In [1]:
import wisps
import splat
import numpy as np
import wisps
import splat
import matplotlib.pyplot as plt
from concurrent.futures import ThreadPoolExecutor, wait , ALL_COMPLETED
from functools import partial
import pandas as pd
In [2]:
def get_object(filename):
sp=wisps.Spectrum(name=filename)
f_test={"f_test": sp.f_test, 'line_chi': sp.line_chi, 'spex_chi': sp.spex_chi,
'spt': sp.spectral_type}
res_dict= {**sp.snr, **sp.indices, **f_test}
return res_dict
def make_data(spectranames, **kwargs):
"""
measure parameters for a bunch of spectra
"""
results=[]
iterables=([spectranames])
method=partial(get_object)
with ThreadPoolExecutor(max_workers=100) as executor:
futures=list(executor.map( method, *iterables, timeout=None, chunksize=10))
results=[x for x in futures]
return pd.DataFrame.from_records(results)
In [3]:
#important=
pred_df=wisps.datasets['stars']
pred_df=pred_df[pred_df.snr2>3.]
In [4]:
d=make_data(pred_df['grism_id'].values[:10])
In [9]:
%prun s=wisps.Spectrum(filename='par321-00019')
921747 function calls (863411 primitive calls) in 1.397 seconds
Ordered by: internal time
ncalls tottime percall cumtime percall filename:lineno(function)
4 0.211 0.053 0.286 0.071 data.py:110(get_readable_fileobj)
32 0.096 0.003 0.926 0.029 indices.py:67(__measure_index)
7708 0.071 0.000 0.567 0.000 function_base.py:3508(_median)
7708 0.065 0.000 0.205 0.000 utils.py:1142(_median_nancheck)
2 0.065 0.033 0.065 0.033 {method 'close' of '_io.FileIO' objects}
7708 0.052 0.000 0.052 0.000 {method 'partition' of 'numpy.ndarray' objects}
9116 0.047 0.000 0.047 0.000 {method 'reduce' of 'numpy.ufunc' objects}
51058/9638 0.041 0.000 0.792 0.000 {built-in method numpy.core._multiarray_umath.implement_array_function}
7600 0.041 0.000 0.041 0.000 {method 'normal' of 'numpy.random.mtrand.RandomState' objects}
7720 0.040 0.000 0.107 0.000 _methods.py:134(_mean)
15416 0.040 0.000 0.059 0.000 numeric.py:1273(normalize_axis_tuple)
7708 0.039 0.000 0.119 0.000 numeric.py:1336(moveaxis)
15404/7708 0.030 0.000 0.717 0.000 function_base.py:3359(_ureduce)
2 0.028 0.014 0.028 0.014 {method 'read' of '_io.TextIOWrapper' objects}
7696 0.024 0.000 0.056 0.000 nanfunctions.py:143(_remove_nan_1d)
31564 0.023 0.000 0.034 0.000 numerictypes.py:293(issubclass_)
50646 0.023 0.000 0.023 0.000 {built-in method numpy.array}
15782 0.021 0.000 0.057 0.000 numerictypes.py:365(issubdtype)
7696 0.018 0.000 0.739 0.000 nanfunctions.py:1023(nanmedian)
7696 0.017 0.000 0.682 0.000 nanfunctions.py:961(_nanmedian1d)
65167 0.016 0.000 0.016 0.000 {built-in method builtins.issubclass}
7716 0.015 0.000 0.122 0.000 fromnumeric.py:3153(mean)
47114 0.015 0.000 0.032 0.000 _asarray.py:88(asanyarray)
7708 0.011 0.000 0.011 0.000 {method 'flatten' of 'numpy.ndarray' objects}
7708 0.011 0.000 0.079 0.000 fromnumeric.py:657(partition)
34046 0.011 0.000 0.011 0.000 {built-in method builtins.isinstance}
7720 0.009 0.000 0.013 0.000 _methods.py:50(_count_reduce_items)
8399/439 0.009 0.000 0.032 0.000 copy.py:132(deepcopy)
2 0.009 0.005 0.009 0.005 {method 'read' of '_io.FileIO' objects}
7708 0.009 0.000 0.598 0.000 function_base.py:3419(median)
7696 0.007 0.000 0.694 0.000 nanfunctions.py:974(_nanmedian)
7696 0.007 0.000 0.754 0.000 <__array_function__ internals>:2(nanmedian)
15416 0.007 0.000 0.013 0.000 numeric.py:1323(<listcomp>)
7714 0.007 0.000 0.007 0.000 {built-in method builtins.sorted}
7716 0.007 0.000 0.137 0.000 <__array_function__ internals>:2(mean)
8458 0.007 0.000 0.018 0.000 fromnumeric.py:55(_wrapfunc)
7966 0.007 0.000 0.033 0.000 <__array_function__ internals>:2(nonzero)
7708 0.007 0.000 0.133 0.000 <__array_function__ internals>:2(moveaxis)
52428/52400 0.007 0.000 0.007 0.000 {built-in method builtins.len}
7966 0.006 0.000 0.006 0.000 {method 'nonzero' of 'numpy.ndarray' objects}
7708 0.006 0.000 0.611 0.000 <__array_function__ internals>:2(median)
7708 0.006 0.000 0.006 0.000 {method 'transpose' of 'numpy.ndarray' objects}
7708 0.006 0.000 0.092 0.000 <__array_function__ internals>:2(partition)
15484 0.006 0.000 0.006 0.000 {built-in method numpy.core._multiarray_umath.normalize_axis_index}
8534 0.006 0.000 0.006 0.000 {method 'ravel' of 'numpy.ndarray' objects}
34914 0.005 0.000 0.005 0.000 {method 'get' of 'dict' objects}
7966 0.005 0.000 0.020 0.000 fromnumeric.py:1759(nonzero)
13755/13659 0.005 0.000 0.007 0.000 {built-in method builtins.getattr}
10316 0.005 0.000 0.005 0.000 {method 'match' of 're.Pattern' objects}
7938 0.004 0.000 0.007 0.000 core.py:6251(isMaskedArray)
9412 0.004 0.000 0.004 0.000 {built-in method builtins.hasattr}
506 0.004 0.000 0.010 0.000 core.py:2085(_expand_and_gather)
7708 0.003 0.000 0.003 0.000 {method 'insert' of 'list' objects}
1152 0.003 0.000 0.011 0.000 fromnumeric.py:73(_wrapreduction)
13733 0.003 0.000 0.003 0.000 {method 'append' of 'list' objects}
64 0.003 0.000 0.019 0.000 _distn_infrastructure.py:1694(pdf)
328/217 0.003 0.000 0.028 0.000 copy.py:236(_deepcopy_dict)
74 0.003 0.000 0.007 0.000 interpolate.py:587(_call_linear)
490 0.003 0.000 0.007 0.000 nanfunctions.py:70(_replace_nan)
2 0.002 0.001 0.002 0.001 {built-in method posix.stat}
15416 0.002 0.000 0.002 0.000 {built-in method _operator.index}
7708 0.002 0.000 0.002 0.000 numeric.py:1399(<listcomp>)
64 0.002 0.000 0.002 0.000 _continuous_distns.py:1677(_logpdf)
230 0.002 0.000 0.003 0.000 interpolate.py:671(_check_bounds)
1212 0.002 0.000 0.008 0.000 quantity.py:535(_new_view)
6 0.002 0.000 0.036 0.006 core.py:306(__init__)
584 0.002 0.000 0.004 0.000 header.py:1161(append)
2748 0.002 0.000 0.002 0.000 quantity.py:394(__array_finalize__)
1152 0.002 0.000 0.002 0.000 fromnumeric.py:74(<dictcomp>)
64 0.002 0.000 0.008 0.000 spectrum_tools.py:468(compute_chi_square)
230 0.002 0.000 0.004 0.000 _util.py:193(_asarray_validated)
632 0.002 0.000 0.005 0.000 copy.py:66(copy)
22 0.002 0.000 0.006 0.000 core.py:713(<listcomp>)
7696 0.002 0.000 0.002 0.000 nanfunctions.py:1018(_nanmedian_dispatcher)
7966 0.002 0.000 0.002 0.000 fromnumeric.py:1755(_nonzero_dispatcher)
7716 0.001 0.000 0.001 0.000 fromnumeric.py:3149(_mean_dispatcher)
230 0.001 0.000 0.014 0.000 interpolate.py:656(_evaluate)
570 0.001 0.000 0.012 0.000 core.py:2010(__init__)
618/15 0.001 0.000 0.026 0.002 copy.py:268(_reconstruct)
5632 0.001 0.000 0.002 0.000 core.py:710(<genexpr>)
7708 0.001 0.000 0.001 0.000 function_base.py:3414(_median_dispatcher)
7708 0.001 0.000 0.001 0.000 fromnumeric.py:653(_partition_dispatcher)
7708 0.001 0.000 0.001 0.000 numeric.py:1332(_moveaxis_dispatcher)
68 0.001 0.000 0.006 0.000 interpolate.py:427(__init__)
36 0.001 0.000 0.001 0.000 {method 'splitlines' of 'str' objects}
1822 0.001 0.000 0.002 0.000 {method 'view' of 'numpy.ndarray' objects}
66 0.001 0.000 0.004 0.000 utilities.py:1315(typeToNum)
70 0.001 0.000 0.008 0.000 _distn_infrastructure.py:545(<listcomp>)
1410 0.001 0.000 0.001 0.000 copy.py:252(_keep_alive)
1294 0.001 0.000 0.002 0.000 core.py:2086(add_unit)
2 0.001 0.001 0.057 0.028 spectrum_tools.py:473(classify)
670/430 0.001 0.000 0.007 0.000 core.py:2132(decompose)
140 0.001 0.000 0.001 0.000 numerictypes.py:578(_can_coerce_all)
822 0.001 0.000 0.001 0.000 {method 'search' of 're.Pattern' objects}
32 0.001 0.000 0.006 0.000 nanfunctions.py:1422(nanvar)
2 0.001 0.000 0.026 0.013 ui.py:334(_guess)
6 0.001 0.000 0.001 0.000 core.py:490(<listcomp>)
11061 0.001 0.000 0.001 0.000 {built-in method builtins.id}
170 0.001 0.000 0.009 0.000 nanfunctions.py:229(nanmin)
370 0.001 0.000 0.002 0.000 {method 'any' of 'numpy.generic' objects}
2 0.001 0.000 0.001 0.000 {method 'read' of 'astropy.io.ascii.cparser.CParser' objects}
6716 0.001 0.000 0.001 0.000 {method 'strip' of 'str' objects}
270 0.001 0.000 0.006 0.000 function_base.py:1628(extract)
12 0.001 0.000 0.001 0.000 utilities.py:449(checkDict)
66 0.001 0.000 0.001 0.000 _distn_infrastructure.py:862(_argcheck)
538 0.001 0.000 0.002 0.000 quantity.py:679(to_value)
152 0.001 0.000 0.002 0.000 _methods.py:63(_clip_dep_is_scalar_nan)
1128 0.001 0.000 0.007 0.000 quantity.py:1032(quantity_iter)
102 0.001 0.000 0.006 0.000 nanfunctions.py:344(nanmax)
66 0.001 0.000 0.004 0.000 tools.py:117(make_spt_number)
116 0.001 0.000 0.005 0.000 quantity.py:423(__array_ufunc__)
230 0.001 0.000 0.020 0.000 polyint.py:62(__call__)
64 0.001 0.000 0.002 0.000 nanfunctions.py:184(_divide_by_count)
12 0.001 0.000 0.015 0.001 equivalencies.py:139(spectral_density)
18 0.001 0.000 0.001 0.000 core.py:64(_normalize_equivalencies)
272/260 0.001 0.000 0.009 0.000 core.py:647(__div__)
74 0.001 0.000 0.001 0.000 {method 'searchsorted' of 'numpy.ndarray' objects}
338 0.001 0.000 0.001 0.000 {method 'take' of 'numpy.ndarray' objects}
538 0.001 0.000 0.002 0.000 {method 'sort' of 'list' objects}
568 0.001 0.000 0.001 0.000 {method 'reshape' of 'numpy.ndarray' objects}
2 0.001 0.000 0.002 0.001 daophot.py:276(process_lines)
66 0.001 0.000 0.001 0.000 utilities.py:49(isNumber)
76 0.001 0.000 0.001 0.000 _methods.py:78(_clip_dep_invoke_with_casting)
276 0.001 0.000 0.001 0.000 {method 'copy' of 'numpy.ndarray' objects}
116 0.001 0.000 0.001 0.000 {function Quantity.__array_ufunc__ at 0x116f2fa60}
1536 0.001 0.000 0.001 0.000 quantity.py:600(_set_unit)
2 0.001 0.000 0.008 0.004 core.py:5453(<listcomp>)
1574 0.001 0.000 0.002 0.000 _asarray.py:16(asarray)
378 0.001 0.000 0.001 0.000 {method '__deepcopy__' of 'numpy.generic' objects}
524 0.001 0.000 0.002 0.000 <__array_function__ internals>:2(copyto)
2 0.001 0.000 0.938 0.469 indices.py:19(measure_indices)
308 0.001 0.000 0.003 0.000 fromnumeric.py:2045(sum)
280 0.001 0.000 0.002 0.000 copy.py:219(_deepcopy_tuple)
116 0.001 0.000 0.002 0.000 converters.py:125(converters_and_unit)
6584 0.001 0.000 0.001 0.000 copy.py:190(_deepcopy_atomic)
154 0.001 0.000 0.001 0.000 {built-in method numpy.arange}
540 0.001 0.000 0.002 0.000 fromnumeric.py:1648(ravel)
660 0.001 0.000 0.002 0.000 core.py:1766(__call__)
70 0.001 0.000 0.010 0.000 _distn_infrastructure.py:520(argsreduce)
156 0.001 0.000 0.001 0.000 {built-in method numpy.core._multiarray_umath.interp}
298/232 0.000 0.000 0.002 0.000 {method 'format' of 'str' objects}
636 0.000 0.000 0.000 0.000 {method 'update' of 'dict' objects}
280 0.000 0.000 0.005 0.000 core.py:2151(is_unity)
1098 0.000 0.000 0.001 0.000 core.py:2120(<lambda>)
2 0.000 0.000 0.029 0.015 core.py:5374(compareSpectra)
68 0.000 0.000 0.000 0.000 {method 'argsort' of 'numpy.ndarray' objects}
230 0.000 0.000 0.004 0.000 polyint.py:88(_prepare_x)
12 0.000 0.000 0.002 0.000 core.py:549(<listcomp>)
618 0.000 0.000 0.000 0.000 {method '__reduce_ex__' of 'object' objects}
156 0.000 0.000 0.002 0.000 function_base.py:1282(interp)
