def discreteWaveletAnalysis(vx, wDict):
from utilities import dataFromDict
try:
import pywt
except:
sys.exit(' Library pywt not installed. Exiting ...')
# nlevel = 4
order = 'freq' # "normal"
wavelet = dataFromDict('wavelet', wDict, allowNone=False)
nlevel = dataFromDict('nlevel', wDict, allowNone=False)
if (wavelet in pywt.wavelist()):
try:
wp = pywt.WaveletPacket(vx, wavelet, 'sym', maxlevel=nlevel)
except:
print(" Wrong wavelet type given. Reverting to default 'db2'. ")
wavelet = 'db2'
wp = pywt.WaveletPacket(vx, wavelet, 'sym', maxlevel=nlevel)
nodes = wp.get_level(nlevel, order=order)
labels = [n.path for n in nodes]
values = np.array([n.data for n in nodes], 'd')
values = abs(values)
return values, labels
def addImagePlotDict(fig, RDict):
global cmaps
R = dataFromDict('R', RDict, allowNone=False)
ex = dataFromDict('extent', RDict, allowNone=True)
ttl = dataFromDict('title', RDict, allowNone=True)
xlbl = dataFromDict('xlabel', RDict, allowNone=True)
ylbl = dataFromDict('ylabel', RDict, allowNone=True)
gOn = dataFromDict('gridOn', RDict, allowNone=False)
lOn = dataFromDict('limsOn', RDict, allowNone=False)
cm = dataFromDict('cmap', RDict, allowNone=True)
orig = dataFromDict('origin', RDict, allowNone=True)
ax = addFigAxes(fig)
im = ax.imshow(np.real(R), origin=orig, extent=ex, aspect='auto', cmap=cm)
ax.set_title(ttl)
ax.set_xlabel(xlbl)
ax.set_ylabel(ylbl)
ax.grid(gOn)
if (lOn):
cbar = userColormapSettings(fig, im, np.max(R), np.min(R))
else:
cbar = fig.colorbar(im)
return fig
def continuousWaveletAnalysis(vx, wDict):
from utilities import dataFromDict
import pywt
wavelet = dataFromDict('wavelet', wDict, allowNone=False)
nfreqs = dataFromDict('nfreqs', wDict, allowNone=False)
dt = dataFromDict('dt', wDict, allowNone=False)
linearFreq = dataFromDict('linearFreq', wDict, allowNone=True)
if (linearFreq):
scales = 1. / np.arange(1, nfreqs)
else:
scales = np.arange(1, nfreqs)
cfs, freq = pywt.cwt(vx, scales, wavelet, dt)
return cfs, freq
def plotCiXY(fig, pDict):
fn = dataFromDict('filename', pDict, allowNone=False)
Cx = dataFromDict('Cx', pDict, allowNone=True)
Cy = dataFromDict('Cy', pDict, allowNone=True)
linemode = dataFromDict('lm', pDict, allowNone=False)
logOn = dataFromDict('logOn', pDict, allowNone=True)
revAxes = dataFromDict('revAxes', pDict, allowNone=True)
ylims = dataFromDict('ylims', pDict, allowNone=True)
xlims = dataFromDict('xlims', pDict, allowNone=True)
labelStr = labelString(fn)
if (Cx is None): Cx = 1.
if (Cy is None): Cy = 1.
d, v, v_l, v_u = ciDataFromFile(fn)
ax = fig.add_axes([0.15, 0.075, 0.8,
0.81]) #[left, up, width, height], fig.add_subplot(111)
d, xp, yp, v_l, v_u = ciScaleVals(d, v, v_l, v_u, Cx, Cy, revAxes)
if (revAxes):
xlb = 'V(d)'
ylb = 'd'
else:
ylb = 'V(d)'
xlb = 'd'
if (logOn):
if (revAxes):
plotf = ax.semilogx
fillbf = ax.fill_betweenx
else:
plotf = ax.semilogy
fillbf = ax.fill_between
else:
plotf = ax.plot
if (revAxes):
fillbf = ax.fill_betweenx
else:
fillbf = ax.fill_between
lines = plotf( xp, yp, linestyle_stack(lm=linemode), lw=3.5, \
label=labelStr, color=color_stack(lm=linemode))
linef = fillbf(d,
v_u,
v_l,
facecolor='white',
edgecolor='white',
alpha=0.25)
ax.set_ybound(lower=ylims[0], upper=ylims[1])
ax.set_xbound(lower=xlims[0], upper=xlims[1])
ax.set_xlabel(xlb)
ax.set_ylabel(ylb)
return fig
def continuousWaveletAnalysis(vx, wDict):
from utilities import dataFromDict
try:
import pywt
except:
sys.exit(' Library pywt not installed. Exiting ...')
