In [2]:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

In [3]:
stability1=[]
stability2=[]

In [4]:
def plot_stability_variations(ax,x,y,title):
    mean,maxi,mini,std=np.mean(y),np.max(y),np.min(y),np.std(y)
    ax.plot(x,y)
    ax.axhline(mean,color="g")
    ax.axhline(mean+std,color="r")
    ax.axhline(mean-std,color="r")
    ax.set_xlabel("Time (s)",fontsize=15)
    ax.set_ylabel("Ids (Amps)",fontsize=15)
    ax.set_title(title,fontsize=15)
    return [mean,std,maxi,mini]

In [5]:
data1=np.loadtxt("235RC/235RC_pin03-13_IdsT_Vds10mV_Vg0constant_2016-07-03_run1.txt",skiprows=1)
data2=np.loadtxt("235RC/235RC_pin06-10_IdsT_Vds10mV_Vg0constant_2016-07-03_run2.txt",skiprows=1)





fig=plt.figure(figsize=(16,7))
ax1=plt.subplot(121)
ax2=plt.subplot(122)
stability1.append(plot_stability_variations(ax1,data1[:,0],data1[:,1],title="Device 1"))
stability2.append(plot_stability_variations(ax2,data2[:,0],data2[:,1],title="Device 2"))
fig.suptitle("time stability after 20hrs relaxation",fontsize=20)


Out[5]:
<matplotlib.text.Text at 0x7fd0df4a5518>

In [6]:
data1=np.loadtxt("235RC/235RC_pin03-13_IdsT_Vds10mV_Vg0constant_2016-07-04_run1.txt",skiprows=1)
data2=np.loadtxt("235RC/235RC_pin06-10_IdsT_Vds10mV_Vg0constant_2016-07-04_run2.txt",skiprows=1)



fig=plt.figure(figsize=(16,7))
ax1=plt.subplot(121)
ax2=plt.subplot(122)
stability1.append(plot_stability_variations(ax1,data1[:,0],data1[:,1],title="Device 1"))
stability2.append(plot_stability_variations(ax2,data2[:,0],data2[:,1],title="Device 2"))
fig.suptitle("time stability after 18.5hrs relaxation",fontsize=20)


Out[6]:
<matplotlib.text.Text at 0x7fd0def42f98>

In [7]:
data1=np.loadtxt("235RC/235RC_pin03-13_IdsT_Vds10mV_Vg0constant_2016-07-05_run1.txt",skiprows=1)
data2=np.loadtxt("235RC/235RC_pin06-10_IdsT_Vds10mV_Vg0constant_2016-07-05_run2.txt",skiprows=1)

fig=plt.figure(figsize=(16,7))
ax1=plt.subplot(121)
ax2=plt.subplot(122)
stability1.append(plot_stability_variations(ax1,data1[:,0],data1[:,1],title="Device 1"))
stability2.append(plot_stability_variations(ax2,data2[:,0],data2[:,1],title="Device 2"))
fig.suptitle("time stability after 18hrs relaxation",fontsize=20)


Out[7]:
<matplotlib.text.Text at 0x7fd0dee71470>

In [8]:
data1=np.loadtxt("235RC/235RC_pin03-13_IdsT_Vds10mV_Vg0constant_2016-07-06_run1.txt",skiprows=1)
data2=np.loadtxt("235RC/235RC_pin06-10_IdsT_Vds10mV_Vg0constant_2016-07-06_run2.txt",skiprows=1)

fig=plt.figure(figsize=(16,7))
ax1=plt.subplot(121)
ax2=plt.subplot(122)
stability1.append(plot_stability_variations(ax1,data1[:,0],data1[:,1],title="Device 1"))
stability2.append(plot_stability_variations(ax2,data2[:,0],data2[:,1],title="Device 2"))
fig.suptitle("time stability after 21hrs relaxation",fontsize=20)


Out[8]:
<function print>

In [9]:
data1=np.loadtxt("235RC/235RC_pin03-13_IdsT_Vds10mV_Vg0constant_2016-07-07_run1.txt",skiprows=1)
data2=np.loadtxt("235RC/235RC_pin06-10_IdsT_Vds10mV_Vg0constant_2016-07-07_run2.txt",skiprows=1)

fig=plt.figure(figsize=(16,7))
ax1=plt.subplot(121)
ax2=plt.subplot(122)
stability1.append(plot_stability_variations(ax1,data1[:,0],data1[:,1],title="Device 1"))
stability2.append(plot_stability_variations(ax2,data2[:,0],data2[:,1],title="Device 2"))
fig.suptitle("time stability after 16hrs relaxation",fontsize=20)


Out[9]:
<matplotlib.text.Text at 0x7fd0dd454f60>

In [15]:
stability1=np.array(stability1)
stability2=np.array(stability2)
fig=plt.figure(figsize=(16,7))
ax1=plt.subplot(121)
ax1.errorbar(range(len(stability1)),stability1[:,0],yerr=stability1[:,1],fmt='r.',markersize=10)
ax1.axis([-0.1,len(stability1)-0.9,min(stability1[:,0]*0.9),max(stability1[:,0]*1.1)])

mean,maxi,mini,std=np.mean(stability1[:,0]),np.max(stability1[:,0]),np.min(stability1[:,0]),np.std(stability1[:,0])
ax1.axhline(mean,color='blue')
ax1.axhline(mean+std,color='orange')
ax1.axhline(mean-std,color='orange')
ax1.axhline(maxi,color='red')
ax1.axhline(mini,color='red')
time=[20,18.5,18,21,16]
ax2=plt.subplot(122)
ax2.errorbar(time,stability2[:,0],yerr=stability2[:,1],fmt='r.',markersize=10)
ax2.axis([min(time)*0.9,max(time)*1.1,min(stability2[:,0]*0.9),max(stability2[:,0]*1.1)])

mean,maxi,mini,std=np.mean(stability2[:,0]),np.max(stability2[:,0]),np.min(stability2[:,0]),np.std(stability2[:,0])
ax2.axhline(mean,color='blue')
ax2.axhline(mean+std,color='orange')
ax2.axhline(mean-std,color='orange')
ax2.axhline(maxi,color='red')
ax2.axhline(mini,color='red')
ax2.set_xlabel("Relaxation time (h)",fontsize=15)
ax2.set_ylabel("Current stability (Amps)",fontsize=15)
ax2.set_title("device 2 current stability",fontsize=15)


Out[15]:
<matplotlib.text.Text at 0x7fd0dd007550>

In [25]:
# print(stability1,stability2)

In [ ]: