from coad.plexos2hdf5 import plexos2hdf5 
import numpy as np
import json
import networkx as nx
import tdsvis
import pandas as pd
import re

tdsvis.offline()

def json_to_networkx(filename):
    """ Converts a json file into nx graph + pos """
    data = json.loads(open(filename).read())
    

    g = nx.DiGraph()
    for node in data['nodes']:
        g.add_node(node['name'], data=node)
        
    for edge in data['edges']:
        g.add_edge(edge['source'], edge['target'])
        
    pos = { x['name']: (x['x'], x['y']) for x in data['pos']}
    
    return g, pos


g, pos = json_to_networkx("data/system/rts.json")

def read_rts(filename):
    df = pd.read_csv(filename)
    df = df.rename(columns={"Unnamed: 0": 'timestamp'})
    df = df.rename(columns={"x": 'timestamp'})
    df['timestamp'] = pd.to_datetime(df['timestamp'])
    df.set_index('timestamp', inplace=True)
    
    return df

RT_Solution_zip = "data/pcm/Model Interesting Week RT Solution/Model Interesting Week RT Solution.zip"
RT_Solution = plexos2hdf5(RT_Solution_zip)

DA_Solution_zip = "data/pcm/Model Interesting Week DA Solution/Model Interesting Week DA Solution.zip"
DA_Solution = plexos2hdf5(DA_Solution_zip)

generator_list=list(RT_Solution["/Generator"])
print generator_list
print len(generator_list)

index= pd.date_range('2024-07-14 00:00:00','2024-7-20 23:55:00', freq='5min')

df_commitment=pd.DataFrame(data=0,index=index,columns=[])
count=0
for i in generator_list:
    
    if str(i)[-1]=='d':
        
        df_commitment[str(i)]=list(RT_Solution["/Generator/" +str(i)+ "/Units Generating/period_0/phase_4"])
    else:
        if count<10:
            gen_name='gen_'+ '0'+ str(count)
            df_commitment[gen_name]=list(RT_Solution["/Generator/" +str(i)+ "/Units Generating/period_0/phase_4"])
        else:
            gen_name='gen_'+ str(count)
            df_commitment[gen_name]=list(RT_Solution["/Generator/" +str(i)+ "/Units Generating/period_0/phase_4"])
        count=count+1   


df_commitment=df_commitment['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_commitment.head()

generator_list=list(RT_Solution["/Generator"])
index= pd.date_range('2024-07-14 00:00:00','2024-7-20 23:55:00', freq='5min')

df_real_power_gen=pd.DataFrame(data=0,index=index,columns=[])
count=0
for i in generator_list:
    
    if str(i)[-1]=='d':
        
        df_real_power_gen[str(i)]=list(RT_Solution["/Generator/" +str(i)+ "/Generation/period_0/phase_4"])
    else:
        if count<10:
            gen_name='gen_'+ '0'+ str(count)
            df_real_power_gen[gen_name]=list(RT_Solution["/Generator/" +str(i)+ "/Generation/period_0/phase_4"])
        else:
            gen_name='gen_'+ str(count)
            df_real_power_gen[gen_name]=list(RT_Solution["/Generator/" +str(i)+ "/Generation/period_0/phase_4"])
        count=count+1 
    
df_real_power_gen=df_real_power_gen['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_real_power_gen.head()

max_wind={'309_wind':159.999756,'317_wind':769.274353,'303_wind':847.488953,'122_wind':715.493347}

df_real_power_gen_norm=df_real_power_gen.copy()
gens_not_found=[]
for i in df_real_power_gen_norm.columns:
    try:
        rating=g.node[str(i)].get('data').get('Pmax')
        df_real_power_gen_norm[str(i)]=df_real_power_gen_norm[str(i)]/float(rating)
    except KeyError:
        #df_real_line_flow_norm=df_real_line_flow_norm.drop(str(i), 1)
        gens_not_found.append(i)
        rating=max_wind[str(i)]
        df_real_power_gen_norm[str(i)]=df_real_power_gen_norm[str(i)]/float(rating)
        
        
        
print  gens_not_found    
df_real_power_gen_norm.head()

generator_list=list(DA_Solution["/Generator"])
index= pd.date_range('2024-07-14 00:00:00','2024-7-20 23:00:00', freq='H')

df_commitment_DA=pd.DataFrame(data=0,index=index,columns=[])
count=0
for i in generator_list:
    
    if str(i)[-1]=='d':
        
        df_commitment_DA[str(i)]=list(DA_Solution["/Generator/" +str(i)+ "/Units Generating/period_0/phase_4"])
    else:
        if count<10:
            gen_name='gen_'+ '0'+ str(count)
            df_commitment_DA[gen_name]=list(DA_Solution["/Generator/" +str(i)+ "/Units Generating/period_0/phase_4"])
        else:
            gen_name='gen_'+ str(count)
            df_commitment_DA[gen_name]=list(DA_Solution["/Generator/" +str(i)+ "/Units Generating/period_0/phase_4"])
        count=count+1   


#df_commitment=df_commitment['2024-07-14 00:00:00':'2024-7-15 00:00:00']

df_commitment_DA=df_commitment_DA.resample('5min').ffill()
df_commitment_DA=df_commitment_DA['2024-07-14 00:00:00':'2024-7-14 23:55:00']
df_commitment_DA.head()

generator_list=list(DA_Solution["/Generator"])
index= pd.date_range('2024-07-14 00:00:00','2024-7-20 23:00:00', freq='H')

df_real_power_gen_DA=pd.DataFrame(data=0,index=index,columns=[])
count=0
for i in generator_list:
    
    if str(i)[-1]=='d':
        
        df_real_power_gen_DA[str(i)]=list(DA_Solution["/Generator/" +str(i)+ "/Generation/period_0/phase_4"])
    else:
        if count<10:
            gen_name='gen_'+ '0'+ str(count)
            df_real_power_gen_DA[gen_name]=list(DA_Solution["/Generator/" +str(i)+ "/Generation/period_0/phase_4"])
        else:
            gen_name='gen_'+ str(count)
            df_real_power_gen_DA[gen_name]=list(DA_Solution["/Generator/" +str(i)+ "/Generation/period_0/phase_4"])
        count=count+1 

        

df_real_power_gen_DA=df_real_power_gen_DA.resample('5min').ffill()
df_real_power_gen_DA=df_real_power_gen_DA['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_real_power_gen_DA.head()

max_wind={'309_wind':159.999756,'317_wind':769.274353,'303_wind':847.488953,'122_wind':715.493347}

df_real_power_gen_norm_DA=df_real_power_gen_DA.copy()
gens_not_found=[]
for i in df_real_power_gen_norm_DA.columns:
    try:
        rating=g.node[str(i)].get('data').get('Pmax')
        df_real_power_gen_norm_DA[str(i)]=df_real_power_gen_norm_DA[str(i)]/float(rating)
    except KeyError:
        #df_real_line_flow_norm=df_real_line_flow_norm.drop(str(i), 1)
        gens_not_found.append(i)
        rating=max_wind[str(i)]
        df_real_power_gen_norm_DA[str(i)]=df_real_power_gen_norm_DA[str(i)]/float(rating)
        
        
        
print  gens_not_found    
df_real_power_gen_norm_DA.head()

line_list=list(RT_Solution["/Line"])
index=pd.date_range('2024-07-14 00:00:00','2024-7-20 23:55:00', freq='5min')

df_real_line_flow=pd.DataFrame(data=0,index=index,columns=[])

for i in line_list:
    if str(i)[-1]==2:
        continue 
        
    else:
        duplicate=str(i)[:-1] + '2'
        line_name='branch_' + str(i)[:-2]
        if duplicate in line_list:
            line_1=np.array(list(RT_Solution["/Line/"+str(i)+"/Flow/period_0/phase_4"]))
            line_2=np.array(list(RT_Solution["/Line/"+duplicate+"/Flow/period_0/phase_4"]))
            df_real_line_flow[line_name]=line_1+line_2
        else:
            df_real_line_flow[line_name]=list(RT_Solution["/Line/"+str(i)+"/Flow/period_0/phase_4"])
            
df_real_line_flow=df_real_line_flow['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_real_line_flow.head()

df_real_line_flow_norm=df_real_line_flow.copy()
branches_not_found=[]
for i in df_real_line_flow_norm.columns:
    try:
        rating=g.node[str(i)].get('data').get('rateA')
        df_real_line_flow_norm[str(i)]=df_real_line_flow_norm[str(i)]/float(rating)
    except KeyError:
        df_real_line_flow_norm=df_real_line_flow_norm.drop(str(i), 1)
        branches_not_found.append(i)
        
print  branches_not_found    
df_real_line_flow_norm.head() 

line_list=list(DA_Solution["/Line"])
index=pd.date_range('2024-07-14 00:00:00','2024-7-20 23:00:00', freq='H')

df_real_line_flow_DA=pd.DataFrame(data=0,index=index,columns=[])

for i in line_list:
    if str(i)[-1]==2:
        continue 
        
    else:
        duplicate=str(i)[:-1] + '2'
        line_name='branch_' + str(i)[:-2]
        if duplicate in line_list:
            line_1=np.array(list(DA_Solution["/Line/"+str(i)+"/Flow/period_0/phase_4"]))
            line_2=np.array(list(DA_Solution["/Line/"+duplicate+"/Flow/period_0/phase_4"]))
            df_real_line_flow_DA[line_name]=line_1+line_2
        else:
            df_real_line_flow_DA[line_name]=list(DA_Solution["/Line/"+str(i)+"/Flow/period_0/phase_4"])

df_real_line_flow_DA=df_real_line_flow_DA.resample('5min').ffill()
df_real_line_flow_DA=df_real_line_flow_DA['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_real_line_flow_DA.head()

df_real_line_flow_norm_DA=df_real_line_flow_DA.copy()
branches_not_found=[]
for i in df_real_line_flow_norm_DA.columns:
    try:
        rating=g.node[str(i)].get('data').get('rateA')
        df_real_line_flow_norm_DA[str(i)]=df_real_line_flow_norm_DA[str(i)]/float(rating)
    except KeyError:
        df_real_line_flow_norm_DA=df_real_line_flow_norm_DA.drop(str(i), 1)
        branches_not_found.append(i)
        
print  branches_not_found    
df_real_line_flow_norm_DA.head() 

bus_list=list(RT_Solution["/Node"])

    
index=pd.date_range('2024-07-14 00:00:00','2024-7-20 23:55:00', freq='5min')

df_bus_voltage=pd.DataFrame(data=0,index=index,columns=bus_list)

for i in bus_list:
   
    df_bus_voltage[str(i)]=list(RT_Solution["/Node/"+str(i)+"/Voltage/period_0/phase_4"])
    df_bus_voltage=df_bus_voltage.rename(columns={str(i):'bus_'+ str(i)})
    
df_bus_voltage=df_bus_voltage['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_bus_voltage.head()

bus_list=list(RT_Solution["/Node"])
index=pd.date_range('2024-07-14 00:00:00','2024-7-20 23:55:00', freq='5min')

df_bus_real_demand=pd.DataFrame(data=0,index=index,columns=bus_list)

for i in bus_list:
   
    df_bus_real_demand[str(i)]=list(RT_Solution["/Node/"+str(i)+"/Load/period_0/phase_4"])
    df_bus_real_demand=df_bus_real_demand.rename(columns={str(i):'bus_'+ str(i)})
    
df_bus_real_demand=df_bus_real_demand['2024-07-14 00:00:00':'2024-7-14 23:55:00']

df_bus_real_demand.head()

network = tdsvis.network(g, pos=pos, table=True, color='power flow', scale=2, width=400,
                         legend=False, node_size={'bus': 2, 'line': 0.25, 'gen': 0.5})

va_line = tdsvis.line(df_bus_real_demand, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Demand',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

vb_line = tdsvis.line(df_real_power_gen, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Generation',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

vc_line = tdsvis.line(df_real_line_flow, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Flow', emit='power flow',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

#tdsvis.plot([network, vm_line, va_line], emit=True, title="Bus data as a function of time")
tdsvis.plot([network, va_line,vb_line,vc_line], emit=True, title="RTS System Over Time")

network = tdsvis.network(g, pos=pos, table=True, color='power flow', scale=2, width=400,
                         legend=False, node_size={'bus': 2, 'line': 0.25, 'gen': 0.5})

va_line = tdsvis.line(df_bus_real_demand, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Demand',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

vb_line = tdsvis.line(df_real_power_gen_norm, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Generation',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

vc_line = tdsvis.line(df_real_line_flow_norm, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Flow', emit='power flow',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

#tdsvis.plot([network, vm_line, va_line], emit=True, title="Bus data as a function of time")
tdsvis.plot([network, va_line,vb_line,vc_line], emit=True, title="Normalized RTS System Over Time")

network = tdsvis.network(g, pos=pos, table=True, color='power generation', scale=2, width=400,
                         legend=False, node_size={'bus': 2, 'line': 0.25, 'gen': 0.5})

va_line = tdsvis.line(df_real_power_gen, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='Real Power Generation', emit='power generation',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})
vs_line = tdsvis.line(df_real_power_gen_DA, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='DA Real Power Generation',
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

vm_line = tdsvis.line(df_commitment_DA, color='lightgrey', 
                   scale=1.5, xlab="Time", ylab='DA Generator Commitment', 
                   margin={'top': 10, 'left': 60, 'right': 10, 'bottom': 50})

tdsvis.plot([network, vm_line, vs_line,va_line], emit=True, title="Generator Data Over Time")