wavelet = dataFromDict('wavelet', wDict, allowNone=False)
nfreqs = dataFromDict('nfreqs', wDict, allowNone=False)
dt = dataFromDict('dt', wDict, allowNone=False)
linearFreq = dataFromDict('linearFreq', wDict, allowNone=True)
if (linearFreq):
scales = 1. / np.arange(1, nfreqs)
else:
scales = np.arange(1, nfreqs)
cfs, freq = pywt.cwt(vx, scales, wavelet, dt)
return cfs, freq
def addContourf(X, Y, Q, CfDict=None):
Xdims = np.array(X.shape)
figDims = 12. * (Xdims[::-1].astype(float) / np.max(Xdims))
#figDims = (11,11)
#figDims = (9,11)
fig = plt.figure(figsize=figDims)
#fig, ax = plt.subplots()
ax = addFigAxes(fig)
# Default values
labelStr = ' Q(X,Y) '
titleStr = ' Title: Q(X,Y) '
cm = None
vx = None
vn = None
levels = None
N = 12
if (CfDict is not None):
titleStr = dataFromDict('title', CfDict, allowNone=False)
labelStr = dataFromDict('label', CfDict, allowNone=False)
cm = dataFromDict('cmap', CfDict, allowNone=True)
N = dataFromDict('N', CfDict, allowNone=True)
vn = dataFromDict('vmin', CfDict, allowNone=True)
vx = dataFromDict('vmax', CfDict, allowNone=True)
levels = dataFromDict('levels', CfDict, allowNone=True)
if (N is None): N = 12
#print(' vmax = {}, vmin = {} '.format(vx,vn))
#levels = [-1e-6, -1e-7, 0, 1e-7, 1e-6]
#CO = plt.contourf(X,Y,Q, levels )
if (levels is not None):
CO = ax.contourf(X, Y, Q, levels, cmap=cm, vmin=vn, vmax=vx)
else:
CO = ax.contourf(X, Y, Q, N, cmap=cm, vmin=vn, vmax=vx)
ax.set_title(titleStr)
cbar = fig.colorbar(CO)
if (vx is not None): cbar.vmax = vx
if (vn is not None): cbar.vmin = vn
cbar.ax.set_ylabel(labelStr,
fontsize=20,
fontstyle='normal',
fontweight='book',
fontname='serif')
return CO
def plotCiDiffXY(fig, pDict):
f1 = dataFromDict('fileref', pDict, allowNone=False)
fn = dataFromDict('filename', pDict, allowNone=False)
Cx = dataFromDict('Cx', pDict, allowNone=True)
Cy = dataFromDict('Cy', pDict, allowNone=True)
linemode = dataFromDict('lm', pDict, allowNone=False)
logOn = dataFromDict('logOn', pDict, allowNone=True)
revAxes = dataFromDict('revAxes', pDict, allowNone=True)
ylims = dataFromDict('ylims', pDict, allowNone=True)
xlims = dataFromDict('xlims', pDict, allowNone=True)
labelStr = labelString(fn)
if (Cx is None): Cx = 1.
if (Cy is None): Cy = 1.
d1, v1, v1_l, v1_u = ciDataFromFile(f1)
d2, v2, v2_l, v2_u = ciDataFromFile(fn)
if (d2[-1] != d1[-1]):
if (d2[-1] > d1[-1]
): # Quick and dirty handling for cases when d2[-1] > d1[-1]
idx = (d2 <= d1[-1]) # Take the terms where values match
d2 = d2[idx]
v2 = v2[idx]
v2_l = v2_l[idx]
v2_u = v2_u[idx] # Shorten
# Compute the ratio to match the resolutions (roughly)
r = np.round((d2[1] - d2[0]) / (d1[1] - d1[0])).astype(int)
# Use the matching indecies only
idm = (np.mod((np.arange(len(d1)) + 1), r) == 0)
d1 = d1[idm]
v1 = v1[idm]
v1_l = v1_l[idm]
v1_u = v1_u[idm]
Lm = min(len(v2), len(v1))
d2 = d2[:Lm]
v2 = v2[:Lm]
v2_l = v2_l[:Lm]
v2_u = v2_u[:Lm]
d1 = d1[:Lm]
v1 = v1[:Lm]
v1_l = v1_l[:Lm]
v1_u = v1_u[:Lm]
d1, x1, y1, v1_l, v1_u = ciScaleVals(d1, v1, v1_l, v1_u, Cx, Cy, revAxes)
d2, x2, y2, v2_l, v2_u = ciScaleVals(d2, v2, v2_l, v2_u, Cx, Cy, revAxes)
xp, yp, dm = ciDiffVals(x1, y1, v1_l, v1_u, x2, y2, v2_l, v2_u, revAxes)
if (revAxes):
xlb = 'D(d)'
ylb = 'd'
else:
ylb = 'D(d)'
xlb = 'd'
ax = addFigAxes(fig)
if (logOn):
if (revAxes):
plotf = ax.semilogx
fillbf = ax.fill_betweenx
else:
plotf = ax.semilogy
fillbf = ax.fill_between
else:
plotf = ax.plot
if (revAxes):
fillbf = ax.fill_betweenx
else:
fillbf = ax.fill_between
lines = plotf( xp, yp, linestyle_stack(lm=linemode), lw=3., \
label=labelStr+r': $\left< | \Delta | \right>$={:.2g}'.format(dm) , color=color_stack(lm=linemode))
#label=r': $\left< | \Delta | \right>$={:.2f}'.format(dm) , color=color_stack(lm=linemode))
#linef = fillbf( d, v_u, v_l, facecolor='gray', alpha=0.25)
ax.set_ybound(lower=ylims[0], upper=ylims[1])
ax.set_xbound(lower=xlims[0], upper=xlims[1])
ax.set_xlabel(xlb)
ax.set_ylabel(ylb)
return fig
def plotXX(fig, pDict):
fileStr = dataFromDict('filename', pDict, allowNone=False)
logOn = dataFromDict('logOn', pDict, allowNone=False)
Cx = dataFromDict('Cx', pDict, allowNone=False)
Cy = dataFromDict('Cy', pDict, allowNone=False)
revAxes = dataFromDict('revAxes', pDict, allowNone=False)
linemode = dataFromDict('lm', pDict, allowNone=False)
linewidth = dataFromDict('lw', pDict, allowNone=False)
ylims = dataFromDict('ylims', pDict, allowNone=True)
xlims = dataFromDict('xlims', pDict, allowNone=True)
try:
x = np.loadtxt(fileStr)
except:
x = np.loadtxt(fileStr, delimiter=',')
ax = addFigAxes(fig)
labelStr = labelString(fileStr)
#lStr = fileStr.rsplit(".", 1)[0] # Remove the ".dat"
#rStr = lStr.rsplit("_")[-1]
#tStr = lStr.split("/", 2)
#if( tStr[0] is "." ):
# lStr = tStr[1]
#else:
# lStr = tStr[0]
#labelStr = lStr+"_"+rStr
# Print each column separately
amax = 0.
Ny = (x.shape[1] - 1)
for i in range(Ny):
if (Ny == 1):
labelXX = labelStr
else:
labelXX = labelStr + '[' + str(i) + ']'
if (revAxes):
yp = Cy * x[:, 0]
xp = Cx * x[:, i + 1]
dp = xp
else:
xp = Cx * x[:, 0]
yp = Cy * x[:, i + 1]
dp = yp
if (logOn):
if (revAxes):
xp = np.abs(xp)
plotf = ax.semilogx
else:
yp = np.abs(yp)
plotf = ax.semilogy
else:
plotf = ax.plot
lines = plotf( xp, yp, \
linestyle_stack(lm=linemode), linewidth=linewidth, \
label=labelXX, color=color_stack(lm=linemode))
lmax = np.abs(np.max(dp)) # Local maximum
if (lmax > amax): amax = lmax
#if( amax <5.e-4 and revAxes):
# if( revAxes ): ax.xaxis.set_major_formatter(FormatStrFormatter('%.2e'))
# else: ax.yaxis.set_major_formatter(FormatStrFormatter('%.2e'))
ax.set_ybound(lower=ylims[0], upper=ylims[1])
ax.set_xbound(lower=xlims[0], upper=xlims[1])
ax.set_xlabel(" X ")
ax.set_ylabel(" Y ")
return fig
def quadrantAnalysis(v1, v2, qDict):
from utilities import dataFromDict
debug = False
# Extract data from dict. Using dict makes future modifications easy.
ijk1 = dataFromDict('ijk1', qDict, allowNone=False)
ijk2 = dataFromDict('ijk2', qDict, False)
nkpoints = dataFromDict('nkpoints', qDict, True)
npx = dataFromDict('npixels', qDict, False)
axisLim = dataFromDict('axisLim', qDict, False)
holewidth = dataFromDict('holewidth', qDict, False)
weighted = dataFromDict('weighted', qDict, True)
# Create arrays for running loops over the selected coordinates.
iList = np.arange(ijk1[0], ijk2[0] + 1)
jList = np.arange(ijk1[1], ijk2[1] + 1)
kList = np.arange(ijk1[2], ijk2[2] + 1)
'''
In quadrant analysis context, using a stride in z-direction is usually not desired.
By default npoints is None.'''
if (nkpoints is None): stride = 1
else: stride = max(((kList[-1] - kList[0]) / nkpoints) + 1, 2)
# Compute the covariance term (for example, u'w')
v = v1 * v2
if (debug):
print('min(v1)={}, max(v1)={}, min(v2)={}, max(v2)={}'\
.format(np.abs(np.min(v1)), np.max(v1), np.abs(np.min(v2)), np.max(v2)))
maxLim = np.abs(axisLim)
minLim = -1. * maxLim
# Determine if some grid points are under the ground level.
k_off = max(groundOffset(v1), groundOffset(v2))
if (k_off > 0 and debug):
print(' {}: ground offset (k_off) = {}'.format(filename, k_off))
x = np.linspace(minLim, maxLim, npx + 1)
y = np.linspace(minLim, maxLim, npx + 1)
dx = (maxLim - minLim) / (npx)
X, Y = np.meshgrid(x, y)
Qi = np.zeros(np.shape(X), float)
nTot = 0
nQ = np.zeros(5, int) # nQ[0] = nQTot
SQ = np.zeros(5, float) # SQ[0] = STot
'''
Q1: u'(+), w'(+), OutwardInteraction
Q2: u'(-), w'(+), Ejection
Q3: u'(-), w'(-), Inward Interaction
Q4: u'(+), w'(-), Sweep
'''
for i in iList:
for j in jList:
for k in kList[::stride]:
vt = v[:, k + k_off, j, i]
vt_mean = np.mean(np.abs(vt))
v1t = v1[:, k + k_off, j, i]
v2t = v2[:, k + k_off, j, i]
for l in range(len(vt)):
SQ[0] += vt[l]
nTot += 1
if (np.abs(vt[l]) > (holewidth * vt_mean)):
n = np.minimum(int((v1t[l] - minLim) / dx), npx)
n = np.maximum(n, 0)
m = np.minimum(int((v2t[l] - minLim) / dx), npx)
m = np.maximum(m, 0)
Qi[m, n] += 1.
nQ[0] += 1
if (v1t[l] > 0. and v2t[l] > 0.):
nQ[1] += 1
SQ[1] += vt[l] # Outward Interaction
elif (v1t[l] < 0. and v2t[l] > 0.):
nQ[2] += 1
SQ[2] += vt[l] # Ejection
elif (v1t[l] < 0. and v2t[l] < 0.):
nQ[3] += 1
SQ[3] += vt[l] # Inward Interaction
else: #( v1t[l] > 0 and v2t[l] < 0. ):
nQ[4] += 1
SQ[4] += vt[l] # Sweep
v = None
v1 = None
v2 = None
Qi /= (np.float(nQ[0]) * dx**2) # Obtain the PDF
if (weighted):
Qi *= np.abs(X * Y)
SQ[0] /= np.float(nTot) # Total contribution
SQ[1:] /= nQ[1:].astype(float) # Average contributions
# Assemble the result dict
rDict = dict()
rDict['nQ'] = nQ
rDict['SQ'] = SQ
#rDict['klims']= np.array([ kList[0], kList[-1] ])
return Qi, X, Y, rDict
