예제 #1
0
def test_list_ids():
    session = Session()
    session.load_arrays(1, TEST, TEST)
    session.load_arrays("1", TEST, TEST2)

    # order of 1 and "1" is not determined
    assert {1, "1"} == set(session.list_data_ids())
    assert_array_equal(TEST2, session.get_data('1').get_dep())
    assert_array_equal(TEST, session.get_data(1).get_dep())
예제 #2
0
def test_list_ids():
    session = Session()
    session.load_arrays(1, TEST, TEST)
    session.load_arrays("1", TEST, TEST2)

    # order of 1 and "1" is not determined
    assert {1, "1"} == set(session.list_data_ids())
    assert_array_equal(TEST2, session.get_data('1').get_dep())
    assert_array_equal(TEST, session.get_data(1).get_dep())
예제 #3
0
def test_list_ids():
    session = Session()
    session.load_arrays(1, [1, 2, 3], [1, 2, 3])
    session.load_arrays("1", [1, 2, 3], [4, 5, 6])

    # order of 1 and "1" is not determined
    assert {1, "1"} == set(session.list_data_ids())
    assert_array_equal([4, 5, 6], session.get_data('1').get_dep())
    assert_array_equal([1, 2, 3], session.get_data(1).get_dep())
예제 #4
0
파일: test_data.py 프로젝트: nplee/sherpa
def test_regression_346(Session):
    session = Session()
    x = numpy.arange(-5, 5.1)
    old_y = x * x + 23.2
    y = numpy.ma.masked_array(old_y, mask=old_y < 35)
    e = numpy.ones(x.size)
    session.load_arrays("mydata", x, y, e)
    filtered_y = session.get_dep("mydata", filter=True)
    assert numpy.allclose(filtered_y, [48.2, 39.2, 39.2, 48.2])
예제 #5
0
파일: test_data.py 프로젝트: nplee/sherpa
def test_data_dep_masked_numpyarray_nomask_ui(data_for_load_arrays, Session):
    session, args, data = data_for_load_arrays
    session = Session()
    posy = POS_Y_ARRAY[type(data)]
    args = list(args)
    args[posy] = numpy.ma.array(args[posy])
    session.load_arrays(*args)
    new_data = session.get_data(data.name)
    # Sherpa's way of saying "mask is not set"
    assert new_data.mask is True
    assert len(new_data.get_dep(filter=True)) == len(args[posy].flatten())
예제 #6
0
def test_data_indeperr_masked_numpyarray_ui(arrpos, data_for_load_arrays, Session):
    session, args, data = data_for_load_arrays
    session = Session()
    i = arrpos[type(data)]
    mask = numpy.random.rand(*(args[i].shape)) > 0.5
    args = list(args)
    args[1] = numpy.ma.array(args[i], mask=mask)
    with pytest.warns(UserWarning, match="for dependent variables only"):
        session.load_arrays(*args)
    new_data = session.get_data(data.name)
    assert len(new_data.get_dep(filter=True)) == len(args[i])
예제 #7
0
def test_save_restore(tmpdir):
    outfile = tmpdir.join("sherpa.save")
    session = Session()
    session.load_arrays(1, TEST, TEST2)
    session.save(str(outfile), clobber=True)
    session.clean()
    assert set() == set(session.list_data_ids())

    session.restore(str(outfile))
    assert {1, } == set(session.list_data_ids())
    assert_array_equal(TEST, session.get_data(1).get_indep()[0])
    assert_array_equal(TEST2, session.get_data(1).get_dep())
예제 #8
0
파일: test_data.py 프로젝트: nplee/sherpa
def test_data_dep_masked_numpyarray_ui(data_for_load_arrays, Session):
    session, args, data = data_for_load_arrays
    session = Session()
    posy = POS_Y_ARRAY[type(data)]
    mask = numpy.random.rand(*(args[posy].shape)) > 0.5
    args = list(args)
    args[posy] = numpy.ma.array(args[posy], mask=mask)
    session.load_arrays(*args)
    new_data = session.get_data(data.name)
    assert new_data.mask.shape == mask.shape
    assert numpy.all(new_data.mask == ~mask)
    assert len(new_data.get_dep(filter=True)) == (~mask).sum()
예제 #9
0
def test_save_restore(tmpdir):
    outfile = tmpdir.join("sherpa.save")
    session = Session()
    session.load_arrays(1, TEST, TEST2)
    session.save(str(outfile), clobber=True)
    session.clean()
    assert set() == set(session.list_data_ids())

    session.restore(str(outfile))
    assert {1, } == set(session.list_data_ids())
    assert_array_equal(TEST, session.get_data(1).get_indep()[0])
    assert_array_equal(TEST2, session.get_data(1).get_dep())
예제 #10
0
파일: test_data.py 프로젝트: nplee/sherpa
def test_load_arrays_no_errors(data_no_errors):
    from sherpa.astro.ui.utils import Session
    session = Session()
    data = data_no_errors
    data_class = data.__class__
    data_args = DATA_NO_ERRORS_ARGS
    args = data_args + (data_class, )
    session.load_arrays(*args)
    new_data = session.get_data(data.name)
    assert new_data is not data
    # DATA-NOTE: Do we need an equality operator for data classes? These tests are very partial
    # Note that when they are created with load_arrays they seem to lose the name, which becomes the ID
    numpy.testing.assert_array_equal(new_data.get_indep(), data.get_indep())
    numpy.testing.assert_array_equal(new_data.get_dep(), data.get_dep())
예제 #11
0
from sherpa.ui.utils import Session
from sherpa.data import Data1DInt
from sherpa.models.basic import Polynom1D


def savefig(name):
    plt.savefig(name)
    print("# Created: {}".format(name))


s = Session()
xlo = [2, 3, 5, 7, 8]
xhi = [3, 5, 6, 8, 9]
y = [10, 27, 14, 10, 14]
s.load_arrays(1, xlo, xhi, y, Data1DInt)
mdl = Polynom1D('mdl')
mdl.c0 = 6
mdl.c1 = 1
s.set_source(mdl)
s.plot_fit()

savefig('ui_plot_fit_basic.png')

s.plot_data(color='black')
p = s.get_model_plot_prefs()
p['marker'] = '*'
p['markerfacecolor'] = 'green'
p['markersize'] = 12
s.plot_model(linestyle=':', alpha=0.7, overplot=True)
예제 #12
0
from sherpa.ui.utils import Session
import sherpa.models.basic

x = [100, 200, 300, 400]
y = [10, 12, 9, 13]

s = Session()
s._add_model_types(sherpa.models.basic)

s.load_arrays(1, x, y)

print("# list_data_ids")
print(s.list_data_ids())

print("# get_data()")
print(repr(s.get_data()))

print("# get_data()")
print(s.get_data())

print("# get_stat_name/get_method_name")
print(s.get_stat_name())
print(s.get_method_name())

s.set_stat('cash')
s.set_method('simplex')

s.set_source('const1d.mdl')

print("# mdl")
print(mdl)