Re: Trying to understand Distributions

Thanks for all the help but still experiencing further problems, maybe 
it is just me but there seems inconsistencies between distributions and 
fit, ppt and pdf calls.

1) Trying to fit exponential, fit does not give scale but pdf seems to 
accept a scale value

2) Also a gamma plot of a second distribution is not showing curve

from astropy.table import Table, join
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pyplot import plot

RawMassEClassEmeasure = 
Table.read('../../GAMA_Data/REMassEClassEmeasure.fits')
#print(RawMassEClassEmeasure.colnames)
# CLEAN DATA
#REMassEClassEmeasure = 
RawMassEClassEmeasure[RawMassEClassEmeasure['CountInCyl']> -500]
RErange = RawMassEClassEmeasure[RawMassEClassEmeasure['CountInCyl']> -500]
RErange1 = RErange[RErange['SurfaceDensity']< 50]

binCount = 100
alphaVal = .3

##### uminusr
fig = plt.figure(figsize=(12, 6), dpi=200)
fig.suptitle('Plot - Histogram Red Galaxies for Elliptical Galaxies')
#fig.legend(loc="upper right")
#import scipy.stats as stats
from scipy import stats
xfield = 'uminusr'
#counts, bins = np.histogram(RErange1[xfield].data,bins=binCount)
#print(counts)

ax1 = fig.add_subplot(4, 1, 1)
ax1.set_ylabel('Galaxy Count')
ax1.set_xlabel(xfield)
#counts, bins = np.histogram(RErange1[xfield].data,bins=binCount)
#ax1.hist(bins[:-1],bins, weights=counts)

ag, bg, cg =stats.gamma.fit(RErange1[xfield].data)
print(ag, bg, cg)
xg0, xg1 = stats.gamma.ppf([0.01, 0.99], ag, loc = bg, scale=cg)
xg = np.linspace(xg0,xg1, int(ag))

an, bn =stats.norm.fit(RErange1[xfield].data)
print(an, bn)
xn0, xn1 = stats.norm.ppf([0.01, 0.99])
xn = np.linspace(xn0,xn1,100)

ax1.plot(xg, stats.gamma.pdf(xg, ag, loc=bg, scale = cg),'r-', lw=2, 
alpha=0.6, label='gamma pdf')
ax1.plot(xn, stats.norm.pdf(xn, an, bn),'y-', lw=2, alpha=0.6, 
label='normal pdf')
ax1.hist(RErange1[xfield].data, bins=binCount, density=True)

xfield = 'CountInCyl'
#counts, bins = np.histogram(RErange1[xfield].data,bins=binCount)
#print(counts)

ax2 = fig.add_subplot(4, 1, 2)
ax2.set_ylabel('Count In Cyl')
ax2.set_xlabel(xfield)
#ae, be, ce = stats.expon.fit(RErange1[xfield].data)
ae, be = stats.expon.fit(RErange1[xfield].data)

xe0, xe1 = stats.expon.ppf([0.01, 0.99])
xe = np.linspace(xe0,xe1,100)
#ax2.plot(xg, stats.expon.pdf(xe, ae, loc=be, scale = ce),'r-', lw=2, 
alpha=0.6, label='gamma pdf')
ax2.hist(RErange1[xfield].data, bins=binCount, density=True)

xfield = 'DistanceTo5nn'
ax3 = fig.add_subplot(4, 1, 3)
ax3.set_ylabel('Distance to 5nn')
ax3.set_xlabel(xfield)

ag, bg, cg =stats.gamma.fit(RErange1[xfield].data)
print(ag, bg, cg)
xg0, xg1 = stats.gamma.ppf([0.01, 0.99], ag, loc = bg, scale=cg)
xg = np.linspace(xg0,xg1, int(ag))

ax3.hist(RErange1[xfield].data, bins=binCount, density=True)
ax3.plot(xg, stats.gamma.pdf(xg, ag, loc=bg, scale = cg),'r-', lw=2, 
alpha=0.6, label='gamma pdf')

plt.show()




> _______________________________________________
> SciPy-User mailing list
> [email protected]
> https://mail.python.org/mailman/listinfo/scipy-user

-- 
========== Art & Ceramics ===========
https://www.instagram.com/ksloan1952/

_______________________________________________
SciPy-User mailing list
[email protected]
https://mail.python.org/mailman/listinfo/scipy-user