def phxCompare(star, wlim=None, maxpow=None, mindw=None, ax=None):
if ax is None: ax = plt.gca()
xf = db.findfiles('ir', 'phx', star, fullpaths=True)
pf = db.panpath(star)
phx = io.read(xf)[0]
pan = io.read(pf)[0]
normfac = pan['normfac'][-1]
if wlim is not None:
phx, pan = utils.keepranges(phx, wlim), utils.keepranges(pan, wlim)
if maxpow or mindw:
pan = utils.fancyBin(pan, maxpow=maxpow, mindw=mindw)
phx = utils.fancyBin(phx, maxpow=maxpow, mindw=mindw)
Fbol = utils.bolo_integral(star)
pan['normflux'] = pan['flux'] / Fbol
pan['normerr'] = pan['error'] / Fbol
phx['normflux'] = phx['flux'] * normfac / Fbol
line = specstep(pan, key='normflux', label='Panspec', ax=ax)
specstep(pan,
key='normerr',
label='Panspec Error',
ax=ax,
color=line.get_color(),
ls=':')
specstep(phx, key='normflux', label='Phoenix', ax=ax, color='r', alpha=0.5)
ax.set_xlim(wlim)
ax.legend(loc='best')
def compare_v20_v10(stars=None, plot=False):
if stars is None:
stars = mlstars
oldfile_template = '/Users/rolo7566/Datasets/MUSCLES/products/archive/panspecs v10/p_msl_pan_-----_{}_panspec_native_resolution.fits'
hlspfile_template = '/Users/rolo7566/Google Drive/Grad School/PhD Work/muscles/share/hlsp/archive/hlsp_muscles_multi_multi_{}_broadband_v10_var-res-sed.fits'
compare_template = '/Users/rolo7566/Google Drive/Grad School/PhD Work/muscles/scratchwork/v10 - v20 comparisons/{' \
'} v20 vs v10 ratio.fits'
for star in stars:
p = io.readpan(star)
op, = io.read(oldfile_template.format(star))
hp, = io.read(hlspfile_template.format(star))
op = red.splice(op, utils.keepranges(hp, 100., 1169.))
p, op = [utils.keepranges(spec, 0, 10000.) for spec in [p, op]]
cs = utils.compare_specs(p, op, savetxt=compare_template.format(star))
cf = compare_template.format(star)
cs.write(cf, overwrite=True)
if plot:
plt.figure()
ss(cs, key='ratio')
plt.title(star)
plt.xlabel('Wavelength $\AA$')
plt.ylabel('Ratio of v20 to v10 SED')
def lya_splices(stars='all'):
if stars == 'all':
stars = rc.stars[:11]
stars.remove('gj551')
dw = 0.05
for star in stars:
pan = io.readpan(star)
pan = utils.keepranges(pan, 1100, 1300)
pan = utils.evenbin(pan, dw)
sf = db.findfiles('u', star, 'coadd', 'cos_g130m')
spec, = io.read(sf)
spec = utils.evenbin(spec, dw)
lf = db.findfiles('u', star, 'mod', 'lya')
lya, = io.read(lf)
plt.figure()
[ss(s, err=False) for s in [pan, spec, lya]]
plt.xlim(1210, 1222)
up, _ = utils.flux_integral(spec, 1217, 1220)
plt.ylim(0, up * 4)
plt.legend(['pan', 'cos', 'lya'], loc='best')
plt.savefig(
os.path.join(rc.scratchpath, 'lya splices',
'{} linear.pdf'.format(star)))
mx = spec['flux'].max()
plt.ylim(mx / 1e7, mx)
plt.yscale('log')
plt.savefig(
os.path.join(rc.scratchpath, 'lya splices',
'{} log.pdf'.format(star)))
def phx_compare_single(star):
pan = io.read(db.panpath(star))[0]
xf = db.findfiles('ir', 'phx', star, fullpaths=True)
phx = io.read(xf)[0]
phx['flux'] *= pan['normfac'][-1]
bands = [rc.fuv, rc.nuv, [rc.vis[0], 5700.]]
(pff, pfe) , (pnf, pne), (pvf, pve) = [utils.flux_integral(pan, *b) for b in bands]
(xff, _) , (xnf, _), (xvf, _) = [utils.flux_integral(phx, *b) for b in bands]
return ((pff - xff)/pff, pfe/pff), ((pnf - xnf)/pnf, pne/pnf), ((pvf - xvf)/pvf, pve/pvf)
def vetcoadd(star, config):
"""Plot the components of a coadded spectrum to check that the coadd agrees."""
coaddfile = db.coaddfile(star, config)
coadd = io.read(coaddfile)
assert len(coadd) == 1
coadd = coadd[0]
sourcefiles = coadd.meta['SOURCESPECS']
sourcespecs = io.read(sourcefiles)
for spec in sourcespecs:
specstep(spec)
specstep(coadd, lw=2.0, c='k', alpha=0.5)
plt.title(path.basename(coadd.meta['FILENAME']))
def read_body(io, expected_size):
"""
Read a (malformed) HTTP body.
Returns:
A (body: bytes, is_malformed: bool) tuple.
"""
body_start = io.tell()
try:
content = b"".join(http1.read_body(io, expected_size, None))
if io.read(): # leftover?
raise HttpException()
return content, False
except HttpException:
io.seek(body_start)
return io.read(), True
def compareEUV(star):
euvfile = db.findfiles('u', 'euv', star, fullpaths=True)[0]
w, f, _ = np.loadtxt(euvfile).T
I0 = np.trapz(f, w)
print 'Trapz from Allison\'s file: %g' % I0
spec = io.read(euvfile)[0]
I1 = np.sum((spec['w1'] - spec['w0']) * spec['flux'])
print 'Direct integration from spectbl version of Allison\'s file: %g' % I1
I2 = np.trapz(spec['flux'], (spec['w0'] + spec['w1']) / 2.0)
print 'Trapz from spectbl version of Allison\'s file: %g' % I2
p = io.read(db.panpath(star))[0]
keep = p['instrument'] == rc.getinsti('mod_euv_young')
p = p[keep]
I3 = np.sum((spec['w1'] - spec['w0']) * spec['flux'])
print 'Direct integration from panspec EUV portion: %g' % I3
def comparespecs(stars, **kwargs):
"""
Parameters
----------
binfunc : function or 'all', optional
Function for regriding spectbls (such as evenbin or powerbin from
reduce). Default is powerbin from 1000 to 5000 AA with R=500.0
Set to 'all' to use the entire spectrum.
axkw
"""
if 'binfunc' in kwargs:
binfunc = kwargs['binfunc']
del kwargs['binfunc']
else:
binfunc = lambda s: utils.powerbin(s, R=5000.0, lo=1100.0, hi=5000.0)
plts = []
for star in stars:
# read in panspectrum
specfile = db.panpath(star)
spec = io.read(specfile)[0]
# interpolate it onto the desired bins
if binfunc != 'all':
spec = binfunc(spec)
# plot
plts.append(normspec(spec, **kwargs))
plt.legend(plts, stars)
def vis_data(request):
global custom_data
data = {
'crystal_data':
"""Cr Te O
1.0
7.016000 0.000000 0.000000
0.000000 7.545000 0.000000
-1.637391 0.000000 9.589209
Cr O Te
4 22 8
direct
0.319200 0.501900 0.384200
0.680800 0.001900 0.115800
0.680800 0.498100 0.615800
0.319200 0.998100 0.884200
0.205000 0.644000 0.212100
0.795000 0.144000 0.287900
0.795000 0.356000 0.787900
0.205000 0.856000 0.712100
0.500000 0.000000 0.500000
0.500000 0.500000 0.000000
0.127000 0.314000 0.342900
0.873000 0.814000 0.157100
0.873000 0.686000 0.657100
0.127000 0.186000 0.842900
0.468000 0.375000 0.262300
0.532000 0.875000 0.237700
0.532000 0.625000 0.737700
0.468000 0.125000 0.762300
0.563000 0.641000 0.451700
0.437000 0.141000 0.048300
0.437000 0.359000 0.548300
0.563000 0.859000 0.951700
0.158000 0.649000 0.486600
0.842000 0.149000 0.013400
0.842000 0.351000 0.513400
0.158000 0.851000 0.986600
0.139700 0.859900 0.176200
0.860300 0.359900 0.323800
0.860300 0.140100 0.823800
0.139700 0.640100 0.676200
0.672300 0.861800 0.415800
0.327700 0.361800 0.084200
0.327700 0.138200 0.584200
0.672300 0.638200 0.915800"""
}
p = request.POST
if request.method == 'POST':
custom_data = p.get('crystal_data', '')
data['crystal_data'] = custom_data
f = io.StringIO()
f.write(custom_data)
s = io.read(f)
#s.symmetrize()
data['structure'] = s
data.update(csrf(request))
custom_data = data['crystal_data']
return render_to_response('analysis/view_data.html', get_globals(data),
