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sprindot_revised.py
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sprindot_revised.py
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#%%
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import openpyxl
import gmaps
#%%
df_ashhto=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/US41/SB_DL/AASHTO_Result.csv')
df_IRI=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/US41/SB_DL/IRI-report_6ft.csv')
df_fwd=pd.read_excel('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/US41/US 41_NB_SB_RP 12+00 to RP 22+23.xlsx',sheet_name="US41-SB")
# df_ashhto=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/I70-WB-PL-96-104 /AASHTO_Result-6ft.csv')
# df_IRI=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/I70-WB-PL-96-104 /IRI-report-6ft.csv')
# df_fwd=pd.read_excel('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/SCI/I70 (PL)_East and West Bound Lane from RP 95+95 to RP 100+65.xlsx',sheet_name="I70-WB")
# df_ashhto=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/I70-EB-PL-96-104/AASHTO_Result-6ft.csv')
# df_IRI=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/I70-EB-PL-96-104/IRI-report-6ft.csv')
# df_fwd=pd.read_excel('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/SCI/I70 (PL)_East and West Bound Lane from RP 95+95 to RP 100+65.xlsx',sheet_name="I70-EB")
# df_ashhto=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/I70-EB-DL-96-104/AASHTO_Result_6ft (2).csv')
# df_IRI=pd.read_csv('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/I70-EB-DL-96-104/IRI-report-6ft.csv')
# df_fwd=pd.read_excel('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/SCI/I70 (DL)_East and West Bound Lane from RP 95+95 to RP 100+65.xlsx',sheet_name="I70-EB")
df_ashhto.columns = df_ashhto.columns.str.replace(' ', '')
df_ashhto.columns = df_ashhto.columns.str.replace(r'\([^)]*\)', '')
df_IRI.columns = df_IRI.columns.str.replace(' ', '')
df_IRI.columns = df_IRI.columns.str.replace(r'\([^)]*\)', '')
df_fwd.columns = df_fwd.columns.str.replace(' ', '')
df_fwd.columns = df_fwd.columns.str.replace(r'\([^)]*\)', '')
df_fwd.columns = df_fwd.columns.str.replace(' ', '')
df_fwd.columns = df_fwd.columns.str.replace(r'\([^)]*\)', '')
# %%
def ashhto_z2(df_ashhto):
df_ashhto_2=df_ashhto.copy()
df_ashhto_2['Zone'] = df_ashhto_2['Zone'].replace(4, np.nan)
df_ashhto_2= df_ashhto_2.dropna(axis=0, subset=['Zone'])
return(df_ashhto_2)
#%%
def ashhto_z4(df_ashhto):
df_ashhto_4=df_ashhto.copy()
df_ashhto_4['Zone'] = df_ashhto_4['Zone'].replace(2, np.nan)
df_ashhto_4= df_ashhto_4.dropna(axis=0, subset=['Zone'])
return(df_ashhto_4)
# %%
def ashhto_dmi(df_ashhto):
df_ashhto["DMI"]=6
df_ashhto.loc[df_ashhto.index[0],"DMI"]=0
df_ashhto["DMI"]=df_ashhto["DMI"].cumsum()
return(df_ashhto)
# %%
df_ashhto_z2=ashhto_z2(df_ashhto)
df_ashhto_z4=ashhto_z4(df_ashhto)
#%%
df_ashhto_z4=ashhto_dmi(df_ashhto_z4)
df_ashhto_z2=ashhto_dmi(df_ashhto_z2)
"""------------------------------
the IRI_CD comparison codes start here
------------------------------------"""
# %%
df_plt_z4=df_ashhto_z4[["DMI","Density"]].copy()
RIRI_dict = dict(zip(df_IRI.RefDMI, df_IRI.R_IRI))
