Commit 29ac5666 authored by Fang Yuedong's avatar Fang Yuedong
Browse files

Baseline

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#!/usr/bin/env python
# encoding: utf-8
"""
Cython
"""
from . import disperse
from . import interp
#from .disperse import *
#from .interp import *
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from __future__ import division
import numpy as np
cimport numpy as np
DTYPE = np.double
ITYPE = np.int64
ctypedef np.double_t DTYPE_t
ctypedef np.uint_t UINT_t
ctypedef np.int_t INT_t
ctypedef np.int64_t LINT_t
ctypedef np.int32_t FINT_t
ctypedef np.float32_t FTYPE_t
import cython
cdef extern from "math.h":
double sqrt(double x)
double exp(double x)
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.embedsignature(True)
def disperse_grism_object(np.ndarray[FTYPE_t, ndim=2] flam,
np.ndarray[LINT_t, ndim=1] idxl,
np.ndarray[DTYPE_t, ndim=1] yfrac,
np.ndarray[DTYPE_t, ndim=1] ysens,
np.ndarray[DTYPE_t, ndim=1] full,
np.ndarray[LINT_t, ndim=1] x0,
np.ndarray[LINT_t, ndim=1] shd,
np.ndarray[LINT_t, ndim=1] shg):
"""Compute a dispersed 2D spectrum
Parameters
----------
flam : direct image matrix, 2 dim [y,x]
idxl: grating disperse light to pixel, pixel index, 1 dim, length = ysens, yfrac
yfrac:
ysense: sensitivity use pixel describe
full: output result ,1 dim, y_beam * x_beam
x0: the center of gal in image thumbnail
shd: shape of direct image
shg: shape of grating image
"""
cdef int i,j,k1,k2
cdef unsigned int nk,nl,k,shx,shy
cdef double fl_ij
nk = len(idxl)
nl = len(full)
for i in range(0-x0[1], x0[1]):
if (x0[1]+i < 0) | (x0[1]+i >= shd[1]):
continue
for j in range(0-x0[0], x0[0]):
if (x0[0]+j < 0) | (x0[0]+j >= shd[0]):
continue
fl_ij = flam[x0[0]+j, x0[1]+i] #/1.e-17
if (fl_ij == 0):
continue
for k in range(nk):
k1 = idxl[k]+j*shg[1]+i
if (k1 >= 0) & (k1 < nl):
full[k1] += ysens[k]*fl_ij*yfrac[k]
k2 = idxl[k]+(j-1)*shg[1]+i
if (k2 >= 0) & (k2 < nl):
full[k2] += ysens[k]*fl_ij*(1-yfrac[k])
return True
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.embedsignature(True)
def compute_segmentation_limits(np.ndarray[FTYPE_t, ndim=2] segm, int seg_id, np.ndarray[FTYPE_t, ndim=2] flam, np.ndarray[LINT_t, ndim=1] shd):
"""Find pixel limits of a segmentation region
Parameters
----------
segm: ndarray (np.float32)
segmentation array
seg_id: int
ID to test
flam: ndarray (float)
Flux array to compute weighted centroid within segmentation region
shd: [int, int]
Shape of segm
"""
cdef int i, j, imin, imax, jmin, jmax, area
cdef double inumer, jnumer, denom, wht_ij
area = 0
imin = shd[0]
imax = 0
jmin = shd[1]
jmax = 0
inumer = 0.
jnumer = 0.
denom = 0.
for i in range(shd[0]):
for j in range(shd[1]):
if segm[i,j] != seg_id:
continue
area += 1
wht_ij = flam[i,j]
inumer += i*wht_ij
jnumer += j*wht_ij
denom += wht_ij
if i < imin:
imin = i
if i > imax:
imax = i
if j < jmin:
jmin = j
if j > jmax:
jmax = j
### No matched pixels
if denom == 0:
denom = -99
return imin, imax, inumer/denom, jmin, jmax, jnumer/denom, area, denom
@cython.boundscheck(False)
@cython.wraparound(False)
@cython.embedsignature(True)
def seg_flux(np.ndarray[FTYPE_t, ndim=2] flam, np.ndarray[LINT_t, ndim=1] idxl, np.ndarray[DTYPE_t, ndim=1] yfrac, np.ndarray[DTYPE_t, ndim=1] ysens, np.ndarray[DTYPE_t, ndim=1] full, np.ndarray[LINT_t, ndim=1] x0, np.ndarray[LINT_t, ndim=1] shd, np.ndarray[LINT_t, ndim=1] shg):
pass
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