def calculate_em(self, wlen='171', dz=100, model=False):
"""
Calculate an approximation of the coronal EmissionMeasure using a given
TemperatureMap object and a particular AIA channel.
Parameters
----------
tmap : CoronaTemps.temperature.TemperatureMap
A TemperatureMap instance containing coronal temperature data
wlen : {'94' | '131' | '171' | '193' | '211' | '335'}
AIA wavelength used to approximate the emission measure. '171', '193'
and '211' are most likely to provide reliable results. Use of other
channels is not recommended.
"""
# Load the appropriate temperature response function
tresp = read('/imaps/holly/home/ajl7/CoronaTemps/aia_tresp')
resp = tresp['resp{}'.format(wlen)]
# Get some information from the TemperatureMap and set up filenames, etc
tempdata = self.data.copy()
tempdata[np.isnan(tempdata)] = 0.0
date = sunpy.time.parse_time(self.date)
if not model:
data_dir = self.data_dir
fits_dir = path.join(data_dir, '{:%Y/%m/%d}/{}'.format(date, wlen))
filename = path.join(fits_dir,
'*{0:%Y?%m?%d}?{0:%H?%M}*fits'.format(date))
if wlen == '94': filename = filename.replace('94', '094')
# Load and appropriately process AIA data
filelist = glob.glob(filename)
if filelist == []:
print 'AIA data not found :('
return
aiamap = Map(filename)
aiamap.data /= aiamap.exposure_time
aiamap = aiaprep(aiamap)
aiamap = aiamap.submap(self.xrange, self.yrange)
else:
fname = '/imaps/holly/home/ajl7/CoronaTemps/data/synthetic/{}/model.fits'.format(wlen)
if wlen == '94': fname = fname.replace('94', '094')
aiamap = Map(fname)
# Create new Map and put EM values in it
emmap = Map(self.data.copy(), self.meta.copy())
indices = np.round((tempdata - 4.0) / 0.05).astype(int)
indices[indices < 0] = 0
indices[indices > 100] = 100
#print emmap.shape, indices.shape, tempdata.shape, aiamap.shape, resp.shape
emmap.data = np.log10(aiamap.data / resp[indices])
#emmap.data = aiamap.data / resp[indices]
emmapcubehelix = _cm.cubehelix(s=2.8, r=-0.7, h=1.4, gamma=1.0)
cm.register_cmap(name='emhelix', data=emmapcubehelix)
emmap.cmap = cm.get_cmap('emhelix')
return emmap
def load_temp_responses(n_wlens=6, corrections=True):
resp = np.zeros((n_wlens, 301))
try:
tresp = read(home + 'aia_tresp')
except IOError:
tresp = read('/imaps/holly/home/ajl7/aia_tresp')
resp[0, 80:181] = tresp['resp94']
resp[1, 80:181] = tresp['resp131']
resp[2, 80:181] = tresp['resp171']
resp[3, 80:181] = tresp['resp193']
resp[4, 80:181] = tresp['resp211']
resp[5, 80:181] = tresp['resp335']
if n_wlens > 6:
resp[6, 80:181] = tresp['resp304']
if corrections:
# Add empirical correction factor for 9.4nm response function below log(T)=6.3
# (see Aschwanden et al 2011)
resp[0:126, 0] = resp[0:126, 0] * 6.7
return resp
def load_temp_responses(n_wlens=6, corrections=True):
resp = np.zeros((n_wlens, 301))
try:
tresp = read(home + 'aia_tresp')
except IOError:
tresp = read('/imaps/holly/home/ajl7/aia_tresp')
resp[0, 80:181] = tresp['resp94']
resp[1, 80:181] = tresp['resp131']
resp[2, 80:181] = tresp['resp171']
resp[3, 80:181] = tresp['resp193']
resp[4, 80:181] = tresp['resp211']
resp[5, 80:181] = tresp['resp335']
if n_wlens > 6:
resp[6, 80:181] = tresp['resp304']
if corrections:
# Add empirical correction factor for 9.4nm response function below log(T)=6.3
# (see Aschwanden et al 2011)
resp[0:126, 0] = resp[0:126, 0]*6.7
return resp
def load_temp_responses(n_wlens=6, corrections=True):
resp = np.zeros((n_wlens, 301))
tresp = read(expanduser('~/CoronaTemps/aia_tresp'))
resp[0, 80:181] = tresp['resp94']
resp[1, 80:181] = tresp['resp131']
resp[2, 80:181] = tresp['resp171']
resp[3, 80:181] = tresp['resp193']
resp[4, 80:181] = tresp['resp211']
resp[5, 80:181] = tresp['resp335']
if n_wlens > 6:
resp[6, 80:181] = tresp['resp304']
if corrections:
# Add empirical correction factor for 9.4nm response function below log(T)=6.3
# (see Aschwanden et al 2011)
resp[0:126, 0] = resp[0:126, 0]*6.7
return resp
plt.colorbar(orientation="horizontal")
diff_im = testarr - rotmap_test
print "SunPy back rotation difference range: {!s}.".format(diff_im.max() - diff_im.min())
diff = fig.add_subplot(236)
plt.imshow(diff_im, cmap=cm.coolwarm)
diff.set_title("Difference between images")
plt.colorbar(orientation="horizontal")
plt.show()
"""
==========
Same test for IDL's rot() function.
==========
"""
idl_arrs = read("idl_fullrot_test")
fig = plt.figure("Core IDL rot() function")
original = fig.add_subplot(231)
plt.imshow(idl_arrs["array"], cmap=cm.coolwarm)
original.set_title("Original image")
plt.colorbar(orientation="horizontal")
rotated = fig.add_subplot(232)
plt.imshow(idl_arrs["fullrot"], cmap=cm.coolwarm)
rotated.set_title("Image rotated 360 degrees")
plt.colorbar(orientation="horizontal")
diff = fig.add_subplot(233)
diff_im = idl_arrs["fullrot_diff"]
print "IDL rot() full rotation difference range: {!s}.".format(diff_im.max() - diff_im.min())
plt.imshow(idl_arrs["fullrot_diff"], cmap=cm.coolwarm)