df_plt_z4['R_IRI']=df_plt_z4['DMI'].map(RIRI_dict)
#%%
df_plt_z4['Density'] = df_plt_z4['Density'].replace(0, np.nan)
df_plt_z4 = df_plt_z4.dropna(axis=0, subset=['Density'])
#%%
q75=df_plt_z4.R_IRI.quantile(0.75)
df_plt_z4 = df_plt_z4[df_plt_z4["R_IRI"] >=q75]
# %%
def plot_comp_z4(df_plot):
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 300
width=1
fig3, ax = plt.subplots()
max_IRI=df_plot["R_IRI"].max() + 100
##max_iri= round(max_iri) #commented when plotting normalised value
max_CD=df_plot["Density"].max() + 1
#max_cd= round(max_cd) #commented when plotting normalised value
ax2 = ax.twinx()
ax2.set_ylabel('crack density(%)',fontsize=8)
ax2.tick_params(labelsize=8)
ax.set_ylim(0,max_IRI)
ax2.set_ylim(0,max_CD)
markerline, stemline,baseline, =ax.stem(df_plot['DMI'], df_plot["R_IRI"],linefmt=':',markerfmt= 'o',label= "R_IRI")
markerline2, stemline2, baseline2, =ax2.stem(df_plot['DMI']+ 0.1, df_plot["Density"], linefmt=':',markerfmt= 'x', label= "CD-Right wheel path")
ax.set_box_aspect(1)
ax.set_ylabel('IRI', fontsize=8)
ax.set_xlabel('DMI values (ft)',fontsize=8)
ax.tick_params(labelsize=8)
ax.set_title('I70-WB-PL Comparison of crack density at zone 4 and Right IRI(iri_q=0.75)',fontsize=8)
#markerline, stemline, baseline, = ax.stem(x,y,linefmt='k-',markerfmt='ko',basefmt='k.')
plt.setp(stemline,color='m', linewidth = 0.8)
plt.setp(markerline,color='m', markersize = 3,markeredgecolor="darkmagenta")
plt.setp(stemline2,color='b', linewidth = 0.8)
plt.setp(markerline2,color='b', markersize = 3,markeredgecolor="darkblue")
ax.axhline(y=270, color='m', linewidth= 0.8,linestyle="--",label="IRI=270")
ax.legend(fontsize=8,loc=1)
ax2.legend(fontsize=8,loc=2)
#ax2.axhline(y=2, color='g', linewidth=0.8)
return(plt.show())
#%%
plot_comp_z4(df_plt_z4)
#%%
df_plt_z2=df_ashhto_z2[["DMI","Density"]].copy()
LIRI_dict = dict(zip(df_IRI.RefDMI, df_IRI.L_IRI))
df_plt_z2['L_IRI']=df_plt_z2['DMI'].map(LIRI_dict)
#%%
df_plt_z2['Density'] = df_plt_z2['Density'].replace(0, np.nan)
df_plt_z2 = df_plt_z2.dropna(axis=0, subset=['Density'])
#%%
q75=df_plt_z2.L_IRI.quantile(0.75)
df_plt_z2 = df_plt_z2[df_plt_z2["L_IRI"] >=q75]
# %%
def plot_comp_z2(df_plot):
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 300
fig3, ax = plt.subplots()
max_IRI=df_plot["L_IRI"].max()+100
##max_iri= round(max_iri) #commented when plotting normalised value
max_CD=df_plot["Density"].max()+1
#max_cd= round(max_cd) #commented when plotting normalised value
ax2 = ax.twinx()
ax2.set_ylabel('crack density(%)',fontsize=8)
ax2.tick_params(labelsize=8)
ax.set_ylim(0,max_IRI)
ax2.set_ylim(0,max_CD)
markerline, stemline, baseline,=ax.stem(df_plot['DMI'], df_plot["L_IRI"],linefmt=':',label= "L_IRI")
markerline2, stemline2, baseline2,=ax2.stem(df_plot['DMI']+ 0.1, df_plot["Density"], linefmt=':',markerfmt= 'x', label= "CD-Left wheel path")
ax.set_box_aspect(1)
ax.set_ylabel('IRI', fontsize=8)
ax.set_xlabel('DMI values (ft)',fontsize=8)
ax.tick_params(labelsize=8)
ax.set_title('I70-WB-PL Comparison of crack density at zone 2, D0 and Left IRI(iri_q=0.75)',fontsize=8)
#markerline, stemline, baseline, = ax.stem(x,y,linefmt='k-',markerfmt='ko',basefmt='k.')
