我们从Python开源项目中，提取了以下10个代码示例，用于说明如何使用numpy.disp()。
def skew_3Dcrystal(crystal, theta): #dx_filter = 1 crystal_skewed = np.zeros(( int(np.floor((crystal.shape[0]/np.cos(theta)))) + 50 , crystal.shape[1], crystal.shape[2] ), dtype=np.complex64) theta = 10*np.pi/180 for i in range(0,crystal.shape[0]-6): for j in range(0,crystal.shape[1]-6): for k in range(0, crystal.shape[2]-6): zs = ceil(j / (1 + np.tan(theta)**2) + i*np.tan(theta)/ ( 1 + np.tan(theta)**2) ) ys = i xs = k crystal_skewed[zs,ys,xs] = crystal[i,j,k] #np.disp(crystal[i,j,k]) #if crystal[i,j,k] crystal_filter2D_skewed = 1 return (crystal_skewed, crystal_filter2D_skewed)
def skew_image(): image_skewed = np.zeros((image.shape[0], ceil((image.shape[1]/np.cos(theta)))+ 50 )) for i in range(0,image.shape[0]): for j in range(0,image.shape[1]): xs = ceil(j / (1 + np.tan(theta)**2) + i*np.tan(theta)/ ( 1 + np.tan(theta)**2) ) #np.disp(xs) ys = i image_skewed[ys,xs] = image[i,j] fft_image_skewed = fft.fftshift(fft.fft2(image_skewed)) return image_skewed, fft_image_skewed # image in reciprocal space #fft_image = fft.fftshift(fft.fft2(image)) # Create crystal: skewed and unskewed. 2D and 3D. # create FFTs of these. Filter out one peak. ################################################
def COM_variation(j, nbr_iter): for i in range (j,nbr_iter): xindex = np.argmax(np.sum(one_position[i],axis=0)) yindex = np.argmax(np.sum(one_position[i],axis=1)) reddot=np.zeros((512,512)) # Make a centred line in x and y intersection at COM reddot[:,xindex] = 500000 reddot[yindex,:] = 500000 np.disp( xindex) plt.figure() noes = ['spring', 'autumn'] plt.imshow(np.log10(one_position[i]), cmap=noes[1] , interpolation = 'none') plt.imshow(np.log10(reddot)) #plt.imshow(np.log10(one_position[1]), cmap = 'hot', interpolation = 'none') #plt.colorbar() funkar ej med flera imshows plt.title('Scan_nbr_%d'%(first_scan_nbr+i)) #COM_variation(0,3)
def disp(mesg, device=None, linefeed=True): """ Display a message on a device. Parameters ---------- mesg : str Message to display. device : object Device to write message. If None, defaults to ``sys.stdout`` which is very similar to ``print``. `device` needs to have ``write()`` and ``flush()`` methods. linefeed : bool, optional Option whether to print a line feed or not. Defaults to True. Raises ------ AttributeError If `device` does not have a ``write()`` or ``flush()`` method. Examples -------- Besides ``sys.stdout``, a file-like object can also be used as it has both required methods: >>> from StringIO import StringIO >>> buf = StringIO() >>> np.disp('"Display" in a file', device=buf) >>> buf.getvalue() '"Display" in a file\\n' """ if device is None: device = sys.stdout if linefeed: device.write('%s\n' % mesg) else: device.write('%s' % mesg) device.flush() return
def pad_diffPatterns(Nx,Ny): #Kan dessa tex heta Nx och Ny när det finns glabala parameterar som heter det? padded_diffPatterns = np.zeros((nbr_scans, Ny, Nx)) x = (Nx - diffSet.shape[2]) / 2 y = (Ny - diffSet.shape[1]) / 2 for i in range(0, nbr_scans): padded_diffPatterns[i, y: y + diffSet.shape[1], x: x+ diffSet.shape[2]] = diffSet[i] np.disp(Nx) return padded_diffPatterns #diffSet = pad_diffPatterns(350,350)# 350 # Sizes of centred cut and padded diffraction patterns
def disp(mesg, device=None, linefeed=True): """ Display a message on a device. Parameters ---------- mesg : str Message to display. device : object Device to write message. If None, defaults to ``sys.stdout`` which is very similar to ``print``. `device` needs to have ``write()`` and ``flush()`` methods. linefeed : bool, optional Option whether to print a line feed or not. Defaults to True. Raises ------ AttributeError If `device` does not have a ``write()`` or ``flush()`` method. Examples -------- Besides ``sys.stdout``, a file-like object can also be used as it has both required methods: >>> from StringIO import StringIO >>> buf = StringIO() >>> np.disp('"Display" in a file', device=buf) >>> buf.getvalue() '"Display" in a file\\n' """ if device is None: device = sys.stdout if linefeed: device.write('%s\n' % mesg) else: device.write('%s' % mesg) device.flush() return # See http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html
