def test_repr(carbognani2019):
pdf = pyedra.HG_fit(carbognani2019)
with pd.option_context("display.show_dimensions", False):
df_body = repr(pdf.model_df).splitlines()
df_dim = list(pdf.model_df.shape)
sdf_dim = f"{df_dim[0]} rows x {df_dim[1]} columns"
fotter = f"\nPyedraFitDataFrame - {sdf_dim}"
expected = "\n".join(df_body + [fotter])
assert repr(pdf) == expected
def test_getitem(carbognani2019, expected_filter):
pdf = pyedra.HG_fit(carbognani2019).model_df
filt = pdf[pdf["id"] == 85]
np.testing.assert_array_equal(filt.id, expected_filter.id)
np.testing.assert_array_almost_equal(filt.H, expected_filter.H)
np.testing.assert_array_almost_equal(
filt.error_H,
expected_filter.error_H,
)
np.testing.assert_array_almost_equal(filt.G, expected_filter.G)
np.testing.assert_array_almost_equal(filt.error_G, expected_filter.error_G)
np.testing.assert_array_almost_equal(filt.R, expected_filter.R)
def test_HG_fit(data, carbognani2019):
noob = data.drop_duplicates(subset="nro", keep="first", inplace=False)
result = pyedra.HG_fit(data)
np.testing.assert_array_equal(noob.nro, result.Asteroid)
for idx, error in enumerate(result.error_H):
np.testing.assert_allclose(
carbognani2019.H[idx], result.H[idx], atol=error
)
for idx, error in enumerate(result.error_G):
np.testing.assert_allclose(
carbognani2019.G[idx], result.G[idx], atol=error
)
def test_repr_html(carbognani2019):
pdf = pyedra.HG_fit(carbognani2019)
ad_id = id(pdf)
with pd.option_context("display.show_dimensions", False):
df_html = pdf.model_df._repr_html_()
rows = f"{pdf.model_df.shape[0]} rows"
columns = f"{pdf.model_df.shape[1]} columns"
footer = f"PyedraFitDataFrame - {rows} x {columns}"
parts = [
f'<div class="pyedra-data-container" id={ad_id}>',
df_html,
footer,
"</div>",
]
expected = "".join(parts)
assert pdf._repr_html_() == expected
def test_dir(carbognani2019):
pdf = pyedra.HG_fit(carbognani2019)
for i in dir(pdf):
assert hasattr(pdf, i)