plt.setp(stemline,color='m', linewidth = 1)
plt.setp(markerline,color='m', markersize = 3,markeredgecolor="darkmagenta")
plt.setp(stemline2,color='b', linewidth = 1)
plt.setp(markerline2,color='b', markersize = 3,markeredgecolor="darkblue")
ax.axhline(y=270, color='m', linewidth= 0.8,linestyle="--", label="IRI=270")
ax.legend(bbox_to_anchor=(1, 1),fontsize=8)
ax2.legend(loc=2,fontsize=8)
return(plt.show())
#%%
plot_comp_z2(df_plt_z2)
"""___________________________________
NOW including the FWD data to plottable data of crack density and IRI
___________________________________________"""
#%%
def nearest(df_fwd, df):
nearest_df=pd.DataFrame()
for index,row in df_fwd.iterrows():
index_value=int(row["DMI"])
ind= df["DMI"].sub(index_value).abs().idxmin()
df_test =df.loc[ind,:]
nearest_df=nearest_df.append(df_test,ignore_index=True)
return(nearest_df)
#%%
df_plt_z2=df_ashhto_z2[["DMI","Density"]].copy()
LIRI_dict = dict(zip(df_IRI.RefDMI, df_IRI.L_IRI))
df_plt_z2["L_IRI"]=df_plt_z2["DMI"].map(LIRI_dict)
df_pltz2_nearest=nearest(df_fwd,df_plt_z2)
df_pltz2_nearest=df_pltz2_nearest.reset_index()
#%%
df_fwd_m=df_fwd[["DMI","D0","D48","AUPP","SCI300","BDI","BCI"]].copy()
df_fwd_m=df_fwd_m.rename(columns={'DMI':'DMI_fwd'})
df_concat_z2=pd.concat([df_pltz2_nearest,df_fwd_m], axis=1)
"""+++++++++++++++++++++++++++++++++++++
This plot is for zone 2 and FWD iri cd BCI SCI BDI data comment the ones you dont want
++++++++++++++++++++++++++++++++++++++++++++++++++++++++"""
# decrease the number of points in the plot to 0.75 quantile
#%%
D0_q75=df_concat_z2.D0.quantile(0.75)
df_concat_z2 = df_concat_z2[df_concat_z2["D0"] >=D0_q75]
#%%
D48_q75=df_concat_z2.D48.quantile(0.75)
df_concat_z2 = df_concat_z2[df_concat_z2["D48"] >=D48_q75]
# %%
def plot_con_z2(df_plot):
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 300
fig, ax = plt.subplots()
fig.subplots_adjust(right=0.75)
max_IRI=df_plot["L_IRI"].max() + 100
##max_iri= round(max_iri) #commented when plotting normalised value
max_CD=df_plot["Density"].max() + 0.1
max_D0=df_plot["D0"].max()+ 1
max_D48=df_plot["D48"].max()+ 1
#max_cd= round(max_cd) #commented when plotting normalised value
ax2 = ax.twinx()
ax3 = ax.twinx()
ax4 = ax3
ax5 = ax3
ax6 = ax3
ax7 = ax3
ax3.spines.right.set_position(("axes", 1.2))
#ax4.spines.right.set_position(("axes", 1.4))
ax2.set_ylabel('Crack-Density(%)',fontsize=8)
ax2.tick_params(labelsize=8)
ax3.set_ylabel('FWD (milli-inches)',fontsize=8)
ax3.tick_params(labelsize=8)
# ax4.set_ylabel('FWD(milli-inches)',fontsize=8)
# ax4.tick_params(labelsize=8)
if max_IRI < 270:
iri= 300
else:
iri= max_IRI +50
if max_D0 < 24.6:
D0= 25
else:
D0= max_D0 +1
ax.set_ylim(0,iri)
ax2.set_ylim(0,max_CD)
ax3.set_ylim(0,D0)
ax4.set_ylim(0,D0)
ax5.set_ylim(0,D0)
ax6.set_ylim(0,D0)
ax7.set_ylim(0,D0)
markerline, stemline, baseline,=ax.stem(df_plot['DMI'], df_plot["L_IRI"],linefmt=':',markerfmt= 'o',basefmt=' ',label= "L_IRI")
markerline.set_markerfacecolor('crimson')
