Hide keyboard shortcuts

Hot-keys on this page

r m x p   toggle line displays

j k   next/prev highlighted chunk

0   (zero) top of page

1   (one) first highlighted chunk

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

# This file is part of meas_extensions_scarlet. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (https://www.lsst.org). 

# See the COPYRIGHT file at the top-level directory of this distribution 

# for details of code ownership. 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the GNU General Public License 

# along with this program. If not, see <https://www.gnu.org/licenses/>. 

 

from scarlet.blend import Blend 

 

__all__ = ["LsstBlend"] 

 

 

class LsstBlend(Blend): 

"""LSST Blend of sources 

 

It is possible that LSST blends might require different 

funtionality than those in scarlet, which is being designed 

for multiresolution blends. So this class exists for any 

LSST specific changes. 

""" 

def get_model(self, seds=None, morphs=None, observation=None): 

model = super().get_model(seds, morphs) 

if observation is not None: 

model = observation.render(model) 

return model 

 

def display_model(self, observation=None, ax=None, filters=None, Q=10, stretch=1, show=True): 

import matplotlib.pyplot as plt 

from astropy.visualization import make_lupton_rgb 

 

model = self.get_model(observation=observation) 

if ax is None: 

fig = plt.figure(figsize=(10, 10)) 

ax = fig.add_subplot(1, 1, 1) 

if filters is None: 

filters = [2, 1, 0] 

imgRgb = make_lupton_rgb(image_r=model[filters[0]], # numpy array for the r channel 

image_g=model[filters[1]], # numpy array for the g channel 

image_b=model[filters[2]], # numpy array for the b channel 

stretch=stretch, Q=Q) # parameters used to stretch and scale the values 

ax.imshow(imgRgb, interpolation='nearest') 

if show: 

plt.show()