'''

This is just a scratchpad script I use inside ipython

'''

from pprint import PrettyPrinter

pp = PrettyPrinter(indent=2)

from collections import defaultdict

from math import log, exp

import numpy

np = numpy

import transaction

import unit_conversion as uc

from sqlalchemy import engine_from_config

from sqlalchemy.orm.relationships import (RelationshipProperty,

ONETOMANY)

from pyramid.paster import (get_appsettings,

setup_logging)

from oil_library import _get_db_session

from oil_library.models import (Base, ImportedRecord, Oil,

Density, Toxicity, Category)

from oil_library.oil_props import OilProps

from oil_library.utilities import get_viscosity, get_boiling_points_from_api

from oil_library.init_oil import density_at_temperature

session = _get_db_session()

oil_obj = session.query(Oil).filter(Oil.name == 'ALASKA NORTH SLOPE').one()

props_obj = OilProps(oil_obj)

viscosity = uc.convert('Kinematic Viscosity', 'm^2/s', 'cSt',

get_viscosity(oil_obj, 273.15 + 38))

print oil_obj, '\n\tviscosity at 38C =', viscosity

for v in oil_obj.kvis:

v_ref, t_ref = v.m_2_s, v.ref_temp_k

print '\tviscosity: {0} m^2/s at {1}K'.format(v.m_2_s, v.ref_temp_k)

print 'imported pour points:', (oil_obj.imported.pour_point_min_k,

oil_obj.imported.pour_point_max_k)

print 'oil pour points:', (oil_obj.pour_point_min_k,

oil_obj.pour_point_max_k)

def get_ptry_values(oil_obj, component_type, sub_fraction=None):

yield (P_try, F_i, T_i, component_type)

def get_sa_mass_fractions(oil_obj):

yield (f_sat, f_arom)

print 'oil cuts:'

pp.pprint(oil_obj.cuts)

print 'oil imported cuts =', oil_obj.imported.cuts

print '\ninitial trial densities:'

K_arom = 10.0

K_sat = 12.0

ptry_values = (list(get_ptry_values(oil_obj, 'Aromatics')) +

list(get_ptry_values(oil_obj, 'Saturates')))

for r in ptry_values:

print '\t', r

for f in oil_obj.sara_fractions:

if f.sara_type in ('Resins', 'Asphaltenes'):

print '\t', (1100.0, f.fraction)

print '\naverage density based on trials assuming equal sub-fractions:'

print sum([(P_try * (F_i * 0.5))

for P_try, F_i, T_i, c_type in ptry_values] +

[(1100.0 * f.fraction) for f in oil_obj.sara_fractions

if f.sara_type in ('Resins', 'Asphaltenes')]

)

print '\nNow try to get saturate/aromatic mass fractions based on trials'

print 'molecular weights:'

for mw in oil_obj.molecular_weights:

print '\t', (mw.sara_type, mw.g_mol, mw.ref_temp_k)

print '\naverage density based on trials using adjusted fractions:'

sa_ratios = list(get_sa_mass_fractions(oil_obj))

ptry_values = (list(get_ptry_values(oil_obj, 'Saturates',

[r[0] for r in sa_ratios])) +

list(get_ptry_values(oil_obj, 'Aromatics',

[r[1] for r in sa_ratios])))

ra_ptry_values = [(1100.0, f.fraction)

for f in oil_obj.sara_fractions

if f.sara_type in ('Resins', 'Asphaltenes')]

print 'adjusted ptry_values:'

pp.pprint(ptry_values)

print 'average ptry', (sum([(P_try * F_i)

for P_try, F_i, T_i, c_type in ptry_values]) /

sum([(F_i) for P_try, F_i, T_i, c_type in ptry_values]))

ptry_avg_density = sum([(P_try * F_i)

)

total_sa_fraction = sum([F_i for P_try, F_i, T_i, c_type in ptry_values])

print '\nSum of SA fractions:', total_sa_fraction

total_ra_fraction = sum([f.fraction for f in oil_obj.sara_fractions

if f.sara_type in ('Resins', 'Asphaltenes')])

print 'Sum of RA fractions:', total_ra_fraction

print 'Sum of SARA fractions:', total_sa_fraction + total_ra_fraction

# our estimated RA fractions deviate a bit from the imported RA fractions

print 'oil resins:', oil_obj.imported.resins

print 'oil aspaltenes:', oil_obj.imported.asphaltene_content

print '\nAdjusted avg density:', ptry_avg_density

oil_density = density_at_temperature(oil_obj, 288.15)

print 'Oil density at 288K:', oil_density

print ('percent deviation: {0}'

.format((oil_density - ptry_avg_density) / oil_density * 100))

print '\n\nNow we will try to adjust our ptry densities to match the oil total density'

oil_sa_avg_density = ((oil_density - total_ra_fraction * 1100.0) /

total_sa_fraction)

print 'SA avg density approximated from Oil & SARA fractions:', oil_sa_avg_density

density_adjustment = oil_sa_avg_density / ptry_avg_density

print 'adjusting ptry densities by a factor of', density_adjustment

ptry_values = [(P_try * density_adjustment, F_i, T_i)

for P_try, F_i, T_i, c_type in ptry_values]

print 'Density adjusted ptry_values:'

pp.pprint(ptry_values)

ptry_avg_density = sum([(P_try * F_i) for P_try, F_i, T_i in ptry_values] +

[(1100.0 * f.fraction)

for f in oil_obj.sara_fractions

if f.sara_type in ('Resins', 'Asphaltenes')])

print '\nDensity adjusted avg density:', ptry_avg_density

print ('percent deviation: {0}'

.format((oil_density - ptry_avg_density) / oil_density * 100))

for o in session.query(Oil):

if o.bullwinkle_fraction > 1.0:

print 'Bullwinkle Fraction:', o.bullwinkle_fraction,

print 'Asphaltene Fraction: ', [af for af in o.sara_fractions

if af.sara_type == 'Asphaltenes'],

print 'API:', o.api

for o in session.query(Oil):

if o.bullwinkle_fraction < 0.0:

print 'Bullwinkle Fraction:', o.bullwinkle_fraction,

print 'Asphaltene Fraction: ', [af for af in o.sara_fractions

if af.sara_type == 'Asphaltenes'],

print 'API:', o.api