In [1]:

    

import numpy as np
import wisps
import pandas as pd
import matplotlib.pyplot as plt
from astropy.io import ascii, fits
import numba
from tqdm import tqdm
%matplotlib inline


    

In [2]:

    

d=fits.open('/users/caganze/total_north_F160W.fits')


    

In [3]:

    

DIST_DATAFRAME=pd.DataFrame.from_records([x.samples for x in wisps.OBSERVED_POINTINGS])


    

In [4]:

    

montedists=np.concatenate(DIST_DATAFRAME.apply(lambda x: np.concatenate(x)).values).astype(np.float64)


    

In [5]:

    

@numba.vectorize
def proper_motion(vt, d):
    """
    mu in arcsec/y
    d in pc
    vt in
    """
    return vt/(4.74*d)


    

In [6]:

    

def get_proper_motions(spt):
    dists=np.concatenate(DIST_DATAFRAME[spt]).astype(float)
    vts=np.random.uniform(10, 100, len(dists))
    return  proper_motion(vts, dists)


    

In [7]:

    

vts=np.random.uniform(10, 100, len(montedists))


    

In [8]:

    

mus= proper_motion(vts, montedists)


    

In [9]:

    

from scipy.stats import kde


    

In [10]:

    

x=vts
y=mus


    

In [11]:

    

idx=np.arange(len(x))


    

In [12]:

    

randomint=np.random.choice(idx, size=100000)


    

In [13]:

    

plt.scatter(x[randomint], np.log10(y[randomint]), s=2, alpha=0.1)
#plt.yscale('log')

plt.xlabel('Vt')
plt.ylabel(r'log $\mu$ (arcsec/yr)')


    

    
Out[13]:





Text(0, 0.5, 'log $\\mu$ (arcsec/yr)')






    

In [14]:

    

h=plt.hist(np.log10(y), bins=32, histtype='step')
plt.xlabel(r'log $\mu$ (arcsec/yr)')


    

    
Out[14]:





Text(0.5, 0, 'log $\\mu$ (arcsec/yr)')






    

In [15]:

    

musspt=[]
for s in tqdm(np.arange(20, 38)):
    musspt.append(get_proper_motions(s))


    

    




100%|██████████| 18/18 [00:00<00:00, 32.69it/s]

In [16]:

    

import matplotlib
from matplotlib import cm

norm = matplotlib.colors.Normalize(vmin=20., vmax=37.0)


    

In [17]:

    

fig, ax=plt.subplots()

for idx,m in enumerate(musspt):
    #print (idx)
    h=plt.hist(np.log10(m), bins=32, histtype='step', color=cm.viridis(norm(idx+20)))
ax.set_xlabel(r'log $\mu$ (arcsec/yr)')


    

    
Out[17]:





Text(0.5, 0, 'log $\\mu$ (arcsec/yr)')






    

In [18]:

    

fig, ax=plt.subplots()

for idx,m in enumerate(musspt):
    x=np.random.uniform(10, 100, len(m))
    ax.scatter(x, np.log10(m), s=2, alpha=0.1, color=cm.viridis(norm(idx+20)))
               
ax.set_ylabel(r'log $\mu$ (arcsec/yr)')
ax.set_xlabel(r'd (pc)')


    

    
Out[18]:





Text(0.5, 0, 'd (pc)')






    

In [19]:

    

destn='/users/caganze/hlsp_candels_hst_wfc3_goodsn-barro19_multi_v1-1_photometry-cat.txt'


    

In [20]:

    

#ascii.read(destn).to_pandas()


    

In [21]:

    

np.random.uniform(1, 100)


    

    
Out[21]:





38.815014672664745

In [ ]: