Python development scripts
Cees Bassa
parent
f33a2ec958
commit
1b33716d7b
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#!/usr/bin/env python
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import os
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from astropy.io import fits
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import matplotlib.pyplot as plt
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import numpy as np
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from astropy import wcs
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from scipy import optimize
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def residual(a,x,y,z):
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return z-(a[0]+a[1]*x+a[2]*y)
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def offsets(ra0,de0,ra,de):
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w=wcs.WCS(naxis=2)
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w.wcs.crpix=np.array([0.0,0.0])
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w.wcs.crval=np.array([ra0,de0])
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w.wcs.cd=np.array([[1.0/3600.0,0.0],[0.0,1.0/3600.0]])
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w.wcs.ctype=["RA---TAN","DEC--TAN"]
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w.wcs.set_pv([(2,1,45.0)])
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world=np.stack((ra,de),axis=-1)
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pix=w.wcs_world2pix(world,1)
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return pix[:,0],pix[:,1]
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def read_pixel_catalog(fname):
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d=np.loadtxt(fname)
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x,y,mag=d[:,0],d[:,1],d[:,2]
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return x,y,mag
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def read_tycho2_catalog(maxmag=9.0):
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hdu=fits.open("/home/bassa/code/python/satellite/astrometry-tycho2/build/tyc2.fits")
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ra=hdu[1].data.field('RA')
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de=hdu[1].data.field('DEC')
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mag=hdu[1].data.field('MAG_VT')
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c=mag<maxmag
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print("Selected %d stars from Tycho-2 catalog with m<%.1f"%(np.sum(c),maxmag))
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return ra[c],de[c],mag[c]
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def match_catalogs(ra,de,x,y,xs,ys,rmin):
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res=[]
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for i in range(len(x)):
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dx,dy=xs-x[i],ys-y[i]
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r=np.sqrt(dx*dx+dy*dy)
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if np.min(r)<rmin:
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j=np.argmin(r)
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res.append([ra[i],de[i],xs[j],ys[j]])
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return np.array(res)
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def fit_wcs(res,x0,y0):
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ra,de,x,y=res[:,0],res[:,1],res[:,2],res[:,3]
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ra0,de0=np.mean(ra),np.mean(de)
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dx,dy=x-x0,y-y0
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for i in range(5):
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w=wcs.WCS(naxis=2)
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w.wcs.crpix=np.array([0.0,0.0])
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w.wcs.crval=np.array([ra0,de0])
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w.wcs.cd=np.array([[1.0,0.0],[0.0,1.0]])
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w.wcs.ctype=["RA---TAN","DEC--TAN"]
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w.wcs.set_pv([(2,1,45.0)])
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world=np.stack((ra,de),axis=-1)
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pix=w.wcs_world2pix(world,1)
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rx,ry=pix[:,0],pix[:,1]
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ax,cov_q,infodict,mesg,ierr=optimize.leastsq(residual,[0.0,0.0,0.0],args=(dx,dy,rx),full_output=1)
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ay,cov_q,infodict,mesg,ierr=optimize.leastsq(residual,[0.0,0.0,0.0],args=(dx,dy,ry),full_output=1)
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ra0,de0=w.wcs_pix2world([[ax[0],ay[0]]],1)[0]
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w=wcs.WCS(naxis=2)
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w.wcs.crpix=np.array([x0,y0])
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w.wcs.crval=np.array([ra0,de0])
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w.wcs.cd=np.array([[ax[1],ax[2]],[ay[1],ay[2]]])
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w.wcs.ctype=["RA---TAN","DEC--TAN"]
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w.wcs.set_pv([(2,1,45.0)])
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whdr={"CRPIX1":x0,"CRPIX2":y0,"CRVAL1":ra0,"CRVAL2":de0,"CD1_1":ax[1],"CD1_2":ax[2],"CD2_1":ay[1],"CD2_2":ay[2],"CTYPE1":"RA---TAN","CTYPE2":"DEC--TAN","CUNIT1":"DEG","CUNIT2":"DEG"}
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return whdr
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# FITS file
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fname="2018-02-12T17:39:55.270.fits"
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# Read fits
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hdu=fits.open(fname)
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# Fix to force WCS with two axes only
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hdu[0].header["NAXIS"]=2
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w=wcs.WCS(hdu[0].header)
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# Read data
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data=hdu[0].data
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zavg,zstd,zmax,znum=data
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ny,nx=zavg.shape
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# Get extrema
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vmin=np.mean(zavg)-2.0*np.std(zavg)
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vmax=np.mean(zavg)+3.0*np.std(zavg)
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# Read pixel catalog
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xs,ys,ms=read_pixel_catalog(fname+".cat")
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# Read Tycho2 catalog
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ra,de,mag=read_tycho2_catalog(9.0)
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# Convert to pixel coordinates
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xc,yc=w.all_world2pix(ra,de,1)
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c=(xc>0) & (xc<nx) & (yc>0) & (yc<ny)
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xt,yt=xc[c],yc[c]
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rat,det=ra[c],de[c]
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# Match catalogs
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res=match_catalogs(rat,det,xt,yt,xs,ys,10.0)
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whdr=fit_wcs(res,nx//2,ny//2)
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#hdu=fits.PrimaryHDU(header=w.to_header(),data=data)
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#hdr=fits.Header()
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hdr=hdu[0].header
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for k,v in whdr.items():
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hdr[k]=v
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hdu=fits.PrimaryHDU(header=hdr,data=data)
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hdu.writeto("test.fits",overwrite=True)
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# Convert catalog stars
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plt.figure(figsize=(10,8))
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plt.imshow(zavg,origin="lower",aspect=1.0,interpolation="None",vmin=vmin,vmax=vmax)
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plt.scatter(xs,ys,s=80,edgecolors="r",facecolors="none")
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plt.scatter(xt,yt,s=150,edgecolors="y",facecolors="none")
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#plt.scatter(xt[c],yt[c],s=50,edgecolors="k",facecolors="none")
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#plt.xlim(0,720)
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#plt.ylim(0,576)
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plt.show()
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#!/usr/bin/env python
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import sys
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from stio import fourframe,satid,observation
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import numpy as np
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import ppgplot
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import matplotlib.pyplot as plt
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from astropy import wcs
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from astropy.coordinates import SkyCoord
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def pos2rel(ff,x,y):
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# Setup wcs
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w=wcs.WCS(naxis=2)
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w.wcs.crpix=ff.crpix
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w.wcs.crval=ff.crval
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w.wcs.cd=ff.cd
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w.wcs.ctype=ff.ctype
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w.wcs.set_pv([(2,1,45.0)])
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world=w.wcs_pix2world(np.array([[x,y]]),1)
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return world[0,0],world[0,1]
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def dec2sex(angle):
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if angle<0.0:
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sign="-"
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else:
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sign="+"
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angle=60.0*np.abs(angle)
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# Settings
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# Minimum predicted velocity (pixels/s)
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drdtmin=10.0
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# Track selection region around prediction (pixels)
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trkrmin=10.0
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# Track selection sigma
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trksig=5.0
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# Minimum track points
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ntrkmin=10
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fname=sys.argv[1]
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# Read four frame
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ff=fourframe(fname)
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# Read satelite IDs
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try:
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f=open(fname+".id")
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except OSError:
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print("Cannot open",fname+".id")
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else:
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lines=f.readlines()
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f.close()
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# ppgplot arrays
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tr=np.array([-0.5,1.0,0.0,-0.5,0.0,1.0])
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heat_l=np.array([0.0,0.2,0.4,0.6,1.0])
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heat_r=np.array([0.0,0.5,1.0,1.0,1.0])
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heat_g=np.array([0.0,0.0,0.5,1.0,1.0])
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heat_b=np.array([0.0,0.0,0.0,0.3,1.0])
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# Loop over identifications
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for line in lines:
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# Decode
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id=satid(line)
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# Skip slow moving objects
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drdt=np.sqrt(id.dxdt**2+id.dydt**2)
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if drdt<drdtmin:
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continue
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# Extract significant pixels
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x,y,t,sig=ff.significant(trksig,id.x0,id.y0,id.dxdt,id.dydt,trkrmin)
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# Fit tracks
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if len(x)>ntrkmin:
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obs=observation(ff,x,y,t,sig)
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obs.ra,obs.de=pos2rel(ff,obs.x0,obs.y0)
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# Plot
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ppgplot.pgopen("/xs")
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ppgplot.pgpap(0.0,1.0)
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ppgplot.pgsvp(0.1,0.95,0.1,0.8)
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ppgplot.pgsch(0.8)
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ppgplot.pgmtxt("T",6.0,0.0,0.0,"UT Date: %.23s COSPAR ID: %04d"%(ff.nfd,ff.site_id))
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ppgplot.pgmtxt("T",4.8,0.0,0.0,"R.A.: %10.5f (%4.1f'') Decl.: %10.5f (%4.1f'')"%(ff.crval[0],3600.0*ff.crres[0],ff.crval[1],3600.0*ff.crres[1]))
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ppgplot.pgmtxt("T",3.6,0.0,0.0,"FoV: %.2f\\(2218)x%.2f\\(2218) Scale: %.2f''x%.2f'' pix\\u-1\\d"%(ff.wx,ff.wy,3600.0*ff.sx,3600.0*ff.sy))
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ppgplot.pgmtxt("T",2.4,0.0,0.0,"Stat: %5.1f+-%.1f (%.1f-%.1f)"%(np.mean(ff.zmax),np.std(ff.zmax),ff.vmin,ff.vmax))
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ppgplot.pgsch(1.0)
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ppgplot.pgwnad(0.0,ff.nx,0.0,ff.ny)
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ppgplot.pglab("x (pix)","y (pix)"," ")
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ppgplot.pgctab(heat_l,heat_r,heat_g,heat_b,5,1.0,0.5)
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ppgplot.pgimag(ff.zmax,ff.nx,ff.ny,0,ff.nx-1,0,ff.ny-1,ff.vmax,ff.vmin,tr)
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ppgplot.pgbox("BCTSNI",0.,0,"BCTSNI",0.,0)
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ppgplot.pgsci(3)
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# ppgplot.pgpt(x,y,4)
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ppgplot.pgsci(4)
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ppgplot.pgpt(np.array([obs.x0]),np.array([obs.y0]),4)
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ppgplot.pgmove(obs.xmin,obs.ymin)
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ppgplot.pgdraw(obs.xmax,obs.ymax)
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ppgplot.pgend()
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plt.figure()
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plt.plot(t,x,'.')
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plt.plot(t,y,'.')
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plt.plot([obs.tmin,obs.tmax],[obs.xmin,obs.xmax])
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plt.plot([obs.tmin,obs.tmax],[obs.ymin,obs.ymax])
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plt.show()
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# Track and stack
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else:
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ztrk=ff.track(id.dxdt,id.dydt,0.0)
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# plt.figure(figsize=(15,10))
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# plt.imshow(ztrk,origin='lower')
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# plt.scatter(id.x0,id.y0,s=150,edgecolors="y",facecolors="none")
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# plt.show()
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@ -0,0 +1,49 @@
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import numpy as np
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import matplotlib.pyplot as plt
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from astropy.io import fits
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import cv2
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import sys
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hdu=fits.open(sys.argv[1])
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data=hdu[0].data
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zavg,zstd,zmax,znum=data
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zsig=(zmax-zavg)/(zstd+1e-9)
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ny,nx=zsig.shape
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tmp=np.zeros(nx*ny*3,dtype='uint8').reshape(ny,nx,3)
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tmp[:,:,0]=zmax.astype('uint8')
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tmp[:,:,1]=0.1*zmax.astype('uint8')
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tmp[:,:,2]=0.1*zmax.astype('uint8')
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img=cv2.cvtColor(tmp,cv2.COLOR_BGR2RGB)
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mask=np.array(zsig>5.0,dtype='uint8')
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tmp=np.zeros(nx*ny*3,dtype='uint8').reshape(ny,nx,3)
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tmp[:,:,0]=255*mask
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tmp[:,:,1]=255*mask
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tmp[:,:,2]=255*mask
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mat=cv2.cvtColor(tmp,cv2.COLOR_BGR2GRAY)
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lines=cv2.HoughLines(mat,1,np.pi/180.0,200)
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if lines is not None:
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for rho,theta in lines[0]:
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a = np.cos(theta)
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b = np.sin(theta)
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x0 = a*rho
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y0 = b*rho
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x1 = int(x0 + 1000*(-b))
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y1 = int(y0 + 1000*(a))
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x2 = int(x0 - 1000*(-b))
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y2 = int(y0 - 1000*(a))
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cv2.line(img,(x1,y1+10),(x2,y2+10),(0,0,255),2)
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minLineLength = 100
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maxLineGap = 10
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lines = cv2.HoughLinesP(mat,1,np.pi/180,100,minLineLength,maxLineGap)
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if lines is not None:
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for x1,y1,x2,y2 in lines[0]:
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cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2)
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cv2.imwrite(sys.argv[1]+'.jpg',img)
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#!/usr/bin/env python
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class iod:
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"""IOD Observation"""
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def __init__(self,line):
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s=line.split()
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self.iodline=line
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self.norad=int(s[0])
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self.cospar="%s %s"%(s[1],s[2])
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self.site=int(s[3])
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self.conditions=s[4]
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self.datestring=s[5]
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def __repr__(self):
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return "%05d %s %04d %s %s"%(self.norad,self.cospar,self.site,self.conditions,self.datestring)
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iodlines=["10529 77 112D 4553 G 20120511214446298 17 25 2034286+472232 37 R",
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"10529 77 112D 4553 G 20120511214452938 17 25 2038653+454274 37 S",
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"23862 96 029D 4553 G 20120511221706217 17 25 2121225+480700 37 S",
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"23862 96 029D 4553 G 20120511221726241 17 25 2122590+453398 37 R"]
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obslist=[iod(line) for line in iodlines]
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print(type(obslist),type(obslist[0]))
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for obs in obslist:
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print(obs)
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@ -0,0 +1,69 @@
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#!/usr/bin/env python
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import numpy as np
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import sys
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from astropy.io import fits
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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fname="2018-02-12T17:39:55.270.fits"
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# Read fits
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hdu=fits.open(fname)
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# Read data
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data=hdu[0].data
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zavg,zstd,zmax,znum=data
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# Read header
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ny,nx=zavg.shape
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nz=hdu[0].header['NFRAMES']
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dt=[hdu[0].header['DT%04d'%i] for i in range(nz)]
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# Sigma frame
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zsig=(zmax-zavg)/(zstd+1e-9)
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# Position
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xm,ym=np.meshgrid(np.arange(nx),np.arange(ny))
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# Selection width
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w=10
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sigma=5.0
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# Selection
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c=(zsig>sigma) & (xm>w) & (xm<nx-w) & (ym>w) & (ym<ny-w)
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x=np.ravel(xm[c])
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y=np.ravel(ym[c])
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inum=np.ravel(znum[c]).astype('int')
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sig=np.ravel(zsig[c])
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t=np.array([dt[i] for i in inum])
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# Load predictions
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d=np.loadtxt(fname+".id",usecols=(1,2,3,4,5,6))
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x0=d[:,0]
