In [1]:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
In [2]:
df_ag2s =  pd.read_csv("Ag2S_compression_ref_Xun_shi.csv")
In [3]:
df_x03_a =  pd.read_csv("64-2_x=0.3_amo_1.csv",header=1)
df_x03_s =  pd.read_csv("63-4_x=0.3_sta_1.csv",header=1)
df_x04_a =  pd.read_csv("63-2_x=0.4_amo_1.csv",header=1)
df_x04_s =  pd.read_csv("65-1_x=0.4_sta_1.csv",header=1)
df_x05_a =  pd.read_csv("66-2_x=0.5_amo_1.csv",header=1)
df_x05_s =  pd.read_csv("66-1_x=0.5_sta_1.csv",header=1)
df_x06_a =  pd.read_csv("61-2_x=0.6_amo_1.csv",header=1)
df_x06_s =  pd.read_csv("61-1_x=0.6_sta_1.csv",header=1)
In [4]:
df_x03_a
Out[4]:
(s) (mm) (N) Unnamed: 3 (%) (MPa) (mm).1
0 0.000 0.0000 2.5410 0.0 0.0000 0.0842 0.0000
1 0.020 0.0000 2.5416 0.0 0.0000 0.0842 0.0000
2 0.040 0.0000 2.4403 0.0 0.0000 0.0808 0.0000
3 0.060 0.0000 2.4472 0.0 0.0000 0.0811 0.0000
4 0.080 0.0000 2.4657 0.0 0.0000 0.0817 0.0000
... ... ... ... ... ... ... ...
77082 1541.328 2.5688 9996.9180 0.0 90.1338 331.1257 2.5688
77083 1541.348 2.5688 9997.6270 0.0 90.1338 331.1492 2.5688
77084 1541.368 2.5689 9998.4629 0.0 90.1358 331.1769 2.5689
77085 1541.388 2.5689 9999.2217 0.0 90.1378 331.2020 2.5689
77086 1541.408 2.5689 10000.0215 0.0 90.1378 331.2285 2.5689

77087 rows × 7 columns

In [5]:
df_al = pd.read_csv("Al_compression.csv")
In [6]:
def plot_strain_stress(l_df,l_d,l_h,l_lab,xmin,xmax,ymin,ymax,filename):
    l_color = ["black","red", "blue","green","cyan","purple","orange","pink","gray","brown"]
    l_mrks = ["o","^", "*","d",">"]
    plt.clf() # initialization
    plt.figure(figsize=(8, 6))
    plt.axis([xmin,xmax,ymin,ymax])
    plt.tick_params(direction="in")
    plt.rcParams["font.family"] = "Times New roman"
    plt.rcParams["axes.linewidth"] = 1.5
    plt.tick_params(direction="in")
    plt.rcParams["xtick.major.size"] = 10
    plt.rcParams["xtick.major.width"] = 1.5
    plt.rcParams["ytick.major.size"] = 10
    plt.rcParams["ytick.major.width"] = 1.5
    plt.rcParams["font.size"] = 30
    #plt.tick_params(labelleft=False)
    #plt.ylabel("Heat flow, mW")
    plt.ylabel(r"Stress (MPa)")
    plt.xlabel(r"Strain (%)")
    l_st = ["-","--",":","-."]
    for i,df in enumerate(l_df):
        d, h = l_d[i],l_h[i]
        S = np.pi*0.25*d*d
        plt.plot(df.iloc[:,1]/d*100,df.iloc[:,2]/S,color=l_color[i],label=l_lab[i])
        #plt.plot(df.iloc[:,4],df.iloc[:,5],color=l_color[i],label=l_lab[i])
    #plt.hlines([0.5],0,1000,linestyle=":")
    plt.legend(loc='upper left')
    plt.savefig(filename,bbox_inches="tight")
    plt.show()
In [7]:
def plot_strain_stress2(l_df,l_dif_s,l_dif_c,l_lst,l_col,l_df_ref,xmin,xmax,ymin,ymax,filename):
    l_mrks = ["o","^", "*","d",">"]
    plt.clf() # initialization
    plt.figure(figsize=(8, 6))
    plt.axis([xmin,xmax,ymin,ymax])
    plt.tick_params(direction="in")
    plt.rcParams["font.family"] = "Times New roman"
    plt.rcParams["axes.linewidth"] = 1.5
    plt.tick_params(direction="in")
    plt.rcParams["xtick.major.size"] = 10
    plt.rcParams["xtick.major.width"] = 1.5
    plt.rcParams["ytick.major.size"] = 10
    plt.rcParams["ytick.major.width"] = 1.5
    plt.rcParams["font.size"] = 30
    #plt.tick_params(labelleft=False)
    #plt.ylabel("Heat flow, mW")
    plt.ylabel(r"Compression stress (MPa)")
    plt.xlabel(r"Strain (%)")
    plt.yscale("log")
    l_st = ["-","--",":","-."]
    for i,df in enumerate(l_df):
        ic = l_dif_c[i]
        plt.plot(df.iloc[:,4]-l_dif_s[i],df.iloc[:,5]-df.iloc[ic,5],color=l_col[i],linestyle = l_lst[i])
    if len(l_df_ref)>0:
        for i,df in enumerate(l_df_ref):
            plt.plot(df.iloc[:,0],df.iloc[:,1],color="black",linestyle=":")
    #plt.hlines([0.5],0,1000,linestyle=":")
    #plt.legend(loc='upper left')
    plt.savefig(filename,bbox_inches="tight")
    plt.show()
In [8]:
l_df = [df_x03_a,df_x04_a,df_x05_a,df_x06_a]
l_dif_s = [5, 5, 5, 6.0]
l_dif_c = [4537,4653,4458,4900]
l_lst = ["-","-","-","-"]
l_col = ["black","red","blue","purple"]
l_df_ref = [df_al,df_ag2s]
plot_strain_stress2(l_df,l_dif_s,l_dif_c,l_lst,l_col,l_df_ref,0,40,1,1e3,"test.jpg")

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In [9]:
l_df = [df_x03_a,df_x03_s,df_x04_a,df_x04_s,df_x05_a,df_x05_s,df_x06_a,df_x06_s]
l_dif_s = [5, 5.5, 5, 5.5, 5, 5.5, 6.0, 5.5]
l_dif_c = [4537,4511,4653,4859,4458,4492,4900,4724]
l_lst = [":","-",":","-",":","-",":","-"]
l_col = ["black","black","red","red","blue","blue","purple","purple"]
plot_strain_stress2(l_df,l_dif_s,l_dif_c,l_lst,l_col,[],0,40,0,200,"test.jpg")

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In [10]:
l_df = [df_x05_a,df_x05_s]
l_dif_s = [ 5, 5.5]
l_dif_c = [4458,4492]
l_lst = ["-","-",":","-",":","-",":","-"]
l_col = ["black","red"]
plot_strain_stress2(l_df,l_dif_s,l_dif_c,l_lst,l_col,[],0,40,0,150,"test.jpg")

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In [11]:
l_df = [df_x03_a,df_x03_s,df_x04_a,df_x04_s,df_x05_a,df_x05_s,df_x06_a,df_x06_s]
l_dif_s = [5.3, 5.5, 5, 5.5, 5, 5.5, 6.0, 5.6]
l_dif_c = [4537,4511,4653,4859,4458,4492,4900,4724]
l_lst = [":","-",":","-",":","-",":","-"]
l_col = ["black","black","red","red","blue","blue","purple","purple"]
plot_strain_stress2(l_df,l_dif_s,l_dif_c,l_lst,l_col,[],0,4,0,50,"test.jpg")

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In [13]:
l_df = [df_x04_s,df_x05_s,df_x06_s]
l_dif_s = [ 5.5, 5.5, 5.5]
l_dif_c = [4859,4492,4724]
l_lst = ["-","-","-"]
l_col = ["red","blue","purple"]
#plot_strain_stress2(l_df,l_dif_s,l_dif_c,l_lst,l_col,0,40,0,150,"test.jpg")
In [14]:
def plot_strain_stress3(iylog,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,l_df_ref,xmin,xmax,ymin,ymax,filename):
    l_mrks = ["o","^", "*","d",">"]
    plt.clf() # initialization
    plt.figure(figsize=(8, 6))
    plt.axis([xmin,xmax,ymin,ymax])
    plt.tick_params(direction="in")
    plt.rcParams["font.family"] = "Times New roman"
    plt.rcParams["axes.linewidth"] = 1.5
    plt.tick_params(direction="in")
    plt.rcParams["xtick.major.size"] = 10
    plt.rcParams["xtick.major.width"] = 1.5
    plt.rcParams["ytick.major.size"] = 10
    plt.rcParams["ytick.major.width"] = 1.5
    plt.rcParams["font.size"] = 30
    #plt.tick_params(labelleft=False)
    #plt.ylabel("Heat flow, mW")
    plt.ylabel(r"Compression stress (MPa)")
    plt.xlabel(r"Strain (%)")
    if iylog == 1:
        plt.yscale("log")
    l_st = ["-","--",":","-."]
    for i,df in enumerate(l_df):
        ic = l_dif_c[i]
        #plt.plot(df.iloc[:,4]-l_dif_s[i],df.iloc[:,5]-df.iloc[ic,5],color=l_col[i],linestyle = l_lst[i])
        #plt.plot((df.iloc[ic:,6]-df.iloc[ic,6])/(l_h0[i]-df.iloc[ic,6]),df.iloc[ic:,5]-df.iloc[ic,5],color=l_col[i],linestyle = l_lst[i])
        plt.plot((df.iloc[:,6]-df.iloc[ic,6])/(l_h0[i]-df.iloc[ic,6])*100,\
                 (df.iloc[:,5]-df.iloc[ic,5])*(1-(df.iloc[:,6]-df.iloc[ic,6])/(l_h0[i]-df.iloc[ic,6])),\
                 color=l_col[i],linestyle = l_lst[i])
        #print(l_h0[i],df.iloc[ic,6])
    if len(l_df_ref)>0:
        for i,df in enumerate(l_df_ref):
            plt.plot(df.iloc[:,0],df.iloc[:,1],color="black",linestyle=":")
    #plt.hlines([0.5],0,1000,linestyle=":")
    #plt.legend(loc='upper left')
    plt.savefig(filename,bbox_inches="tight")
    plt.show()
In [15]:
l_df = [df_x03_a,df_x04_a,df_x05_a,df_x06_a]
l_dif_s = [5, 5, 5, 6.0]
l_dif_c = [4600,4653,4550,4900]
l_h0 = [2.853,3.1,2.97,2.72]
l_lst = ["-","-","-","-"]
l_col = ["black","red","blue","purple"]
l_df_ref = [df_al,df_ag2s]
plot_strain_stress3(1,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,l_df_ref,0,40,1,1e3,"test.jpg")

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In [16]:
l_df = [df_x03_a,df_x04_a,df_x05_a,df_x06_a]
l_dif_s = [5, 5, 5, 6.0]
l_dif_c = [4600,4653,4550,4900]
l_h0 = [2.853,3.1,2.97,2.72]
l_lst = ["-","-","-","-"]
l_col = ["black","red","blue","purple"]
l_df_ref = []
plot_strain_stress3(0,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,l_df_ref,-0.1,2,0,3e1,"test.jpg")

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In [16]:
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
import numpy as np
In [17]:
l_df = [df_x06_s,df_x05_a]
l_dif_s = [  5.5, 5]
l_dif_c = [4724,4550]
l_lst = ["-","-"]
l_col = ["green","red"]
l_h0 = [2.73,2.97]
plot_strain_stress3(1,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,[],0,40,1,1e3,"test.jpg")

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In [23]:
l_df = [df_x06_s,df_x05_a]
l_dif_s = [  5.5, 5]
l_dif_c = [4850,4550]
l_lst = ["-","-"]
l_col = ["green","red"]
l_h0 = [2.73,2.97]
plot_strain_stress3(0,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,[],0,2,0,20,"test.jpg")

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In [15]:
l_df = [df_x06_a,df_x05_a,df_x03_s]
l_dif_s = [6,5,5.5]
l_dif_c = [4900,4550,4511]
l_lst = ["-"]*len(l_df)
l_col = ["black","red","blue"]
l_h0 = [2.72,2.97,2.73]
l_df_ref = [df_al,df_ag2s]
plot_strain_stress3(1,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,l_df_ref,0,40,1,1e3,"test.jpg")

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In [24]:
l_df = [df_x06_a,df_x05_a,df_x03_s]
l_dif_s = [6,5,5.5]
l_dif_c = [4900,4550,4511]
l_lst = ["-"]*len(l_df)
l_col = ["black","red","blue"]
l_h0 = [2.72,2.97,2.73]
l_df_ref = [df_al,df_ag2s]
plot_strain_stress3(0,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,[],-0.1,4,0,2e1,"test.jpg")

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In [38]:
l_df = [df_x04_s,df_x05_s,df_x06_s,df_x05_a]
l_dif_s = [ 5.5, 5.5, 5.5]
l_dif_c = [4859,4492,4850,4550]
l_lst = ["-","-","-",":"]
l_col = ["red","blue","purple","blue"]
l_h0 = [2.73,2.94,2.72,2.97]
plot_strain_stress3(0,l_df,l_dif_s,l_dif_c,l_lst,l_col,l_h0,[],0,2,0,2e1,"test.jpg")

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In [69]:
def fit(df,n1,n2):
    return curve_fit(linear,0.01*df.iloc[n1:n2,4],df.iloc[n1:n2,5])
In [70]:
def linear(x,a,b):
    return a*x+b
In [72]:
p_x03a = fit(df_x03_a,4300,5000)
p_x03a
Out[72]:
(array([747.33388928, -27.98349781]),
 array([[37.34071876, -2.02995227],
        [-2.02995227,  0.11056247]]))
In [73]:
p_x03s = fit(df_x03_s,4511,5336)
p_x03s
Out[73]:
(array([1060.21035737,  -47.87998264]),
 array([[ 1.15035002, -0.06910579],
        [-0.06910579,  0.00416117]]))
In [74]:
p_x04a = fit(df_x04_a,4300,5000)
p_x04a
Out[74]:
(array([1241.69081471,  -48.96219715]),
 array([[25.85906875, -1.2929288 ],
        [-1.2929288 ,  0.06476714]]))
In [75]:
p_x04s = fit(df_x04_s,4511,5336)
p_x04s
Out[75]:
(array([1326.37845615,  -59.65899265]),
 array([[21.3287582 , -1.18964498],
        [-1.18964498,  0.06651001]]))
In [76]:
p_x05a = fit(df_x05_a,4300,5000)
p_x05a
Out[76]:
(array([779.54650817, -28.98287406]),
 array([[34.06264938, -1.77721066],
        [-1.77721066,  0.09290065]]))
In [77]:
p_x05s = fit(df_x05_s,4511,5336)
p_x05s
Out[77]:
(array([1093.55901783,  -49.94146525]),
 array([[49.09357589, -2.96098483],
        [-2.96098483,  0.17900494]]))
In [78]:
p_x06a = fit(df_x06_a,4900,5715)
p_x06a
Out[78]:
(array([720.33335894, -32.50256546]),
 array([[ 0.2491464 , -0.01619875],
        [-0.01619875,  0.00105526]]))
In [84]:
p_x06s = fit(df_x06_s,4711,6000)
p_x06s
Out[84]:
(array([906.28142292, -39.73576392]),
 array([[13.98196818, -0.87247454],
        [-0.87247454,  0.05470506]]))