class needed_param(): path = os.getcwd() #store the uvf, mod and fits files of the maps in a list files = [] for filename in sorted(glob.glob(path+'/UVF/*.uvf*')): files.append(filename) #for the moment as well, you can also read the file with header = pf.getheader(uvffile) and then freq = header['CRVAL4'], all that would be easier in general as i dont need to depend of having a similar modification date in all of them ----> leads to changing the function order_by_nu models = [] for filename in sorted(glob.glob(path+'/MODELS/*.mod*')): models.append(filename) #for the moment, in the modelfit file it is posible to read the frequency, which will simplify how to get it in general fits = [] for filename in sorted(glob.glob(path+'/FITS/*.fits*')): fits.append(filename) modelfit = [] for filename in sorted(glob.glob(path+'/modelfit/*.mod*')): modelfit.append(filename) #for the moment, in the modelfit file it is posible to read the frequency, which will simplify how to get it in general modelfit.sort(key=natural_keys) modelfiterror = [] for filename in sorted(glob.glob(path+'/modelfit/*.dat*')): modelfiterror.append(filename) #for the moment, in the modelfit file it is posible to read the frequency, which will simplify how to get it in general modelfiterror.sort(key=natural_keys) coreshiftfile = [] for filename in sorted(glob.glob(path+'/coreshiftmeas/*.meas*')): coreshiftfile.append(filename) #for the moment, in the modelfit file it is posible to read the frequency, which will simplify how to get it in general #initialize arrays cell = np.array([0.]*len(fits)) bmaj = np.array([0.]*len(fits)) bmin = np.array([0.]*len(fits)) bpa = np.array([0.]*len(fits)) freq = np.array([0.]*len(fits)) beam = np.array([0.]*len(fits)) size_map = np.array([0.]*len(fits)) size_map_y =np.array([0.]*len(fits)) #order the the list by frequency and #getting the corresponding values of the previous initialized arrays ordered by frequency #(lower to higher) ordered_params = order_by_nu(files,models,fits,False) freq = ordered_params[0] files = ordered_params[8] models = ordered_params[9] fits = ordered_params[10] #source name header = take_header(fits[0],False) source_name = header[8]
def findingBEAM(self,checkBOXes,freq): #self.checks,freq ###stop_event,checkBOXes,freq
#self.myLongTask.start()
self.fits_conv = []
for filename in sorted(glob.glob(needed_param.path+'/CONV/*.fits*')):
self.fits_conv.append(filename)
files_temp = self.fits_conv
models_temp = self.fits_conv
###ORDER THEM BY FREQUENCY
ordered_params_conv = order_by_nu(files_temp,files_temp,self.fits_conv)
self.freq_conv = ordered_params_conv[0]
self.beam_conv = ordered_params_conv[5]
self.fits_conv = ordered_params_conv[10]
finding_beam = beam_array(checkBOXes,freq,self.freq_conv,self.beam_conv)
self.freq1_index,self.freq2_index,self.index_beam12 = finding_beam[0],finding_beam[1],finding_beam[2]
self.beam1,self.beam2 = finding_beam[3],finding_beam[4]
if len(self.index_beam12)== 1:
track_freq1 = self.index_beam12[0][0]
index_freq1 = self.freq1_index[0][track_freq1]
self.fits1 = self.fits_conv[index_freq1]
track_freq2 = self.index_beam12[0][1]-len(self.freq1_index[0])
index_freq2 = self.freq2_index[0][track_freq2]
self.fits2 = self.fits_conv[index_freq2]
self.labelFITS1file.setText(self.fits1[len(needed_param.path):])
self.labelFITS2file.setText(self.fits2[len(needed_param.path):])
see_if_OK = check_map_params(str(self.fits1),str(self.fits2))
OK = see_if_OK[0]
if OK == True:
self.labelFITS1file.setStyleSheet('QLabel {color: green } QLabel {font: Bold }')
self.labelFITS2file.setStyleSheet('QLabel {color: green } QLabel {font: Bold }')
self.labelOK.setText("Files OK")
self.labelOK.setStyleSheet('QLabel {color: green } QLabel {font: Bold }')
else:
self.labelFITS1file.setStyleSheet('QLabel {color: red } QLabel {font: Bold }')
self.labelFITS2file.setStyleSheet('QLabel {color: red } QLabel {font: Bold }')
self.labelOK.setText("Convolve the files with the same beam,cell and mapsize")
self.labelOK.setStyleSheet('QLabel {color: red } QLabel {font: Bold }')
else:
ShiftWindow.diff_beams = []
for i in xrange(0,len(self.index_beam12)):
ShiftWindow.diff_beams.append(self.beam1[self.index_beam12[i][0]])
self.wi = popup_beams()
self.wi.show()
self.wi.selectButton.clicked.connect(lambda: self.getBEAM(self.wi.checks2, ShiftWindow.diff_beams,self.beam1,self.beam2,self.freq1_index,self.freq2_index,self.fits_conv))
return popup_beams
class needed_param():
path = os.getcwd()
if not os.path.exists('Plot_fitted_synchrotron'):
os.makedirs('Plot_fitted_synchrotron')
if not os.path.exists('Plot_fitted_PL'):
os.makedirs('Plot_fitted_PL')
if not os.path.exists('Plot_fitted_synchrotronExtrapolated'):
os.makedirs('Plot_fitted_synchrotronExtrapolated')
#store the uvf, mod and fits files of the maps in a list
files = []
for filename in sorted(glob.glob(path+'/UVF/*.uvf*')):
files.append(filename)
models = []
for filename in sorted(glob.glob(path+'/MODELS/*.mod*')):
models.append(filename)
fits = []
for filename in sorted(glob.glob(path+'/FITS/*.fits*')):
fits.append(filename)
#initialize arrays
cell = np.array([0.]*len(fits))
bmaj = np.array([0.]*len(fits))
bmin = np.array([0.]*len(fits))
bpa = np.array([0.]*len(fits))
freq = np.array([0.]*len(fits))
beam = np.array([0.]*len(fits))
size_map = np.array([0.]*len(fits))
size_map_y =np.array([0.]*len(fits))
#order the the list by frequency and
#getting the corresponding values of the previous initialized arrays ordered by frequency
#(lower to higher)
ordered_params = order_by_nu(files,models,fits,False)
freq = ordered_params[0]
files = ordered_params[8]
models = ordered_params[9]
fits = ordered_params[10]
#source name
header = take_header(fits[0],False)
source_name = header[8]
class needed_param():
path = os.getcwd()
#store the uvf, mod and fits files of the maps in a list
files = []
for filename in sorted(glob.glob(path + '/UVF/*.uvf*')):
files.append(filename)
models = []
for filename in sorted(glob.glob(path + '/MODELS/*.mod*')):
models.append(filename)
fits = []
for filename in sorted(glob.glob(path + '/FITS/*.fits*')):
fits.append(filename)
modelfit = []
for filename in sorted(glob.glob(path + '/modelfit/*.mod*')):
modelfit.append(filename)
modelfit.sort(key=natural_keys)
#initialize arrays
cell = np.array([0.] * len(fits))
bmaj = np.array([0.] * len(fits))
bmin = np.array([0.] * len(fits))
bpa = np.array([0.] * len(fits))
freq = np.array([0.] * len(fits))
beam = np.array([0.] * len(fits))
size_map = np.array([0.] * len(fits))
size_map_y = np.array([0.] * len(fits))
#order the the list by frequency and
#getting the corresponding values of the previous initialized arrays ordered by frequency
#(lower to higher)
ordered_params = order_by_nu(files, models, fits, False)
freqOrig = ordered_params[0]
beam = ordered_params[5]
files = ordered_params[8]
models = ordered_params[9]
fits = ordered_params[10]
freq = freqOrig.copy()
units = []
for i in xrange(0, len(freq)):
if freq[i] < 0.5:
freq[i] = freq[i] * 1000
units.append('MHz')
else:
units.append('GHz')
units = np.asarray(units)
#source name
header = take_header(fits[0], False)
source_name = header[8]
#reads the modelfit files and obtains the modelfit values and errors
if len(modelfit) > 0:
if os.path.isfile('pos_errors.dat'):
errors = True
else:
errors = None
mod_parameters = read_modfile(modelfit, beam, errors)
"""
r, errr = radial distance and error of the component
psi, errpsi = position angle and error of the component
size, errsize = size and error of the component
"""
r, errr = mod_parameters[0], mod_parameters[1]
psi, errpsi = mod_parameters[2], mod_parameters[3]
size, errsize = mod_parameters[4], mod_parameters[5]
flux, errflux = mod_parameters[7], mod_parameters[8]
#with the radial distance and position angle, the central positions of the components in RA and DEC are calculated
"""
x, errx = position in RA and error of the component