markerline2, stemline2, baseline2,=ax2.stem(df_plot['DMI'], df_plot["Density"], linefmt=':',markerfmt= 'D', basefmt=' ', label= "CD_Left wheel path")
markerline2.set_markerfacecolor('blue')
markerline3, stemline3, baseline3,=ax3.stem(df_plot['DMI_fwd'], df_plot["D0"], linefmt=':',markerfmt= 'x',basefmt=' ', label= "D0-surface")
markerline3.set_markerfacecolor('darkslategrey')
markerline4, stemline4, baseline4,=ax4.stem(df_plot['DMI_fwd'], df_plot["D48"], linefmt=':',markerfmt= 's',basefmt=' ', label= "D48-subgrade")
markerline4.set_markerfacecolor('orange')
markerline5, stemline5, baseline5,=ax5.stem(df_plot['DMI_fwd'], df_plot["SCI300"], linefmt=':',markerfmt= 'D', basefmt=' ', label= "SCI300-surface")
markerline5.set_markerfacecolor('gold')
markerline6, stemline6, baseline6,=ax6.stem(df_plot['DMI_fwd'], df_plot["BDI"], linefmt=':',markerfmt= 'o',basefmt=' ', label= "BDI-Middle layer")
markerline6.set_markerfacecolor('crimson')
markerline7, stemline7, baseline7,=ax7.stem(df_plot['DMI_fwd'], df_plot["BCI"], linefmt=':',markerfmt= 'x',basefmt=' ', label= "BCI- Lower layer")
markerline7.set_markerfacecolor('navy')
ax.set_box_aspect(1)
ax.set_ylabel('IRI (in/mi)', fontsize=8)
ax.tick_params(labelsize=8)
ax.set_xlabel('DMI values(ft)',fontsize=8)
ax.set_title('US41-NB-DL Comparison of crack density at zone 2(left wheel), D0 , D48, SCI300, BDI, BCI and left IRI',fontsize=8)
#markerline, stemline, baseline, = ax.stem(x,y,linefmt='k-',markerfmt='ko',basefmt='k.')
plt.setp(stemline,color='m', linewidth = 0.8)
plt.setp(markerline, markersize = 3,markeredgecolor="m",markeredgewidth=0.5)
plt.setp(stemline2,color='darkgoldenrod', linewidth = 0.8)
plt.setp(markerline2, markersize = 3,markeredgecolor="darkgoldenrod", markeredgewidth=0.7)
plt.setp(stemline3,color='darkslategrey', linewidth = 0.8)
plt.setp(markerline3, markersize = 6 ,markeredgecolor="darkslategrey",markeredgewidth=0.9)
plt.setp(stemline4,color='green', linewidth = 0.8)
plt.setp(markerline4, markersize =6,markeredgecolor="green",markeredgewidth=0.7)
plt.setp(stemline5,color='black', linewidth = 0.8)
plt.setp(markerline5, markersize = 5,markeredgecolor="black",markeredgewidth=0.7)
plt.setp(stemline6,color='darkgreen', linewidth = 0.8)
plt.setp(markerline6, markersize = 4,markeredgecolor="darkgreen",markeredgewidth=0.8)
plt.setp(stemline7,color='navy', linewidth = 0.8)
plt.setp(markerline7, markersize = 6,markeredgecolor="navy", markeredgewidth=0.5)
ax.axhline(y=270, color='m', linewidth= 0.8, linestyle="--",label="IRI=270")
ax3.axhline(y=24.6, color='darkslategrey', linewidth= 0.8, linestyle="--", label="D0=24.6")
ax4.axhline(y=1.8, color='g', linewidth= 0.8, linestyle="--", label="D48=1.8")
ax5.axhline(y=8, color='black', linewidth= 0.8, linestyle="--", label="SCI300=8")
ax6.axhline(y=4.5, color='red', linewidth= 0.8, linestyle="--", label="BDI=4.5")
ax7.axhline(y=4, color='blue', linewidth= 0.8, linestyle="--", label="BCI=4")
ax.legend(bbox_to_anchor=(-0.2,1),loc=1,fontsize=6,markerscale=1)
