michael-petersen

'''
outcoef.py
(broken out of exptool)

tools to read coefficient files and do rudimentary manipulation.

MSP 30 April 2020

'''

michael-petersen

Principal Components and Data comparison.

michael-petersen

// C++ program to calculate test breakdown of Legendre polynomials

// clang++ -I/opt/local/include/eigen3 -o legendre legendre_test.cpp
#include <iostream>
#include <cmath>

#include <Eigen/Eigen>


#define MINEPS 1.0e-10

michael-petersen

###################################################################
# a 1-d Monte Carlo example
###################################################################

import numpy as np
import matplotlib.pyplot as plt

# first, set up the gaussian we want to approximate
gaussmean = 0.0
gaussdisp = 0.3

michael-petersen

import numpy as np
import matplotlib.pyplot as plt

def read_outlog(filename):
    """definition to read EXP 'OUTLOG'-style files
    One large dictionary is returned, with sub-dictionaries.
    Each component is returned as a sub-dictionary, with positions,
      velocities, and energy conservation.
    An additional sub-dictionary, with global quantities, is also included.

michael-petersen

import numpy as np
import matplotlib.pyplot as plt

def read_orbtrace(filename):
    """definition to read EXP 'ORBTRACE'-style files
    One large dictionary is returned, with sub-dictionaries.
    Each orbit is returned as a sub-dictionary, with positions,
      velocities, and accelerations.
    """

michael-petersen

import numpy as np

from simple_density_functions import *

def makemodel(func,M,funcargs,rvals = 10.**np.linspace(-2.,4.,2000),pfile='',plabel = '',verbose=True):
    """make an EXP-compatible spherical basis function table
    
    inputs
    -------------
    func        : (function) the callable functional form of the density

michael-petersen

import numpy as np

def return_density(logr,weights=1.,rangevals=[-2, 6],bins=500,d2=False):
    """return_density
    
    simple binned density using logarithmically spaced bins
    
    inputs
    ---------
    logr        : (array) log radii of particles to bin

michael-petersen

import numpy as np

def gen_sphere_surface(npoints):
    """generate a sphere of stars, evenly spaced on the surface of a sphere"""
    npoint = 0
    points = np.zeros([npoints,3])
    a = 4*np.pi/npoints
    d = np.sqrt(a)
    Mtheta = np.floor(np.pi/d).astype('int')
    dtheta = np.pi/Mtheta

michael-petersen

#!/bin/sh

# we want to create a grid of simulations, from
# lmax \in [2,4,6,8,12,16,24,32,64]
# nmax \in [2,4,8,16,24,32,48,64,128]

# for an ensemble of 10 simulations, e.g.
# run in run1a run1b run1c run1d run1e run1f run1g run1h run1i run1j

for run in run2a run2b run2c run2d run2e run2f