# Path: indra/util/plot_formatting.py
# def set_fig_params():
# def format_axis(ax, label_padding=2, tick_padding=0, yticks_position='left'):
# GREEN = "#66C2A5"
# ORANGE = "#FC8D62"
# PURPLE = "#8DA0CB"


import numpy
import matplotlib.pyplot as plt
from indra.util import plot_formatting as pf
from ATM_v1 import model as ATM_v1
from ATM_v2 import model as ATM_v2
from ATM_v3 import model as ATM_v3
from ATM_v4a import model as ATM_v4a
from ATM_v4b import model as ATM_v4b
from ATR_v1 import model as ATR_v1
from ATR_v2 import model as ATR_v2
from ATR_v3 import model as ATR_v3
from run_p53_model import run_model
from pysb.bng import generate_equations
from pysb.simulator import ScipyOdeSimulator as Solver

# Import ATM models

# Import ATR models


def sample_params(mu, sigma):
    r = numpy.random.randn(len(mu))
    p = numpy.power(10, mu + r*sigma)
    return p

def parameter_sweep(model, sigma, ns):
    generate_equations(model)
    logp = [numpy.log10(p.value) for p in model.parameters]
    ts = numpy.linspace(0, 20*3600, 20*60)
    solver = Solver(model, ts)

# Path: indra/util/plot_formatting.py
# def set_fig_params():
# def format_axis(ax, label_padding=2, tick_padding=0, yticks_position='left'):
# GREEN = "#66C2A5"
# ORANGE = "#FC8D62"
# PURPLE = "#8DA0CB"


# Path: models/p53_model/param_analysis.py
import numpy
import matplotlib.pyplot as plt
from indra.util import plot_formatting as pf
from ATM_v1 import model as ATM_v1
from ATM_v2 import model as ATM_v2
from ATM_v3 import model as ATM_v3
from ATM_v4a import model as ATM_v4a
from ATM_v4b import model as ATM_v4b
from ATR_v1 import model as ATR_v1
from ATR_v2 import model as ATR_v2
from ATR_v3 import model as ATR_v3
from run_p53_model import run_model
from pysb.bng import generate_equations
from pysb.simulator import ScipyOdeSimulator as Solver


# Import ATM models

# Import ATR models


def sample_params(mu, sigma):
    r = numpy.random.randn(len(mu))
    p = numpy.power(10, mu + r*sigma)
    return p

def parameter_sweep(model, sigma, ns):
    generate_equations(model)
    logp = [numpy.log10(p.value) for p in model.parameters]
    ts = numpy.linspace(0, 20*3600, 20*60)
    solver = Solver(model, ts)

    pf.set_fig_params()