def get_test_histograms2():
""" Get set 2 of test histograms
"""
# dummy dataset with mixed types
# convert timestamp (col D) to nanosec since 1970-1-1
df = pd.util.testing.makeMixedDataFrame()
# building 1d-, 2d-histogram (iteratively)
hist1 = hg.Categorize(unit('C'))
hist2 = hg.Bin(5, 0, 5, unit('A'), value=hist1)
hist3 = hg.Bin(5, 0, 5, unit('A'))
hist4 = hg.Categorize(unit('C'), value=hist3)
# fill them
hist1.fill.numpy(df)
hist2.fill.numpy(df)
hist3.fill.numpy(df)
hist4.fill.numpy(df)
hc1 = HistogramContainer(hist1)
hc2 = HistogramContainer(hist2)
hc3 = HistogramContainer(hist3)
hc4 = HistogramContainer(hist4)
return df, hc1, hc2, hc3, hc4
def test_project_on_x():
df = get_test_data()
hist1 = hg.Categorize(unit('C'))
hist2 = hg.Bin(5, 0, 5, unit('A'), value=hist1)
hist3 = hg.Bin(5, 0, 5, unit('A'))
hist4 = hg.Categorize(unit('C'), value=hist3)
for hist in [hist1, hist2, hist3, hist4]:
hist.fill.numpy(df)
histA = project_on_x(hist2)
histC = project_on_x(hist4)
bin_edgesA = histA.bin_edges()
bin_entriesA = histA.bin_entries()
bin_edges3 = hist3.bin_edges()
bin_entries3 = hist3.bin_entries()
bin_labelsC = histC.bin_labels()
bin_entriesC = histC.bin_entries()
bin_labels1 = hist1.bin_labels()
bin_entries1 = hist1.bin_entries(bin_labelsC) # match order of labels
np.testing.assert_array_equal(bin_edgesA, bin_edges3)
np.testing.assert_array_equal(bin_entriesA, bin_entries3)
np.testing.assert_array_equal(sorted(bin_labelsC), sorted(bin_labels1))
np.testing.assert_array_equal(bin_entriesC, bin_entries1)
def test_assert_similar_hists():
""" Test assert on similarity of list of histograms
Check similarity of: type, n-dim, sub-hists, specific type attributes
"""
# dummy dataset with mixed types
# convert timestamp (col D) to nanosec since 1970-1-1
df = pd.util.testing.makeMixedDataFrame()
df['date'] = df['D'].apply(to_ns)
# building 1d-, 2d-, and 3d-histogram (iteratively)
hist0 = hg.Bin(5, 0, 5, unit('A'))
hist1 = hg.Categorize(unit('C'))
hist2 = hg.Bin(5, 0, 5, unit('A'), value=hist1)
hist3 = hg.Categorize(unit('C'), value=hist0)
hist4 = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist2)
hist5 = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist3)
# fill them
for hist in [hist0, hist1, hist2, hist3, hist4, hist5]:
hist.fill.numpy(df)
hc0 = HistogramContainer(hist0)
hc1 = HistogramContainer(hist1)
hc2 = HistogramContainer(hist2)
hc3 = HistogramContainer(hist3)
hc4 = HistogramContainer(hist4)
hc5 = HistogramContainer(hist5)
for hc in [hc0, hc1, hc2, hc3, hc4, hc5]:
assert check_similar_hists([hc, hc])
args01 = ['']
args23 = ['']
args45 = ['']
try:
assert_similar_hists([hc0, hc1])
except AssertionError as e:
args01 = e.args
try:
assert_similar_hists([hc2, hc3])
except AssertionError as e:
args23 = e.args
try:
assert_similar_hists([hc4, hc5])
except AssertionError as e:
args45 = e.args
assert args01[0] == 'Input histograms are not all similar.'
assert args23[0] == 'Input histograms are not all similar.'
assert args45[0] == 'Input histograms are not all similar.'