970 0.000 0.000 0.000 0.000 utils.py:251(resolve_fractions)
584 0.000 0.000 0.001 0.000 card.py:568(normalize_keyword)
212 0.000 0.000 0.006 0.000 nanfunctions.py:558(nansum)
348 0.000 0.000 0.004 0.000 fromnumeric.py:2189(any)
218 0.000 0.000 0.001 0.000 re.py:271(_compile)
40 0.000 0.000 0.002 0.000 core.py:1385(_get_reader)
2136 0.000 0.000 0.000 0.000 {method 'items' of 'dict' objects}
70 0.000 0.000 0.001 0.000 shape_base.py:24(atleast_1d)
2 0.000 0.000 0.105 0.053 spectrum_tools.py:438(f_test)
249 0.000 0.000 0.002 0.000 copy.py:210(_deepcopy_list)
68 0.000 0.000 0.001 0.000 interpolate.py:549(fill_value)
308 0.000 0.000 0.004 0.000 <__array_function__ internals>:2(sum)
1684 0.000 0.000 0.000 0.000 core.py:734(__hash__)
86 0.000 0.000 0.004 0.000 core.py:922(_to)
1398 0.000 0.000 0.000 0.000 core.py:1957(__hash__)
1482 0.000 0.000 0.000 0.000 quantity.py:736(unit)
4 0.000 0.000 0.010 0.003 header.py:78(__init__)
540 0.000 0.000 0.003 0.000 <__array_function__ internals>:2(ravel)
2 0.000 0.000 0.001 0.000 core.py:1341(process_lines)
18 0.000 0.000 0.000 0.000 {method 'read_header' of 'astropy.io.ascii.cparser.CParser' objects}
348 0.000 0.000 0.005 0.000 <__array_function__ internals>:2(any)
230 0.000 0.000 0.001 0.000 polyint.py:94(_finish_y)
2 0.000 0.000 0.020 0.010 utilities.py:2135(<listcomp>)
152 0.000 0.000 0.001 0.000 fromnumeric.py:2986(ndim)
76 0.000 0.000 0.003 0.000 _methods.py:97(_clip)
430 0.000 0.000 0.000 0.000 utils.py:197(validate_power)
68 0.000 0.000 0.001 0.000 polyint.py:113(_set_yi)
588 0.000 0.000 0.005 0.000 header.py:827(<genexpr>)
616 0.000 0.000 0.000 0.000 copyreg.py:87(__newobj__)
570 0.000 0.000 0.001 0.000 utils.py:173(sanitize_scale)
40 0.000 0.000 0.001 0.000 quantity.py:272(__new__)
1256 0.000 0.000 0.000 0.000 core.py:1574(name)
128 0.000 0.000 0.001 0.000 _ufunc_config.py:39(seterr)
338 0.000 0.000 0.001 0.000 fromnumeric.py:97(take)
32 0.000 0.000 0.006 0.000 nanfunctions.py:1570(nanstd)
338 0.000 0.000 0.002 0.000 <__array_function__ internals>:2(take)
16 0.000 0.000 0.004 0.000 fastbasic.py:65(read)
506 0.000 0.000 0.000 0.000 core.py:2119(<listcomp>)
2 0.000 0.000 1.393 0.697 spectrum_tools.py:297(filepath)
18 0.000 0.000 0.002 0.000 core.py:849(convert)
18 0.000 0.000 0.001 0.000 equivalencies.py:104(spectral)
156 0.000 0.000 0.002 0.000 interpolate.py:583(_call_linear_np)
128 0.000 0.000 0.000 0.000 _ufunc_config.py:139(geterr)
608 0.000 0.000 0.000 0.000 utils.py:163(is_effectively_unity)
584 0.000 0.000 0.000 0.000 card.py:478(field_specifier)
32 0.000 0.000 0.001 0.000 generic.py:499(_format_unit_list)
498 0.000 0.000 0.002 0.000 _methods.py:44(_any)
270 0.000 0.000 0.007 0.000 <__array_function__ internals>:2(extract)
1168 0.000 0.000 0.000 0.000 card.py:213(keyword)
64 0.000 0.000 0.000 0.000 _distn_infrastructure.py:895(_support_mask)
248 0.000 0.000 0.002 0.000 <__array_function__ internals>:2(all)
92 0.000 0.000 0.004 0.000 core.py:685(__mul__)
212 0.000 0.000 0.006 0.000 <__array_function__ internals>:2(nansum)
150 0.000 0.000 0.000 0.000 {built-in method numpy.zeros}
248 0.000 0.000 0.002 0.000 fromnumeric.py:2277(all)
158 0.000 0.000 0.003 0.000 fromnumeric.py:2629(amin)
280 0.000 0.000 0.002 0.000 copy.py:220(<listcomp>)
128 0.000 0.000 0.000 0.000 {method 'findall' of 're.Pattern' objects}
330/306 0.000 0.000 0.000 0.000 core.py:1951(decompose)
12 0.000 0.000 0.004 0.000 core.py:988(computeSN)
200/140 0.000 0.000 0.000 0.000 column.py:849(__setattr__)
24 0.000 0.000 0.014 0.001 core.py:1131(read)
832 0.000 0.000 0.000 0.000 {method 'find' of 'str' objects}
42 0.000 0.000 0.001 0.000 generic.py:27(_to_string)
776 0.000 0.000 0.000 0.000 core.py:2071(bases)
980 0.000 0.000 0.000 0.000 numerictypes.py:587(<listcomp>)
90 0.000 0.000 0.001 0.000 fromnumeric.py:2504(amax)
168 0.000 0.000 0.001 0.000 core.py:2023(<listcomp>)
68 0.000 0.000 0.001 0.000 polyint.py:105(_reshape_yi)
1564 0.000 0.000 0.000 0.000 {method 'lower' of 'str' objects}
68 0.000 0.000 0.000 0.000 interpolate.py:316(_check_broadcast_up_to)
64 0.000 0.000 0.001 0.000 typeof.py:24(typeof)
4 0.000 0.000 0.001 0.000 _distn_infrastructure.py:1862(sf)
170 0.000 0.000 0.010 0.000 <__array_function__ internals>:2(nanmin)
270 0.000 0.000 0.000 0.000 _collections_abc.py:879(__iter__)
156 0.000 0.000 0.000 0.000 type_check.py:282(iscomplexobj)
28 0.000 0.000 0.001 0.000 core.py:703(__rmul__)
230 0.000 0.000 0.000 0.000 base.py:1189(isspmatrix)
1086 0.000 0.000 0.000 0.000 {method 'startswith' of 'str' objects}
2 0.000 0.000 0.341 0.170 ui.py:204(read)
280 0.000 0.000 0.001 0.000 <frozen importlib._bootstrap>:1009(_handle_fromlist)
4 0.000 0.000 0.003 0.001 core.py:1903(normalize)
24 0.000 0.000 0.000 0.000 core.py:1114(__init__)
158 0.000 0.000 0.003 0.000 <__array_function__ internals>:2(amin)
70 0.000 0.000 0.002 0.000 numerictypes.py:602(find_common_type)
82 0.000 0.000 0.001 0.000 core.py:643(__pow__)
506 0.000 0.000 0.000 0.000 core.py:2122(<listcomp>)
156 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(iscomplexobj)
156 0.000 0.000 0.002 0.000 <__array_function__ internals>:2(interp)
2 0.000 0.000 0.020 0.010 utilities.py:2080(weightedMeanVar)
64 0.000 0.000 0.000 0.000 functools.py:768(dispatch)
64 0.000 0.000 0.002 0.000 _continuous_distns.py:1671(_pdf)
68 0.000 0.000 0.001 0.000 polyint.py:133(_set_dtype)
12 0.000 0.000 0.001 0.000 equivalencies.py:184(converter)
4 0.000 0.000 0.000 0.000 latex.py:53(find_latex_line)
2 0.000 0.000 0.000 0.000 ipac.py:83(process_lines)
102 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(where)
4 0.000 0.000 0.002 0.000 _stats_mstats_common.py:15(linregress)
86 0.000 0.000 0.000 0.000 {method 'astype' of 'numpy.ndarray' objects}
74 0.000 0.000 0.001 0.000 fromnumeric.py:1229(searchsorted)
24 0.000 0.000 0.002 0.000 quantity.py:949(__truediv__)
64 0.000 0.000 0.001 0.000 dispatcher.py:521(typeof_pyval)
506 0.000 0.000 0.000 0.000 core.py:2123(<listcomp>)
128 0.000 0.000 0.000 0.000 <frozen importlib._bootstrap>:416(parent)
2 0.000 0.000 0.000 0.000 ui.py:498(_get_guess_kwargs_list)
754 0.000 0.000 0.000 0.000 {method 'keys' of 'dict' objects}
4 0.000 0.000 0.002 0.001 spectrum_tools.py:421(fit_a_line)
102 0.000 0.000 0.007 0.000 <__array_function__ internals>:2(nanmax)
810 0.000 0.000 0.000 0.000 {method 'groups' of 're.Match' objects}
336 0.000 0.000 0.000 0.000 utilities.py:484(<listcomp>)
124 0.000 0.000 0.000 0.000 {built-in method builtins.any}
1098 0.000 0.000 0.000 0.000 {method 'join' of 'str' objects}
82 0.000 0.000 0.000 0.000 {built-in method numpy.core._multiarray_umath._insert}
4 0.000 0.000 0.001 0.000 function_base.py:2245(cov)
152 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(ndim)
10 0.000 0.000 0.001 0.000 fastbasic.py:275(_read_header)
302 0.000 0.000 0.001 0.000 daophot.py:241(<genexpr>)
16 0.000 0.000 0.001 0.000 fastbasic.py:28(__init__)
4 0.000 0.000 0.000 0.000 latex.py:81(<listcomp>)
90 0.000 0.000 0.002 0.000 <__array_function__ internals>:2(amax)
68 0.000 0.000 0.001 0.000 polyint.py:55(__init__)
686 0.000 0.000 0.000 0.000 {built-in method __new__ of type object at 0x10dd88778}
64 0.000 0.000 0.000 0.000 weakref.py:395(__getitem__)
152 0.000 0.000 0.000 0.000 _methods.py:73(_clip_dep_is_byte_swapped)
22 0.000 0.000 0.008 0.000 quantity.py:651(to)
68 0.000 0.000 0.000 0.000 numeric.py:1211(rollaxis)
26 0.000 0.000 0.000 0.000 core.py:1043(_is_number)
588 0.000 0.000 0.000 0.000 header.py:327(_modified)
32 0.000 0.000 0.000 0.000 fromnumeric.py:3028(size)
152 0.000 0.000 0.000 0.000 core.py:1547(get_format_name)
1 0.000 0.000 1.397 1.397 <string>:1(<module>)
20 0.000 0.000 0.001 0.000 quantity.py:922(__mul__)
55 0.000 0.000 0.000 0.000 {method '__deepcopy__' of 'numpy.ndarray' objects}
128 0.000 0.000 0.001 0.000 re.py:215(findall)
22 0.000 0.000 0.005 0.000 core.py:892(_get_converter)
266 0.000 0.000 0.001 0.000 quantity.py:621(__deepcopy__)
6 0.000 0.000 0.036 0.006 spectrum_tools.py:198(splat_spectrum)
82 0.000 0.000 0.000 0.000 function_base.py:1684(place)
76 0.000 0.000 0.004 0.000 {method 'clip' of 'numpy.ndarray' objects}
2 0.000 0.000 0.000 0.000 shape_base.py:82(atleast_2d)
524 0.000 0.000 0.000 0.000 multiarray.py:1043(copyto)
22 0.000 0.000 0.007 0.000 quantity.py:644(_to_value)
510 0.000 0.000 0.000 0.000 {method 'endswith' of 'str' objects}
64 0.000 0.000 0.000 0.000 functools.py:822(wrapper)
64 0.000 0.000 0.000 0.000 _ufunc_config.py:437(__init__)
128 0.000 0.000 0.000 0.000 {method 'rpartition' of 'str' objects}
42 0.000 0.000 0.000 0.000 utilities.py:76(isUnit)
128 0.000 0.000 0.000 0.000 {built-in method numpy.seterrobj}
2 0.000 0.000 0.001 0.000 _distn_infrastructure.py:1777(cdf)
2 0.000 0.000 0.000 0.000 cds.py:172(<listcomp>)
68 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(argsort)
74 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(searchsorted)
128 0.000 0.000 0.001 0.000 {method 'any' of 'numpy.ndarray' objects}
112 0.000 0.000 0.000 0.000 converters.py:163(<listcomp>)
40 0.000 0.000 0.002 0.000 ui.py:113(get_reader)
2 0.000 0.000 0.001 0.001 spectrum_tools.py:230(_compute_snr)
68 0.000 0.000 0.001 0.000 fromnumeric.py:978(argsort)
1 0.000 0.000 1.397 1.397 spectrum_tools.py:87(__init__)
64 0.000 0.000 0.000 0.000 {built-in method builtins.all}
540 0.000 0.000 0.000 0.000 fromnumeric.py:1644(_ravel_dispatcher)
64 0.000 0.000 0.000 0.000 core.py:2041(<listcomp>)
24 0.000 0.000 0.007 0.000 core.py:717(get_data_lines)
171 0.000 0.000 0.000 0.000 {method 'split' of 'str' objects}
2 0.000 0.000 0.000 0.000 core.py:5551(generateMask)
14 0.000 0.000 0.000 0.000 fastbasic.py:143(check_header)
82 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(place)
152 0.000 0.000 0.000 0.000 generic.py:495(_get_unit_name)
64 0.000 0.000 0.001 0.000 _ufunc_config.py:441(__enter__)
70 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(atleast_1d)
48 0.000 0.000 0.000 0.000 {built-in method _abc._abc_instancecheck}
256 0.000 0.000 0.000 0.000 {built-in method numpy.geterrobj}
60/40 0.000 0.000 0.000 0.000 data_info.py:317(__setattr__)
64 0.000 0.000 0.000 0.000 _ufunc_config.py:446(__exit__)
68 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(rollaxis)
200 0.000 0.000 0.000 0.000 {built-in method builtins.setattr}
12 0.000 0.000 0.000 0.000 configuration.py:375(__call__)
372 0.000 0.000 0.000 0.000 core.py:2064(scale)
70 0.000 0.000 0.000 0.000 numerictypes.py:654(<listcomp>)
102 0.000 0.000 0.000 0.000 core.py:1954(is_unity)
264 0.000 0.000 0.000 0.000 converters.py:168(<genexpr>)
158 0.000 0.000 0.000 0.000 {method 'replace' of 'str' objects}
350 0.000 0.000 0.000 0.000 core.py:2078(powers)
270 0.000 0.000 0.000 0.000 __init__.py:1084(__getitem__)
64 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(putmask)
12 0.000 0.000 0.002 0.000 constant.py:188(_instance_or_super)
10 0.000 0.000 0.001 0.000 column.py:182(__new__)
2 0.000 0.000 0.001 0.000 daophot.py:228(search_multiline)
16 0.000 0.000 0.000 0.000 utils.py:14(get_grouped_by_powers)
4 0.000 0.000 0.000 0.000 ui.py:53(_probably_html)
418 0.000 0.000 0.000 0.000 {method 'upper' of 'str' objects}
24 0.000 0.000 0.000 0.000 core.py:686(__init__)
22 0.000 0.000 0.006 0.000 core.py:695(process_lines)
38 0.000 0.000 0.001 0.000 core.py:528(__repr__)
22 0.000 0.000 0.007 0.000 core.py:955(to)
46 0.000 0.000 0.000 0.000 quantity.py:477(_result_as_quantity)
146 0.000 0.000 0.000 0.000 {method 'count' of 'str' objects}
70 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(shape)
4 0.000 0.000 0.000 0.000 stride_tricks.py:116(_broadcast_to)
4 0.000 0.000 0.000 0.000 header.py:797(clear)
132 0.000 0.000 0.000 0.000 interpolate.py:333(_do_extrapolate)
2 0.000 0.000 0.000 0.000 converters.py:108(can_have_arbitrary_unit)
338 0.000 0.000 0.000 0.000 fromnumeric.py:93(_take_dispatcher)
24 0.000 0.000 0.000 0.000 configuration.py:476(get_config)
28 0.000 0.000 0.000 0.000 quantity.py:1075(__len__)
2 0.000 0.000 0.001 0.000 core.py:2678(trim)
12 0.000 0.000 0.002 0.000 core.py:541(update_meta)
194 0.000 0.000 0.000 0.000 {method 'pop' of 'dict' objects}
348 0.000 0.000 0.000 0.000 fromnumeric.py:2185(_any_dispatcher)
18 0.000 0.000 0.000 0.000 generic.py:466(parse)
12 0.000 0.000 0.002 0.000 quantity.py:764(cgs)
2 0.000 0.000 0.001 0.001 table.py:794(_init_from_list)
32 0.000 0.000 0.000 0.000 nanfunctions.py:114(_copyto)
20 0.000 0.000 0.002 0.000 core.py:843(_apply_equivalencies)
18 0.000 0.000 0.000 0.000 generic.py:451(_parse_unit)
22 0.000 0.000 0.000 0.000 core.py:2319(_condition_arg)
40 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(can_cast)
30 0.000 0.000 0.000 0.000 equivalencies.py:40(__init__)
14 0.000 0.000 0.000 0.000 core.py:420(__call__)
64 0.000 0.000 0.000 0.000 {method 'all' of 'numpy.ndarray' objects}
114 0.000 0.000 0.000 0.000 core.py:1672(decompose)
24 0.000 0.000 0.000 0.000 {method 'setup_tokenizer' of 'astropy.io.ascii.cparser.CParser' objects}
510 0.000 0.000 0.000 0.000 {method 'rstrip' of 'str' objects}
514 0.000 0.000 0.000 0.000 {built-in method builtins.callable}
32 0.000 0.000 0.006 0.000 <__array_function__ internals>:2(nanvar)
32 0.000 0.000 0.006 0.000 <__array_function__ internals>:2(nanstd)
16 0.000 0.000 0.286 0.018 {built-in method builtins.next}
248 0.000 0.000 0.000 0.000 fromnumeric.py:2273(_all_dispatcher)
60 0.000 0.000 0.000 0.000 decorators.py:738(__get__)
16 0.000 0.000 0.000 0.000 utils.py:113(format_power)
2 0.000 0.000 0.000 0.000 indices.py:51(<dictcomp>)
308 0.000 0.000 0.000 0.000 fromnumeric.py:2040(_sum_dispatcher)
12 0.000 0.000 0.000 0.000 enum.py:830(__or__)
270 0.000 0.000 0.000 0.000 function_base.py:1624(_extract_dispatcher)
64 0.000 0.000 0.000 0.000 <string>:1(__new__)
2 0.000 0.000 0.000 0.000 fastbasic.py:317(_read_header)
4 0.000 0.000 0.000 0.000 _continuous_distns.py:5264(_sf)
1 0.000 0.000 1.397 1.397 {built-in method builtins.exec}
64 0.000 0.000 0.000 0.000 generic.py:502(<lambda>)
24 0.000 0.000 0.004 0.000 core.py:280(get_lines)
2 0.000 0.000 0.000 0.000 {built-in method builtins.sum}
18 0.000 0.000 0.002 0.000 core.py:616(_normalize_equivalencies)
4 0.000 0.000 0.000 0.000 core.py:901(<lambda>)
510 0.000 0.000 0.000 0.000 core.py:512(<genexpr>)
20 0.000 0.000 0.000 0.000 core.py:222(equivalencies)
4 0.000 0.000 0.000 0.000 fixedwidth.py:83(get_cols)
212 0.000 0.000 0.000 0.000 nanfunctions.py:554(_nansum_dispatcher)
36 0.000 0.000 0.000 0.000 configobj.py:550(__getitem__)
24 0.000 0.000 0.000 0.000 helpers.py:217(helper_division)
12 0.000 0.000 0.000 0.000 {method 'sub' of 're.Pattern' objects}
64 0.000 0.000 0.000 0.000 typeof.py:140(_typeof_str)
156 0.000 0.000 0.000 0.000 function_base.py:1278(_interp_dispatcher)
16 0.000 0.000 0.001 0.000 core.py:2054(__repr__)
50 0.000 0.000 0.000 0.000 contextlib.py:358(__exit__)
42 0.000 0.000 0.001 0.000 generic.py:517(to_string)
4 0.000 0.000 0.001 0.000 core.py:2240(scale)
2 0.000 0.000 0.002 0.001 table.py:391(__init__)
32 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(size)
134 0.000 0.000 0.000 0.000 {method 'item' of 'numpy.ndarray' objects}
20 0.000 0.000 0.000 0.000 misc.py:34(isiterable)
46 0.000 0.000 0.000 0.000 quantity.py:517(__quantity_subclass__)
52 0.000 0.000 0.001 0.000 core.py:501(_get_line_index)
2 0.000 0.000 0.000 0.000 table.py:879(_init_from_cols)
76 0.000 0.000 0.000 0.000 _distn_infrastructure.py:874(_get_support)
1 0.000 0.000 0.674 0.674 spectrum_tools.py:377(filename)
36 0.000 0.000 0.000 0.000 {method 'squeeze' of 'numpy.ndarray' objects}
170 0.000 0.000 0.000 0.000 nanfunctions.py:225(_nanmin_dispatcher)
24 0.000 0.000 0.000 0.000 enum.py:284(__call__)
70 0.000 0.000 0.000 0.000 fromnumeric.py:1856(shape)
24 0.000 0.000 0.000 0.000 core.py:1407(<genexpr>)
48 0.000 0.000 0.000 0.000 abc.py:137(__instancecheck__)
4 0.000 0.000 0.000 0.000 {method 'round' of 'numpy.generic' objects}
152 0.000 0.000 0.000 0.000 fromnumeric.py:2982(_ndim_dispatcher)
4 0.000 0.000 0.000 0.000 function_base.py:293(average)
164 0.000 0.000 0.000 0.000 core.py:948(<genexpr>)
