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test_trace.py
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test_trace.py
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# -*- coding: utf-8 -*-
import math
import pickle
import warnings
from copy import deepcopy
from unittest import mock
from packaging.version import parse as parse_version
import numpy as np
import numpy.ma as ma
from obspy import Stream, Trace, __version__, read, read_inventory
from obspy import UTCDateTime as UTC
from obspy.core import Stats
from obspy.core.util.base import _get_entry_points
from obspy.io.xseed import Parser
import pytest
class TestTrace:
"""
Test suite for obspy.core.trace.Trace.
"""
@staticmethod
def __remove_processing(tr):
"""
Removes all processing information in the trace object.
Useful for testing.
"""
if "processing" not in tr.stats:
return
del tr.stats.processing
def test_init(self):
"""
Tests the __init__ method of the Trace class.
"""
# NumPy ndarray
tr = Trace(data=np.arange(4))
assert len(tr) == 4
# NumPy masked array
data = np.ma.array([0, 1, 2, 3], mask=[True, True, False, False])
tr = Trace(data=data)
assert len(tr) == 4
# other data types will raise
with pytest.raises(ValueError):
Trace(data=[0, 1, 2, 3])
with pytest.raises(ValueError):
Trace(data=(0, 1, 2, 3))
with pytest.raises(ValueError):
Trace(data='1234')
def test_setattr(self):
"""
Tests the __setattr__ method of the Trace class.
"""
# NumPy ndarray
tr = Trace()
tr.data = np.arange(4)
assert len(tr) == 4
# NumPy masked array
tr = Trace()
tr.data = np.ma.array([0, 1, 2, 3], mask=[True, True, False, False])
assert len(tr) == 4
# other data types will raise
tr = Trace()
with pytest.raises(ValueError):
tr.__setattr__('data', [0, 1, 2, 3])
with pytest.raises(ValueError):
tr.__setattr__('data', (0, 1, 2, 3))
with pytest.raises(ValueError):
tr.__setattr__('data', '1234')
def test_len(self):
"""
Tests the __len__ and count methods of the Trace class.
"""
trace = Trace(data=np.arange(1000))
assert len(trace) == 1000
assert trace.count() == 1000
def test_mul(self):
"""
Tests the __mul__ method of the Trace class.
"""
tr = Trace(data=np.arange(10))
st = tr * 5
assert len(st) == 5
# you may only multiply using an integer
with pytest.raises(TypeError):
tr.__mul__(2.5)
with pytest.raises(TypeError):
tr.__mul__('1234')
def test_truediv(self):
"""
Tests the __truediv__ method of the Trace class.
"""
tr = Trace(data=np.arange(1000))
st = tr / 5
assert len(st) == 5
assert len(st[0]) == 200
# you may only multiply using an integer
with pytest.raises(TypeError):
tr.__truediv__(2.5)
with pytest.raises(TypeError):
tr.__truediv__('1234')
def test_ltrim(self):
"""
Tests the ltrim method of the Trace class.
"""
# set up
trace = Trace(data=np.arange(1000))
start = UTC(2000, 1, 1, 0, 0, 0, 0)
trace.stats.starttime = start
trace.stats.sampling_rate = 200.0
end = UTC(2000, 1, 1, 0, 0, 4, 995000)
# verify
trace.verify()
# UTCDateTime/int/float required
with pytest.raises(TypeError):
trace._ltrim('1234')
with pytest.raises(TypeError):
trace._ltrim([1, 2, 3, 4])
# ltrim 100 samples
tr = deepcopy(trace)
tr._ltrim(0.5)
tr.verify()
np.testing.assert_array_equal(tr.data[0:5],
np.array([100, 101, 102, 103, 104]))
assert len(tr.data) == 900
assert tr.stats.npts == 900
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start + 0.5
assert tr.stats.endtime == end
# ltrim 202 samples
tr = deepcopy(trace)
tr._ltrim(1.010)
tr.verify()
np.testing.assert_array_equal(tr.data[0:5],
np.array([202, 203, 204, 205, 206]))
assert len(tr.data) == 798
assert tr.stats.npts == 798
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start + 1.010
assert tr.stats.endtime == end
# ltrim to UTCDateTime
tr = deepcopy(trace)
tr._ltrim(UTC(2000, 1, 1, 0, 0, 1, 10000))
tr.verify()
np.testing.assert_array_equal(tr.data[0:5],
np.array([202, 203, 204, 205, 206]))
assert len(tr.data) == 798
assert tr.stats.npts == 798
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start + 1.010
assert tr.stats.endtime == end
# some sanity checks
# negative start time as datetime
tr = deepcopy(trace)
tr._ltrim(start - 1, pad=True)
tr.verify()
assert tr.stats.starttime == start - 1
np.testing.assert_array_equal(trace.data, tr.data[200:])
assert tr.stats.endtime == trace.stats.endtime
# negative start time as integer
tr = deepcopy(trace)
tr._ltrim(-100, pad=True)
tr.verify()
assert tr.stats.starttime == start - 100
delta = 100 * trace.stats.sampling_rate
np.testing.assert_array_equal(trace.data, tr.data[int(delta):])
assert tr.stats.endtime == trace.stats.endtime
# start time > end time
tr = deepcopy(trace)
tr._ltrim(trace.stats.endtime + 100)
tr.verify()
assert tr.stats.starttime == trace.stats.endtime + 100
np.testing.assert_array_equal(tr.data, np.empty(0))
assert tr.stats.endtime == tr.stats.starttime
# start time == end time
tr = deepcopy(trace)
tr._ltrim(5)
tr.verify()
assert tr.stats.starttime == trace.stats.starttime + 5
np.testing.assert_array_equal(tr.data, np.empty(0))
assert tr.stats.endtime == tr.stats.starttime
# start time == end time
tr = deepcopy(trace)
tr._ltrim(5.1)
tr.verify()
assert tr.stats.starttime == trace.stats.starttime + 5.1
np.testing.assert_array_equal(tr.data, np.empty(0))
assert tr.stats.endtime == tr.stats.starttime
def test_rtrim(self):
"""
Tests the rtrim method of the Trace class.
"""
# set up
trace = Trace(data=np.arange(1000))
start = UTC(2000, 1, 1, 0, 0, 0, 0)
trace.stats.starttime = start
trace.stats.sampling_rate = 200.0
end = UTC(2000, 1, 1, 0, 0, 4, 995000)
trace.verify()
# UTCDateTime/int/float required
with pytest.raises(TypeError):
trace._rtrim('1234')
with pytest.raises(TypeError):
trace._rtrim([1, 2, 3, 4])
# rtrim 100 samples
tr = deepcopy(trace)
tr._rtrim(0.5)
tr.verify()
np.testing.assert_array_equal(tr.data[-5:],
np.array([895, 896, 897, 898, 899]))
assert len(tr.data) == 900
assert tr.stats.npts == 900
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start
assert tr.stats.endtime == end - 0.5
# rtrim 202 samples
tr = deepcopy(trace)
tr._rtrim(1.010)
tr.verify()
np.testing.assert_array_equal(tr.data[-5:],
np.array([793, 794, 795, 796, 797]))
assert len(tr.data) == 798
assert tr.stats.npts == 798
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start
assert tr.stats.endtime == end - 1.010
# rtrim 1 minute via UTCDateTime
tr = deepcopy(trace)
tr._rtrim(UTC(2000, 1, 1, 0, 0, 3, 985000))
tr.verify()
np.testing.assert_array_equal(tr.data[-5:],
np.array([793, 794, 795, 796, 797]))
assert len(tr.data) == 798
assert tr.stats.npts == 798
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start
assert tr.stats.endtime == end - 1.010
# some sanity checks
# negative end time
tr = deepcopy(trace)
t = UTC(1999, 12, 31)
tr._rtrim(t)
tr.verify()
assert tr.stats.endtime == t
np.testing.assert_array_equal(tr.data, np.empty(0))
# negative end time with given seconds
tr = deepcopy(trace)
tr._rtrim(100)
tr.verify()
assert tr.stats.endtime == trace.stats.endtime - 100
np.testing.assert_array_equal(tr.data, np.empty(0))
assert tr.stats.endtime == tr.stats.starttime
# end time > start time
tr = deepcopy(trace)
t = UTC(2001)
tr._rtrim(t)
tr.verify()
assert tr.stats.endtime == t
np.testing.assert_array_equal(tr.data, np.empty(0))
assert tr.stats.endtime == tr.stats.starttime
# end time > start time given seconds
tr = deepcopy(trace)
tr._rtrim(5.1)
tr.verify()
delta = int(math.floor(round(5.1 * trace.stats.sampling_rate, 7)))
endtime = trace.stats.starttime + trace.stats.delta * \
(trace.stats.npts - delta - 1)
assert tr.stats.endtime == endtime
np.testing.assert_array_equal(tr.data, np.empty(0))