def get_test_histograms1():
""" Get set 1 of test histograms
"""
# dummy dataset with mixed types
# convert timestamp (col D) to nanosec since 1970-1-1
df = pd.util.testing.makeMixedDataFrame()
df['date'] = df['D'].apply(to_ns)
df['boolT'] = True
df['boolF'] = False
# building 1d-, 2d-, and 3d-histogram (iteratively)
hist1 = hg.Categorize(unit('C'))
hist2 = hg.Bin(5, 0, 5, unit('A'), value=hist1)
hist3 = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist2)
# fill them
hist1.fill.numpy(df)
hist2.fill.numpy(df)
hist3.fill.numpy(df)
hc1 = HistogramContainer(hist1)
hc2 = HistogramContainer(hist2)
hc3 = HistogramContainer(hist3)
return df, hc1, hc2, hc3
def test_prepare_2dgrid():
""" Test preparation of grid for extraction of number of entries for 2d hists
"""
df, hc1, hc2, hc3 = get_test_histograms1()
# building 1d-, 2d-, and 3d-histogram (iteratively)
hist1 = hg.Categorize(unit('C'))
hist2 = hg.Bin(5, 0, 5, unit('A'), value=hist1)
hist3 = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist2)
# fill them
hist1.fill.numpy(df)
hist2.fill.numpy(df)
hist3.fill.numpy(df)
xkeys1, ykeys1 = prepare_2dgrid(hist1)
xkeys2, ykeys2 = prepare_2dgrid(hist2)
xkeys3, ykeys3 = prepare_2dgrid(hist3)
np.testing.assert_array_equal(xkeys1, [])
np.testing.assert_array_equal(ykeys1, [])
np.testing.assert_array_equal(xkeys2, [0, 1, 2, 3, 4])
np.testing.assert_array_equal(ykeys2,
['foo1', 'foo2', 'foo3', 'foo4', 'foo5'])
np.testing.assert_array_equal(xkeys3, [0, 1, 4, 5, 6])
np.testing.assert_array_equal(ykeys3, [0, 1, 2, 3, 4])
def test_check_similar_hists():
"""Test similarity of list of histograms
Check similarity of: type, n-dim, sub-hists, specific type attributes
"""
# dummy dataset with mixed types
# convert timestamp (col D) to nanosec since 1970-1-1
df = pd.util.testing.makeMixedDataFrame()
df["date"] = df["D"].apply(to_ns)
# building 1d-, 2d-, and 3d-histogram (iteratively)
hist0 = hg.Bin(5, 0, 5, unit("A"))
hist1 = hg.Categorize(unit("C"))
hist2 = hg.Bin(5, 0, 5, unit("A"), value=hist1)
hist3 = hg.Categorize(unit("C"), value=hist0)
hist4 = hg.SparselyBin(
origin=pd.Timestamp("2009-01-01").value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit("date"),
value=hist2,
)
hist5 = hg.SparselyBin(
origin=pd.Timestamp("2009-01-01").value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit("date"),
value=hist3,
)
# fill them
for hist in [hist0, hist1, hist2, hist3, hist4, hist5]:
hist.fill.numpy(df)
hc0 = HistogramContainer(hist0)
hc1 = HistogramContainer(hist1)
hc2 = HistogramContainer(hist2)
hc3 = HistogramContainer(hist3)
hc4 = HistogramContainer(hist4)
hc5 = HistogramContainer(hist5)
for hc in [hc0, hc1, hc2, hc3, hc4, hc5]:
assert check_similar_hists([hc, hc])
assert not check_similar_hists([hc0, hc1])
assert not check_similar_hists([hc2, hc3])
assert not check_similar_hists([hc4, hc5])
def get_histograms():
df = get_test_data()
hist1 = hg.Categorize(unit('C'))
hist2 = hg.Bin(5, 0, 5, unit('A'), value=hist1)
hist3 = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist2)
for hist in [hist1, hist2, hist3]:
hist.fill.numpy(df)
return hist1, hist2, hist3
def test_project_split2dhist_on_axis():
df = get_test_data()
histA = hg.Bin(5, 0, 5, unit('A'))
histC = hg.Categorize(unit('C'))
hist1 = hg.Categorize(unit('C'), value=histA)
hist2 = hg.Bin(5, 0, 5, unit('A'), value=histC)
histDCA = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist1)
histDAC = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=hist2)
histDA = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=histA)
histDC = hg.SparselyBin(origin=pd.Timestamp('2009-01-01').value,
binWidth=pd.Timedelta(days=1).value,
quantity=unit('date'),
value=histC)
for hist in [histDA, histDC, histDCA, histDAC]:
hist.fill.numpy(df)
# split along date axis
splitAC = HistogramContainer(histDAC).split_hist_along_first_dimension(
xname='x', yname='y', short_keys=True, convert_time_index=True)
splitCA = HistogramContainer(histDCA).split_hist_along_first_dimension(
xname='x', yname='y', short_keys=True, convert_time_index=True)
splitA0 = HistogramContainer(histDA).split_hist_along_first_dimension(
xname='x', yname='y', short_keys=True, convert_time_index=True)
splitC0 = HistogramContainer(histDC).split_hist_along_first_dimension(
xname='x', yname='y', short_keys=True, convert_time_index=True)
splitA1 = project_split2dhist_on_axis(splitAC, 'x')
splitA2 = project_split2dhist_on_axis(splitCA, 'y')
splitC1 = project_split2dhist_on_axis(splitAC, 'y')
splitC2 = project_split2dhist_on_axis(splitCA, 'x')
assert len(splitA0) == len(splitA1)
assert len(splitA0) == len(splitA2)
for key, h0 in splitA0.items():
assert key in splitA1
assert key in splitA2
h1 = splitA1[key]
h2 = splitA2[key]
bin_edges0 = h0.bin_edges()
bin_edges1 = h1.bin_edges()
bin_edges2 = h2.bin_edges()
bin_entries0 = h0.bin_entries()
bin_entries1 = h1.bin_entries()
bin_entries2 = h2.bin_entries()
np.testing.assert_array_equal(bin_edges0, bin_edges1)
np.testing.assert_array_equal(bin_edges0, bin_edges2)
np.testing.assert_array_equal(bin_entries0, bin_entries1)
np.testing.assert_array_equal(bin_entries0, bin_entries2)
assert len(splitC0) == len(splitC1)
assert len(splitC0) == len(splitC2)
for key, h0 in splitC0.items():
assert key in splitC1
assert key in splitC2
h1 = splitC1[key]
h2 = splitC2[key]
bin_labels0 = h0.bin_labels()
bin_labels1 = h1.bin_labels()
bin_labels2 = h2.bin_labels()
bin_entries0 = h0.bin_entries()
bin_entries1 = h1.bin_entries(bin_labels0)
bin_entries2 = h2.bin_entries(bin_labels0)
np.testing.assert_array_equal(sorted(bin_labels0), sorted(bin_labels1))
np.testing.assert_array_equal(sorted(bin_labels0), sorted(bin_labels2))
np.testing.assert_array_equal(bin_entries0, bin_entries1)
np.testing.assert_array_equal(bin_entries0, bin_entries2)