RequestContext(request))
def test_faster_export(self):
# generate 3k users
start = time.time()
user_count = User.objects.count()
User.objects.bulk_create([User(
username='******' % i) for i in range(3000)])
# print('created 3k users in %.1f seconds' % (time.time() - start))
self.assertEqual(User.objects.count(), 3000 + user_count)
start = time.time()
with user_grant_permission(self.user, [
'auth.change_user', 'auth.adminactions_export_user']):
res = self.app.get('/', user='******')
res = res.click('Users')
form = res.forms['changelist-form']
form['action'] = self.action_name
form['select_across'] = 1
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res = res.form.submit('apply')
res_time = (time.time() - start)
# print('Response returned in %.1f seconds' % res_time)
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read())
sheet = w.sheet_by_index(0)
self.assertEqual(sheet.nrows, 3000 + user_count + 1)
self.assertLessEqual(res_time, 6.5, "Response should return under 6.5 "
"seconds, was %.2f" % res_time)
def blackbody_fit(star):
"""Return a function that is a blackbody fit to the phoenix spectrum for the star. The fit is to the unnormalized
phoenix spectrum, so the fit function values must be multiplied by the appropriate normalization factor to match
the normalized spectrum."""
phx = io.read(db.findfiles('ir', 'phx', star))[0]
# recursively identify relative maxima until there are fewer than N points
N = 10000
keep = np.arange(len(phx))
while len(keep) > N:
temp, = argrelmax(phx['flux'][keep])
keep = keep[temp]
Teff = rc.starprops['Teff_muscles'][star]
efac = const.h * const.c / const.k_B / (Teff * u.K)
efac = efac.to(u.angstrom).value
w = (phx['w0'] + phx['w1']) / 2.0
w = w[keep]
planck_shape = 1.0 / w**5 / (np.exp(efac / w) - 1)
y = phx['flux'][keep]
Sfy = np.sum(planck_shape * y)
Sff = np.sum(planck_shape**2)
norm = Sfy / Sff
return lambda w: norm / w**5 / (np.exp(efac / w) - 1)
def parse(cls, raw):
altered = raw
comment = ""
if altered.startswith("HTTP response [") or altered.startswith(
"HTTP redirect ["):
io = io.StringIO(raw)
first_line = io.readline()
parts = cls.extract_status.search(first_line)
status_line = "HTTP/1.0 %s %s" % (parts.group(1), parts.group(2))
remain = io.read()
altered = status_line + "\r\n" + remain
comment = first_line
response = http.client.HTTPResponse(FakeSocket(altered))
response.begin()
try:
content = response.read(-1)
except http.client.IncompleteRead:
content = raw[raw.find("\r\n\r\n") + 4:].rstrip("\r\n")
return cls(
httpVersion="HTTP/1.1" if response.version == 11 else "HTTP/1.0",
status=response.status,
statusText=response.reason,
headers=response.msg,
content=content,
comment=comment,
raw=raw)
def initialize_phase(config, timepoint):
image_list, image_idx = kchip_io.list_images(
config['image']['base_path'], config['image']['names'][timepoint])
phase_df = []
for xy in image_idx:
print 'Now analyzing: ', xy[0], ',', xy[1]
t = kchip_io.read(config, x=xy[0], y=xy[1], t=timepoint, number=5)
gfp, dyes, phase = split_channels(config, t)
mask = dye_mask(config, dyes) * phase_mask(config, phase)
phase_signal = range_filter(phase_high_pass(config, phase))
phase_props = regionprops(mask, phase_signal)
gfp_props = regionprops(mask, gfp)
one = np.asarray([p['centroid'] for p in phase_props])
two = np.asarray([p['mean_intensity']
for p in phase_props])[:, np.newaxis]
three = np.asarray([p['mean_intensity']
for p in gfp_props])[:, np.newaxis]
data = np.hstack((one, two, three))
phase_df_ = pd.DataFrame(data=data,
columns=['ImageX', 'ImageY', 'pGFP', 'Phase'])
phase_df_['IndexX'] = xy[0]
phase_df_['IndexY'] = xy[1]
phase_df.append(phase_df_)
phase_df = pd.concat(phase_df)
phase_df.reset_index(inplace=True, drop=True)
return phase_df
def find_coaddfile(specfiles):
"""
Look for a file that is the coaddition of the provided spectlbs.
Returns the filename if it exists and it contains data from all of the
provided spectbls, otherwise returns none.
"""
# check for multiple configurations
insts = np.array(map(parse_instrument, specfiles))
if any(insts[:-1] != insts[:-1]):
return NotImplemented("...can't deal with different data sources.")
coaddfile = coaddpath(specfiles[0])
if os.path.isfile(coaddfile):
coadd, = io.read(coaddfile)
# check that the coadd contains the same data as the spectbls
# return none if any is missing
csourcespecs = coadd.meta['SOURCESPECS']
for sf in specfiles:
if parse_name(sf) not in csourcespecs:
return None
return coaddfile
# if the file doesn't exist, return None
else:
return None
def test_issue_93(self):
# default date(time) format in XLS export doesn't import well on excel
with user_grant_permission(
self.user,
['demo.change_demomodel', 'demo.adminactions_export_demomodel']):
res = self.app.get('/', user='******')
res = res.click('Demo models')
form = res.forms['changelist-form']
form['action'] = self.action_name
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res.form['columns'] = [
'date',
]
res = res.form.submit('apply')
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read(),
formatting_info=True)
sheet = w.sheet_by_index(0)
cell = sheet.cell(1, 1)
fmt = w.xf_list[cell.xf_index]
format_key = fmt.format_key
format = w.format_map[format_key] # gets a Format object
self.assertEqual(cell.value, 41303.0)
self.assertEqual(cell.ctype, 3)
self.assertEqual(format.format_str, u'd/m/Y')
def test_use_display_ko(self):
with user_grant_permission(self.user, ['demo.change_demomodel', 'demo.adminactions_export_demomodel']):
res = self.app.get('/', user='******')
res = res.click('Demo models')
form = res.forms['changelist-form']
form['action'] = self.action_name
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res.form['columns'] = ['char', 'text', 'bigint', 'choices'
'']
res = res.form.submit('apply')
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read())
sheet = w.sheet_by_index(0)
self.assertEquals(sheet.cell_value(0, 1), u'Chäř')
self.assertEquals(sheet.cell_value(0, 2), u'bigint')
self.assertEquals(sheet.cell_value(0, 3), u'text')
self.assertEquals(sheet.cell_value(0, 4), u'choices')
self.assertEquals(sheet.cell_value(1, 1), u'Pizzä ïs Gööd')
self.assertEquals(sheet.cell_value(1, 2), 333333333.0)
self.assertEquals(sheet.cell_value(1, 3), u'lorem ipsum')
self.assertEquals(sheet.cell_value(1, 4), 2.0)
def phxFit(star='gj832', ax=None):
if ax is None: ax = plt.gca()
ax.autoscale(axis='x', tight=True)
ax.set_yscale('log')
pan = io.readpan(star)
bolo = utils.bolo_integral(star)
xf = db.findfiles('ir', 'phx', star, fullpaths=True)
phx = io.read(xf)[0]
phx['flux'] *= pan['normfac'][-1]
pan = pan[pan['instrument'] != pan['instrument'][-1]]
fmin = np.min(pan['error'][pan['error'] > 0]) / bolo
rng = [phx['w0'][0], 6000.]