# end time == start time
# returns one sample!
tr = deepcopy(trace)
tr._rtrim(4.995)
tr.verify()
np.testing.assert_array_equal(tr.data, np.array([0]))
assert len(tr.data) == 1
assert tr.stats.npts == 1
assert tr.stats.sampling_rate == 200.0
assert tr.stats.starttime == start
assert tr.stats.endtime == start
def test_rtrim_with_padding(self):
"""
Tests the _rtrim() method of the Trace class with padding. It has
already been tested in the two sided trimming tests. This is just to
have an explicit test. Also tests issue #429.
"""
# set up
trace = Trace(data=np.arange(10))
start = UTC(2000, 1, 1, 0, 0, 0, 0)
trace.stats.starttime = start
trace.stats.sampling_rate = 1.0
trace.verify()
# Pad with no fill_value will mask the additional values.
tr = trace.copy()
end = tr.stats.endtime
tr._rtrim(end + 10, pad=True)
assert tr.stats.endtime == trace.stats.endtime + 10
np.testing.assert_array_equal(tr.data[0:10], np.arange(10))
# Check that the first couple of entries are not masked.
assert not tr.data[0:10].mask.any()
# All the other entries should be masked.
assert tr.data[10:].mask.all()
# Pad with fill_value.
tr = trace.copy()
end = tr.stats.endtime
tr._rtrim(end + 10, pad=True, fill_value=-33)
assert tr.stats.endtime == trace.stats.endtime + 10
# The first ten entries should not have changed.
np.testing.assert_array_equal(tr.data[0:10], np.arange(10))
# The rest should be filled with the fill_value.
np.testing.assert_array_equal(tr.data[10:], np.ones(10) * -33)
def test_trim(self):
"""
Tests the trim method of the Trace class.
"""
# set up
trace = Trace(data=np.arange(1001))
start = UTC(2000, 1, 1, 0, 0, 0, 0)
trace.stats.starttime = start
trace.stats.sampling_rate = 200.0
end = UTC(2000, 1, 1, 0, 0, 5, 0)
trace.verify()
# rtrim 100 samples
trace.trim(0.5, 0.5)
trace.verify()
np.testing.assert_array_equal(trace.data[-5:],
np.array([896, 897, 898, 899, 900]))
np.testing.assert_array_equal(trace.data[:5],
np.array([100, 101, 102, 103, 104]))
assert len(trace.data) == 801
assert trace.stats.npts == 801
assert trace.stats.sampling_rate == 200.0
assert trace.stats.starttime == start + 0.5
assert trace.stats.endtime == end - 0.5
# start time should be before end time
with pytest.raises(ValueError):
trace.trim(end, start)
def test_trim_all_does_not_change_dtype(self):
"""
If a Trace is completely trimmed, e.g. no data samples are remaining,
the dtype should remain unchanged.
A trace with no data samples is not really senseful but the dtype
should not be changed anyways.
