# Import the necessary modules:
import sys
import numpy as np
# Import the modules from the MCcubed package:
sys.path.append("../MCcubed/")
import MCcubed as mc3
sys.path.append("../MCcubed/examples/models/")
from quadratic import quad
# Create a synthetic dataset using a quadratic polynomial curve:
x = np.linspace(0, 10, 100) # Independent variable of the model
p0 = 3, -2.4, 0.5 # True-underlying model parameters
y = quad(p0, x) # Noiseless model
uncert = np.sqrt(np.abs(y)) # Data points uncertainty
error = np.random.normal(0, uncert) # Noise for the data
data = y + error # Noisy data set
mu = mc3.utils
mu.savebin([data, uncert], 'data.npz')
# indparams contains additional arguments of func (if necessary). Each
# additional argument is an item in the indparams tuple:
mu.savebin([x], 'indp.npz')
# Set the arguments to the file names:
data = 'data.npz'
indparams = 'indp.npz'
# MCMC algorithm:
# working directory.
# Import the necessary modules:
import sys
import numpy as np
# Import the modules from the MCcubed package:
sys.path.append("../MCcubed/")
import MCcubed as mc3
sys.path.append("../MCcubed/examples/models/")
from quadratic import quad
# Create a synthetic dataset using a quadratic polynomial curve:
x = np.linspace(0, 10, 1000) # Independent variable of the model
p0 = [3, -2.4, 0.5] # True-underlying model parameters
y = quad(p0, x) # Noiseless model
uncert = np.sqrt(np.abs(y)) # Data points uncertainty
error = np.random.normal(0, uncert) # Noise for the data
data = y + error # Noisy data set
# Define the modeling function as a callable:
# The first argument of func() must be the fitting parameters
sys.path.append("../MCcubed/examples/models/")
from quadratic import quad
func = quad
# A three-elements tuple indicates the function name, the module
# name (without the '.py' extension), and the path to the module.
func = ("quad", "quadratic", "../MCcubed/examples/models/")
# Alternatively, if the module is already within the scope of the
import sys
import numpy as np
import matplotlib.pyplot as plt
sys.path.append("../../src")
import mccubed as mc3
import mcplots as mp
import mcutils as mu
# Get function to model/sample.
sys.path.append("../")
from quadratic import quad
# Create a synthetic dataset:
x = np.linspace(0, 10, 100) # Independent model variable
p0 = 3, -2.4, 0.5 # True-underlying model parameters
y = quad(p0, x) # Noiseless model
uncert = np.sqrt(np.abs(y)) # Data points uncertainty
error = np.random.normal(0, uncert) # Noise for the data
data = y + error # Noisy data set
# Set the MCMC arguments:
# -----------------------
help(mc3.mcmc) # Displays the MCMC function docstring.
# Define the function to model the data in the MCMC: As a requirement, the
# first argument of func must be the set of fitting parameters.
# Define as callable:
func = quad
# Or by function name and module name:
# func = ("quad", "quadratic")
def test_quad1():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(1) == 6
import sys
import numpy as np
import matplotlib.pyplot as plt
sys.path.append("../../src")
import mccubed as mc3
import mcplots as mp
import mcutils as mu
# Get function to model/sample.
sys.path.append("../")
from quadratic import quad
# Create a synthetic dataset:
x = np.linspace(0, 10, 100) # Independent model variable
p0 = 3, -2.4, 0.5 # True-underlying model parameters
y = quad(p0, x) # Noiseless model
uncert = np.sqrt(np.abs(y)) # Data points uncertainty
error = np.random.normal(0, uncert) # Noise for the data
data = y + error # Noisy data set
# Set the MCMC arguments:
# -----------------------
help(mc3.mcmc) # Displays the MCMC function docstring.
# Define the function to model the data in the MCMC: As a requirement, the
# first argument of func must be the set of fitting parameters.
# Define as callable:
func = quad
# Or by function name and module name:
# func = ("quad", "quadratic")
def test_quad3():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(3) == 28
def test_quad0():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(0) == 1
def test_quad2():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(2) == 15
def test_quad1():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(1) == 6
def test_quad0():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(0) == 1
def test_quad3():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(3) == 28
def test_quad2():
my_quad = quad(a=2, b=3, c=1)
assert my_quad(2) == 15
