'''
JMK Engineering Inc. Python Library for design and such.
by: Jeff MacKinnon

email: jeff@jmkengineering.com

Circuit Design Functions

'''
import pandas as pd
import numpy as np
import math

# Need to add the various table files here.
from .jepl_tables import *


def voltage_drop(voltage, current, conductor_size, length, num_phase = 3, material ='cu', num_runs = 1, code = 'CEC', power_factor = 'dc', raceway = True,insul_temp = 75):

    '''    
    This function will return the drop in voltage and in percent of the supply.

    For CEC this function uses Table D3 and the function VD = K * F * i * L / 1000
    K -> is a table lookup based on the conductor material, size raceway and powerfactor
    F -> is the system factor, 2 for single phase and sqrt(3) for three phase
    
    '''

    material = material.upper()
    code = code.upper()
    power_factor = power_factor.upper()
    #conductor_size = str(conductor_size)
    valid_insul_temp = [60,75,90]
    valid_code = ['CEC', 
    ]
    valid_material = ['CU',
                      'AL',
    ]
    valid_power_factor = ['DC', 
                            '1', 
                            '0.9', 
                            '0.8'
    ]

    if insul_temp not in valid_insul_temp:
        return print(temp + " is not valid. The valid temps are "+ str(valid_insul_temp))
    if code not in valid_code:
        return print(code + " is not a valid code. The valid codes are "+ str(valid_code))
    if material not in valid_material:
        return print(material + " is not a valid material. I should be 'al' or 'cu'.")
    if power_factor not in valid_power_factor:
        return print(valid_power_factor + " is not a valid load_type.")

    #
    # Find K
    #

    # Select the correct table
    if (code == 'CEC') :
        D3headers = cectableD3[0]
        D3rows = cectableD3[1:]
        df = pd.DataFrame(D3rows, columns=D3headers)
    else:
        return ('The variables were\'t right, but I\'m a loss to why.')

    # Select the correct column

    if (material == 'CU') & (power_factor == 'DC'):
        column = 'cu_dc'
    elif material == 'CU' & power_factor == '1':
        column = 'cu_100pf'
    elif material == 'CU' & power_factor == '0.9' & raceway == False:
        column = 'cu_cable_90pf'
    elif material == 'CU' & power_factor == '0.8' & raceway == False:
        column = 'cu_cable_80pf'
    elif material == 'CU' & power_factor == '0.9' & raceway == True:
        column = 'cu_raceway_90pf'
    elif material == 'CU' & power_factor == '0.8' & raceway == True:
        column = 'cu_raceway_80pf'
    elif material == 'AL' & power_factor == 'DC':
        column = 'al_dc'
    elif material == 'AL' & power_factor == '1':
        column = 'al_100pf'
    elif material == 'AL' & power_factor == '0.9' & raceway == False:
        column = 'al_cable_90pf'
    elif material == 'AL' & power_factor == '0.8' & raceway == False:
        column = 'al_cable_80pf'
    elif material == 'AL' & power_factor == '0.9' & raceway == True:
        column = 'al_raceway_90pf'
    elif material == 'AL' & power_factor == '0.8' & raceway == True:
        column = 'al_raceway_80pf'
    else:
        return ('Can\'t calculate K factor')

    # Determine the ampacity of the max conductor size
    K_loc = df.loc[df['size'] == conductor_size,column]
    K = K_loc.item()
    #print(K)

    #
    # Find F
    #

    if num_phase == 3:
        F = math.sqrt(3)
    else:
        F = 2
    
    #print(F)
    #print(current)
    #print(length)
    voltage_drop = K * F * current * length / 1000
    percent_voltage_drop = (voltage_drop / voltage) 

    return [voltage_drop, percent_voltage_drop]


def current_for_lookup(current,max_current):

    '''
        This is a helper function for conductor_size. It is used to calculate the number of parallel runs needed,
        and the conductor current for those runs.
    '''

    num_parallel = math.ceil(current / max_current) 
    con_current = current / num_parallel

    return (con_current,num_parallel)

def conductor_size(current, temp = 75, material = 'cu', code = 'CEC', raceway = True, ambient = 30, max = 500, load_type = None):

    '''
    The default temp column will be the 75C column as most terminals are rated for this.
    The default code is CEC as that is where I am.

    I still need to incorporate ambient temperature deratings, but that will be a future improvement

    '''
    material = material.upper()
    code = code.upper()
    max = str(max)
    valid_temp = [60,75,90]
    valid_temp_str = [str(x) for x in valid_temp]
    valid_code = ['CEC', 
    ]
    valid_material = ['CU',
                      'AL',
    ]
    valid_load_type = ['normal','xfmr','xfmrp','xfmrs','motor',None]

    
    #check to make sure that the values are valid
    if temp not in valid_temp:
        return print(temp + " is not valid. The valid temps are "+ str(valid_temp_str))
    if code not in valid_code:
        return print(code + " is not a valid code. The valid codes are "+ str(valid_code))
    if material not in valid_material:
        return print(material + " is not a valid material. I should be 'al' or 'cu'.")
    if load_type not in valid_load_type:
        return print(load_type + " is not a valid load_type.")

    if temp == 90:
        column = '90C'
    elif temp == 75:
        column = '75C'
    else:
        column = '60C'

    '''
        Per CEC rules 26-256 and 28-106 Transformer and Motor conductors should be sized 125% of the rated current.
    '''
    list_125 = ['xfmr','xfmrp','xfmrs', 'motor']
    if load_type in list_125:
        current = 1.25 * current


    # Seclect the proper table
        
    if (code == 'CEC') & (material == 'CU') & (raceway == False):
        df = pd.DataFrame(cectable1, columns=['size', '60C', '75C', '90C'])
    elif (code == 'CEC') & (material == 'CU') & (raceway == True): 
        df = pd.DataFrame(cectable2, columns=['size', '60C', '75C', '90C'])
    elif (code == 'CEC') & (material == 'AL') & (raceway == False): 
        df = pd.DataFrame(cectable3, columns=['size', '60C', '75C', '90C'])
    elif (code == 'CEC') & (material == 'AL') & (raceway == True): 
        df = pd.DataFrame(cectable4, columns=['size', '60C', '75C', '90C'])
    elif (code =='NEC') & (material =='CU'):
        return (' I haven\'t created this table yet')
    elif (code =='NEC') & (material =='AL'):
        return (' I haven\'t created this table yet')
    else:
        return ('The variables were\'t right, but I\'m a loss to why.')

    '''
        Using the correct table, calculate the number of parallel runs needed with the maximum conductor size, 
        and the resulting wire size.
    '''

    # Determine the ampacity of the max conductor size
    max_df = df.loc[df['size'] == max,column]
    max_current = max_df.item()
    #print(max_current)

    # The current that we will need to 
    current_lookup = current_for_lookup(current,max_current)
    current = current_lookup[0]
    num_parallel = current_lookup[1]

    
    # Calculate the absolute difference for all values and find the index of the minimum difference
    sectioned_df = df.loc[df[column] >= current,column]

    closest_index = sectioned_df.idxmin()

    # Retrieve the nearest value using the found index
    conductor_size = df['size'].iloc[closest_index]

    return [conductor_size,num_parallel]

def conductor_ampacity(conductor, temp = 75, material = 'cu', code = 'CEC', raceway = True, ambient = 30):

    '''
        Calculates the ampacity of a conductor size and material using code tables.

    '''

    material = material.upper()
    code = code.upper()
    valid_temp = [60,75,90]
    valid_temp_str = [str(x) for x in valid_temp]
    valid_code = ['CEC', 
    ]
    valid_material = ['CU',
                      'AL',
    ]

    if temp == 90:
        column = '90C'
    elif temp == 75:
        column = '75C'
    else:
        column = '60C'

    if (code == 'CEC') & (material == 'CU') & (raceway == False):
        df = pd.DataFrame(cectable1, columns=['size', '60C', '75C', '90C'])
    elif (code == 'CEC') & (material == 'CU') & (raceway == True): 
        df = pd.DataFrame(cectable2, columns=['size', '60C', '75C', '90C'])
    elif (code == 'CEC') & (material == 'AL') & (raceway == False): 
        df = pd.DataFrame(cectable3, columns=['size', '60C', '75C', '90C'])
    elif (code == 'CEC') & (material == 'AL') & (raceway == True): 
        df = pd.DataFrame(cectable4, columns=['size', '60C', '75C', '90C'])
    elif (code =='NEC') & (material =='CU'):
        return (' I haven\'t created this table yet')
    elif (code =='NEC') & (material =='AL'):
        return (' I haven\'t created this table yet')
    else:
        return ('The variables were\'t right, but I\'m a loss to why.')

    # Determine the ampacity of the conductor size
    result_df = df.loc[df['size'] == conductor,column]
    conductor_ampacity = result_df.item()
    #print(conductor_ampacity)

    return conductor_ampacity


    '''
        This function calculates the bonding wire or bus based on the circuit ampacity.

    '''

    material = material.upper()
    code = code.upper()
    valid_code = ['CEC', 
    ]
    valid_material = ['CU',
                      'AL',
    ]

    # Select the correct table
    if code == 'CEC':
        table16headers = cectable16[0]
        table16rows = cectable16[1:]
        df = pd.DataFrame(table16rows, columns=table16headers)
    else:
        return ('The variables were\'t right, but I\'m a loss to why.')

    # Select the correct column

    if material == 'CU' and bus == False:
        column = 'copper wire'
    elif material == 'CU' and bus == True:
        column = 'copper bus'
    elif material == 'AL' and bus == False:
        column = 'aluminum wire'
    elif material == 'AL' and bus == True:
        column = 'caluminum bus'
    else:
        return ('Can\'t calculate K factor')

    # Calculate the absolute difference for all values and find the index of the minimum difference
    sectioned_df = df.loc[df['current'] >= conductor_ampacity,'current']
    closest_index = sectioned_df.idxmin()

    # Retrieve the nearest value using the found index
    bond_size = df[column].iloc[closest_index]

    return bond_size


## This doesn't work yet, but its getting
def conduit_size(num_cc,cc_con,bond,material='SCH80'):

    # Calculate fill requirements based on Table 8

    valid_material = ['RMC', # Rigid Metal Conduit
                      'FMC', # Flexible Metal Conduit
                      'RPVC', # Rigid PVC
                      'EB1', # Type EB1
                      'DB2', # Type DB2
                      'LTMC', # Liquid Tight Metal Conduit
                      'LTNMC', # Liquid Tight non-metallic conduit
                      'EMT', # electrical metallic tubing
                      'ENT', # electrical non-metallic tubing
                      'SCH40', # HDPE Schedule 40
                      'SCH80', # HDPE Schedule 80
                      #'DR9', # HDPE DR9
                      #'DR11', # HDPE DR11
                      #'DR135', # HDPE DR13.5
                      #'DR155' # HDPE DR15.5
    ]



    if material not in valid_material:
        return print(material + " is not a valid material. I should be 'al' or 'cu'.")

    import numpy as np
    x = np.array(valid_material)
    db_result_index = np.where(x == material)[0][0]

    if num_cc == 1:
        percent_fill = 0.53
    elif num_cc == 2:
        percent_fill = 0.31
    else:
        percent_fill = 0.4

    # Wire Size and diameter

    wire_size = [
        #   ['tradesize',area mm^2]
            ['14',2.08],
            ['12',3.31],
            ['10',5.26],
            ['8',8.37],
            ['6',13.3],
            ['4',21.2],
            ['3',26.7],
            ['2',33.6],
            ['1',42.4],
            ['1/0',53.5],
            ['2/0',67.4],
            ['3/0',85],
            ['4/0',107],
            ['250',127],
            ['300',152],
            ['350',177],
            ['400',203],
            ['500',253],
            ['600',304],
            ['700',355],
            ['800',405],
            ['900',456],
            ['1000',507],
            ['1250',633],
            ['1500',760],
            ['1750',887],
            ['2000',1010]
            ]

    # Calculate the area of current carrying conductors 
    
    x = np.array(wire_size)
    row = np.where(x == cc_con)[0][0]
    current_carrying_conductor_area = wire_size[row][1]
    cc_area = current_carrying_conductor_area * num_cc

    # Bond Area

    row = np.where(x == bond)[0][0]
    bond_area = wire_size[row][1]

    # Total conductor area

    area_conductors = cc_area + bond_area
    #print(area_conductors)

    min_trade_area = area_conductors / percent_fill # The minimum area of the conduit 
    #print(min_trade_area)


    parameter = ' WHERE ' + material + ' > ' + str(min_trade_area)

    try:
        with sqlite3.connect("jepl-cec21.db") as con:
            cur = con.cursor()
            cur.execute('SELECT "Trade Size" from "Table9"'+ parameter )
            table = cur.fetchone()
            conduit = table

    except sqlite3.OperationalError as e:
        print(e)

  
    
    result_raw = conduit[0]
    result_name = str(conduit[0]) + 'mm ' + material


    return result_raw,result_name
    


    

def cable_schedule_naming(conductor_size,conductors,runs = 1,bond='BOND'):

    '''
        Converts the conductor size from the above functions to something that can be added to a database/schedule.
    '''
    
    if conductor_size == '1/0' or conductor_size == '2/0' or conductor_size == '3/0' or conductor_size == '4/0':
        unit = "AWG"
    elif int(conductor_size) > 24:
        unit = 'kcmil'
    else: 
        unit = 'AWG'
    
    if bond == 'BOND':
        bondtext = bond
    elif int(bond) > 24:
        bondtext = '#' + str(bond) + 'kcmil'
    else: 
        bondtext = '#' + str(bond) + 'AWG'
    
    if runs > 1:
        cable_text = str(runs) + "x " + str(conductors) + "C #" + str(conductor_size) + unit + " + " + bondtext
    else:
        cable_text = str(conductors) + "C #" + str(conductor_size) + unit + " + " + bondtext

    return cable_text