ax2.legend(bbox_to_anchor=(-0.2, 0.9),loc=1,fontsize=6, markerscale=1) #using a loc1 with bbox fixes the location to right corner and helps the bbox to plot at the right position
ax3.legend(bbox_to_anchor=(-0.2,0.9),loc=1,fontsize=6,markerscale=1)
ax4.legend(bbox_to_anchor=(-0.2, 0.85),loc=1,fontsize=6,markerscale=1)
ax5.legend(bbox_to_anchor=(-0.2, 0.8),loc=1,fontsize=6,markerscale=1)
ax6.legend(bbox_to_anchor=(-0.2, 0.75),loc=1,fontsize=6,markerscale=1)
ax7.legend(bbox_to_anchor=(-0.2, 0.7),loc=1,fontsize=6,markerscale=1)
ax.set_facecolor('lavenderblush')
return(plt.show())
#%%
plot_con_z2(df_concat_z2)
# %%
df_plt_z4=df_ashhto_z4[["DMI","Density"]].copy()
RIRI_dict = dict(zip(df_IRI.RefDMI, df_IRI.R_IRI))
df_plt_z4['R_IRI']=df_plt_z4['DMI'].map(RIRI_dict)
df_pltz4_nearest=nearest(df_fwd,df_plt_z4)
df_pltz4_nearest=df_pltz4_nearest.reset_index()
#%%
df_fwd_m=df_fwd[["DMI","D0","D48","SCI300","BDI","BCI"]].copy()
df_fwd_m=df_fwd_m.rename(columns={'DMI':'DMI_fwd'})
df_concat_z4=pd.concat([df_pltz4_nearest,df_fwd_m], axis=1)
# %%
def plot_con_z4(df_plot):
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 300
fig, ax = plt.subplots()
max_IRI=df_plot["R_IRI"].max()
##max_iri= round(max_iri) #commented when plotting normalised value
max_CD=df_plot["Density"].max() + 0.1
max_D0=df_plot["D0"].max() + 1
max_D48=df_plot["D48"].max() + 1
#max_cd= round(max_cd) #commented when plotting normalised value
ax2 = ax.twinx()
ax3 = ax.twinx()
ax4 = ax.twinx()
ax3.spines.right.set_position(("axes", 1.2))
ax4.spines.right.set_position(("axes", 1.4))
ax2.set_ylabel('crack density(%)',fontsize=6)
ax2.tick_params(labelsize=8)
ax3.set_ylabel('D0 (milli-inches)',fontsize=7)
ax3.tick_params(labelsize=8)
ax4.set_ylabel('D48(milli-inches)',fontsize=7)
ax4.tick_params(labelsize=8)
if max_IRI < 270:
iri= 300
else:
iri= max_IRI +50
if max_D0 < 24.6:
D0= 25
else:
D0= max_D0 +1
ax.set_ylim(0,iri)
ax2.set_ylim(0,max_CD)
ax3.set_ylim(0,D0)
ax4.set_ylim(0,D0)
markerline, stemline, baseline,=ax.stem(df_plot['DMI'], df_plot["R_IRI"],linefmt=':',markerfmt= 'o',label= "R_IRI")
markerline.set_markerfacecolor('m')
markerline2, stemline2, baseline2,=ax2.stem(df_plot['DMI']+ 0.1, df_plot["Density"], linefmt=':',markerfmt= 'D', label= "CD_right wheel path")
markerline2.set_markerfacecolor('b')
markerline3, stemline3, baseline3,=ax3.stem(df_plot['DMI_fwd'], df_plot["D0"], linefmt=':',markerfmt= 'x', label= "D0-surface")
markerline3.set_markerfacecolor('k')
markerline4, stemline4, baseline4,=ax4.stem(df_plot['DMI_fwd'], df_plot["D48"], linefmt=':',markerfmt= 's', label= "D48-subgrade")
markerline4.set_markerfacecolor('g')
ax.set_box_aspect(1)
ax.set_ylabel('IRI', fontsize=8)
ax.set_xlabel('DMI values (ft)',fontsize=8)
ax.tick_params(labelsize=8)
ax.set_title('I70-EB-PL Comparison of crack density at zone 4, D0,D48 and Right IRI',fontsize=7)
#markerline, stemline, baseline, = ax.stem(x,y,linefmt='k-',markerfmt='ko',basefmt='k.')
