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fine.py
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fine.py
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import pandas as pd
import numpy as np
from reading_spans import get_span as gs
import matplotlib.pyplot as plt
import seaborn as sns
class Master:
def get_master(path,spanid):
mylist=list(range(-200,20001))
master=pd.DataFrame(mylist)
df_tnd,df_hdd,df_drt,df_dit,df_blow=gs.get_df(path)
all_df=[df_tnd,df_hdd,df_drt,df_dit,df_blow]
df_all_span=gs.spanify(all_df,spanid)
master['tnd_ot']=False
master['tnd_ot_marker']=False
master['tnd_hdd']=False
master['tnd_hdd_marker']=False
for i in range(len(df_all_span[0])):
if df_all_span[0]['Method_Execution'][i]=='OT':
master['tnd_ot']=master['tnd_ot']+master[0].between(int(df_all_span[0]['Chainage_From'][i]),int(df_all_span[0]['Chainage_To'][i]),inclusive="both")
master['tnd_ot_marker']=master['tnd_ot_marker']+master[0].between(int(df_all_span[0]['Chainage_From'][i]),int(df_all_span[0]['Chainage_From'][i]),inclusive="both")
master['tnd_ot_marker']=master['tnd_ot_marker']+master[0].between(int(df_all_span[0]['Chainage_To'][i]),int(df_all_span[0]['Chainage_To'][i]),inclusive="both")
elif (df_all_span[0]['Method_Execution'][i]=='HDD'):
master['tnd_hdd']=master['tnd_hdd']+master[0].between(int(df_all_span[0]['Chainage_From'][i]),int(df_all_span[0]['Chainage_To'][i]),inclusive="both")
master['tnd_hdd_marker']=master['tnd_hdd_marker']+master[0].between(int(df_all_span[0]['Chainage_From'][i]),int(df_all_span[0]['Chainage_From'][i]),inclusive="both")
master['tnd_hdd_marker']=master['tnd_hdd_marker']+master[0].between(int(df_all_span[0]['Chainage_To'][i]),int(df_all_span[0]['Chainage_To'][i]),inclusive="both")
master['hdd']=False
master['hdd_marker']=False
for i in range(len(df_all_span[1])):
master['hdd']=master['hdd']+master[0].between(int(df_all_span[1]['Chainage_From'][i]),int(df_all_span[1]['Chainage_To'][i]),inclusive="both")
master['hdd_marker']=master['hdd_marker']+master[0].between(int(df_all_span[1]['Chainage_From'][i]),int(df_all_span[1]['Chainage_From'][i]),inclusive="both")
master['hdd_marker']=master['hdd_marker']+master[0].between(int(df_all_span[1]['Chainage_To'][i]),int(df_all_span[1]['Chainage_To'][i]),inclusive="both")
master['drt']=False
master['drt_marker']=False
master['drt_duct_dam']=False
master['drt_duct_dam_marker']=False
for i in range(len(df_all_span[2])):
master['drt']=master['drt']+master[0].between(int(df_all_span[2]['Chainage_From'][i]),int(df_all_span[2]['Chainage_To'][i]),inclusive="both")
master['drt_marker']=master['drt_marker']+master[0].between(int(df_all_span[2]['Chainage_From'][i]),int(df_all_span[2]['Chainage_From'][i]),inclusive="both")
master['drt_marker']=master['drt_marker']+master[0].between(int(df_all_span[2]['Chainage_To'][i]),int(df_all_span[2]['Chainage_To'][i]),inclusive="both")
if type(df_all_span[2]['Duct_dam_punct_loc_ch_from'][i])==int:
master['drt_duct_dam']=master['drt_duct_dam']+master[0].between(int(df_all_span[2]['Duct_dam_punct_loc_ch_from'][i]),int(df_all_span[2]['Duct_dam_punct_loc_ch_to'][i]),inclusive="both")
master['drt_duct_dam_marker']=master['drt_duct_dam_marker']+master[0].between(int(df_all_span[2]['Duct_dam_punct_loc_ch_from'][i]),int(df_all_span[2]['Duct_dam_punct_loc_ch_from'][i]),inclusive="both")
master['drt_duct_dam_marker']=master['drt_duct_dam_marker']+master[0].between(int(df_all_span[2]['Duct_dam_punct_loc_ch_to'][i]),int(df_all_span[2]['Duct_dam_punct_loc_ch_to'][i]),inclusive="both")
master['dit']=False
master['dit_marker']=False
master['dit_duct_miss']=False
master['dit_duct_miss_marker']=False
for i in range(len(df_all_span[3])):
master['dit']=master['dit']+master[0].between(int(df_all_span[3]['Chainage_From'][i]),int(df_all_span[3]['Chainage_To'][i]),inclusive="both")
master['dit_marker']=master['dit_marker']+master[0].between(int(df_all_span[3]['Chainage_From'][i]),int(df_all_span[3]['Chainage_From'][i]),inclusive="both")
master['dit_marker']=master['dit_marker']+master[0].between(int(df_all_span[3]['Chainage_To'][i]),int(df_all_span[3]['Chainage_To'][i]),inclusive="both")
if type(df_all_span[3]['mb_duct_missing_sec_from'][i])==int:
master['dit_duct_miss']=master['dit_duct_miss']+master[0].between(int(df_all_span[3]['mb_duct_missing_sec_from'][i]),int(df_all_span[3]['mb_duct_missing_sec_to'][i]),inclusive="both")
master['dit_duct_miss_marker']=master['dit_duct_miss_marker']+master[0].between(int(df_all_span[3]['mb_duct_missing_sec_from'][i]),int(df_all_span[3]['mb_duct_missing_sec_from'][i]),inclusive="both")
master['dit_duct_miss_marker']=master['dit_duct_miss_marker']+master[0].between(int(df_all_span[3]['mb_duct_missing_sec_to'][i]),int(df_all_span[3]['mb_duct_missing_sec_to'][i]),inclusive="both")
master['blow']=False
master['blow_marker']=False
for i in range(len(df_all_span[4])):
master['blow']=master['blow']+master[0].between(int(df_all_span[4]['Chainage_From'][i]),int(df_all_span[4]['Chainage_To'][i]),inclusive="both")
master['blow_marker']=master['blow_marker']+master[0].between(int(df_all_span[4]['Chainage_From'][i]),int(df_all_span[4]['Chainage_From'][i]),inclusive="both")
master['blow_marker']=master['blow_marker']+master[0].between(int(df_all_span[4]['Chainage_To'][i]),int(df_all_span[4]['Chainage_To'][i]),inclusive="both")
#print(master.info())
master.rename(columns = {0:'Chainage'}, inplace = True)
master['duct_overlap']=False
for i in range(len(master)):
if master['drt_duct_dam'][i]*master['dit_duct_miss'][i]==True:
master['duct_overlap'][i]=True
master['tnd_overlap']=False
for i in range(len(master)):
if master['hdd'][i]*master['tnd_ot'][i]==True:
master['tnd_overlap'][i]=True
return master
# loading data-set
#iris = sns.load_dataset(master)
# plotting strip plot with seaborn
# deciding the attributes of dataset on
# which plot should be made
#ax = sns.swarmplot(x=master['hdd'], y=master[0])