In [12]:

    

import sys,os

import numpy as np
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx

#this works apparently only for savefig stuff
mpl.rcParams['figure.figsize']=(6.0,4.0)    #(6.0,4.0)
mpl.rcParams['font.size']=10                #10 
mpl.rcParams['savefig.dpi']=400             #72 
mpl.rcParams['figure.subplot.bottom']=.1    #.125


plt.rc('font', family='serif')
plt.rc('text', usetex=True)

#inline Shit
%matplotlib inline
%config InlineBackend.figure_format='png'
%config InlineBackend.rc = {'figure.facecolor': 'white', 'figure.subplot.bottom': 0.125, 'figure.edgecolor': 'white', 'savefig.dpi': 400, 'figure.figsize': (12.0, 8.0), 'font.size': 10}

#GUi shit
%matplotlib tk

mpl.get_configdir()


    

    
Out[12]:





'/home/zfmgpu/.config/matplotlib'

In [15]:

    

bodies = [10e3,100e3,500e3,1e6,10e6]
colors =['r','b','g','k','y']
for i, b in enumerate(bodies): 
    
    nB = b

    typeSize = 8;
    bytesPerState= (7+6)*typeSize
    mbytesPerTimeStep = nB*bytesPerState + 1*typeSize;
    print(mbytesPerTimeStep)
    mbytesPerTimeStep / (1024*1024)
    
    deltaT = 1/30
    print("deltaT:", deltaT)
    timeEnd = 10;
    nTS = timeEnd/deltaT
    print("nTS:", nTS)
    
#     #Method 3
#     deltaTList = np.linspace(0.001,0.04,300)
#     bytesMethod3Total = (float(timeEnd)/deltaTList * (bytesPerState + 1*typeSize) * nB) / (1024**3)
#     plt.plot(deltaTList,bytesMethod3Total, colors[i]+'-', label="One File per Body (nB: %d k)" % (nB/1000))
    
    
    
    #Method 1/2
    deltaTList = np.linspace(0.001,0.04,300)
    bytesMethod3Total = (float(timeEnd)/deltaTList * mbytesPerTimeStep) / (1024**3)
    plt.plot(deltaTList,bytesMethod3Total, colors[i]+'--', label="Single File (nB: %d k)" % (nB/1000))
   

    
ax = plt.gca()
ax.grid()
ax.minorticks_on()
ax.set_title("Data Consumption for Simulation")
ax.set_xlabel(r'$\Delta$T')
ax.set_ylabel("Gb of Data")
#ax.set_yscale('log')
ax.set_xscale('log')
ax.legend()


    

    




1040008.0
deltaT: 0.03333333333333333
nTS: 300.0
10400008.0
deltaT: 0.03333333333333333
nTS: 300.0
52000008.0
deltaT: 0.03333333333333333
nTS: 300.0
104000008.0
deltaT: 0.03333333333333333
nTS: 300.0
1040000008.0
deltaT: 0.03333333333333333
nTS: 300.0






    
Out[15]:





<matplotlib.legend.Legend at 0x7f0a43b6ebd0>

In [20]:

    

plt.close('all')

bodies = [10e3,100e3,500e3,1e6,2e6]
colors =['r','b','g','k','y']
for i, b in enumerate(bodies): 
    
    nB = b
    typeSize = 8; 
    bytesPerState= (7+6)*typeSize
    mbytesPerTimeStep = nB*bytesPerState + 1*typeSize;
    print(mbytesPerTimeStep)
    mbytesPerTimeStep / (1024*1024)
    
    deltaT = 1/30
    print("deltaT:", deltaT)
    timeEnd = 10;
    nTS = timeEnd/deltaT
    print("nTS:", nTS)
    
#     #Method 3
#     deltaTList = np.linspace(0.001,0.04,300)
#     bytesMethod3Total = (float(timeEnd)/deltaTList * (bytesPerState + 1*typeSize) * nB) / (1024**3)
#     plt.plot(deltaTList,bytesMethod3Total, colors[i]+'--', label="One File per Body (nB: %d k)" % (nB/1000))
    
    
    
    #Method 1/2
    deltaTList = np.linspace(0.001,0.04,300)
    bytesMethod3Total = (float(timeEnd)/deltaTList * mbytesPerTimeStep) / (1024**3)
    plt.plot(deltaTList,bytesMethod3Total, colors[i]+'-', label="Single File (nB: %d k)" % (nB/1000))
   

    
ax = plt.gca()
ax.grid()
ax.minorticks_on()
ax.set_title("Data Consumption for Simulation")
ax.set_xlabel(r'$\Delta$T')
ax.set_ylabel("Gb of Data")
#ax.set_yscale('log')
#ax.set_xscale('log')
ax.legend()
plt.show()


    

    




1040008.0
deltaT: 0.03333333333333333
nTS: 300.0
10400008.0
deltaT: 0.03333333333333333
nTS: 300.0
52000008.0
deltaT: 0.03333333333333333
nTS: 300.0
104000008.0
deltaT: 0.03333333333333333
nTS: 300.0
208000008.0
deltaT: 0.03333333333333333
nTS: 300.0

In [5]:

    




    

    
Out[5]:





0.001

In [5]: