示例#1
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def test_ui_source_methods_with_full_model(clean_ui, setup_ui_full):

    ui.load_data('full', setup_ui_full.ascii)
    ui.set_full_model('full', 'powlaw1d.p1')

    # Test Case 1
    with pytest.raises(IdentifierErr) as exc:
        ui.get_source('full')

    emsg = "Convolved model\n'powlaw1d.p1'\n is set for dataset full. You should use get_model instead."
    assert str(exc.value) == emsg

    with pytest.raises(IdentifierErr) as exc:
        ui.plot_source('full')

    emsg = "Convolved model\n'powlaw1d.p1'\n is set for dataset full. You should use plot_model instead."
    assert str(exc.value) == emsg

    with pytest.raises(IdentifierErr) as exc:
        ui.get_source_plot('full')

    emsg = "Convolved model\n'powlaw1d.p1'\n is set for dataset full. You should use get_model_plot instead."
    assert str(exc.value) == emsg

    # Test Case 2
    ui.set_source('full', 'powlaw1d.p2')
    ui.get_source('full')

    # Test Case 3
    ui.load_data('not_full', setup_ui_full.ascii)
    with pytest.raises(IdentifierErr) as exc:
        ui.get_source('not_full')

    emsg = 'source not_full has not been set, consider using set_source() or set_model()'
    assert emsg == str(exc.value)
示例#2
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    def test_source_methods_with_full_model(self):
        from sherpa.utils.err import IdentifierErr

        ui.load_data('full', self.ascii)
        ui.set_full_model('full', 'powlaw1d.p1')

        # Test Case 1
        try:
            ui.get_source('full')
        except IdentifierErr as e:
            self.assertRegex(
                str(e),
                "Convolved model\n.*\n is set for dataset full. You should use get_model instead.",
                str(e))
        try:
            ui.plot_source('full')
        except IdentifierErr as e:
            self.assertRegex(
                str(e),
                "Convolved model\n.*\n is set for dataset full. You should use plot_model instead.",
                str(e))

        # Test Case 2
        ui.set_source('full', 'powlaw1d.p2')
        ui.get_source('full')

        # Test Case 3
        ui.load_data('not_full', self.ascii)
        try:
            ui.get_source('not_full')
        except IdentifierErr as e:
            self.assertEqual(
                'source not_full has not been set, consider using set_source() or set_model()',
                str(e))
示例#3
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    def test_source_methods_with_full_model(self):
        from sherpa.utils.err import IdentifierErr

        ui.load_data('full', self.ascii)
        ui.set_full_model('full', 'powlaw1d.p1')

        # Test Case 1
        try:
            ui.get_source('full')
        except IdentifierErr as e:
            self.assertRegexpMatches(str(e), "Convolved model\n.*\n is set for dataset full. You should use get_model instead.", str(e))
        try:
            ui.plot_source('full')
        except IdentifierErr as e:
            self.assertEquals("Convolved model\n'p1'\n is set for dataset full. You should use plot_model instead.", str(e))

        # Test Case 2
        ui.set_source('full', 'powlaw1d.p2')
        ui.get_source('full')

        # Test Case 3
        ui.load_data('not_full', self.ascii)
        try:
            ui.get_source('not_full')
        except IdentifierErr as e:
            self.assertEquals('source not_full has not been set, consider using set_source() or set_model()', str(e))
示例#4
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    def setUp(self):
        self._old_logger_level = logger.getEffectiveLevel()
        logger.setLevel(logging.ERROR)
        ui.clean()

        self.ascii = self.make_path('sim.poisson.1.dat')

        self.wrong_stat_msg = "Fit statistic must be cash, cstat or wstat, not {}"
        self.wstat_err_msg = "No background data has been supplied. Use cstat"
        self.no_covar_msg = "covariance has not been performed"
        self.fail_msg = "Call should not have succeeded"
        self.right_stats = {'cash', 'cstat', 'wstat'}
        self.model = PowLaw1D("p1")

        ui.load_data(self.ascii)
        ui.set_model(self.model)
示例#5
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    def setUp(self):
        self._old_logger_level = logger.getEffectiveLevel()
        logger.setLevel(logging.ERROR)
        ui.clean()

        self.ascii = self.make_path('sim.poisson.1.dat')

        self.wrong_stat_msg = "Fit statistic must be cash, cstat or wstat, not {}"
        self.wstat_err_msg = "No background data has been supplied. Use cstat"
        self.no_covar_msg = "covariance has not been performed"
        self.fail_msg = "Call should not have succeeded"
        self.right_stats = {'cash', 'cstat', 'wstat'}
        self.model = PowLaw1D("p1")

        ui.load_data(self.ascii)
        ui.set_model(self.model)
示例#6
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 def test_ascii(self):
     ui.load_data(1, self.ascii)
     ui.load_data(1, self.ascii, 2)
     ui.load_data(1, self.ascii, 2, ("col2", "col1"))
# coding: utf-8

import sherpa.ui as ui

ui.load_data("default_interp", "load_template_with_interpolation-bb_data.dat")
ui.load_template_model('bb1', "bb_index.dat")
ui.load_template_model('bb2', "bb_index.dat")
ui.set_model("default_interp", bb1+bb2)
ui.freeze("bb1.dummy")
ui.freeze("bb2.dummy")
ui.fit("default_interp")
示例#8
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 def test_reading_strings(self):
     ui.load_data(self.template_idx, require_floats=False)
# coding: utf-8

import sherpa.ui as ui
from sherpa.models.template import KNNInterpolator

ui.load_data("custom_interp", "load_template_interpolator-bb_data.dat")
ui.load_template_interpolator('knn', KNNInterpolator, k=2, order=1)
ui.load_template_model('bb1', "bb_index.dat", template_interpolator_name='knn')
ui.set_model("custom_interp", "bb1")
ui.freeze("bb1.dummy")
ui.fit("custom_interp")

示例#10
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def setup_covar(make_data_path):

    print("A")
    ui.load_data(make_data_path('sim.poisson.1.dat'))
    ui.set_model(PowLaw1D("p1"))
示例#11
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def test_ui_ascii(clean_ui, setup_ui_full):
    ui.load_data(1, setup_ui_full.ascii)
    ui.load_data(1, setup_ui_full.ascii, 2)
    ui.load_data(1, setup_ui_full.ascii, 2, ("col2", "col1"))
示例#12
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def test_not_reading_header_without_comment(make_data_path):
    with pytest.raises(ValueError):
        ui.load_data(make_data_path('agn2'))
# coding: utf-8
import sherpa.ui as ui

ui.load_data("load_template_without_interpolation-bb_data.dat")
ui.load_template_model('bb1', "bb_index.dat", template_interpolator_name=None)
ui.set_source('bb1')
assert ui.get_source().is_discrete
ui.set_source('bb1*const1d.c1+gauss1d.g2**const1d.c2')
assert ui.get_source().is_discrete
# coding: utf-8
import sherpa.ui as ui

ui.load_data("bb_data.dat")
ui.load_template_model('bb1', "bb_index.dat", template_interpolator_name=None)
ui.set_method('gridsearch')
ui.set_method_opt('sequence', [[2234, 0],[3512,0]])
ui.set_source('bb1')
ui.fit()
示例#15
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# coding: utf-8

import sherpa.ui as ui

ui.load_data("default_interp", "bb_data.dat")
ui.load_template_model('bb1', "bb_index.dat")
ui.load_template_model('bb2', "bb_index.dat")
ui.set_model("default_interp", bb1+bb2)
ui.freeze("bb1.dummy")
ui.freeze("bb2.dummy")
ui.fit("default_interp")
示例#16
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 def test_ascii(self):
     ui.load_data(1, self.ascii)
     ui.load_data(1, self.ascii, 2)
     ui.load_data(1, self.ascii, 2, ("col2", "col1"))
示例#17
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def test_require_float(make_data_path):
    with pytest.raises(ValueError):
        ui.load_data(make_data_path('agn2'))
示例#18
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def test_reading_floats(make_data_path):
    ui.load_data(make_data_path('agn2_fixed'))
示例#19
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def test_reading_strings(make_data_path):
    ui.load_data(make_data_path('table.txt'), require_floats=False)
示例#20
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# coding: utf-8

import sherpa.ui as ui
from sherpa.models.template import KNNInterpolator

ui.load_data("custom_interp", "bb_data.dat")
ui.load_template_interpolator('knn', KNNInterpolator, k=2, order=1)
ui.load_template_model('bb1', "bb_index.dat", template_interpolator_name='knn')
ui.set_model("custom_interp", "bb1")
ui.freeze("bb1.dummy")
ui.fit("custom_interp")

示例#21
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 def test_reading_floats(self):
     ui.load_data(self.agn2_fixed)
示例#22
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 def test_reading_floats(self):
     ui.load_data(self.agn2_fixed)
示例#23
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 def test_reading_strings(self):
     ui.load_data(self.template_idx, require_floats=False)
# coding: utf-8

import sherpa.ui as ui

ui.load_data("default_interp", "load_template_with_interpolation-bb_data.dat")
ui.load_template_model('bb1', "bb_index.dat")
ui.set_model("default_interp", bb1)
ui.set_method('gridsearch')
ui.set_method_opt('sequence', ui.get_model_component('bb1').parvals)
ui.fit("default_interp")
示例#25
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def fit_evol(dateglob='20?????', rootdir='darkhist_peaknorm', outroot='', xmin=25.0, xmax=4000,
             conf=True, gauss=False):
    results = {}
    fileglob = os.path.join(rootdir, '{}.dat'.format(dateglob))

    for i, filename in enumerate(glob(fileglob)):
        filedate = re.search(r'(\d{7})', filename).group(1)
        print "\n\n*************** {} *****************".format(filename)
        plt.figure(1)
        ui.load_data(1, filename, 2)
        data = ui.get_data()
        ui.ignore(None, xmin)
        ui.ignore(xmax, None)

        dark_models.xall = data.x
        # dark_models.imin = np.where(xall > xmin)[0][0]
        # dark_models.imax = np.where(xall > xmax)[0][0]

        sbp.gamma1 = 0.05
        sbp.gamma2 = 3.15
        sbp.gamma2.min = 2.
        sbp.gamma2.max = 4.
        sbp.x_b = 130.
        sbp.x_b.min = 100.
        sbp.x_b.max = 160.
        sbp.x_r = 50.
        ok = (data.x > 40) & (data.x < 60)
        sbp.ampl1 = np.mean(data.y[ok])

        if gauss:
            fit_gauss_sbp()
        else:
            fit_sbp()

        pars = (sbp.gamma1.val, sbp.gamma2.val, sbp.x_b.val, sbp.x_r.val, sbp.ampl1.val)
        fit_y = dark_models.smooth_broken_pow(pars, data.x)

        if conf:
            ui.set_conf_opt('numcores', 1)
            ui.conf()
            res = ui.get_conf_results()
            result = dict((x, getattr(res, x))
                          for x in ('parnames', 'parmins', 'parvals', 'parmaxes'))
            result['x'] = data.x
            result['y'] = data.y
            result['y_fit'] = fit_y
            results[filedate] = result

        if outroot is not None:
            ui.notice(0, xmax)
            ui.set_xlog()
            ui.set_ylog()
            ui.plot_fit()
            plt.xlim(1, 1e4)
            plt.ylim(0.5, 1e5)
            plt.grid(True)
            plt.xlabel('Dark current (e-/sec)')
            outfile = os.path.join(rootdir, '{}{}.png'.format(outroot, filedate))
            print 'Writing', outfile
            plt.savefig(outfile)

            if conf:
                outfile = os.path.join(rootdir, '{}{}.pkl'.format(outroot, filedate))
                print 'Writing', outfile
                pickle.dump(result, open(outfile, 'w'), protocol=-1)

    if outroot is not None:
        outfile = os.path.join(rootdir, '{}fits.pkl'.format(outroot))
        print 'Writing', outfile
        pickle.dump(results, open(outfile, 'w'), protocol=-1)

    return results