phx, pan = [
utils.keepranges(spec, rng, ends='loose') for spec in [phx, pan]
]
phx, pan = [utils.fancyBin(s, mindw=10.0) for s in [phx, pan]]
pan['flux'][pan['flux'] < pan['error'] / 2.0] = np.nan
pan['normflux'] = pan['flux'] / bolo
phx['normflux'] = phx['flux'] / bolo
ymax = 10**np.ceil(np.log10(np.max(phx['normflux'])))
ymin = 10**np.floor(np.log10(fmin) - 3)
ax.set_ylim(ymin, ymax)
pline = plot.specstep(pan, ax=ax, color='k', err=False, key='normflux')
xline = plot.specstep(phx, ax=ax, color='gray', err=False, key='normflux')
ax.legend((pline, xline), ('$HST$ Data', 'PHOENIX Model'),
loc='lower right')
def test_success(self):
with user_grant_permission(self.user, ['auth.change_user', 'auth.adminactions_export_user']):
res = self.app.get('/', user='******')
res = res.click('Users')
form = res.forms['changelist-form']
form['action'] = self.action_name
# form.set('_selected_action', True, 0)
# form.set('_selected_action', True, 1)
# form.set('_selected_action', True, 2)
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res.form['columns'] = ['id', 'username', 'first_name'
'']
res = res.form.submit('apply')
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read())
sheet = w.sheet_by_index(0)
self.assertEquals(sheet.cell_value(0, 0), u'#')
self.assertEquals(sheet.cell_value(0, 1), u'ID')
self.assertEquals(sheet.cell_value(0, 2), u'username')
self.assertEquals(sheet.cell_value(0, 3), u'first name')
self.assertEquals(sheet.cell_value(1, 1), 1.0)
self.assertEquals(sheet.cell_value(1, 2), u'sax')
self.assertEquals(sheet.cell_value(2, 2), u'user')
def test_use_display_ko(self):
with user_grant_permission(
self.user,
['demo.change_demomodel', 'demo.adminactions_export_demomodel']):
res = self.app.get('/', user='******')
res = res.click('Demo models')
form = res.forms['changelist-form']
form['action'] = self.action_name
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res.form['columns'] = ['char', 'text', 'bigint', 'choices' '']
res = res.form.submit('apply')
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read())
sheet = w.sheet_by_index(0)
self.assertEquals(sheet.cell_value(0, 1), u'Chäř')
self.assertEquals(sheet.cell_value(0, 2), u'bigint')
self.assertEquals(sheet.cell_value(0, 3), u'text')
self.assertEquals(sheet.cell_value(0, 4), u'choices')
self.assertEquals(sheet.cell_value(1, 1), u'Pizzä ïs Gööd')
self.assertEquals(sheet.cell_value(1, 2), 333333333.0)
self.assertEquals(sheet.cell_value(1, 3), u'lorem ipsum')
self.assertEquals(sheet.cell_value(1, 4), 2.0)
def upload_chunks(io, path, options, upload=None, etags=None):
if not etags:
etags = []
bytes_written = 0
while True:
headers = {
"part": 1
} if not upload else {
"ref": upload.ref,
"part": upload.part_number + 1
}
upload = file_action.begin_upload(path, headers, options)[0]
buf = io.read(upload.partsize)
if buf == b'' or buf == "": # Empty bytearray means EOF for BytesIO, Empty String means EOF for StringIO
return (upload, etags, bytes_written)
if buf is not None: # None means no data but io still open
bytes_written += len(buf)
response = Api.api_client().send_remote_request(
upload.http_method, upload.upload_uri,
{"Content-Length": str(len(buf))}, buf)
if "ETag" in response.headers:
etags.append({
"etag": response.headers["ETag"].strip('"'),
"part": upload.part_number
})
def test_success(self):
with user_grant_permission(
self.user,
['auth.change_user', 'auth.adminactions_export_user']):
res = self.app.get('/', user='******')
res = res.click('Users')
form = res.forms['changelist-form']
form['action'] = self.action_name
# form.set('_selected_action', True, 0)
# form.set('_selected_action', True, 1)
# form.set('_selected_action', True, 2)
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res.form['columns'] = ['id', 'username', 'first_name' '']
res = res.form.submit('apply')
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read())
sheet = w.sheet_by_index(0)
self.assertEquals(sheet.cell_value(0, 0), u'#')
self.assertEquals(sheet.cell_value(0, 1), u'ID')
self.assertEquals(sheet.cell_value(0, 2), u'username')
self.assertEquals(sheet.cell_value(0, 3), u'first name')
self.assertEquals(sheet.cell_value(1, 1), 1.0)
self.assertEquals(sheet.cell_value(1, 2), u'sax')
self.assertEquals(sheet.cell_value(2, 2), u'user')
def initialize_post_wells(config, timepoint):
''' Identify wells in post-merge timepoint. Returns post_wells dataFrame.
Inputs:
- config, the config dictionary
- timepoint, the name of the timepoint to analyze (e.g. t0, t1, t2 ...) (should correspond to name in config file)
Outputs:
- post_wells, dataFrame'''
image_list, image_idx = kchip_io.list_images(
config['image']['base_path'], config['image']['names'][timepoint])
post_wells = []
for xy in image_idx:
print 'Now analyzing: ' + str(xy[0]) + ',' + str(xy[1])
# Read in image
post_img = kchip_io.read(config, x=xy[0], y=xy[1], t=timepoint)
post_wells_ = drop.post_img_to_wells(config, post_img)
post_wells_.insert(0, 'IndexY', xy[1])
post_wells_.insert(0, 'IndexX', xy[0])
post_wells.append(post_wells_)
post_wells = pd.concat(post_wells)
post_wells.reset_index(inplace=True, drop=True)
return post_wells
def test_issue_93(self):
# default date(time) format in XLS export doesn't import well on excel
with user_grant_permission(self.user, ['demo.change_demomodel',
'demo.adminactions_export_demomodel']):
res = self.app.get('/', user='******')
res = res.click('Demo models')
form = res.forms['changelist-form']
form['action'] = self.action_name
self._select_rows(form)
res = form.submit()
res.form['header'] = 1
res.form['columns'] = ['date', ]
res = res.form.submit('apply')
io = six.BytesIO(res.body)
io.seek(0)
w = xlrd.open_workbook(file_contents=io.read(), formatting_info=True)
sheet = w.sheet_by_index(0)
cell = sheet.cell(1, 1)
fmt = w.xf_list[cell.xf_index]
format_key = fmt.format_key
format = w.format_map[format_key] # gets a Format object
self.assertEqual(cell.value, 41303.0)
self.assertEqual(cell.ctype, 3)
self.assertEqual(format.format_str, u'd/m/Y')
def plotspec(version, ax):
f, = db.findfiles(rc.hlsppath, star, 'broadband', version, res)
spec, = io.read(f)
spec = utils.keepranges(spec, 0, maxw)
spec = utils.evenbin(spec, binto)
plt.axes(ax)
piecespec(spec)
plt.text(0.05, 0.9, version, transform=ax.transAxes)
def execute(operator, operand, acc):
"""Execute a single instruction, and return new desired accumulator result"""
global program_counter, z_flag, p_flag, memory, halt_flag
if operator == instruction.HLT: # 0xx
if operand == 0: # HLT 00 is actually HLT
halt_flag = True
elif operator == instruction.ADD: # 1xx
acc += memory[operand]
acc = truncate(acc)
elif operator == instruction.SUB: # 2xx
acc -= memory[operand]
acc = truncate(acc)
elif operator == instruction.STA: # 3xx
memory[operand] = acc
##trace("m[" + str(operand) + "]=" + str(acc))
elif operator == instruction.LDA: # 5xx
acc = memory[operand]
##trace("a=m[" + str(operand) + "]")
elif operator == instruction.BRA: # 6xx
program_counter = operand
elif operator == instruction.BRZ: # 7xx
if z_flag:
program_counter = operand
elif operator == instruction.BRP: # 8xx
if p_flag:
program_counter = operand
elif operator == instruction.IO: # 9xx
if operand == instruction.getOperand(instruction.INP): # 901
if not STDIN_REDIRECTED:
sys.stdout.write("in? ")
value = io.read()
#TODO: should we cope with negative numbers here and complement appropriately?
#TODO: Should honour buswidth here depending on decimal/binary/hexadecimal io mode
if value < 0 or value > 999:
raise ValueError("Out of range value:" + str(value))
acc = truncate(value)
elif operand == instruction.getOperand(instruction.OUT): # 902
if not STDOUT_REDIRECTED:
sys.stdout.write("out=")
io.write(acc)
else: # unhandled operator
raise ValueError("Unknown operator:" + str(operator))
update_flags(acc)
return acc
def execute(operator, operand, acc):
"""Execute a single instruction, and return new desired accumulator result"""
global program_counter, z_flag, p_flag, memory, halt_flag
if operator == instruction.HLT: # 0xx
if operand == 0: # HLT 00 is actually HLT
halt_flag = True
elif operator == instruction.ADD: # 1xx
acc += memory[operand]
acc = truncate(acc)
elif operator == instruction.SUB: # 2xx
acc -= memory[operand]
acc = truncate(acc)
elif operator == instruction.STA: # 3xx
memory[operand] = acc
##trace("m[" + str(operand) + "]=" + str(acc))
elif operator == instruction.LDA: # 5xx
acc = memory[operand]
##trace("a=m[" + str(operand) + "]")
elif operator == instruction.BRA: # 6xx
program_counter = operand
elif operator == instruction.BRZ: # 7xx
if z_flag:
program_counter = operand
elif operator == instruction.BRP: # 8xx
if p_flag:
program_counter = operand
elif operator == instruction.IO: # 9xx
if operand == instruction.getOperand(instruction.INP): # 901
if not STDIN_REDIRECTED:
sys.stdout.write("in? ")
value = io.read()
#TODO: should we cope with negative numbers here and complement appropriately?
#TODO: Should honour buswidth here depending on decimal/binary/hexadecimal io mode
if value < 0 or value > 999:
raise ValueError("Out of range value:" + str(value))
acc = truncate(value)
elif operand == instruction.getOperand(instruction.OUT): # 902
if not STDOUT_REDIRECTED:
sys.stdout.write("out=")
io.write(acc)
else: # unhandled operator
raise ValueError("Unknown operator:" + str(operator))
update_flags(acc)
return acc
def plotnorm(spec_or_star, ax=plt.gca(), clip=1e-10):
if type(spec_or_star) is str:
spec = io.read(db.Rpanpath(spec_or_star, 10000))[0]
else:
spec = spec_or_star
spec = utils.add_normflux(spec)
bad = spec['normflux'] < 1e-10
spec['normflux'][bad] = np.nan
plot.specstep(spec, ax=ax)
def scan(id):
vision = get_vision_client()
datastore_image= read(id)
content = io.read(datastore_image)
image = types.Image(content=content)
response = vision.text_detection(image= image)
texts = response.text_annotations
for text in texts:
return ('\n"{}"'.format(text.description))
def vetpanspec(pan_or_star, constant_dw=None, redlim=8000.0):
"""Plot unnormalized components of the panspec with the panspec to see that
all choices were good. Phoenix spectrum is excluded because it is too big."""
if type(pan_or_star) is str:
star = pan_or_star
panspec = io.read(db.panpath(star))[0]
else:
panspec = pan_or_star
star = panspec.meta['STAR']
files = db.panfiles(star)[0]
panspec = utils.keepranges(panspec, 0.0, redlim)
if constant_dw is None:
plotfun = specstep
else:
panspec = utils.evenbin(panspec, constant_dw)
wbins = utils.wbins(panspec)
def plotfun(spec, **kwargs):
s = utils.rebin(spec, wbins)
return specstep(s, **kwargs)
for f in files:
if 'phx' in f: continue
specs = io.read(f)
for spec in specs:
p = plotfun(spec, err=True)[0]
x = (spec['w0'][0] + spec['w0'][-1]) / 2.0
y = np.mean(spec['flux'])
inst = db.parse_instrument(spec.meta['NAME'])
plt.text(x,
y,
inst,
bbox={
'facecolor': 'w',
'alpha': 0.5,
'color': p.get_color()
},
ha='center',
va='center')
plotfun(panspec, color='k', alpha=0.5)
ymax = np.max(utils.keepranges(panspec, 3000.0, 8000.0)['flux'])
plt.gca().set_ylim(-0.01 * ymax, 1.05 * ymax)
plt.draw()
def initialize_droplets(config):
'''Initialize the droplets DataFrame by finding droplets in all images.
