Image analysis¶

example + adding fitting methods

In [1]:

from pyemittance.image import Image
import numpy as np
import matplotlib.pyplot as plt

from pyemittance.image import Image import numpy as np import matplotlib.pyplot as plt

In [2]:

# get example data
image = np.load("./saved_images/1618446887_img.npy", allow_pickle = True)
ncol = np.load("./saved_images/1618446887_ncol.npy", allow_pickle = True)
nrow = np.load("./saved_images/1618446887_nrow.npy", allow_pickle = True)

# get example data image = np.load("./saved_images/1618446887_img.npy", allow_pickle = True) ncol = np.load("./saved_images/1618446887_ncol.npy", allow_pickle = True) nrow = np.load("./saved_images/1618446887_nrow.npy", allow_pickle = True)

In [3]:

# standard way to reshape the image array
im = Image(image, ncol, nrow)
im.reshape_im()
profx, profy = im.get_im_projection()

# standard way to reshape the image array im = Image(image, ncol, nrow) im.reshape_im() profx, profy = im.get_im_projection()

In [4]:

plt.imshow(im.proc_image)

plt.imshow(im.proc_image)

Out[4]:

<matplotlib.image.AxesImage at 0x7f6777f07970>

In [5]:

plt.plot(profx, label="x-profile")
plt.plot(profy, label="y-profile")
plt.legend()

plt.plot(profx, label="x-profile") plt.plot(profy, label="y-profile") plt.legend()

Out[5]:

<matplotlib.legend.Legend at 0x7f676fd6c820>

Example of how this is called in pyemittance¶

In [6]:

# returns: xsize, ysize, xsize_error, ysize_error, x_amplitude, y_amplitude
fit_res = im.get_sizes(method = "gaussian", show_plots = True)
xsize, ysize, xsize_error, ysize_error, x_amplitude, y_amplitude = fit_res

# returns: xsize, ysize, xsize_error, ysize_error, x_amplitude, y_amplitude fit_res = im.get_sizes(method = "gaussian", show_plots = True) xsize, ysize, xsize_error, ysize_error, x_amplitude, y_amplitude = fit_res

Gaussian + linear bg function example¶

In [7]:

from pyemittance.bs_fitting_methods import fit_gaussian_linear_background

from pyemittance.bs_fitting_methods import fit_gaussian_linear_background

In [8]:

fit_gaussian_linear_background(profx)

fit_gaussian_linear_background(profx)

Out[8]:

(array([3217.84266293,  185.43343034,    7.45136335]),
 array([104.61474965,   0.27784605,   0.28365575]))

In [9]:

fit_gaussian_linear_background(profy)

fit_gaussian_linear_background(profy)

Out[9]:

(array([1991.90020444,  146.34583081,   11.56409759]),
 array([44.40883484,  0.29357206,  0.30790032]))

Adding a fitting method:¶

Need to write an asymmetric Gaussian + linear bg function to import as:¶

fit_asym_gaussian_linear_background

and to pass an array like in the cell above and return a fit with the results:¶

size (Gaussian width), error on the size, and the amplitude

In [ ]: