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from scipy import optimize
from scipy import stats


def gaussian(x, p):
    n = len(p) // 2
    return np.add.reduce([p[i] * stats.norm.pdf(x, scale=p[n + i]) for i in range(n)])


def fit_gauss_sym(x, y, n=2, origin=True, full=True, positive=True):

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%%This is often best used in a latex file in two-column mode.  To do that, do:
%%
%%\usepackage{multicol}  % before \begin{document}
%% ... document ...
%%\begin{multicols}{2}
%%\bibliography{filename}{}
%%\bibliographystyle{apj_short_prop}
%%\end{multicols}

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def interp_orbit(ix, snap_list, npts=51, rtol=1e-5):
    ns = len(snap_list) - 1
    ts = np.array([si.t for si in snap_list.values()])

    t_list = np.empty((ns, npts))
    xv_list = np.empty((len(ix), ns, npts, 6))

    for i, si in enumerate(snap_list.values()):
        print(i, end=',', flush=True)

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#!/usr/bin/env python
import sys
import json

for file in sys.argv[1:]:
    print('# file: %s' % file)
    print('# vi: filetype=python')
    print('')
    code = json.load(open(file))

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class CubicSplineExtrap(CubicSpline):
    def __init__(self, x, y, bc_type='not-a-knot', extrapolate='linear'):
        """
        Linearly extrapolate outside the range

        extrapolate: False, float, 'const', 'linear', 'cubic', or a 2-tuple of them

        Example
        -------
        from scipy.interpolate import PchipInterpolator, CubicSpline

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import numpy as np
import proplot as pplt
from matplotlib import pyplot as plt
import cartopy.geodesic


def add_ticks(ax, labelpad=None):
    """
    Only works for major ticks on the left and bottom.

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# create env and install dependency
conda create -n agama python=3.8 numpy gsl glpk eigen cvxopt
conda activate agama

# download files
cd $HOME/src
wget https://github.com/GalacticDynamics-Oxford/Agama/archive/master.zip -O agama.zip
wget https://github.com/GalacticDynamics-Oxford/unsio/archive/master.zip -O unsio.zip
wget https://github.com/cvxopt/cvxopt/archive/master.zip -O cvxopt.zip
unzip agama.zip

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"""
Add exponentiated variance (EV) acquisition function to skopt.

Author:
    Zhaozhou Li ([email protected])
"""

import numpy as np
import warnings
import skopt.acquisition

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"""
author: 
    Zhaozhou Li ([email protected])

history:
    This code is taken from my project mw_mass3.
"""

import numpy as np
from scipy.interpolate import CubicSpline

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"""
Python IO for nemo snapshot

Author: syrte ([email protected])

Example:
    file = '../data/N1e6_d0.22_g0.16_0.00_f0.00.snap'
    snap = open_nemo(file, file_meta=False)

    print(snap.History.data, end='\n\n')