def save(self, fn):
d = dict(orders=self.orders, wvl_list=[], x_list=[], y_list=[])
for o in self.orders:
zd = self.zdata[o]
d["wvl_list"].append(zd.wvl)
d["x_list"].append(zd.x)
d["y_list"].append(zd.y)
from json_helper import json_dump
json_dump(d, open(fn, "w"))
def save(self, fn):
d = dict(orders=self.orders,
wvl_list=[],
x_list=[],
y_list=[])
for o in self.orders:
zd = self.zdata[o]
d["wvl_list"].append(zd.wvl)
d["x_list"].append(zd.x)
d["y_list"].append(zd.y)
from json_helper import json_dump
json_dump(d, open(fn, "w"))
def save(self, mastername, masterhdu=None):
fn, ext = os.path.splitext(mastername)
dict_to_save = dict()
for k, d in self.items():
if hasattr(d, "shape") and (d.shape == masterhdu.data.shape):
if d.dtype == bool:
d = d.astype("i8")
if masterhdu is not None:
hdu = pyfits.PrimaryHDU(header=masterhdu.header, data=d)
else:
hdu = pyfits.PrimaryHDU(data=d)
fn0 = "".join([fn, ".", k, ".fits"])
hdu.writeto(fn0, clobber=True)
dict_to_save[k + ".fits"] = os.path.basename(fn0)
else:
dict_to_save[k] = d
if dict_to_save:
json_dump(dict_to_save, open(mastername, "w"))
def save(self, mastername, masterhdu=None):
fn, ext = os.path.splitext(mastername)
dict_to_save = dict()
for k, d in self.items():
if hasattr(d, "shape") and (d.shape == masterhdu.data.shape):
if d.dtype == bool:
d = d.astype("i8")
if masterhdu is not None:
hdu = pyfits.PrimaryHDU(header=masterhdu.header,
data=d)
else:
hdu = pyfits.PrimaryHDU(data=d)
fn0 = "".join([fn, ".", k, ".fits"])
hdu.writeto(fn0, clobber=True)
dict_to_save[k+".fits"] = os.path.basename(fn0)
else:
dict_to_save[k] = d
if dict_to_save:
json_dump(dict_to_save, open(mastername, "w"))
d = dict(wvl_list=[],
ref_indices_list=[],
pixpos_list=[],
orders=orders,
ref_name=ref_name)
for wvl, s, _ in zip(wvl_sol, s_list, ddd_list):
wvl_reference_filtered, matched_indices, centroids = _
d["wvl_list"].append(wvl_reference_filtered)
d["ref_indices_list"].append(matched_indices)
d["pixpos_list"].append(centroids)
from json_helper import json_dump
json_dump(
d,
open("%s_IGRINS_identified_%s_%s.json" % (REF_TYPE, band, utdate),
"w"))
for wvl, s, _ in zip(wvl_sol, s_list, ddd_list):
wvl_reference_filtered, matched_indices, centroids = _
fig = figure()
ax = fig.add_subplot(111)
draw_one(wvl, s, wvl_reference_filtered, centroids, ax=ax)
if 0:
json.dump([[(s[0], list(s[1])) for s in ss] for ss, d in matched_list2],
open("thar_identified_%s_%s.json" % (band, date), "w"))
i = 20
clf()
if 1:
band = "K"
utdate = "20140525"
import json
s_list = json.load(open("arc_spec_sky_%s_%s.json" % (band, utdate)))
wvl_sol = json.load(open("wvl_sol_phase0_%s_%s.json" \
% (band, utdate)))
bootstrap_name = "hitran_bootstrap_K_20140316.json"
bootstrap = json.load(open(bootstrap_name))
sol_sol = reidentify(wvl_sol, s_list, bootstrap)
from json_helper import json_dump
if 1:
json_dump(sol_sol,
open("hitran_reidentified_%s_%s.json" % (band, utdate),
"w"),
)
if 0:
if 0:
import matplotlib.pyplot as plt
plt.clf()
ax = plt.subplot(311)
ax.plot(wvl_igr, s_igr_m)
ax.plot(wvl1, ss)
for ll, sol in zip(hitrans_detected[i], sol_list):
xx = sol[0][0]+np.array(ll)-ll[0]
ax.vlines(xx, ymin=0, ymax=sol[0][2])
ax.hlines(sol[0][2]*0.5,
def store(self, fn, masterhdu):
json_dump(self, open(fn, "w"))
def store(self, fn, masterhdu=None):
json_dump(self, open(fn, "w"))
if 1:
band = "K"
utdate = "20140525"
import json
s_list = json.load(open("arc_spec_sky_%s_%s.json" % (band, utdate)))
wvl_sol = json.load(open("wvl_sol_phase0_%s_%s.json" \
% (band, utdate)))
bootstrap_name = "hitran_bootstrap_K_20140316.json"
bootstrap = json.load(open(bootstrap_name))
sol_sol = reidentify(wvl_sol, s_list, bootstrap)
from json_helper import json_dump
if 1:
json_dump(
sol_sol,
open("hitran_reidentified_%s_%s.json" % (band, utdate), "w"),
)
if 0:
if 0:
import matplotlib.pyplot as plt
plt.clf()
ax = plt.subplot(311)
ax.plot(wvl_igr, s_igr_m)
ax.plot(wvl1, ss)
for ll, sol in zip(hitrans_detected[i], sol_list):
xx = sol[0][0] + np.array(ll) - ll[0]
ax.vlines(xx, ymin=0, ymax=sol[0][2])
ax.hlines(sol[0][2] * 0.5,
xmin=xx - sol[0][1],
_ = ddd(wvl, s, wvl_reference)
ddd_list.append(_)
d = dict(wvl_list=[], ref_indices_list=[], pixpos_list=[],
orders=orders,
ref_name=ref_name)
for wvl, s, _ in zip(wvl_sol, s_list, ddd_list):
wvl_reference_filtered, matched_indices, centroids = _
d["wvl_list"].append(wvl_reference_filtered)
d["ref_indices_list"].append(matched_indices)
d["pixpos_list"].append(centroids)
from json_helper import json_dump
json_dump(d, open("%s_IGRINS_identified_%s_%s.json" % (REF_TYPE, band, utdate),"w"))
for wvl, s, _ in zip(wvl_sol, s_list, ddd_list):
wvl_reference_filtered, matched_indices, centroids = _
fig = figure()
ax = fig.add_subplot(111)
draw_one(wvl, s, wvl_reference_filtered, centroids, ax=ax)
if 0:
json.dump([[(s[0], list(s[1])) for s in ss] for ss, d in matched_list2],
open("thar_identified_%s_%s.json" % (band, date),"w"))
def save(self, fn):
from json_helper import json_dump
json_dump(self.data, open(fn, "w"))
def save(self, fn):
from json_helper import json_dump
json_dump(self.data, open(fn,"w"))