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y0=d[:,1]
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t0=np.zeros_like(x0)
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x1=d[:,2]
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y1=d[:,3]
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t1=d[:,4]
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for i in range(len(x0)):
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xr=x0[i]+(x1[i]-x0[i])*(t-t0[i])/(t1[i]-t0[i])
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yr=y0[i]+(y1[i]-y0[i])*(t-t0[i])/(t1[i]-t0[i])
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r=np.sqrt((x-xr)**2+(y-yr)**2)
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c=r<10.0
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print(i,np.sum(c))
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plt.figure()
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plt.plot([x0[i],x1[i]],[y0[i],y1[i]],'r')
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plt.scatter(x[c],y[c],c=t[c],s=10.0*(sig[c]-sigma))
|
||||
plt.scatter(x,y,c=t,s=1)
|
||||
plt.show()
|
||||
|
||||
#fig=plt.figure()
|
||||
#ax=fig.add_subplot(111,projection='3d')
|
||||
#ax.scatter(x,y,t,c=t,s=10*(sig-5))
|
||||
|
||||
#for i in range(len(x0)):
|
||||
# ax.plot([x0[i],x1[i]],[y0[i],y1[i]],[t0[i],t1[i]],'k')
|
||||
#plt.show()
|
||||
|
|
@ -0,0 +1,173 @@
|
|||
#!/usr/bin/env python
|
||||
|
||||
import numpy as np
|
||||
from astropy.io import fits
|
||||
from astropy.time import Time
|
||||
|
||||
class observation:
|
||||
"""Satellite observation"""
|
||||
|
||||
def __init__(self,ff,x,y,t,sig):
|
||||
"""Fit a satellite track"""
|
||||
|
||||
# Get times
|
||||
self.tmin=np.min(t)
|
||||
self.tmid=np.mean(t)
|
||||
self.tmax=np.max(t)
|
||||
self.mjd=ff.mjd+self.tmid/86400.0
|
||||
self.nfd=Time(self.mjd,format='mjd',scale='utc').isot
|
||||
|
||||
# Very simple polynomial fit; no weighting, no cleaning
|
||||
px=np.polyfit(t-self.tmid,x,1)
|
||||
py=np.polyfit(t-self.tmid,y,1)
|
||||
|
||||
# Store
|
||||
self.x0=px[1]
|
||||
self.y0=py[1]
|
||||
self.dxdt=px[0]
|
||||
self.dydt=py[0]
|
||||
self.xmin=self.x0+self.dxdt*(self.tmin-self.tmid)
|
||||
self.ymin=self.y0+self.dydt*(self.tmin-self.tmid)
|
||||
self.xmax=self.x0+self.dxdt*(self.tmax-self.tmid)
|
||||
self.ymax=self.y0+self.dydt*(self.tmax-self.tmid)
|
||||
|
||||
class satid:
|
||||
"""Satellite identifications"""
|
||||
|
||||
def __init__(self,line):
|
||||
s=line.split()
|
||||
self.nfd=s[0]
|
||||
self.x0=float(s[1])
|
||||
self.y0=float(s[2])
|
||||
self.t0=0.0
|
||||
self.x1=float(s[3])
|
||||
self.y1=float(s[4])
|
||||
self.t1=float(s[5])
|
||||
self.norad=int(s[6])
|
||||
self.catalog=s[7]
|
||||
self.state=s[8]
|
||||
self.dxdt=(self.x1-self.x0)/(self.t1-self.t0)
|
||||
self.dydt=(self.y1-self.y0)/(self.t1-self.t0)
|
||||
|
||||
def __repr__(self):
|
||||
return "%s %f %f %f -> %f %f %f %d %s %s"%(self.nfd,self.x0,self.y0,self.t0,self.x1,self.y1,self.t1,self.norad,self.catalog,self.state)
|
||||
|
||||
class fourframe:
|
||||
"""Four frame class"""
|
||||
|
||||
def __init__(self,fname=None):
|
||||
if fname==None:
|
||||
# Initialize empty fourframe
|
||||
self.nx=0
|
||||
self.ny=0
|
||||
self.nz=0
|
||||
self.mjd=-1
|
||||
self.nfd=None
|
||||
self.zavg=None
|
||||
self.zstd=None
|
||||
self.zmax=None
|
||||
self.znum=None
|
||||
self.dt=None
|
||||
self.site_id=0
|
||||
self.observer=None
|
||||
self.texp=0.0
|
||||
self.fname=None
|
||||
self.crpix=np.array([0.0,0.0])
|
||||
self.crval=np.array([0.0,0.0])
|
||||
self.cd=np.array([[1.0,0.0],[0.0,1.0]])
|
||||
self.ctype=["RA---TAN","DEC--TAN"]
|
||||
self.cunit=np.array(["deg","deg"])
|
||||
self.crres=np.array([0.0,0.0])
|
||||
else:
|
||||
# Read FITS file
|
||||
hdu=fits.open(fname)
|
||||
|
||||
# Read image planes
|
||||
self.zavg,self.zstd,self.zmax,self.znum=hdu[0].data
|
||||
|
||||
# Frame properties
|
||||
self.ny,self.nx=self.zavg.shape
|
||||
self.nz=hdu[0].header['NFRAMES']
|
||||
|
||||
# Read frame time oselfsets
|
||||
self.dt=np.array([hdu[0].header['DT%04d'%i] for i in range(self.nz)])
|
||||
|
||||
# Read header
|
||||
self.mjd=hdu[0].header['MJD-OBS']
|
||||
self.nfd=hdu[0].header['DATE-OBS']
|
||||
self.site_id=hdu[0].header['COSPAR']
|
||||
self.observer=hdu[0].header['OBSERVER']
|
||||
self.texp=hdu[0].header['EXPTIME']
|
||||
self.fname=fname
|
||||
|
||||
# Astrometry keywords
|
||||
self.crpix=np.array([hdu[0].header['CRPIX1'],hdu[0].header['CRPIX2']])
|
||||
self.crval=np.array([hdu[0].header['CRVAL1'],hdu[0].header['CRVAL2']])
|
||||
self.cd=np.array([[hdu[0].header['CD1_1'],hdu[0].header['CD1_2']],
|
||||
[hdu[0].header['CD2_1'],hdu[0].header['CD2_2']]])
|
||||
self.ctype=[hdu[0].header['CTYPE1'],hdu[0].header['CTYPE2']]
|
||||
self.cunit=[hdu[0].header['CUNIT1'],hdu[0].header['CUNIT2']]
|
||||
self.crres=np.array([hdu[0].header['CRRES1'],hdu[0].header['CRRES2']])
|
||||
|
||||
self.sx=np.sqrt(self.cd[0,0]**2+self.cd[1,0]**2)
|
||||
self.sy=np.sqrt(self.cd[0,1]**2+self.cd[1,1]**2)
|
||||
self.wx=self.nx*self.sx
|
||||
self.wy=self.ny*self.sy
|
||||
self.vmin=np.mean(self.zmax)-2.0*np.std(self.zmax)
|
||||
self.vmax=np.mean(self.zmax)+6.0*np.std(self.zmax)
|
||||
|
||||
|
||||
def significant(self,sigma,x0,y0,dxdt,dydt,rmin=10.0):
|
||||
"""Extract significant points"""
|
||||
|
||||
# Generate sigma frame
|
||||
zsig=(self.zmax-self.zavg)/(self.zstd+1e-9)
|
||||
|
||||
# Select
|
||||
c=(zsig>sigma)
|
||||
|
||||
# Positions
|
||||
xm,ym=np.meshgrid(np.arange(self.nx),np.arange(self.ny))
|
||||
x,y=np.ravel(xm[c]),np.ravel(ym[c])
|
||||
inum=np.ravel(self.znum[c]).astype('int')
|
||||
sig=np.ravel(zsig[c])
|
||||
t=np.array([self.dt[i] for i in inum])
|
||||
|
||||
# Predicted positions
|
||||
xr=x0+dxdt*t
|
||||
yr=y0+dydt*t
|
||||
r=np.sqrt((x-xr)**2+(y-yr)**2)
|
||||
c=r<rmin
|
||||
|
||||
return x[c],y[c],t[c],sig[c]
|
||||
|
||||
def track(self,dxdt,dydt,tref):
|
||||
"""Track and stack"""
|
||||
# Empty frame
|
||||
ztrk=np.zeros_like(self.zavg)
|
||||
|
||||
# Loop over frames
|
||||
for i in range(self.nz):
|
||||
dx=int(np.round(dxdt*(self.dt[i]-tref)))
|
||||
dy=int(np.round(dydt*(self.dt[i]-tref)))
|
||||
if dx>=0:
|
||||
i1min,i1max=dx,self.nx-1
|
||||
i2min,i2max=0,self.nx-dx-1
|
||||
else:
|
||||
i1min,i1max=0,self.nx+dx-1
|
||||
i2min,i2max=-dx,self.nx-1
|
||||
if dy>=0:
|
||||
j1min,j1max=dy,self.ny-1
|
||||
j2min,j2max=0,self.ny-dy-1
|
||||
else:
|
||||
j1min,j1max=0,self.ny+dy-1
|
||||
j2min,j2max=-dy,self.ny-1
|
||||
zsel=np.where(self.znum==i,self.zmax,0.0)
|
||||
ztrk[j2min:j2max,i2min:i2max]+=zsel[j1min:j1max,i1min:i1max]
|
||||
|
||||
return ztrk
|
||||
|
||||
def __repr__(self):
|
||||
return "%s %dx%dx%d %s %.3f %d %s"%(self.fname,self.nx,self.ny,self.nz,self.nfd,self.texp,self.site_id,self.observer)
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,34 @@
|
|||
#!/usr/bin/env python
|
||||
from astropy.coordinates import SkyCoord,EarthLocation,AltAz,get_sun
|
||||
from astropy.time import Time
|
||||
import astropy.units as u
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from scipy import optimize,interpolate
|
||||
|
||||
|
||||
|
||||
loc=EarthLocation(lat=52.8344*u.deg,lon=6.3785*u.deg,height=10*u.m)
|
||||
t0=Time.now()
|
||||
refalt=-6.0
|
||||
|
||||
# Compute solar position every 10 minutes
|
||||
t=Time(t0.mjd+np.arange(144)/144.0,format='mjd',scale='utc')
|
||||
psun=get_sun(t)
|
||||
hor=psun.transform_to(AltAz(obstime=t,location=loc))
|
||||
|
||||
# Interpolating function
|
||||
alt_diff=hor.alt.deg-refalt
|
||||
f=interpolate.interp1d(t.mjd,alt_diff)
|
||||
|
||||
# Find sunrise/sunset
|
||||
sign=alt_diff[1:]*alt_diff[:-1]
|
||||
idx=np.where(sign<0.0)[0]
|
||||
for i in idx:
|
||||
# Set
|
||||
if alt_diff[i]>alt_diff[i+1]:
|
||||
tset=Time(optimize.bisect(f,t[i].mjd,t[i+1].mjd),format='mjd',scale='utc')
|
||||
# Rise
|
||||
else:
|
||||
trise=Time(optimize.bisect(f,t[i].mjd,t[i+1].mjd),format='mjd',scale='utc')
|
||||
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
#!/usr/bin/env python
|
||||
from skyfield.positionlib import ICRF
|
||||
from skyfield.api import load,Topos
|
||||
|
||||
ts=load.timescale()
|
||||
t=ts.now()
|
||||
observer=Topos(latitude_degrees=52.8344,longitude_degrees=6.3785,elevation_m=10.0)
|
||||
p=ICRF([0.0,0.0,0.0],observer_data=observer,t=t)
|
||||
q=p.from_altaz(alt_degrees=30.0,az_degrees=30.0)
|
||||
|
||||
print(p,q)
|
||||
Loading…
Reference in New Issue