def plotIsoStaImpedance(ax, loc, array, flag, par='abs',
pSym='s', pColor=None, addLabel='', zorder=1):
appResFact = 1/(8*np.pi**2*10**(-7))
treshold = 1.0 # 1 meter
indUniSta = np.sqrt(np.sum((array[['x','y']].view((float,2))-loc)**2,axis=1)) < treshold
freq = array['freq'][indUniSta]
if par == 'abs':
zPlot = np.abs(array[flag][indUniSta])
elif par == 'real':
zPlot = np.real(array[flag][indUniSta])
elif par == 'imag':
zPlot = np.imag(array[flag][indUniSta])
elif par == 'res':
zPlot = (appResFact/freq)*np.abs(array[flag][indUniSta])**2
elif par == 'phs':
zPlot = np.arctan2(array[flag][indUniSta].imag,array[flag][indUniSta].real)*(180/np.pi)
if not pColor:
if 'xx' in flag:
lab = 'XX'
pColor = 'g'
elif 'xy' in flag:
lab = 'XY'
pColor = 'r'
elif 'yx' in flag:
lab = 'YX'
pColor = 'b'
elif 'yy' in flag:
lab = 'YY'
pColor = 'y'
ax.plot(freq,zPlot,color=pColor,marker=pSym,label=flag+addLabel,zorder=zorder)
def fft2(image, invert=False):
"""
Perform a two-dimensional fft in an iterative way
:param image: np array
:param invert: true if ifft
:return: processed image as np array
"""
shape = image.shape
im = np.full(image.size, complex(0))
for i, each in enumerate(image.reshape(-1)):
im[i] = complex(each)
length = len(im)
lg_n = 0
t = 1 << lg_n
while t < length:
lg_n += 1
t = 1 << lg_n
for i in range(length):
if i < rev(i, lg_n):
ind = rev(i, lg_n)
im[i], im[ind] = im[ind], im[i]
ln = 2
while ln <= length:
angle = 2 * np.pi * (-1 if invert else 1)
wlen = np.complex(np.cos(angle), np.sin(angle))
for i in range(0, length, ln):
w = np.complex(1)
for j in range(ln // 2):
v = np.real(im[i + j + ln // 2] * w)
u = np.complex(np.real(im[i + j]), v)
im[i + j] = np.real(u + v)
im[i + j + ln // 2] = np.real(u - v)
w *= wlen
ln <<= 1
if invert:
for i in range(length):
im[i] /= length
return im.reshape(shape)
def drogEdgeDetectorFilter(self, img, ret_grad=False, pillow=True):
if pillow:
img = img.convert('L')
open_cv_image = np.array(img)
width, height = 0, 0
if not pillow:
height, width = img.shape
else:
width, height = img.size
cv2.GaussianBlur(open_cv_image, (15, 15), 0)
# Create sobel x and y matrix
sobel_x = np.array([[-1, 0, 1],
[-2, 0, 2],
[-1, 0, 1]])
sobel_y = np.array([[-1, -2, -1],
[0, 0, 0],
[1, 2, 1]])
kernel1 = np.zeros(open_cv_image.shape)
kernel1[:sobel_x.shape[0], :sobel_x.shape[1]] = sobel_x
kernel1 = np.fft.fft2(kernel1)
kernel2 = np.zeros(open_cv_image.shape)
kernel2[:sobel_y.shape[0], :sobel_y.shape[1]] = sobel_y
kernel2 = np.fft.fft2(kernel2)
im = np.array(open_cv_image)
fim = np.fft.fft2(im)
Gx = np.real(np.fft.ifft2(kernel1 * fim)).astype(float)
Gy = np.real(np.fft.ifft2(kernel2 * fim)).astype(float)
open_cv_image = abs(Gx/4) + abs(Gy/4)
img = Image.fromarray(open_cv_image)
img = img.convert('L')
if ret_grad:
return Gx, Gy
return img
def plotIsoFreqNStipper(ax,freq,array,flag,par='abs',colorbar=True,colorNorm='SymLog',cLevel=True,contour=True):
indUniFreq = np.where(freq==array['freq'])
x, y = array['x'][indUniFreq],array['y'][indUniFreq]
if par == 'abs':
cmap = plt.get_cmap('OrRd_r')#seismic')
zPlot = np.abs(array[flag][indUniFreq])
if cLevel:
level = np.logspace(-4,0,33)
clevel = np.logspace(-4,0,5)
else:
level = np.linspace(zPlot.min(),zPlot.max(),100)
clevel = np.linspace(zPlot.min(),zPlot.max(),10)
if colorNorm=='SymLog':
plotNorm = colors.LogNorm()
else:
plotNorm = colors.Normalize()
elif par == 'real':
cmap = plt.get_cmap('RdYlBu')
zPlot = np.real(array[flag][indUniFreq])
if cLevel:
level = np.concatenate((-np.logspace(0,-4,33),np.logspace(-4,0,33)))
clevel = np.concatenate((-np.logspace(0,-4,5),np.logspace(-4,0,5)))
else:
level = np.linspace(zPlot.min(),zPlot.max(),100)
clevel = np.linspace(zPlot.min(),zPlot.max(),10)
if colorNorm=='SymLog':
plotNorm = colors.SymLogNorm(1e-4,linscale=2)
else:
plotNorm = colors.Normalize()
elif par == 'imag':
cmap = plt.get_cmap('RdYlBu')
zPlot = np.imag(array[flag][indUniFreq])
if cLevel:
level = np.concatenate((-np.logspace(0,-4,33),np.logspace(-4,0,33)))
clevel = np.concatenate((-np.logspace(0,-4,5),np.logspace(-4,0,5)))
else:
level = np.linspace(zPlot.min(),zPlot.max(),100)
clevel = np.linspace(zPlot.min(),zPlot.max(),10)
if colorNorm=='SymLog':
plotNorm = colors.SymLogNorm(1e-4,linscale=2)
else:
plotNorm = colors.Normalize()
if contour:
cs = ax.tricontourf(x,y,zPlot,levels=level,cmap=cmap,norm=plotNorm)#,extend='both')
else:
uniX,uniY = np.unique(x),np.unique(y)
X,Y = np.meshgrid(np.append(uniX-25,uniX[-1]+25),np.append(uniY-25,uniY[-1]+25))
cs = ax.pcolor(X,Y,np.reshape(zPlot,(len(uniY),len(uniX))),levels=level,cmap=cmap,norm=plotNorm,edgecolors='k', linewidths=0.5)
if colorbar:
plt.colorbar(cs,cax=ax.cax,ticks=clevel,format='%1.2e')
ax.set_title(flag+' '+par,fontsize=8)
def plotIsoStaImpedance(ax,
loc,
array,
flag,
par="abs",
pSym="s",
pColor=None,
addLabel="",
zorder=1):
appResFact = 1 / (8 * np.pi**2 * 10**(-7))
treshold = 1.0 # 1 meter
indUniSta = (np.sqrt(
np.sum((array[["x", "y"]].copy().view(
(float, 2)) - loc)**2, axis=1)) < treshold)
freq = array["freq"][indUniSta]
if par == "abs":
zPlot = np.abs(array[flag][indUniSta])
elif par == "real":
zPlot = np.real(array[flag][indUniSta])
elif par == "imag":
zPlot = np.imag(array[flag][indUniSta])
elif par == "res":
zPlot = (appResFact / freq) * np.abs(array[flag][indUniSta])**2
elif par == "phs":
zPlot = np.arctan2(array[flag][indUniSta].imag,
array[flag][indUniSta].real) * (180 / np.pi)
if not pColor:
if "xx" in flag:
lab = "XX"
pColor = "g"
elif "xy" in flag:
lab = "XY"
pColor = "r"
elif "yx" in flag:
lab = "YX"
pColor = "b"
elif "yy" in flag:
lab = "YY"
pColor = "y"
ax.plot(freq,
zPlot,
color=pColor,
marker=pSym,
label=flag + addLabel,
zorder=zorder)