22 0.000 0.000 0.000 0.000 __init__.py:30(get_format)
156 0.000 0.000 0.000 0.000 type_check.py:209(_is_type_dispatcher)
10 0.000 0.000 0.000 0.000 data_info.py:232(__init__)
102 0.000 0.000 0.000 0.000 nanfunctions.py:340(_nanmax_dispatcher)
4 0.000 0.000 0.000 0.000 core.py:557(get_cols)
36 0.000 0.000 0.000 0.000 core.py:594(process_lines)
6 0.000 0.000 0.000 0.000 fromnumeric.py:42(_wrapit)
6 0.000 0.000 0.000 0.000 equivalencies.py:124(<lambda>)
26 0.000 0.000 0.000 0.000 types.py:164(__get__)
64 0.000 0.000 0.000 0.000 copy.py:273(<genexpr>)
14 0.000 0.000 0.000 0.000 helpers.py:213(helper_multiplication)
6 0.000 0.000 0.000 0.000 {built-in method _csv.reader}
50 0.000 0.000 0.000 0.000 contextlib.py:352(__init__)
12 0.000 0.000 0.000 0.000 validate.py:746(_is_num_param)
12 0.000 0.000 0.001 0.000 utilities.py:529(checkInstrument)
10 0.000 0.000 0.001 0.000 fastbasic.py:251(__init__)
8 0.000 0.000 0.000 0.000 quantity.py:1038(__getitem__)
20 0.000 0.000 0.000 0.000 data_info.py:264(__get__)
68 0.000 0.000 0.000 0.000 helpers.py:95(helper_onearg_test)
24 0.000 0.000 0.000 0.000 core.py:535(__init__)
10 0.000 0.000 0.000 0.000 column.py:352(__array_finalize__)
6 0.000 0.000 0.000 0.000 {method 'round' of 'numpy.ndarray' objects}
2 0.000 0.000 0.000 0.000 _continuous_distns.py:1684(_cdf)
66 0.000 0.000 0.000 0.000 _methods.py:47(_all)
38 0.000 0.000 0.000 0.000 core.py:281(get_current_unit_registry)
2 0.000 0.000 0.001 0.000 helpers.py:28(get_converter)
10 0.000 0.000 0.000 0.000 column.py:730(_copy_attrs)
14 0.000 0.000 0.000 0.000 re.py:170(match)
12 0.000 0.000 0.002 0.000 constant.py:204(cgs)
2 0.000 0.000 0.000 0.000 basic.py:310(get_cols)
2 0.000 0.000 0.000 0.000 table.py:942(_make_table_from_cols)
2 0.000 0.000 0.000 0.000 misc.py:35(sortmore)
158 0.000 0.000 0.000 0.000 fromnumeric.py:2624(_amin_dispatcher)
174 0.000 0.000 0.000 0.000 core.py:503(__deepcopy__)
12 0.000 0.000 0.000 0.000 quantity.py:810(__getattr__)
4 0.000 0.000 0.000 0.000 quantity.py:989(__pow__)
12 0.000 0.000 0.000 0.000 core.py:552(<listcomp>)
6 0.000 0.000 0.000 0.000 _distn_infrastructure.py:899(_open_support_mask)
80 0.000 0.000 0.000 0.000 {built-in method time.time}
4 0.000 0.000 0.065 0.016 contextlib.py:116(__exit__)
12 0.000 0.000 0.000 0.000 {method 'item' of 'numpy.generic' objects}
12 0.000 0.000 0.000 0.000 validate.py:637(_parse_with_caching)
4 0.000 0.000 0.000 0.000 core.py:1333(physical_type)
150 0.000 0.000 0.000 0.000 core.py:1450(is_unity)
12 0.000 0.000 0.000 0.000 constant.py:135(__quantity_subclass__)
20 0.000 0.000 0.000 0.000 table.py:1344(__getitem__)
2 0.000 0.000 0.057 0.028 spectrum_tools.py:209(classify_by_standard)
76 0.000 0.000 0.000 0.000 {built-in method _operator.mul}
64 0.000 0.000 0.000 0.000 {built-in method _abc.get_cache_token}
2 0.000 0.000 0.000 0.000 codecs.py:319(decode)
54 0.000 0.000 0.000 0.000 re.py:232(compile)
66 0.000 0.000 0.000 0.000 core.py:588(powers)
30 0.000 0.000 0.000 0.000 quantity.py:774(isscalar)
6 0.000 0.000 0.000 0.000 {built-in method _locale.setlocale}
4 0.000 0.000 0.000 0.000 contextlib.py:81(__init__)
74 0.000 0.000 0.000 0.000 fromnumeric.py:1225(_searchsorted_dispatcher)
90 0.000 0.000 0.000 0.000 fromnumeric.py:2499(_amax_dispatcher)
66 0.000 0.000 0.000 0.000 core.py:581(bases)
76 0.000 0.000 0.000 0.000 helpers.py:21(_d)
2 0.000 0.000 0.000 0.000 daophot.py:93(update_meta)
18 0.000 0.000 0.000 0.000 core.py:142(registry)
12 0.000 0.000 0.000 0.000 validate.py:593(check)
18 0.000 0.000 0.000 0.000 generic.py:479(_do_parse)
8 0.000 0.000 0.000 0.000 core.py:615(colnames)
4 0.000 0.000 0.000 0.000 core.py:632(check_column_names)
2 0.000 0.000 0.002 0.001 fastbasic.py:258(make_table)
2 0.000 0.000 0.000 0.000 sextractor.py:20(get_cols)
2 0.000 0.000 0.000 0.000 {method 'seek' of '_io.TextIOWrapper' objects}
24 0.000 0.000 0.000 0.000 enum.py:526(__new__)
102 0.000 0.000 0.000 0.000 multiarray.py:312(where)
4 0.000 0.000 0.000 0.000 misc.py:824(set_locale)
4 0.000 0.000 0.000 0.000 table.py:166(__init__)
2 0.000 0.000 0.000 0.000 table.py:948(<listcomp>)
4 0.000 0.000 0.010 0.003 header.py:806(copy)
4 0.000 0.000 0.000 0.000 latex.py:313(__init__)
2 0.000 0.000 0.000 0.000 parse.py:361(urlparse)
64 0.000 0.000 0.000 0.000 multiarray.py:1078(putmask)
68 0.000 0.000 0.000 0.000 numeric.py:1207(_rollaxis_dispatcher)
8 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(round_)
20 0.000 0.000 0.000 0.000 data_info.py:295(__getattr__)
18 0.000 0.000 0.000 0.000 equivalencies.py:55(__eq__)
4 0.000 0.000 0.000 0.000 fastbasic.py:344(<genexpr>)
2 0.000 0.000 0.000 0.000 daophot.py:40(parse_col_defs)
10 0.000 0.000 0.000 0.000 re.py:180(search)
82 0.000 0.000 0.000 0.000 function_base.py:1680(_place_dispatcher)
12 0.000 0.000 0.000 0.000 configuration.py:442(_validate_val)
4 0.000 0.000 0.000 0.000 core.py:533(_get_physical_type_id)
6 0.000 0.000 0.001 0.000 helpers.py:45(get_converters_and_unit)
24 0.000 0.000 0.000 0.000 {built-in method builtins.iter}
2 0.000 0.000 0.000 0.000 {built-in method _codecs.utf_8_decode}
70 0.000 0.000 0.000 0.000 fromnumeric.py:1852(_shape_dispatcher)
10 0.000 0.000 0.000 0.000 fromnumeric.py:3079(around)
8 0.000 0.000 0.000 0.000 fromnumeric.py:3512(round_)
2 0.000 0.000 0.000 0.000 column.py:56(<listcomp>)
