def test_eq(self):
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
other1 = Histogram1D(bins, values, underflow=2, overflow=1)
assert other1 == example
bins = [1.22, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
other2 = Histogram1D(bins, values, underflow=2, overflow=1)
assert other2 != example
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 13, 7.2]
other3 = Histogram1D(bins, values, underflow=2, overflow=1)
assert other3 != example
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
errors2 = [4, 0, 3, 7.2]
other4 = Histogram1D(bins, values, errors2, underflow=2, overflow=1)
assert other4 == example
errors2 = [4, 0, 3, 8.2]
other5 = Histogram1D(bins, values, errors2, underflow=2, overflow=1)
assert other5 != example
def test_compat(self):
book1, book2 = BaseBook(), BaseBook()
book1["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["a"].fill_n(np.asarray([0, 0, 0]))
book2["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["a"].fill_n(np.asarray([0, 0, 0]))
compat = book1.compatible(book2)
self.assertEqual(compat, True)
def test_fill(self):
data = [1, 1, 1, 2, 2]
bins = range(1, 4)
b = ArtemisBook()
b["book.one"] = Histogram1D(bins, stats={"sum": 0.0, "sum2": 0.0})
b["book.two"] = Histogram1D(bins, stats={"sum": 0.0, "sum2": 0.0})
b.fill("book", "one", data)
b.fill("book", "two", data)
self.assertEqual(b["book.one"].frequencies.tolist(), [3, 2])
self.assertEqual(b["book.two"].frequencies.tolist(), [3, 2])
def test_eq_with_underflows(self):
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
other1 = Histogram1D(bins, values, underflow=2)
assert other1 != example
other2 = Histogram1D(bins, values, overflow=1)
assert other2 != example
other3 = Histogram1D(bins, values, overflow=1, underflow=2)
assert other3 == example
def test_subtract_correct_histogram(self):
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [1, 0, 0, 1]
other = Histogram1D(bins, values)
sum = example - other
assert np.allclose(sum.bins, example.bins)
assert np.allclose(sum.frequencies, [3, 0, 3, 6.2])
def test_add_correct_histogram(self):
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [1, 1, 0, 1]
other = Histogram1D(bins, values)
sum = example + other
assert np.allclose(sum.bins, example.bins)
assert np.allclose(sum.frequencies, [5, 1, 3, 8.2])
def test_copy_meta(self):
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
errors2 = [1, 0, 4, 2.6]
h1 = Histogram1D(bins, values, errors2, custom1="custom1", name="name")
copy = h1.copy()
assert h1.meta_data == copy.meta_data
def test_match(self):
bins = range(-5, 5)
h = Histogram1D(bins, stats={"sum": 0.0, "sum2": 0.0})
outer = BaseBook()
outer["one-a"] = h
outer["one-b"] = h
outer["one-c"] = h
self.assertEqual(len(outer["one*"]), 3)
def test_fill_dtype(self):
h = Histogram1D([[0, 1], [1, 2], [2, 3]], [1, 2, 3])
assert h.dtype == np.int64
assert np.allclose(h.frequencies, [1, 2, 3])
h.fill(1.3, weight=2.2)
# assert h.dtype == np.float
assert np.allclose(h.frequencies, [1, 4.2, 3])
def test_msg(self):
book1, book2 = ArtemisBook(), ArtemisBook()
book1["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["a"].fill_n(np.asarray([0, 0, 0]))
book1["b"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["b"].fill_n(np.asarray([0, 1, 1]))
book1["d"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["d"].fill_n(np.asarray([]))
book2["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["a"].fill_n(np.asarray([2, 2]))
book2["b"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["b"].fill_n(np.asarray([0, 3, 3, 3, 3]))
book2["c"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["c"].fill_n(np.asarray([0, 1, 2, 3]))
book = book1 + book2
self.assertEqual(book["a"].frequencies.tolist(), [3, 0, 2])
self.assertEqual(book["b"].frequencies.tolist(), [2, 2, 4])
self.assertEqual(book["d"].frequencies.tolist(), [0, 0, 0])
self.assertEqual(book["c"].frequencies.tolist(), [1, 1, 2])
msg = book._to_message()
book3 = book._from_message(msg)
# TODO
# assertion fails in CI
print(book == book3)
# self.assertEqual(book, book3)
self.assertEqual(book3["a"].frequencies.tolist(), [3, 0, 2])
self.assertEqual(book3["b"].frequencies.tolist(), [2, 2, 4])
self.assertEqual(book3["d"].frequencies.tolist(), [0, 0, 0])
self.assertEqual(book3["c"].frequencies.tolist(), [1, 1, 2])
def test_subtract_wrong_histograms(self):
with self.assertRaises(RuntimeError):
wrong_bins = [
[], # No bins
[1.2, 1.5, 1.7, 1.8], # Too few
[1.2, 1.44, 1.5, 1.7, 1.8], # Different
[1.2, 1.4, 1.5, 1.7, 1.8, 1.0], # Too many
]
values = [1, 1, 0, 2.2, 3, 4, 4]
for binset in wrong_bins:
other = Histogram1D(binset, values[:len(binset) - 1])
with self.assertRaises(RuntimeError):
example - other
def book(self, algname, name, bins, axis_name=None, timer=False):
name_ = "."
name_ = name_.join([algname, name])
self.__logger.info("Booking %s", name_)
# TODO
# Explore more options for correctly initializing h1
value = self._get(name)
if value is not None:
self.__logger.error("Histogram already exists %s", name_)
else:
try:
h = Histogram1D(bins, stats={"sum": 0.0, "sum2": 0.0})
except Exception:
self.__logger.error("Physt fails to book")
raise
self[name_] = h
if timer is True:
self._timers[name_] = []
if axis_name:
self._get(name_).axis_name = axis_name
def rebook(self, excludes=[]):
"""
Force reset of all histograms with a copy
do NOT include copying data
"""
self._rebooked = True
for n, x in self:
if n in excludes:
continue
timer = self._timers.get(n, None)
if timer is None:
bins = x.binning
else:
try:
bins = autobinning(timer)
except IndexError:
self.__logger.warning("%s fails rebook, use original bins",
n)
bins = x.binning
del self._timers[n]
self._set(n, Histogram1D(bins, stats={"sum": 0.0, "sum2": 0.0}))
def test_iadd(self):
book1, book2 = BaseBook(), BaseBook()
book1["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["a"].fill_n(np.asarray([0, 0, 0]))
book1["b"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["b"].fill_n(np.asarray([0, 1, 1]))
book1["d"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book1["d"].fill_n(np.asarray([]))
book2["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["a"].fill_n(np.asarray([2, 2]))
book2["b"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["b"].fill_n(np.asarray([0, 3, 3, 3, 3]))
book2["c"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
book2["c"].fill_n(np.asarray([0, 1, 2, 3]))
book1 += book2
self.assertEqual(book1["a"].frequencies.tolist(), [3, 0, 2])
self.assertEqual(book1["b"].frequencies.tolist(), [2, 2, 4])
self.assertEqual(book1["d"].frequencies.tolist(), [0, 0, 0])
self.assertEqual(book1["c"].frequencies.tolist(), [1, 1, 2])
def test_get_set(self):
book = BaseBook()
book["a"] = Histogram1D(range(0, 4), stats={"sum": 0.0, "sum2": 0.0})
self.assertEqual(isinstance(book["a"], HistogramBase), True)
# This module includes code from the Physt Project
#
# (C) Jan Pipek, 2016-9, MIT licence
# See https://github.com/janpipek/physt
import sys
import os
sys.path = [os.path.join(os.path.dirname(__file__), "..")] + sys.path
from artemis_externals.physt.histogram1d import Histogram1D
from artemis_externals.physt import h1
import numpy as np
import unittest
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
example = Histogram1D(bins, values, overflow=1, underflow=2)
class TestBins(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_nbins(self):
assert example.bin_count == 4
def test_edges(self):
assert np.allclose(example.bin_left_edges, [1.2, 1.4, 1.5, 1.7])
assert np.allclose(example.bin_right_edges, [1.4, 1.5, 1.7, 1.8])
def test_copy_with_errors(self):
bins = [1.2, 1.4, 1.5, 1.7, 1.8]
values = [4, 0, 3, 7.2]
errors2 = [1, 0, 4, 2.6]
h1 = Histogram1D(bins, values, errors2)
assert h1.copy() == h1