Inputs:
- config, the config dictionary created from config
Outputs:
- droplets (DataFrame), with Image index and position, and RGB data
'''
# Determine image list
image_list, image_idx = kchip_io.list_images(
config['image']['base_path'], config['image']['names']['premerge'])
# initialize list of droplets dataframes from each image
droplets = []
# initialize average f_img, which later averages all the fourier transforms
# to detect the rotation
f_img = 0
for xy in image_idx:
print 'Creating droplets from: ' + str(xy[0]) + ',' + str(xy[1])
# Read in image
img = kchip_io.read(config, x=xy[0], y=xy[1], t='premerge')
# Locate droplets and store in temporary dataframe, then append to list of dataframes
droplets_ = drop.find_droplets(img.sum(axis=2))
droplets_.insert(0, 'IndexY', xy[1])
droplets_.insert(0, 'IndexX', xy[0])
# Pull out the RGB value for each droplet and store in dataframe
# Compute local average
dyes = drop.local_average(img[:, :, config['image']['dyes']])
to_add = pd.DataFrame(dyes[droplets_['ImageY'], droplets_['ImageX']])
# Fix a bug where if there is only 1 droplet detected it is wrong orientaiton
if to_add.shape[1] != 3:
to_add = to_add.T
droplets_[['R', 'G', 'B']] = to_add
# append dataframe
droplets.append(droplets_)
# fft the image, clip, and store update average
f_img += matchmask.clip_image(matchmask.fft(
img.mean(axis=2))).astype('float') / len(image_idx)
# Concatenate all the droplets_ dataframes
droplets = pd.concat(droplets).reset_index(drop=True)
# Correct the rotation
droplets, rotation_theta = apply_rotation(droplets, f_img)
return droplets, rotation_theta
def register(config,img_tuple,t='premerge',t2='t0'):
'''Register a translation between a given pre- and post-merge image tuple
Inputs:
- config, the config file dictionary
- img_tuple: a tuple of image pathnames for pre- and post-merge images
- t: the pre-merge timepoint name
- t2: the post-merge timepoint name
Returns:
- shift, a 1 x 2 numpy array to be "translated/subtracted" from coordinates in the second image in tuple
'''
# Read images
pre_img = kchip_io.read(config, x=img_tuple[0],y=img_tuple[1],t=t)
post_img = kchip_io.read(config, x=img_tuple[0],y=img_tuple[1],t=t2)
slices = np.delete(np.arange(pre_img.shape[2]),config['image']['bugs'])
shift,error,diffphase = register_translation(pre_img[:,:,slices], post_img[:,:,slices])
return shift[:-1]
def cyclespec(files):
plt.ioff()
for f in files:
specs = io.read(f)
for spec in specs:
specstep(spec)
plt.title(path.basename(f))
plt.xlabel('Wavelength [$\AA$]')
plt.ylabel('Flux [erg/s/cm$^2$/$\AA$]')
plt.show()
plt.ion()
def phx_norm_compare():
oldfile_template = '/Users/rolo7566/Datasets/MUSCLES/products/archive/panspecs v10/p_msl_pan_-----_{}_panspec_native_resolution.fits'
for star in mlstars:
op, = io.read(oldfile_template.format(star))
ofac = op['normfac'][-1]
p = io.readpan(star)
fac = p['normfac'][-1]
chng = abs(fac / ofac - 1) * 100.
name = rc.starprops['name txt'][star]
print '{:8s} | {:6.1f}'.format(name, chng)
def stackpans(range=[1310, 1350],
keeprange=[1100, 2000],
xlim=None,
norm=True,
offfac=1.0):
if xlim is None: xlim = keeprange
pans = []
for star in rc.observed:
p = io.read(db.panpath(star))[0]
pans.append(utils.keepranges(p, *keeprange))
stackspecs(pans, range, norm=norm, offfac=offfac, xlim=xlim)
def test_utf8_writer(self):
writer = converters.getwriter('utf-8')
io = writer(self.io)
io.write(self.u_japanese + '\n')
io.seek(0)
result = io.read().strip()
tools.eq_(result, self.utf8_japanese)
io.seek(0)
io.truncate(0)
io.write(self.euc_jp_japanese + b'\n')
io.seek(0)
result = io.read().strip()
tools.eq_(result, self.euc_jp_japanese)
io.seek(0)
io.truncate(0)
io.write(self.utf8_japanese + b'\n')
io.seek(0)
result = io.read().strip()
tools.eq_(result, self.utf8_japanese)
def test_utf8_writer(self):
writer = converters.getwriter('utf-8')
io = writer(self.io)
io.write(self.u_japanese + '\n')
io.seek(0)
result = io.read().strip()
tools.eq_(result, self.utf8_japanese)
io.seek(0)
io.truncate(0)
io.write(self.euc_jp_japanese + b'\n')
io.seek(0)
result = io.read().strip()
tools.eq_(result, self.euc_jp_japanese)
io.seek(0)
io.truncate(0)
io.write(self.utf8_japanese + b'\n')
io.seek(0)
result = io.read().strip()
tools.eq_(result, self.utf8_japanese)
def load(filename, memory, startaddr=0):
"""Load from a file into memory"""
f = open(filename, "rt")
addr = startaddr
while True:
instr = io.read(file=f)
if instr != None:
memory[addr] = instr
addr += 1
else:
break
f.close()