10 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(around)
70 0.000 0.000 0.000 0.000 shape_base.py:20(_atleast_1d_dispatcher)
66 0.000 0.000 0.000 0.000 core.py:574(scale)
20 0.000 0.000 0.000 0.000 data_info.py:257(_parent)
4 0.000 0.000 0.000 0.000 ecsv.py:27(process_lines)
8 0.000 0.000 0.000 0.000 ui.py:92(<genexpr>)
12 0.000 0.000 0.000 0.000 re.py:185(sub)
68 0.000 0.000 0.000 0.000 fromnumeric.py:974(_argsort_dispatcher)
32 0.000 0.000 0.000 0.000 fromnumeric.py:3024(_size_dispatcher)
10 0.000 0.000 0.000 0.000 validate.py:1073(is_string)
12 0.000 0.000 0.000 0.000 validate.py:651(_check_value)
90 0.000 0.000 0.000 0.000 data_info.py:236(<genexpr>)
10 0.000 0.000 0.001 0.000 column.py:835(__new__)
2 0.000 0.000 0.000 0.000 data.py:85(_is_url)
4 0.000 0.000 0.000 0.000 fixedwidth.py:296(__init__)
2 0.000 0.000 0.000 0.000 shape_base.py:223(vstack)
12 0.000 0.000 0.000 0.000 configuration.py:270(__get__)
4 0.000 0.000 0.000 0.000 core.py:742(__eq__)
10 0.000 0.000 0.000 0.000 data_info.py:496(__init__)
4 0.000 0.000 0.000 0.000 core.py:539(<listcomp>)
2 0.000 0.000 0.000 0.000 column.py:54(_auto_names)
30 0.000 0.000 0.000 0.000 np_utils.py:160(fix_column_name)
2 0.000 0.000 0.000 0.000 ecsv.py:93(get_cols)
4 0.000 0.000 0.000 0.000 _continuous_distns.py:5240(_argcheck)
6 0.000 0.000 0.000 0.000 locale.py:589(setlocale)
2 0.000 0.000 0.000 0.000 parse.py:409(urlsplit)
12 0.000 0.000 0.000 0.000 core.py:263(__init__)
8 0.000 0.000 0.000 0.000 core.py:449(<listcomp>)
10 0.000 0.000 0.000 0.000 column.py:403(name)
4 0.000 0.000 0.000 0.000 fixedwidth.py:75(get_line)
2 0.000 0.000 0.000 0.000 misc.py:119(groupmore)
2 0.000 0.000 0.000 0.000 ui.py:192(_get_fast_reader_dict)
56 0.000 0.000 0.000 0.000 {function Section.__getitem__ at 0x116e2b6a8}
2 0.000 0.000 0.000 0.000 {built-in method _locale.nl_langinfo}
2 0.000 0.000 0.000 0.000 {method 'seek' of '_io.FileIO' objects}
2 0.000 0.000 0.000 0.000 _bootlocale.py:33(getpreferredencoding)
4 0.000 0.000 0.000 0.000 contextlib.py:237(helper)
2 0.000 0.000 0.000 0.000 {method 'all' of 'numpy.generic' objects}
70 0.000 0.000 0.000 0.000 numerictypes.py:655(<listcomp>)
2 0.000 0.000 0.000 0.000 numeric.py:166(ones)
4 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(cov)
2 0.000 0.000 0.000 0.000 validate.py:839(is_float)
4 0.000 0.000 0.000 0.000 core.py:875(get_err_str)
20 0.000 0.000 0.000 0.000 table.py:179(__getitem__)
12 0.000 0.000 0.000 0.000 table.py:757(<genexpr>)
12 0.000 0.000 0.000 0.000 table.py:972(itercols)
38 0.000 0.000 0.000 0.000 spectrum_tools.py:154(wave)
24 0.000 0.000 0.000 0.000 {method 'copy' of 'list' objects}
26 0.000 0.000 0.000 0.000 enum.py:628(value)
40 0.000 0.000 0.000 0.000 multiarray.py:469(can_cast)
18 0.000 0.000 0.000 0.000 core.py:848(make_converter)
20 0.000 0.000 0.000 0.000 data_info.py:238(_parent)
20 0.000 0.000 0.000 0.000 column.py:611(unit)
4 0.000 0.000 0.000 0.000 table.py:1508(_set_masked)
2 0.000 0.000 0.000 0.000 fixedwidth.py:403(__init__)
2 0.000 0.000 0.000 0.000 ipac.py:161(get_cols)
12 0.000 0.000 0.000 0.000 {method 'rsplit' of 'str' objects}
2 0.000 0.000 0.002 0.001 genericpath.py:16(exists)
4 0.000 0.000 0.221 0.055 contextlib.py:107(__enter__)
32 0.000 0.000 0.000 0.000 nanfunctions.py:1417(_nanvar_dispatcher)
4 0.000 0.000 0.000 0.000 core.py:595(to_string)
12 0.000 0.000 0.000 0.000 metadata.py:406(__set__)
4 0.000 0.000 0.000 0.000 physical.py:48(get_physical_type)
4 0.000 0.000 0.000 0.000 fastbasic.py:60(_read_header)
30 0.000 0.000 0.000 0.000 column.py:240(parent_table)
20 0.000 0.000 0.000 0.000 column.py:250(parent_table)
10 0.000 0.000 0.000 0.000 table.py:1046(_add_as_mixin_column)
20 0.000 0.000 0.000 0.000 table.py:1539(ColumnClass)
2 0.000 0.000 0.000 0.000 fastbasic.py:312(__init__)
2 0.000 0.000 0.000 0.000 cds.py:164(process_lines)
4 0.000 0.000 0.000 0.000 misc.py:16(first_true_index)
24 0.000 0.000 0.000 0.000 {method 'copy' of 'dict' objects}
18 0.000 0.000 0.000 0.000 {method 'lstrip' of 'str' objects}
50 0.000 0.000 0.000 0.000 contextlib.py:355(__enter__)
4 0.000 0.000 0.000 0.000 parse.py:109(_coerce_args)
6 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(concatenate)
2 0.000 0.000 0.000 0.000 {built-in method numpy.empty}
4 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(dot)
4 0.000 0.000 0.000 0.000 core.py:761(__ne__)
12 0.000 0.000 0.000 0.000 constant.py:155(name)
2 0.000 0.000 0.000 0.000 fastbasic.py:214(__init__)
4 0.000 0.000 0.000 0.000 table.py:755(_set_masked_from_cols)
4 0.000 0.000 0.010 0.003 header.py:835(__deepcopy__)
4 0.000 0.000 0.000 0.000 latex.py:332(<listcomp>)
2 0.000 0.000 0.000 0.000 ipac.py:439(__init__)
2 0.000 0.000 0.000 0.000 codecs.py:309(__init__)
2 0.000 0.000 0.000 0.000 fromnumeric.py:1974(clip)
4 0.000 0.000 0.000 0.000 core.py:538(_set_cols_from_names)
24 0.000 0.000 0.000 0.000 core.py:618(<genexpr>)
10 0.000 0.000 0.000 0.000 table.py:142(has_info_class)
10 0.000 0.000 0.000 0.000 table.py:203(__setitem__)
2 0.000 0.000 0.000 0.000 table.py:530(<listcomp>)
2 0.000 0.000 0.001 0.001 table.py:862(_init_from_dict)
2 0.000 0.000 0.000 0.000 cds.py:292(__init__)
6 0.000 0.000 0.000 0.000 {method 'get_names' of 'astropy.io.ascii.cparser.CParser' objects}
14 0.000 0.000 0.000 0.000 {method 'get_header_names' of 'astropy.io.ascii.cparser.CParser' objects}