y, erry = position in DEC and error of the component
"""
x_and_y = x_y(r, errr, psi, errpsi, errors)
x, errx = np.asarray(x_and_y[0]), np.asarray(x_and_y[1])
y, erry = np.asarray(x_and_y[2]), np.asarray(x_and_y[3])
#for plotting the components in the map
"""
pts_arr = points for drawing the external countour of the ellipse, i.e., the ellipse itself
x_el_arr = points for the x axis in the x direction of the ellipse. They are between (x_cent_component - size component) and (x_cent_component + size component).They are a total of 50
y_elH_arr = points for the y axis in the x direction of the ellipse. It is a constant, so it is the same value 50 times, for using it with x_el_arr
y_el_arr = points for the y axis in the y direction of the ellipse. They are between (y_cent_component - size component) and (y_cent_component + size component). They are a total of 50
x_elH_arr = points for the x axis in the y direction of the ellipse. It is a constant, so it is the same value 50 times, for using it with y_el_arr
"""
pts_arr = []
pt_arr = []
x_el_arr = []
x_elH_arr = []
y_el_arr = []
y_elH_arr = []
ellipse_plot = ellipse_axis_lines(x, y, size)
pts_arr, pt_arr = ellipse_plot[0], ellipse_plot[1]
x_el_arr, y_el_arr = ellipse_plot[2], ellipse_plot[3]
x_elH_arr, y_elH_arr = ellipse_plot[4], ellipse_plot[5]
class needed_files():
path = os.getcwd()
sourcepath = os.getcwd()
if not os.path.exists('UVF'):
os.makedirs('UVF')
if not os.path.exists('MODELS'):
os.makedirs('MODELS')
if not os.path.exists('FITS'):
os.makedirs('FITS')
if not os.path.exists('CONV'):
os.makedirs('CONV')
if not os.path.exists('CONV_ALL'):
os.makedirs('CONV_ALL')
if not os.path.exists('SHIFT'):
os.makedirs('SHIFT')
if not os.path.exists('Shift_parameters'):
os.makedirs('Shift_parameters')
if not os.path.exists('SHIFT_ALL'):
os.makedirs('SHIFT_ALL')
if not os.path.exists('Plot_fitted'):
os.makedirs('Plot_fitted')
if not os.path.exists('SPIX_MAPS'):
os.makedirs('SPIX_MAPS')
if not os.path.exists('coreshiftmeas'):
os.makedirs('coreshiftmeas')
source = os.listdir(sourcepath)
destinationpath_uvf = path+'/UVF/'
destinationpath_models = path+'/MODELS/'
destinationpath_fits = path+'/FITS/'
for files in source:
if files.endswith('.uvf'):
shutil.move(os.path.join(sourcepath,files), os.path.join(destinationpath_uvf,files))
if files.endswith('.mod'):
shutil.move(os.path.join(sourcepath,files), os.path.join(destinationpath_models,files))
if files.endswith('.fits'):
shutil.move(os.path.join(sourcepath,files), os.path.join(destinationpath_fits,files))
#store the uvf, mod and fits files of the maps in a list
files = []
for filename in sorted(glob.glob(path+'/UVF/*.uvf*')):
files.append(filename)
models = []
for filename in sorted(glob.glob(path+'/MODELS/*.mod*')):
models.append(filename)
fits = []
for filename in sorted(glob.glob(path+'/FITS/*.fits*')):
fits.append(filename)
#initialize arrays
cell = np.array([0.]*len(fits))
bmaj = np.array([0.]*len(fits))
bmin = np.array([0.]*len(fits))
bpa = np.array([0.]*len(fits))
freq = np.array([0.]*len(fits))
beam = np.array([0.]*len(fits))
size_map = np.array([0.]*len(fits))
size_map_y =np.array([0.]*len(fits))
#order the the list by frequency and
#getting the corresponding values of the previous initialized arrays ordered by frequency
#(lower to higher)
ordered_params = order_by_nu(files,models,fits,False)
freqOrig = ordered_params[0]
cell = ordered_params[1]
bmaj = ordered_params[2]
bmin = ordered_params[3]
bpa = ordered_params[4]
beam = ordered_params[5]
size_map = ordered_params[6]
size_map_y = ordered_params[7]
files = ordered_params[8]
models = ordered_params[9]
fits = ordered_params[10]
freq = freqOrig.copy()
units = []
for i in xrange(0,len(freq)):
if freq[i] < 0.5:
freq[i] = freq[i]*1000
units.append('MHz')
else:
units.append('GHz')
units = np.asarray(units)
#source name
header = take_header(fits[0],False)
source_name = header[8]
xshift = 0
yshift = 0