"""
# Choose non native dtype.
tr = Trace(np.arange(100, dtype=np.int16))
tr.trim(UTC(10000), UTC(20000))
# Assert the result.
assert len(tr.data) == 0
assert tr.data.dtype == np.int16
def test_add_trace_with_gap(self):
"""
Tests __add__ method of the Trace class.
"""
# set up
tr1 = Trace(data=np.arange(1000))
tr1.stats.sampling_rate = 200
start = UTC(2000, 1, 1, 0, 0, 0, 0)
tr1.stats.starttime = start
tr2 = Trace(data=np.arange(0, 1000)[::-1])
tr2.stats.sampling_rate = 200
tr2.stats.starttime = start + 10
# verify
tr1.verify()
tr2.verify()
# add
trace = tr1 + tr2
# stats
assert trace.stats.starttime == start
assert trace.stats.endtime == start + 14.995
assert trace.stats.sampling_rate == 200
assert trace.stats.npts == 3000
# data
assert len(trace) == 3000
assert trace[0] == 0
assert trace[999] == 999
assert ma.is_masked(trace[1000])
assert ma.is_masked(trace[1999])
assert trace[2000] == 999
assert trace[2999] == 0
# verify
trace.verify()
def test_add_trace_with_overlap(self):
"""
Tests __add__ method of the Trace class.
"""
# set up
tr1 = Trace(data=np.arange(1000))
tr1.stats.sampling_rate = 200
start = UTC(2000, 1, 1, 0, 0, 0, 0)
tr1.stats.starttime = start
tr2 = Trace(data=np.arange(0, 1000)[::-1])
tr2.stats.sampling_rate = 200
tr2.stats.starttime = start + 4
# add
trace = tr1 + tr2
# stats
assert trace.stats.starttime == start
assert trace.stats.endtime == start + 8.995
assert trace.stats.sampling_rate == 200
assert trace.stats.npts == 1800
# data
assert len(trace) == 1800
assert trace[0] == 0
assert trace[799] == 799
assert trace[800].mask
assert trace[999].mask
assert trace[1000] == 799
assert trace[1799] == 0
# verify
trace.verify()
def test_add_same_trace(self):
"""
Tests __add__ method of the Trace class.
"""
# set up
tr1 = Trace(data=np.arange(1001))
# add
trace = tr1 + tr1
# should return exact the same values
assert trace.stats == tr1.stats
np.testing.assert_array_equal(trace.data, tr1.data)
# verify
trace.verify()
def test_add_trace_within_trace(self):
"""
Tests __add__ method of the Trace class.
"""
# set up
tr1 = Trace(data=np.arange(1001))
tr1.stats.sampling_rate = 200
start = UTC(2000, 1, 1, 0, 0, 0, 0)
tr1.stats.starttime = start
tr2 = Trace(data=np.arange(201))
tr2.stats.sampling_rate = 200
tr2.stats.starttime = start + 1
# add
trace = tr1 + tr2
# should return exact the same values like trace 1
assert trace.stats == tr1.stats
mask = np.zeros(len(tr1)).astype(np.bool_)
mask[200:401] = True
np.testing.assert_array_equal(trace.data.mask, mask)
np.testing.assert_array_equal(trace.data.data[:200], tr1.data[:200])
np.testing.assert_array_equal(trace.data.data[401:], tr1.data[401:])
# add the other way around
trace = tr2 + tr1
# should return exact the same values like trace 1
assert trace.stats == tr1.stats
np.testing.assert_array_equal(trace.data.mask, mask)
np.testing.assert_array_equal(trace.data.data[:200], tr1.data[:200])
np.testing.assert_array_equal(trace.data.data[401:], tr1.data[401:])
# verify
trace.verify()
def test_add_gap_and_overlap(self):
"""
Test order of merging traces.