2 0.000 0.000 0.000 0.000 ipac.py:92(update_meta)
4 0.000 0.000 0.000 0.000 daophot.py:106(<lambda>)
4 0.000 0.000 0.000 0.000 misc.py:126(<genexpr>)
14 0.000 0.000 0.000 0.000 spectrum_tools.py:158(flux)
14 0.000 0.000 0.000 0.000 spectrum_tools.py:166(noise)
12 0.000 0.000 0.000 0.000 {method 'setdefault' of 'collections.OrderedDict' objects}
4 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(result_type)
2 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(clip)
2 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(atleast_2d)
4 0.000 0.000 0.000 0.000 function_base.py:257(iterable)
4 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(average)
4 0.000 0.000 0.000 0.000 stride_tricks.py:143(broadcast_to)
4 0.000 0.000 0.000 0.000 <__array_function__ internals>:2(broadcast_to)
32 0.000 0.000 0.000 0.000 nanfunctions.py:1565(_nanstd_dispatcher)
4 0.000 0.000 0.000 0.000 core.py:541(<listcomp>)
4 0.000 0.000 0.000 0.000 helpers.py:103(helper_square)
2 0.000 0.000 0.000 0.000 table.py:742(_check_names_dtype)
12 0.000 0.000 0.000 0.000 table.py:882(<genexpr>)
12 0.000 0.000 0.000 0.000 table.py:960(<genexpr>)
2 0.000 0.000 0.000 0.000 latex.py:409(start_line)
2 0.000 0.000 0.000 0.000 latex.py:447(__init__)
2 0.000 0.000 0.001 0.000 daophot.py:207(get_data_lines)
2 0.000 0.000 0.002 0.001 sextractor.py:140(read)
2 0.000 0.000 0.000 0.000 daophot.py:388(__init__)
2 0.000 0.000 0.000 0.000 misc.py:26(first_false_index)
2 0.000 0.000 0.000 0.000 rst.py:57(__init__)
4 0.000 0.000 0.000 0.000 {method 'mean' of 'numpy.ndarray' objects}
2 0.000 0.000 0.000 0.000 {method 'min' of 'numpy.ndarray' objects}
18 0.000 0.000 0.000 0.000 fromnumeric.py:3075(_around_dispatcher)
2 0.000 0.000 0.001 0.000 <__array_function__ internals>:2(vstack)
4 0.000 0.000 0.000 0.000 function_base.py:289(_average_dispatcher)
2 0.000 0.000 0.000 0.000 quantity.py:1025(__iter__)
2 0.000 0.000 0.001 0.000 helpers.py:278(helper_twoarg_comparison)
16 0.000 0.000 0.000 0.000 core.py:362(process_val)
4 0.000 0.000 0.000 0.000 basic.py:339(<genexpr>)
2 0.000 0.000 0.000 0.000 table.py:762(<genexpr>)
2 0.000 0.000 0.000 0.000 table.py:893(<listcomp>)
18 0.000 0.000 0.000 0.000 table.py:1499(masked)
2 0.000 0.000 0.000 0.000 latex.py:172(start_line)
2 0.000 0.000 0.000 0.000 daophot.py:203(__init__)
4 0.000 0.000 0.000 0.000 misc.py:21(<lambda>)
4 0.000 0.000 0.000 0.000 {built-in method _operator.not_}
2 0.000 0.000 0.000 0.000 codecs.py:260(__init__)
4 0.000 0.000 0.000 0.000 {method 'conj' of 'numpy.ndarray' objects}
2 0.000 0.000 0.000 0.000 {method 'max' of 'numpy.ndarray' objects}
2 0.000 0.000 0.000 0.000 _methods.py:32(_amin)
2 0.000 0.000 0.000 0.000 shape_base.py:219(_vhstack_dispatcher)
8 0.000 0.000 0.000 0.000 stride_tricks.py:121(<genexpr>)
16 0.000 0.000 0.000 0.000 core.py:321(process_lines)
2 0.000 0.000 0.000 0.000 core.py:366(__call__)
2 0.000 0.000 0.000 0.000 core.py:412(process_line)
2 0.000 0.000 0.000 0.000 cds.py:300(read)
2 0.000 0.000 0.000 0.000 daophot.py:37(__init__)
2 0.000 0.000 0.000 0.000 ipac.py:175(<listcomp>)
2 0.000 0.000 0.000 0.000 ui.py:179(_get_format_class)
2 0.000 0.000 0.000 0.000 {built-in method builtins.abs}
2 0.000 0.000 0.000 0.000 codecs.py:276(reset)
2 0.000 0.000 0.000 0.000 codecs.py:327(reset)
6 0.000 0.000 0.000 0.000 multiarray.py:145(concatenate)
4 0.000 0.000 0.000 0.000 multiarray.py:635(result_type)
4 0.000 0.000 0.000 0.000 multiarray.py:707(dot)
2 0.000 0.000 0.000 0.000 shape_base.py:208(_arrays_for_stack_dispatcher)
4 0.000 0.000 0.000 0.000 quantity.py:338(<genexpr>)
1 0.000 0.000 0.000 0.000 perfomance.py:37(memoized_func)
4 0.000 0.000 0.000 0.000 latex.py:80(process_lines)
2 0.000 0.000 0.000 0.000 latex.py:125(start_line)
2 0.000 0.000 0.000 0.000 misc.py:124(<lambda>)
2 0.000 0.000 0.000 0.000 spectrum_tools.py:174(spectral_type)
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
2 0.000 0.000 0.000 0.000 fromnumeric.py:1970(_clip_dispatcher)
2 0.000 0.000 0.000 0.000 _methods.py:28(_amax)
4 0.000 0.000 0.000 0.000 function_base.py:2240(_cov_dispatcher)
4 0.000 0.000 0.000 0.000 stride_tricks.py:139(_broadcast_to_dispatcher)
2 0.000 0.000 0.000 0.000 basic.py:331(<listcomp>)
10 0.000 0.000 0.000 0.000 column.py:396(name)
4 0.000 0.000 0.000 0.000 table.py:798(<genexpr>)
2 0.000 0.000 0.000 0.000 table.py:865(<listcomp>)
10 0.000 0.000 0.000 0.000 table.py:868(_convert_col_for_table)
2 0.000 0.000 0.000 0.000 {method 'set_names' of 'astropy.io.ascii.cparser.CParser' objects}
2 0.000 0.000 0.000 0.000 misc.py:96(<lambda>)
2 0.000 0.000 0.000 0.000 misc.py:102(<lambda>)
4 0.000 0.000 0.000 0.000 <string>:2(_parse_args)
1 0.000 0.000 0.000 0.000 spectrum_tools.py:288(filepath)
2 0.000 0.000 0.000 0.000 {method 'end' of 're.Match' objects}
4 0.000 0.000 0.000 0.000 parse.py:98(_noop)
2 0.000 0.000 0.000 0.000 shape_base.py:78(_atleast_2d_dispatcher)
4 0.000 0.000 0.000 0.000 stride_tricks.py:26(_maybe_view_as_subclass)
2 0.000 0.000 0.000 0.000 core.py:435(<listcomp>)
2 0.000 0.000 0.000 0.000 ecsv.py:86(update_meta)
In [5]:
pred_df['grism_id'].values[:10]
Out[5]:
array(['par321-00019', 'par321-00073', 'par321-00046', 'par321-00469',
'par321-00007', 'par321-20003', 'par321-00130', 'par321-00071',
'par321-00243', 'par321-00540'], dtype=object)
In [ ]:
Content source: caganze/wisps
Similar notebooks: