)):
        ax = axes[i//2][i%2]
        # meas[nr].get_info_from_name()
        meas[nr].style.set_style(default=True)
        meas[nr].plot_strayfield(ax)

        inset = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=(.6, .08, .4, .4),
                       bbox_transform=ax.transAxes)
        max_b = meas[nr].up.B.max()
        inset.plot([-max_b, max_b], [0, 0], 'r--', linewidth=.75)
        B_ext, B_stray = meas[nr].get_downminusup_strayfield()
        inset.plot(B_ext, B_stray)
        inset.set_title("Down-minus-Up-Difference")

    #plt.savefig('compare_all_strayfield.png')
    #plt.savefig('compare_all_strayfield.pdf')



for i in range(len(all_angles)//4):
    fig, axes = plt.subplots(2,2, figsize=(16,9))
    plot_four_measurement(meas, all_angles[4*i:4*i+4], axes)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-11-384a03c3c052> in <module>
     23 for i in range(len(all_angles)//4):
     24     fig, axes = plt.subplots(2,2, figsize=(16,9))
---> 25     plot_four_measurement(meas, all_angles[4*i:4*i+4], axes)

<ipython-input-11-384a03c3c052> in plot_four_measurement(meas, all_angles, axes)
      5         # meas[nr].get_info_from_name()
      6         meas[nr].style.set_style(default=True)
----> 7         meas[nr].plot_strayfield(ax)
      8
      9         inset = inset_axes(ax, width='100%', height='90%',

/notebooks/ana/ana/hloop.py in plot_strayfield(self, ax, figtitle, **kwargs)
    436             None.:
    437         """
--> 438         self.set_factor(kwargs.get('factor', 1e3))
    439         self.calculate_strayfield()
    440

/notebooks/ana/ana/hloop.py in set_factor(self, factor)
    205         """
    206         self.up.Vx8 /= self.factor
--> 207         self.down.Vx8 /= self.factor
    208         if (self.parallel):
    209             self.up.Vx9 /= self.factor

AttributeError: 'Hloop' object has no attribute 'down'
../_images/notebooks_01_Hloop_16_1.png
../_images/notebooks_01_Hloop_16_2.png
../_images/notebooks_01_Hloop_16_3.png
../_images/notebooks_01_Hloop_16_4.png
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../_images/notebooks_01_Hloop_16_8.png

Plot single measurements

[12]:

#meas = {}
for nr in all_angles:
    fig, ax = plt.subplots(1, 1, figsize=(16,9))
    meas[nr].style.set_style(default=True)

    try:
        meas[nr].plot_strayfield(ax)
    except:
        continue

    inset = inset_axes(ax, width='100%', height='90%',
                       bbox_to_anchor=(.6, .05, .4, .4),
                       bbox_transform=ax.transAxes)
    max_b = meas[nr].up.B.max()
    inset.plot([-max_b, max_b], [0, 0], 'r--', linewidth=.75)
    B_ext, B_stray = meas[nr].get_downminusup_strayfield()
    inset.plot(B_ext, B_stray)
    inset.set_ylabel("$\Delta B_z$ [$mT$]")
    inset.set_title("Down-minus-Up-Difference")

    #plt.savefig('plot/m%s_%s_%sdeg.png' % (nr,meas[nr].data['Structure'],meas[nr].data['Angle']))
    #plt.savefig('plot/m%s_%s_%sdeg.pdf' % (nr,meas[nr].data['Structure'],meas[nr].data['Angle']))

<ipython-input-12-bfb78f2f7c96>:3: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).
  fig, ax = plt.subplots(1, 1, figsize=(16,9))
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Show Measurement Infos

[13]:

df = pd.DataFrame({}, index=[], columns=['Type',
                     'Date',
                     'Structure',
                     'Angle',
                     'I1',
                     'I2',
                     'Vin',
                     'R11',
                     'R12',
                     'R13',
                     'R21',
                     'C11',
                     'C21',
                     'T',
                     'SR',
                     'Vrem1',
                     'Vrem2',
                     'Bcoer1',
                     'Bcoer2'])
for nr, m in meas.items():
    data = m.info

    try:
        m.fit()
    except:
        pass

    try:
        rem1, rem2 = m.get_remanence()
        data['Vrem1'], data['Vrem2'] = rem1.Vx8, rem2.Vx8
    except:
        pass

    try:
        mean, coer1, coer2 = m.get_coercive_field()
        data['V0'], data['Bcoer1'], data['Bcoer2'] = mean, coer1.B, coer2.B
    except:
        pass

    newdf = pd.DataFrame(data, index=[nr])
    if(df.empty):
        df = newdf
    else:
        df = pd.concat([df, newdf])

[14]:

df

[14]:
Type Date Structure Angle I1 I2 Vin R11 R12 R13 ... deg type1 dir type2 date time GBIP8 B gate R1
152 Hloop (Gradio) 07.04.2019 01:33 Plusses -85 1-13 8-6 2.5 1M 7.5k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
153 Hloop (Gradio) 07.04.2019 10:00 Crosses -85 2-12 8-6 2.5 1M 4k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
148 Hloop (Gradio) 06.04.2019 12:00 Plusses -80 1-13 8-6 2.5 1M 8.25k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
149 Hloop (Gradio) 06.04.2019 17:000 Crosses -80 2-12 8-6 2.5 1M 3.75k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
138 Hloop (Gradio) 02.04.2019 19:00 Plusses -75 1-13 8-6 2.5 1M 2k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
86 Hloop (Gradio) 24.03.2019 14:00 Crosses 100 2-12 8-6 2.5 1M 2.25k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
88 None (Gradio) NaN Plusses 105 1-13 8-6 2.5V 1MO NaN 0 ... 105 Hloop up Gradio 20190324 2000 14-7 1T 0V 2.6kO
89 None (Gradio) NaN Crosses 105 1-13 8-6 2.5V 1MO NaN 0 ... 105 Hloop down Gradio 20190325 0800 14-7 0.75T 0V 1.4kO
91 Hloop (Gradio) 25.03.2019 14:00 Plusses 110 1-13 8-6 2.5 1M 5.15k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
93 Hloop (Gradio) 25.03.2019 22:00 Crosses 110 1-13 8-6 2.5 1M 2.25k 0 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

78 rows × 33 columns