def plotIsoStaImpedance(ax,
loc,
array,
flag,
par='abs',
pSym='s',
pColor=None,
addLabel='',
zorder=1):
appResFact = 1 / (8 * np.pi**2 * 10**(-7))
treshold = 1.0 # 1 meter
indUniSta = np.sqrt(
np.sum((array[['x', 'y']].view(
(float, 2)) - loc)**2, axis=1)) < treshold
freq = array['freq'][indUniSta]
if par == 'abs':
zPlot = np.abs(array[flag][indUniSta])
elif par == 'real':
zPlot = np.real(array[flag][indUniSta])
elif par == 'imag':
zPlot = np.imag(array[flag][indUniSta])
elif par == 'res':
zPlot = (appResFact / freq) * np.abs(array[flag][indUniSta])**2
elif par == 'phs':
zPlot = np.arctan2(array[flag][indUniSta].imag,
array[flag][indUniSta].real) * (180 / np.pi)
if not pColor:
if 'xx' in flag:
lab = 'XX'
pColor = 'g'
elif 'xy' in flag:
lab = 'XY'
pColor = 'r'
elif 'yx' in flag:
lab = 'YX'
pColor = 'b'
elif 'yy' in flag:
lab = 'YY'
pColor = 'y'
ax.plot(freq,
zPlot,
color=pColor,
marker=pSym,
label=flag + addLabel,
zorder=zorder)
def plotIsoFreqNSDiff(
ax,
freq,
arrayList,
flag,
par="abs",
colorbar=True,
cLevel=True,
mask=None,
contourLine=True,
useLog=False,
):
indUniFreq0 = np.where(freq == arrayList[0]["freq"])
indUniFreq1 = np.where(freq == arrayList[1]["freq"])
seicmap = plt.get_cmap("RdYlBu") # seismic')
x, y = arrayList[0]["x"][indUniFreq0], arrayList[0]["y"][indUniFreq0]
if par == "abs":
if useLog:
zPlot = (np.log10(np.abs(arrayList[0][flag][indUniFreq0])) -
np.log10(np.abs(arrayList[1][flag][indUniFreq1]))
) / np.log10(np.abs(arrayList[1][flag][indUniFreq1]))
else:
zPlot = (np.abs(arrayList[0][flag][indUniFreq0]) -
np.abs(arrayList[1][flag][indUniFreq1])) / np.abs(
arrayList[1][flag][indUniFreq1])
if mask:
maskInd = np.logical_or(
np.abs(arrayList[0][flag][indUniFreq0]) < 1e-3,
np.abs(arrayList[1][flag][indUniFreq1]) < 1e-3,
)
zPlot = np.ma.array(zPlot)
zPlot[maskInd] = mask
if cLevel:
level = np.arange(-200, 201, 10)
clevel = np.arange(-200, 201, 25)
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
elif par == "real":
if useLog:
zPlot = (
np.log10(np.real(arrayList[0][flag][indUniFreq0])) -
np.log10(np.real(arrayList[1][flag][indUniFreq1]))) / np.log10(
np.abs((np.real(arrayList[1][flag][indUniFreq1]))))
else:
zPlot = (np.real(arrayList[0][flag][indUniFreq0]) -
np.real(arrayList[1][flag][indUniFreq1])) / np.abs(
(np.real(arrayList[1][flag][indUniFreq1])))
if mask:
maskInd = np.logical_or(
np.abs(np.real(arrayList[0][flag][indUniFreq0])) < 1e-3,
np.abs(np.real(arrayList[1][flag][indUniFreq1])) < 1e-3,
)
zPlot = np.ma.array(zPlot)
zPlot[maskInd] = mask
if cLevel:
level = np.arange(-200, 201, 10)
clevel = np.arange(-200, 201, 25)
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
elif par == "imag":
if useLog:
zPlot = (
np.log10(np.imag(arrayList[0][flag][indUniFreq0])) -
np.log10(np.imag(arrayList[1][flag][indUniFreq1]))) / np.log10(
np.abs((np.imag(arrayList[1][flag][indUniFreq1]))))
else:
zPlot = (np.imag(arrayList[0][flag][indUniFreq0]) -
np.imag(arrayList[1][flag][indUniFreq1])) / np.abs(
(np.imag(arrayList[1][flag][indUniFreq1])))
if mask:
maskInd = np.logical_or(
np.abs(np.imag(arrayList[0][flag][indUniFreq0])) < 1e-3,
np.abs(np.imag(arrayList[1][flag][indUniFreq1])) < 1e-3,
)
zPlot = np.ma.array(zPlot)
zPlot[maskInd] = mask
if cLevel:
level = np.arange(-200, 201, 10)
clevel = np.arange(-200, 201, 25)
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
cs = ax.tricontourf(
x, y, zPlot * 100, levels=level * 100, cmap=seicmap,
extend="both") # ,norm=colors.SymLogNorm(1e-2,linscale=2))
if contourLine:
csl = ax.tricontour(x, y, zPlot * 100, levels=clevel * 100, colors="k")
plt.clabel(csl, fontsize=7, inline=1, fmt="%1.1e", inline_spacing=10)
if colorbar:
cb = plt.colorbar(cs, cax=ax.cax, ticks=clevel * 100, format="%1.1e")
for t in cb.ax.get_yticklabels():
t.set_rotation(60)
t.set_fontsize(8)
ax.set_title(flag + " " + par, fontsize=8)
def plotIsoFreqNSimpedance(
ax,
freq,
array,
flag,
par="abs",
colorbar=True,
colorNorm="SymLog",
cLevel=True,
contour=True,
):
indUniFreq = np.where(freq == array["freq"])
x, y = array["x"][indUniFreq], array["y"][indUniFreq]
if par == "abs":
zPlot = np.abs(array[flag][indUniFreq])
cmap = plt.get_cmap("OrRd_r") # seismic')
level = np.logspace(0, -5, 31)
clevel = np.logspace(0, -4, 5)
plotNorm = colors.LogNorm()
elif par == "real":
zPlot = np.real(array[flag][indUniFreq])
cmap = plt.get_cmap("RdYlBu")
if cLevel:
level = np.concatenate(
(-np.logspace(0, -10, 31), np.logspace(-10, 0, 31)))
clevel = np.concatenate(
(-np.logspace(0, -8, 5), np.logspace(-8, 0, 5)))
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
if colorNorm == "SymLog":
plotNorm = colors.SymLogNorm(1e-10, linscale=2)
else:
plotNorm = colors.Normalize()
elif par == "imag":
zPlot = np.imag(array[flag][indUniFreq])
cmap = plt.get_cmap("RdYlBu")
level = np.concatenate(
(-np.logspace(0, -10, 31), np.logspace(-10, 0, 31)))
clevel = np.concatenate((-np.logspace(0, -8, 5), np.logspace(-8, 0,
5)))
plotNorm = colors.SymLogNorm(1e-10, linscale=2)
if cLevel:
level = np.concatenate(
(-np.logspace(0, -10, 31), np.logspace(-10, 0, 31)))
clevel = np.concatenate(
(-np.logspace(0, -8, 5), np.logspace(-8, 0, 5)))
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
if colorNorm == "SymLog":
plotNorm = colors.SymLogNorm(1e-10, linscale=2)
elif colorNorm == "Lin":
plotNorm = colors.Normalize()
if contour:
cs = ax.tricontourf(x,
y,
zPlot,
levels=level,
cmap=cmap,
norm=plotNorm) # ,extend='both')
else:
uniX, uniY = np.unique(x), np.unique(y)
X, Y = np.meshgrid(np.append(uniX - 25, uniX[-1] + 25),
np.append(uniY - 25, uniY[-1] + 25))
cs = ax.pcolor(X,
Y,
np.reshape(zPlot, (len(uniY), len(uniX))),
cmap=cmap,
norm=plotNorm)
if colorbar:
plt.colorbar(cs, cax=ax.cax, ticks=clevel, format="%1.2e")
ax.set_title(flag + " " + par, fontsize=8)
return cs
def plotPsudoSectNSimpedance(
ax,
sectDict,
array,
flag,
par="abs",
colorbar=True,
colorNorm="None",
cLevel=None,
contour=True,
):
indSect = np.where(sectDict.values()[0] == array[sectDict.keys()[0]])
# Define the plot axes
if "x" in sectDict.keys()[0]:
x = array["y"][indSect]
else:
x = array["x"][indSect]
y = array["freq"][indSect]
if par == "abs":
zPlot = np.abs(array[flag][indSect])
cmap = plt.get_cmap("OrRd_r") # seismic')
if cLevel:
level = np.logspace(0, -5, 31, endpoint=True)
clevel = np.logspace(0, -4, 5, endpoint=True)
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100, endpoint=True)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10, endpoint=True)
elif par == "ares":
zPlot = np.abs(array[flag][indSect])**2 / (8 * np.pi**2 * 10**(-7) *
array["freq"][indSect])
cmap = plt.get_cmap("RdYlBu") # seismic)
if cLevel:
zMax = np.log10(cLevel[1])
zMin = np.log10(cLevel[0])
else:
zMax = np.ceil(np.log10(np.abs(zPlot).max()))
zMin = np.floor(np.log10(np.abs(zPlot).min()))
level = np.logspace(zMin, zMax, (zMax - zMin) * 8 + 1, endpoint=True)
clevel = np.logspace(zMin, zMax, (zMax - zMin) * 2 + 1, endpoint=True)
plotNorm = colors.LogNorm()
elif par == "aphs":
zPlot = np.arctan2(array[flag][indSect].imag,
array[flag][indSect].real) * (180 / np.pi)
cmap = plt.get_cmap("RdYlBu") # seismic)
if cLevel:
zMax = cLevel[1]
zMin = cLevel[0]
else:
zMax = np.ceil(zPlot).max()
zMin = np.floor(zPlot).min()
level = np.arange(zMin, zMax + 0.1, 1)
clevel = np.arange(zMin, zMax + 0.1, 10)
plotNorm = colors.Normalize()
elif par == "real":
zPlot = np.real(array[flag][indSect])
cmap = plt.get_cmap("Spectral") # ('RdYlBu')
if cLevel:
zMax = np.log10(cLevel[1])
zMin = np.log10(cLevel[0])
else:
zMax = np.ceil(np.log10(np.abs(zPlot).max()))
zMin = np.floor(np.log10(np.abs(zPlot).min()))
level = np.concatenate((
-np.logspace(
zMax, zMin - 0.125, (zMax - zMin) * 8 + 1, endpoint=True),
np.logspace(zMin - 0.125,
zMax, (zMax - zMin) * 8 + 1,
endpoint=True),
))
clevel = np.concatenate((
-np.logspace(zMax, zMin, (zMax - zMin) * 1 + 1, endpoint=True),
np.logspace(zMin, zMax, (zMax - zMin) * 1 + 1, endpoint=True),
))
plotNorm = colors.SymLogNorm(np.abs(level).min(), linscale=0.1)
elif par == "imag":
zPlot = np.imag(array[flag][indSect])
cmap = plt.get_cmap("Spectral") # ('RdYlBu')
if cLevel:
zMax = np.log10(cLevel[1])
zMin = np.log10(cLevel[0])
else:
zMax = np.ceil(np.log10(np.abs(zPlot).max()))
zMin = np.floor(np.log10(np.abs(zPlot).min()))
level = np.concatenate((
-np.logspace(
zMax, zMin - 0.125, (zMax - zMin) * 8 + 1, endpoint=True),
np.logspace(zMin - 0.125,
zMax, (zMax - zMin) * 8 + 1,
endpoint=True),
))
clevel = np.concatenate((
-np.logspace(zMax, zMin, (zMax - zMin) * 1 + 1, endpoint=True),
np.logspace(zMin, zMax, (zMax - zMin) * 1 + 1, endpoint=True),
))
plotNorm = colors.SymLogNorm(np.abs(level).min(), linscale=0.1)
if colorNorm == "SymLog":
plotNorm = colors.SymLogNorm(np.abs(level).min(), linscale=0.1)
elif colorNorm == "Lin":
plotNorm = colors.Normalize()
elif colorNorm == "Log":
plotNorm = colors.LogNorm()
if contour:
cs = ax.tricontourf(x,
y,
zPlot,
levels=level,
cmap=cmap,
norm=plotNorm) # ,extend='both')
else:
uniX, uniY = np.unique(x), np.unique(y)
X, Y = np.meshgrid(np.append(uniX - 25, uniX[-1] + 25),
np.append(uniY - 25, uniY[-1] + 25))
cs = ax.pcolor(X,
Y,
np.reshape(zPlot, (len(uniY), len(uniX))),
cmap=cmap,
norm=plotNorm)
if colorbar:
csB = plt.colorbar(cs, cax=ax.cax, ticks=clevel, format="%1.2e")
# csB.on_mappable_changed(cs)
ax.set_title(flag + " " + par, fontsize=8)
return cs, csB
return cs, None
def plotIsoFreqNStipper(ax,
freq,
array,
flag,
par='abs',
colorbar=True,
colorNorm='SymLog',
cLevel=True,
contour=True):
indUniFreq = np.where(freq == array['freq'])
x, y = array['x'][indUniFreq], array['y'][indUniFreq]
if par == 'abs':
cmap = plt.get_cmap('OrRd_r') #seismic')
zPlot = np.abs(array[flag][indUniFreq])
if cLevel:
level = np.logspace(-4, 0, 33)
clevel = np.logspace(-4, 0, 5)
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
if colorNorm == 'SymLog':
plotNorm = colors.LogNorm()
else:
plotNorm = colors.Normalize()
elif par == 'real':
cmap = plt.get_cmap('RdYlBu')
zPlot = np.real(array[flag][indUniFreq])
if cLevel:
level = np.concatenate(
(-np.logspace(0, -4, 33), np.logspace(-4, 0, 33)))
clevel = np.concatenate(
(-np.logspace(0, -4, 5), np.logspace(-4, 0, 5)))
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
if colorNorm == 'SymLog':
plotNorm = colors.SymLogNorm(1e-4, linscale=2)
else:
plotNorm = colors.Normalize()
elif par == 'imag':
cmap = plt.get_cmap('RdYlBu')
zPlot = np.imag(array[flag][indUniFreq])
if cLevel:
level = np.concatenate(
(-np.logspace(0, -4, 33), np.logspace(-4, 0, 33)))
clevel = np.concatenate(
(-np.logspace(0, -4, 5), np.logspace(-4, 0, 5)))
else:
level = np.linspace(zPlot.min(), zPlot.max(), 100)
clevel = np.linspace(zPlot.min(), zPlot.max(), 10)
if colorNorm == 'SymLog':
plotNorm = colors.SymLogNorm(1e-4, linscale=2)
else:
plotNorm = colors.Normalize()
if contour:
cs = ax.tricontourf(x,
y,
zPlot,
levels=level,
cmap=cmap,
norm=plotNorm) #,extend='both')
else:
uniX, uniY = np.unique(x), np.unique(y)
X, Y = np.meshgrid(np.append(uniX - 25, uniX[-1] + 25),
np.append(uniY - 25, uniY[-1] + 25))
cs = ax.pcolor(X,
Y,
np.reshape(zPlot, (len(uniY), len(uniX))),
levels=level,
cmap=cmap,
norm=plotNorm,
edgecolors='k',
linewidths=0.5)
if colorbar:
plt.colorbar(cs, cax=ax.cax, ticks=clevel, format='%1.2e')
ax.set_title(flag + ' ' + par, fontsize=8)
def plotIsoFreqNSDiff(ax,freq,arrayList,flag,par='abs',colorbar=True,cLevel=True,mask=None,contourLine=True,useLog=False):
indUniFreq0 = np.where(freq==arrayList[0]['freq'])
indUniFreq1 = np.where(freq==arrayList[1]['freq'])
seicmap = plt.get_cmap('RdYlBu')#seismic')
x, y = arrayList[0]['x'][indUniFreq0],arrayList[0]['y'][indUniFreq0]
if par == 'abs':
if useLog:
zPlot = (np.log10(np.abs(arrayList[0][flag][indUniFreq0])) - np.log10(np.abs(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs(arrayList[1][flag][indUniFreq1]))
else:
zPlot = (np.abs(arrayList[0][flag][indUniFreq0]) - np.abs(arrayList[1][flag][indUniFreq1]))/np.abs(arrayList[1][flag][indUniFreq1])
if mask:
maskInd = np.logical_or(np.abs(arrayList[0][flag][indUniFreq0])< 1e-3,np.abs(arrayList[1][flag][indUniFreq1]) < 1e-3)
zPlot = np.ma.array(zPlot)
zPlot[maskInd] = mask
if cLevel:
level = np.arange(-200,201,10)
clevel = np.arange(-200,201,25)
else:
level = np.linspace(zPlot.min(),zPlot.max(),100)
clevel = np.linspace(zPlot.min(),zPlot.max(),10)
elif par == 'real':
if useLog:
zPlot = (np.log10(np.real(arrayList[0][flag][indUniFreq0])) -np.log10(np.real(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs((np.real(arrayList[1][flag][indUniFreq1]))))
else:
zPlot = (np.real(arrayList[0][flag][indUniFreq0]) -np.real(arrayList[1][flag][indUniFreq1]))/np.abs((np.real(arrayList[1][flag][indUniFreq1])))
if mask:
maskInd = np.logical_or(np.abs(np.real(arrayList[0][flag][indUniFreq0])) < 1e-3,np.abs(np.real(arrayList[1][flag][indUniFreq1])) < 1e-3)
zPlot = np.ma.array(zPlot)
zPlot[maskInd] = mask
if cLevel:
level = np.arange(-200,201,10)
clevel = np.arange(-200,201,25)
else:
level = np.linspace(zPlot.min(),zPlot.max(),100)
clevel = np.linspace(zPlot.min(),zPlot.max(),10)
elif par == 'imag':
if useLog:
zPlot = (np.log10(np.imag(arrayList[0][flag][indUniFreq0])) -np.log10(np.imag(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs((np.imag(arrayList[1][flag][indUniFreq1]))))
else:
zPlot = (np.imag(arrayList[0][flag][indUniFreq0]) -np.imag(arrayList[1][flag][indUniFreq1]))/np.abs((np.imag(arrayList[1][flag][indUniFreq1])))
if mask:
maskInd = np.logical_or(np.abs(np.imag(arrayList[0][flag][indUniFreq0])) < 1e-3,np.abs(np.imag(arrayList[1][flag][indUniFreq1])) < 1e-3)
zPlot = np.ma.array(zPlot)
zPlot[maskInd] = mask
if cLevel:
level = np.arange(-200,201,10)
clevel = np.arange(-200,201,25)
else:
level = np.linspace(zPlot.min(),zPlot.max(),100)
clevel = np.linspace(zPlot.min(),zPlot.max(),10)
cs = ax.tricontourf(x,y,zPlot*100,levels=level*100,cmap=seicmap,extend='both') #,norm=colors.SymLogNorm(1e-2,linscale=2))
if contourLine:
csl = ax.tricontour(x,y,zPlot*100,levels=clevel*100,colors='k')
plt.clabel(csl, fontsize=7, inline=1,fmt='%1.1e',inline_spacing=10)
if colorbar:
cb = plt.colorbar(cs,cax=ax.cax,ticks=clevel*100,format='%1.1e')
for t in cb.ax.get_yticklabels():
t.set_rotation(60)
t.set_fontsize(8)
ax.set_title(flag+' '+par,fontsize=8)
def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colorNorm='None',cLevel=None,contour=True):
indSect = np.where(sectDict.values()[0]==array[sectDict.keys()[0]])
# Define the plot axes
if 'x' in sectDict.keys()[0]:
x = array['y'][indSect]
else:
x = array['x'][indSect]
y = array['freq'][indSect]
if par == 'abs':
zPlot = np.abs(array[flag][indSect])
cmap = plt.get_cmap('OrRd_r')#seismic')
if cLevel:
level = np.logspace(0,-5,31,endpoint=True)
clevel = np.logspace(0,-4,5,endpoint=True)
else:
level = np.linspace(zPlot.min(),zPlot.max(),100,endpoint=True)
clevel = np.linspace(zPlot.min(),zPlot.max(),10,endpoint=True)
elif par == 'ares':
zPlot = np.abs(array[flag][indSect])**2/(8*np.pi**2*10**(-7)*array['freq'][indSect])
cmap = plt.get_cmap('RdYlBu')#seismic)
if cLevel:
zMax = np.log10(cLevel[1])
zMin = np.log10(cLevel[0])
else:
zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
zMin = (np.floor(np.log10(np.abs(zPlot).min())))
level = np.logspace(zMin,zMax,(zMax-zMin)*8+1,endpoint=True)
clevel = np.logspace(zMin,zMax,(zMax-zMin)*2+1,endpoint=True)
plotNorm = colors.LogNorm()
elif par == 'aphs':
zPlot = np.arctan2(array[flag][indSect].imag,array[flag][indSect].real)*(180/np.pi)
cmap = plt.get_cmap('RdYlBu')#seismic)
if cLevel:
zMax = cLevel[1]
zMin = cLevel[0]
else:
zMax = (np.ceil(zPlot).max())
zMin = (np.floor(zPlot).min())
level = np.arange(zMin,zMax+.1,1)
clevel = np.arange(zMin,zMax+.1,10)
plotNorm = colors.Normalize()
elif par == 'real':
zPlot = np.real(array[flag][indSect])
cmap = plt.get_cmap('Spectral') #('RdYlBu')
if cLevel:
zMax = np.log10(cLevel[1])
zMin = np.log10(cLevel[0])
else:
zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
zMin = (np.floor(np.log10(np.abs(zPlot).min())))
level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
elif par == 'imag':
zPlot = np.imag(array[flag][indSect])
cmap = plt.get_cmap('Spectral') #('RdYlBu')
if cLevel:
zMax = np.log10(cLevel[1])
zMin = np.log10(cLevel[0])
else:
zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
zMin = (np.floor(np.log10(np.abs(zPlot).min())))
level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
if colorNorm=='SymLog':
plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
elif colorNorm=='Lin':
plotNorm = colors.Normalize()
elif colorNorm=='Log':
plotNorm = colors.LogNorm()
if contour:
cs = ax.tricontourf(x,y,zPlot,levels=level,cmap=cmap,norm=plotNorm)#,extend='both')
else:
uniX,uniY = np.unique(x),np.unique(y)
X,Y = np.meshgrid(np.append(uniX-25,uniX[-1]+25),np.append(uniY-25,uniY[-1]+25))
cs = ax.pcolor(X,Y,np.reshape(zPlot,(len(uniY),len(uniX))),cmap=cmap,norm=plotNorm)
if colorbar:
csB = plt.colorbar(cs,cax=ax.cax,ticks=clevel,format='%1.2e')
# csB.on_mappable_changed(cs)
ax.set_title(flag+' '+par,fontsize=8)
return cs, csB
return cs,None