def find_dataType(S):
s=browse.get_string(S.fileCine,'/PIV','.cine')
if not s=='':
return '2D_PIVmovie'
s=browse.get_string(S.fileCine,'Bubbles','.cine')
if not s=='':
return '2D_bubbles'
return 'Unknown'
def get_parameters(file):
List_key = ['zl', 'yl', 'xl', 't0', 'tl', 'y0', 'x0', 'z0']
param = {}
for k in List_key[:-1]:
param[k] = int(
browse.get_string(file, '_' + k + '_', end='_', display=False))
k = List_key[-1]
param[k] = int(
browse.get_string(file, '_' + k + '_', end='/', display=False))
return param
def draw_grid(M,ax,x0,y0,Mesh=50,Bar=10,H=10,N=5,facecolor='y',edgecolor='k',linewidth=2):
"""
Draw the grid at the specified position.
"""
file = M.Sdata.fileCine
ind = browse.get_string(os.path.basename(file),'_M',end='mm')
if M.Id.date=='2016_03_05':
ind = 24
if not ind=='':
Bar = 4
H = 8
Mesh = int(ind)#print(int(ind))
N = 9
else:
Mesh = 50
positions = [(i*Mesh+x0,y0) for i in range(-(N//2),N//2+1)]
width = Bar
height = H
# grid = []
for p in positions:
square = patches.Rectangle(centered(p,width,height),width,height,facecolor=facecolor,edgecolor=edgecolor,linewidth=linewidth)
ax.add_patch(square)
def saveDir(file, post=''):
fileroot = browse.get_string(file, '', '.cine', 0)
if not (fileroot == ''):
Dir = fileroot + post + '/'
root = 'im'
if not os.path.isdir(Dir):
os.makedirs(Dir)
else:
print('not a cine file')
return Dir, root
def make_movie(cinefile,nimage,start=0,stop=1,step=1,folder='',framerate=30,quality=50):
#generate a folder with tiff images : it would be easier if a avi file is generated directly
root = os.path.basename(cinefile)
base = browse.get_string(root,'',end='.cine')
if folder=='':
folder = os.path.dirname(cinefile)
folder = '/References'
print(folder+base)
cine2pic.cine2tiff(cinefile,mode='Sample',step=step,ctime=2,start=start,stop=nimage*step+start,folder=folder,post=base)
def make_timestep_files(fileList, Dt=1, starts=[], ends=[], Dt_list=[]):
"""
Generate a timestep .txt file that will be used to process the data with the right time step
INPUT
-----
fileList : list of filename to process
Dt : int. timestep to be applied. Default value : 1
Rmq : could be switched to a list of timestep and associated start/end indexes for each timestep
Optionnal variables (not implemented yet) : starts, ends and Dt_list to set a list of timestep for different instants in the movie.
OUTPUT
-----
NONE
"""
keys = ['start', 'end', 'Dt']
for file in fileList[args.start:args.end]:
n = str(browse.get_string(file, start='_n', end='_'))
try:
int(n)
except:
n = ''
if n == '':
#get the number of images from the cinefile
c = cine.Cine(file)
n = c.len() - 1
print(n)
values = [[0], [n], [Dt]]
base = browse.get_string(os.path.basename(file), '', '.cine')
file_timestep = os.path.dirname(
file) + '/PIV_timestep_' + base + '.txt'
if not os.path.isfile(file_timestep):
rw_data.write_dictionnary(file_timestep, keys, values)
def get_data(fileList):
dataList = []
for name in fileList:
W = browse.get_number(name, '_W', 'pix_')
Dt = int(browse.get_string(name, 'pix_Dt_', '_'))
Header, Data = rw_data.read_dataFile(name, ',', ',')
# indexA=browse.get_number(Header[1],'A: im','.tiff') #name of the image is localized on the second line of the ASCII file
# indexB=browse.get_number(Header[1],'B: im','.tiff')
Data = pivlab.switch_keys(Data)
dataList.append(Data)
for key in ['u', 'v']:
Data[key] = (cdata.rm_nans([np.asarray(Data[key])], d=1,
rate=0.05))[0]
return dataList
def chose_label(M):
base=os.path.basename(M.dataDir)
# i=browse.get_string(base,'olymer')
print(base)
c=browse.get_string(base,start='_',end='ppm',from_end=True)
print(c)
if len(c)>0:
print(c)
if int(c)==100:
color = 'b'
symbol = ''
if int(c)==200:
color = 'r'
symbol = ''
label = color + symbol
else:
label = ''
return label
def make_result_folder(fileList,
type_analysis='Sample',
algo='PIVlab',
W=32,
ratio=None):
"""
Create folders for storing the PIVlab Data (now processed in matlab)
INPUT
-----
fileList : List of string
filename List to be read
type_analysis : string (default value 'Sample')
Standard presaved types of analysis (Sample = 1/10 images processed, Full_single', every images, Full_double every pair of image (effective ratio = 2))
Full_single : ratio = 1
Full_double : ratio = 2
Sample : ratio = 10
algo : string (default value 'PIVlab')
Name of the PIV algorithm used to processed the data
W : int (default value = 16)
Window size used for PIV processing.
ratio : number of images / number of pair of images processed. default value = 10. Can be set to standard values using type_analysis
OUTPUT
------
None
0 """
types = dict(Sample=ratio, Full_double=2, Full_single=1)
if type_analysis in types.keys():
ratio = types[type_analysis]
else:
#use the value given in argument for ratio
pass
for file in fileList[args.start:args.end]:
Dir = os.path.dirname(file)
rootDir = Dir + '/PIV_data'
basename = browse.get_string(os.path.basename(file), '', end='.cine')
foldername = rootDir + '/' + algo + '_ratio' + str(ratio) + '_W' + str(
W) + 'pix_' + basename
if not os.path.isdir(foldername):
os.makedirs(foldername)
def make_ref_file(cinefile,folder=''):
keys = ['fx','im0','x0','y0','angle']
List_info = [[0] for i in range(len(keys))]
if folder=='':
folder = os.path.dirname(cinefile)
#generate an empty ref file associated to each cine file
#Should be manually filled out from images measurements
cinebase = browse.get_string(os.path.basename(cinefile),'','.cine')
name = folder +'Ref_'+cinebase+'.txt'
if not os.path.isfile(name):
print(name)
#check first if a Ref file exists already
# Ref_PIV_sv_vp_zoom_Polymer_200ppm_X25mm_fps5000_n18000_beta500mu_H1180mm_S300mm
rw_data.write_dictionnary(name,keys,List_info)
else:
print('Reference file exists already')
pass
#directory = '/Volumes/labshared3/Stephane/Experiments/Accelerated_grid/2015_03_24/'
#gen(directory)
def title(M):
date = M.Id.date
typ = browse.get_string(M.dataDir,'piston12mm_',end='_f5Hz')
savedir = './Vortex_Turbulence/Vortex_propagation/'+date+'/'+typ+'/'
print(savedir)
return savedir
def compile(Mlist, V=None, method='circulation'):
symbol = {'50': '^', '125': 'o', '250': 's'}
color = {'circulation': 'r', 'vorticity': 'b', 'joseph': 'k'}
labels = {key: color[method] + symbol[key] for key in symbol.keys()}
if V == None:
sub_labels = labels
piston_v = None
else:
piston_v = str(V)
sub_labels = {piston_v: labels[piston_v]} #,'125':'ro','250':'bs'}
figs = {}
for i, M in enumerate(Mlist):
piston1 = browse.get_string(M.Sdata.fileCine,
'_v',
end='.cine',
shift=0,
display=False,
from_end=True)
piston2 = browse.get_string(M.Sdata.fileCine,
'_v',
end='_p30mum',
shift=0,
display=False,
from_end=True)
error = 0.25
for piston in [piston1, piston2]:
if piston in sub_labels.keys():
print(M.dataDir)
dx = np.mean(np.diff(M.x[0, :]))
print('Spatial scale : ' + str(dx) + ' mm/box')
lc, std_lc, Gamma, std_Gamma = compute(M,
method=method,
display=False,
fignum=(i + 1) * 2)
# print(piston,dx,lc,std_lc)
if std_lc / lc < error:
graphes.errorbar(dx,
lc, [0],
std_lc,
label=labels[piston],
fignum=250)
figs.update(graphes.legende('mm/box', 'Core size (mm)',
''))
graphes.set_axis(0, 1.5, 0, 6.)
if method == 'circulation':
# if np.abs(std_Gamma/Gamma)<error:
graphes.errorbar(dx,
Gamma, [0],
std_Gamma,
label=labels[piston],
fignum=251)
figs.update(
graphes.legende('mm/box', 'Circulation (mm^2/s)',
''))
graphes.set_axis(0, 1.5, -2 * 10**4, 0)
#print(piston,dx,lc,std_lc
print('')
print('figure', figs)
print(figs)
graphes.save_figs(figs,
suffix='Compilation_method_' + method + '_v' + piston_v)