plt.setp(stemline,color='m', linewidth = 1)
plt.setp(markerline, markersize = 2.5,markeredgecolor="darkmagenta")
plt.setp(stemline2,color='blue', linewidth = 1)
plt.setp(markerline2, markersize = 3,markeredgecolor="darkblue")
plt.setp(stemline3,color='black', linewidth =1)
plt.setp(markerline3, markersize = 5,markeredgecolor="black")
plt.setp(stemline4,color='g', linewidth = 1)
plt.setp(markerline4, markersize = 3,markeredgecolor="darkgreen")
ax.axhline(y=270, color='m', linewidth= 0.8, label="IRI=270")
ax3.axhline(y=24.6, color='k', linewidth= 0.8, linestyle="--", label="D0=24.6")
ax4.axhline(y=1.8, color='g', linewidth= 0.8, linestyle="--", label="D48=1.8")
ax.legend(loc=1,fontsize=6,markerscale=4)
ax2.legend(loc=2,fontsize=6, markerscale=4)
ax3.legend(loc=9,fontsize=6,markerscale=4)
ax4.legend(bbox_to_anchor=(1, 0.75),loc=1,fontsize=6,markerscale=4)
return(plt.show())
#%%
plot_con_z4(df_concat_z4)
"""______________________________
including FWD SCI300, BDI etc"
_________________________________"""
# decrease the number of points in the plot to 0.75 quantile
#%%
D0_q75=df_concat_z4.D0.quantile(0.75)
df_concat_z4 = df_concat_z4[df_concat_z4["D0"] >=D0_q75]
#%%
D48_q75=df_concat_z4.D48.quantile(0.75)
df_concat_z4 = df_concat_z4[df_concat_z4["D48"] >=D48_q75]
#%%
def plot_con_z4(df_plot):
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 300
fig, ax = plt.subplots()
fig.subplots_adjust(right=0.75)
max_IRI=df_plot["R_IRI"].max() + 100
##max_iri= round(max_iri) #commented when plotting normalised value
max_CD=df_plot["Density"].max() + 0.1
max_D0=df_plot["D0"].max()+ 1
max_D48=df_plot["D48"].max()+ 1
#max_cd= round(max_cd) #commented when plotting normalised value
ax2 = ax.twinx()
ax3 = ax.twinx()
ax4 = ax3
ax5 = ax3
ax6 = ax3
ax7 = ax3
ax3.spines.right.set_position(("axes", 1.2))
#ax4.spines.right.set_position(("axes", 1.4))
ax2.set_ylabel('Crack-Density(%)',fontsize=8)
ax2.tick_params(labelsize=8)
ax3.set_ylabel('FWD (milli-inches)',fontsize=8)
ax3.tick_params(labelsize=8)
# ax4.set_ylabel('FWD(milli-inches)',fontsize=8)
# ax4.tick_params(labelsize=8)
if max_IRI < 270:
iri= 300
else:
iri= max_IRI +50
if max_D0 < 24.6:
D0= 25
else:
D0= max_D0 +1
ax.set_ylim(0,iri)
ax2.set_ylim(0,max_CD)
ax3.set_ylim(0,D0)
ax4.set_ylim(0,D0)
ax5.set_ylim(0,D0)
ax6.set_ylim(0,D0)
ax7.set_ylim(0,D0)
markerline, stemline, baseline,=ax.stem(df_plot['DMI'], df_plot["R_IRI"],linefmt=':',markerfmt= 'o',basefmt=' ',label= "R_IRI")
markerline.set_markerfacecolor('crimson')
