import pvlib
import pandas as pd

import psutil
import os

cec_modules = pvlib.pvsystem._parse_raw_sam_df('/media/share/libraries/CEC Modules.csv')
# Following parameters are set as defaults as suggested in the PVLib source code
cec_modules.loc['b', :] = 0.05
cec_modules.loc['EgRef', :] = 1.121
cec_modules.loc['dEgdT', :] = -0.0002677
cec_inverters = pvlib.pvsystem._parse_raw_sam_df('/media/share/libraries/cecinverter.csv')


def get_system():
    return pvlib.pvsystem.PVSystem(surface_tilt=25,
                                   surface_azimuth=180,
                                   inverter='Siemens_Industry__SINVERT_PVM20_UL_480V__CEC_2012_',
                                   module='Canadian_Solar_CS5P_235P',
                                   inverter_parameters=cec_inverters['Siemens_Industry__SINVERT_PVM20_UL_480V__CEC_2012_'],
                                   module_parameters=cec_modules['Canadian_Solar_CS5P_235P'],
                                   name='test')


def get_location():
    return pvlib.location.Location(latitude=50.936389, longitude=6.952778, altitude=50)


def get_mc(system, location):
    return pvlib.modelchain.ModelChain(system, location,
                                       dc_model='singlediode', ac_model='snlinverter', spectral_model='no_loss',
                                       temp_model='sapm', aoi_model='ashrae', solar_position_method='nrel_numba',
                                       transposition_model='haydavies', losses_model='pvwatts',
                                       clearsky_model='simplified_solis', orientation_strategy=None)


def get_weather(mc, times):
    weather = pd.DataFrame(index=times, data={'temp_air': 20, 'wind_speed': 5})

    weather[['ghi', 'dni', 'dhi']] = mc.location.get_clearsky(mc.solar_position.index,
                                                              mc.clearsky_model)
    return weather


def get_mem_usage(process):
    return process.memory_info()[0] / float(2 ** 20)


times = pd.DatetimeIndex(start='2018-06-18 00:00', end='2018-06-19 00:00', freq='15min')
result = pd.DataFrame(data={'output': 0}, index=[times])
rg = 30

process = psutil.Process(os.getpid())
mem_usage = pd.Series(index=range(rg))

for i in range(rg):
    system = get_system()
    location = get_location()
    mc = get_mc(system, location)

    mc.solar_position = mc.location.get_solarposition(times)

    weather = get_weather(mc, times)

    mc.run_model(times=times, weather=weather)

    print('{} of {}'.format(i, rg))

    result['output'] += mc.ac

    mem_usage[i] = get_mem_usage(process)


print('Mem_usage with pvlib version {}'.format(pvlib.__version__))
print(mem_usage)
mem_usage.to_csv('/media/share/mem_usage.csv', sep=';', decimal=',', header=True)