In [1]:

    

case_name = 'Delta_Wing_Large_Radius'


    

In [2]:

    

remote_data = True

data_dir='/gpfs/cfms/workarea/projects/hyper_flux/delta_wing_high_Re/Delta_Wing_Large_Fine_Mesh'

data_host='acimpoeru@vis03'

remote_server_auto = True

paraview_cmd='mpiexec /gpfs/apps/bin/pvserver'
if not remote_server_auto:
    paraview_cmd=None

if not remote_data:
    data_host='localhost'
    paraview_cmd=None


    

In [3]:

    

%pylab inline
from paraview.simple import *

paraview.simple._DisableFirstRenderCameraReset()
import pylab as pl


    

    




Populating the interactive namespace from numpy and matplotlib
paraview version 4.2.0-75-gff3f889

In [ ]:

    

from zutil.post import pvserver_connect
if remote_data:
    pvserver_connect(data_host=data_host,data_dir=data_dir,paraview_cmd=paraview_cmd)


    

In [5]:

    

from zutil.post import get_case_parameters,print_html_parameters
parameters=get_case_parameters(case_name,data_host=data_host,data_dir=data_dir)


    

In [6]:

    

from zutil.post import get_status_dict
status=get_status_dict(case_name,data_host=data_host,data_dir=data_dir)
num_procs = str(status['num processor'])


    

In [7]:

    

alpha = 13.3 # degrees
reference_area = 594720.0 # inches^2
reference_length = 275.8 # inches, mean chord. 
reference_span = 1156.75 # inches

from IPython.display import HTML
HTML(print_html_parameters(parameters))


    

    
Out[7]:





pressure
407552.8904
temperature
322.0389
Reynolds No
6000000.0
Ref length
0.66666666
Speed
0.0
Mach No
0.4

In [8]:

    

import zutil
import zutil.post as post
reload(zutil)
reload(post)
from zutil.post import cp_profile_wall_from_file
from zutil.post import cp_profile_wall_from_file_span
def plot_cp_profile(ax,file_root,loc):
    force_data = cp_profile_wall_from_file_span(file_root,
                              [1.0,0.0,0.0],
                              [loc, 0.0 , 0.0],
                              func=plot_array,
                              axis=ax,
                              loc=loc,
                              alpha=alpha)
loop = 0
loop_data = {}
def plot_array(data_array,pts_array,**kwargs):
    global loop, loop_data
    ax = kwargs['axis']
    loc = kwargs['loc']
    #alpha = kwargs['alpha']
    cp_array = data_array.GetPointData()['cp']
    chord_array = data_array.GetPointData()['chord']
    ax.plot(chord_array, cp_array , 'b.',color='k',label='zCFD SST', markersize=20)
    ax.legend(loc = 'upper left',numpoints=1,prop = prop)
    loop_data[loop] = (chord_array,cp_array)
    loop += 1


    

In [9]:

    

# Reproduce plots from delta wing presentation

from collections import OrderedDict
station_values = OrderedDict([("S01" , 0.2), ("S02" , 0.4), ("S03" , 0.6), ("S04" , 0.8),("S05",0.95)])


    

In [10]:

    

import zutil
import zutil.post as post
from zutil.post import get_csv_data
from collections import OrderedDict



#stat = OrderedDict([("S01" ,(0.2,cp_u_s02[0],cp_u_s02[1],cp_l_s02[0],cp_l_s02[1])),
#                    ("S02" ,(0.4,cp_u_s04[0],cp_u_s04[1],cp_l_s04[0],cp_l_s04[1])),
#                    ("S03" ,(0.6,cp_u_s06[0],cp_u_s06[1],cp_l_s06[0],cp_l_s06[1])),
#                    ("S04" ,(0.8,cp_u_s08[0],cp_u_s08[1],cp_l_s08[0],cp_l_s08[1]))
#                  ])


    

    




[]

In [11]:

    

from zutil.post import get_case_root
from zutil.post import get_chord_spanwise
import matplotlib.font_manager as fm
prop=fm.FontProperties(size=20)

fig = pl.figure(figsize=(30, 50),dpi=150, facecolor='w', edgecolor='k')
fig2 = pl.figure(figsize=(30, 50),dpi=150, facecolor='w', edgecolor='k')

plot = 1
for key in stat:
        loc = stat[key][0]
        ax = fig.add_subplot(len(station_values),2,plot)
        ax.set_title('$C_p$ at x/c = '+str(loc), fontsize=40, fontweight='bold')
        ax.grid(True)
        ax.set_xlabel('y/c - Spanwise',fontsize=20, fontweight='bold')
        ax.set_ylabel('$C_p$',fontsize=50, fontweight='bold')
        ax.axis([0.0,1.01,0.5,-3.0])
        plot_cp_profile(ax,get_case_root(case_name,num_procs),loc)
        ax.plot(stat[key][1],stat[key][2],'b.',color='r',label='Experiment', markersize=20)
        ax.plot(stat[key][3],stat[key][4],'b.',color='r', markersize=20)

        ax.legend(loc = 'upper left',numpoints=1,prop = prop)
        plot += 1    
from matplotlib.backends.backend_pdf import PdfPages
pp = PdfPages('Large_delta.pdf')
pp.savefig()
pp.close()
fig.savefig("Large_delta.png")
show()
from IPython.display import FileLink, display 
display(FileLink('Large_delta.png'))


    

    




use append poly data filter
use append poly data filter
use append poly data filter
use composite data append
use append poly data filter
use append poly data filter
use append poly data filter
use composite data append
use append poly data filter
use append poly data filter
use append poly data filter
use composite data append
use append poly data filter
use append poly data filter
use append poly data filter
use composite data append






    













    






<matplotlib.figure.Figure at 0x116141150>






    





Large_delta.png

In [12]:

    

from zutil.post import residual_plot, get_case_report
residual_plot(get_case_report(case_name))
show()


    

In [13]:

    

#if remote_data:
#    #print 'Disconnecting from remote paraview server connection'
#    Disconnect()