markerline2, stemline2, baseline2,=ax2.stem(df_plot['DMI'], df_plot["Density"], linefmt=':',markerfmt= 'D', basefmt=' ', label= "CD_Left wheel path")
markerline2.set_markerfacecolor('blue')
markerline3, stemline3, baseline3,=ax3.stem(df_plot['DMI_fwd'], df_plot["D0"], linefmt=':',markerfmt= 'x',basefmt=' ', label= "D0-surface")
markerline3.set_markerfacecolor('darkslategrey')
markerline4, stemline4, baseline4,=ax4.stem(df_plot['DMI_fwd'], df_plot["D48"], linefmt=':',markerfmt= 's',basefmt=' ', label= "D48-subgrade")
markerline4.set_markerfacecolor('orange')
markerline5, stemline5, baseline5,=ax5.stem(df_plot['DMI_fwd'], df_plot["SCI300"], linefmt=':',markerfmt= 'D', basefmt=' ', label= "SCI300-surface")
markerline5.set_markerfacecolor('gold')
markerline6, stemline6, baseline6,=ax6.stem(df_plot['DMI_fwd'], df_plot["BDI"], linefmt=':',markerfmt= 'o',basefmt=' ', label= "BDI-Middle layer")
markerline6.set_markerfacecolor('crimson')
markerline7, stemline7, baseline7,=ax7.stem(df_plot['DMI_fwd'], df_plot["BCI"], linefmt=':',markerfmt= 'x',basefmt=' ', label= "BCI- Lower layer")
markerline7.set_markerfacecolor('navy')
ax.set_box_aspect(1)
ax.set_ylabel('IRI (in/mi)', fontsize=8)
ax.tick_params(labelsize=8)
ax.set_xlabel('DMI values(ft)',fontsize=8)
ax.set_title('US41-SB-DL Comparison of crack density at zone 4(right wheel), D0, D48, SCI300, BDI, BCI and Right IRI',fontsize=8)
#markerline, stemline, baseline, = ax.stem(x,y,linefmt='k-',markerfmt='ko',basefmt='k.')
plt.setp(stemline,color='m', linewidth = 0.8)
plt.setp(markerline, markersize = 3,markeredgecolor="m",markeredgewidth=0.5)
plt.setp(stemline2,color='darkgoldenrod', linewidth = 0.8)
plt.setp(markerline2, markersize = 3,markeredgecolor="darkgoldenrod", markeredgewidth=0.7)
plt.setp(stemline3,color='darkslategrey', linewidth = 0.8)
plt.setp(markerline3, markersize = 6 ,markeredgecolor="darkslategrey",markeredgewidth=0.9)
plt.setp(stemline4,color='green', linewidth = 0.8)
plt.setp(markerline4, markersize =6,markeredgecolor="green",markeredgewidth=0.7)
plt.setp(stemline5,color='black', linewidth = 0.8)
plt.setp(markerline5, markersize = 5,markeredgecolor="black",markeredgewidth=0.7)
plt.setp(stemline6,color='darkgreen', linewidth = 0.8)
plt.setp(markerline6, markersize = 4,markeredgecolor="darkgreen",markeredgewidth=0.8)
plt.setp(stemline7,color='navy', linewidth = 0.8)
plt.setp(markerline7, markersize = 6,markeredgecolor="navy", markeredgewidth=0.5)
ax.axhline(y=270, color='m', linewidth= 0.8, linestyle="--",label="IRI=270")
ax3.axhline(y=24.6, color='darkslategrey', linewidth= 0.8, linestyle="--", label="D0=24.6")
ax4.axhline(y=1.8, color='g', linewidth= 0.8, linestyle="--", label="D48=1.8")
ax5.axhline(y=8, color='black', linewidth= 0.8, linestyle="--", label="SCI300=8")
ax6.axhline(y=4.5, color='red', linewidth= 0.8, linestyle="--", label="BDI=4.5")
ax7.axhline(y=4, color='blue', linewidth= 0.8, linestyle="--", label="BCI=4")
ax.legend(bbox_to_anchor=(-0.2,1),loc=1,fontsize=6,markerscale=1)
ax2.legend(bbox_to_anchor=(-0.2, 0.9),loc=1,fontsize=6, markerscale=1) #using a loc1 with bbox fixes the location to right corner and helps the bbox to plot at the right position
ax3.legend(bbox_to_anchor=(-0.2,0.9),loc=1,fontsize=6,markerscale=1)
ax4.legend(bbox_to_anchor=(-0.2, 0.85),loc=1,fontsize=6,markerscale=1)
ax5.legend(bbox_to_anchor=(-0.2, 0.8),loc=1,fontsize=6,markerscale=1)
ax6.legend(bbox_to_anchor=(-0.2, 0.75),loc=1,fontsize=6,markerscale=1)
ax7.legend(bbox_to_anchor=(-0.2, 0.7),loc=1,fontsize=6,markerscale=1)
ax.set_facecolor('mintcream')
return(plt.show())
#%%
plot_con_z4(df_concat_z4)
# %%
df_plt_z4_ca=df_ashhto_10_z4[["DMI","CrkArea"]].copy()
z4_dict = dict(zip(df_ashhto_100_z4.DMI, df_ashhto_100_z4.CrkArea))
df_plt_z4_ca['CrkArea_100z4']=df_plt_z4_ca['DMI'].map(z4_dict)
# %%
def plot_comp(df_plot):
import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 900
width=0.9
fig3, ax = plt.subplots()
#pos = len(df_plot['DMI'])
#ind = np.arange(pos, step = 1)
max_10=df_plot["CrkArea"].max()
##max_iri= round(max_iri) #commented when plotting normalised value
max_100=df_plot["CrkArea_100z4"].max()
#max_cd= round(max_cd) #commented when plotting normalised value
ax2 = ax.twinx()
ax2.set_ylabel('CrkArea_z4',fontsize=8)
ax.set_ylim(0,max_100)
ax2.set_ylim(0,max_10)
ax.plot(df_plot['DMI'], df_plot["CrkArea_100z4"],alpha=1,color='blue',label= "CrkArea_100")
ax2.plot(df_plot['DMI']+0.9, df_plot["CrkArea"], alpha=1, color='red', label= "CrkArea_10")
ax.legend(loc=2,fontsize=8)
ax2.legend(loc=1,fontsize=8)
ax.set_box_aspect(0.25)
ax.set_ylabel('CrkArea_100z4', fontsize=8)
ax.set_xlabel('DMI values',fontsize=8)
ax.set_title(' Comparison of CrkArea at 10 DMI and 100 DMI for zone 4',fontsize=10)
return(plt.show())
# %%
plot_comp(df_plt_z4_ca)
# %%
df_liri=pd.read_excel('/Users/jhasneha/Documents/SPRINDOT/summer2021/SPRINDOT/boxwhisker.xlsx',sheet_name="R_iri")
column=[]
fig4, ax = plt.subplots()
column=list(df_liri.columns.values)
ax=df_liri.boxplot(column=column)
dict=ax.boxplot(df_liri)
ax.set_title(' Box whisker plot for R_IRI ',fontsize=10)
plt.xticks(rotation = 15)
ax.set_ylabel('IRI (in/mi)', fontsize=8)
df_liri.describe()
# %%