"""
# set up
tr1 = Trace(data=np.arange(1000))
tr1.stats.sampling_rate = 200
start = UTC(2000, 1, 1, 0, 0, 0, 0)
tr1.stats.starttime = start
tr2 = Trace(data=np.arange(1000)[::-1])
tr2.stats.sampling_rate = 200
tr2.stats.starttime = start + 4
tr3 = Trace(data=np.arange(1000)[::-1])
tr3.stats.sampling_rate = 200
tr3.stats.starttime = start + 12
# overlap
overlap = tr1 + tr2
assert len(overlap) == 1800
mask = np.zeros(1800).astype(np.bool_)
mask[800:1000] = True
np.testing.assert_array_equal(overlap.data.mask, mask)
np.testing.assert_array_equal(overlap.data.data[:800], tr1.data[:800])
np.testing.assert_array_equal(overlap.data.data[1000:], tr2.data[200:])
# overlap + gap
overlap_gap = overlap + tr3
assert len(overlap_gap) == 3400
mask = np.zeros(3400).astype(np.bool_)
mask[800:1000] = True
mask[1800:2400] = True
np.testing.assert_array_equal(overlap_gap.data.mask, mask)
np.testing.assert_array_equal(overlap_gap.data.data[:800],
tr1.data[:800])
np.testing.assert_array_equal(overlap_gap.data.data[1000:1800],
tr2.data[200:])
np.testing.assert_array_equal(overlap_gap.data.data[2400:], tr3.data)
# gap
gap = tr2 + tr3
assert len(gap) == 2600
mask = np.zeros(2600).astype(np.bool_)
mask[1000:1600] = True
np.testing.assert_array_equal(gap.data.mask, mask)
np.testing.assert_array_equal(gap.data.data[:1000], tr2.data)
np.testing.assert_array_equal(gap.data.data[1600:], tr3.data)
def test_add_into_gap(self):
"""
Test __add__ method of the Trace class
Adding a trace that fits perfectly into gap in a trace
"""
my_array = np.arange(6, dtype=np.int32)
stats = Stats()
stats.network = 'VI'
stats['starttime'] = UTC(2009, 8, 5, 0, 0, 0)
stats['npts'] = 0
stats['station'] = 'IKJA'
stats['channel'] = 'EHZ'
stats['sampling_rate'] = 1
bigtrace = Trace(data=np.array([], dtype=np.int32), header=stats)
bigtrace_sort = bigtrace.copy()
stats['npts'] = len(my_array)
my_trace = Trace(data=my_array, header=stats)
stats['npts'] = 2
trace1 = Trace(data=my_array[0:2].copy(), header=stats)
stats['starttime'] = UTC(2009, 8, 5, 0, 0, 2)
trace2 = Trace(data=my_array[2:4].copy(), header=stats)
stats['starttime'] = UTC(2009, 8, 5, 0, 0, 4)
trace3 = Trace(data=my_array[4:6].copy(), header=stats)
tr1 = bigtrace
tr2 = bigtrace_sort
for method in [0, 1]:
# Random
bigtrace = tr1.copy()
bigtrace = bigtrace.__add__(trace1, method=method)
bigtrace = bigtrace.__add__(trace3, method=method)
bigtrace = bigtrace.__add__(trace2, method=method)
# Sorted
bigtrace_sort = tr2.copy()
bigtrace_sort = bigtrace_sort.__add__(trace1, method=method)
bigtrace_sort = bigtrace_sort.__add__(trace2, method=method)
bigtrace_sort = bigtrace_sort.__add__(trace3, method=method)
for tr in (bigtrace, bigtrace_sort):
assert isinstance(tr, Trace)
assert not isinstance(tr.data, np.ma.masked_array)
assert (bigtrace_sort.data == my_array).all()
fail_pattern = "\n\tExpected %s\n\tbut got %s"
failinfo = fail_pattern % (my_trace, bigtrace_sort)
failinfo += fail_pattern % (my_trace.data, bigtrace_sort.data)
assert bigtrace_sort == my_trace, failinfo
failinfo = fail_pattern % (my_array, bigtrace.data)
assert (bigtrace.data == my_array).all(), failinfo
failinfo = fail_pattern % (my_trace, bigtrace)
failinfo += fail_pattern % (my_trace.data, bigtrace.data)
assert bigtrace == my_trace, failinfo
for array_ in (bigtrace.data, bigtrace_sort.data):
failinfo = fail_pattern % (my_array.dtype, array_.dtype)
assert my_array.dtype == array_.dtype, failinfo
def test_slice(self):
"""
Tests the slicing of trace objects.
"""
tr = Trace(data=np.arange(10, dtype=np.int32))
mempos = tr.data.ctypes.data
t = tr.stats.starttime
tr1 = tr.slice(t + 2, t + 8)
tr1.data[0] = 10
assert tr.data[2] == 10
assert tr.data.ctypes.data == mempos
assert tr.data[2:9].ctypes.data == tr1.data.ctypes.data
assert tr1.data.ctypes.data - 8 == mempos
# Test the processing information for the slicing. The sliced trace
# should have a processing information showing that it has been
# trimmed. The original trace should have nothing.
tr = Trace(data=np.arange(10, dtype=np.int32))
tr2 = tr.slice(tr.stats.starttime)
assert "processing" not in tr.stats
assert "processing" in tr2.stats
assert "trim" in tr2.stats.processing[0]
def test_slice_no_starttime_or_endtime(self):
"""
Tests the slicing of trace objects with no start time or end time
provided. Compares results against the equivalent trim() operation
"""
tr_orig = Trace(data=np.arange(10, dtype=np.int32))
tr = tr_orig.copy()
# two time points outside the trace and two inside
t1 = tr.stats.starttime - 2
t2 = tr.stats.starttime + 2
t3 = tr.stats.endtime - 3
t4 = tr.stats.endtime + 2
# test 1: only removing data at left side
tr_trim = tr_orig.copy()
tr_trim.trim(starttime=t2)
assert tr_trim == tr.slice(starttime=t2)
tr2 = tr.slice(starttime=t2, endtime=t4)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
# test 2: only removing data at right side
tr_trim = tr_orig.copy()
tr_trim.trim(endtime=t3)
assert tr_trim == tr.slice(endtime=t3)
tr2 = tr.slice(starttime=t1, endtime=t3)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
# test 3: not removing data at all
tr_trim = tr_orig.copy()
tr_trim.trim(starttime=t1, endtime=t4)
tr2 = tr.slice()
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(starttime=t1)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(endtime=t4)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(starttime=t1, endtime=t4)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr_trim.trim()
tr2 = tr.slice()
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(starttime=t1)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(endtime=t4)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(starttime=t1, endtime=t4)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
# test 4: removing data at left and right side
tr_trim = tr_orig.copy()
tr_trim.trim(starttime=t2, endtime=t3)
assert tr_trim == tr.slice(t2, t3)
assert tr_trim == tr.slice(starttime=t2, endtime=t3)
# test 5: no data left after operation
tr_trim = tr_orig.copy()
tr_trim.trim(starttime=t4)
tr2 = tr.slice(starttime=t4)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
tr2 = tr.slice(starttime=t4, endtime=t4 + 1)
self.__remove_processing(tr_trim)
self.__remove_processing(tr2)
assert tr_trim == tr2
def test_slice_nearest_sample(self):
"""
Tests slicing with the nearest sample flag set to on or off.
"""
tr = Trace(data=np.arange(6))
# Samples at:
# 0 10 20 30 40 50
tr.stats.sampling_rate = 0.1
# Nearest sample flag defaults to true.
tr2 = tr.slice(UTC(4), UTC(44))
assert tr2.stats.starttime == UTC(0)
assert tr2.stats.endtime == UTC(40)
tr2 = tr.slice(UTC(8), UTC(48))
assert tr2.stats.starttime == UTC(10)
assert tr2.stats.endtime == UTC(50)
# Setting it to False changes the returned values.
tr2 = tr.slice(UTC(4), UTC(44), nearest_sample=False)
assert tr2.stats.starttime == UTC(10)
assert tr2.stats.endtime == UTC(40)
tr2 = tr.slice(UTC(8), UTC(48), nearest_sample=False)
assert tr2.stats.starttime == UTC(10)
assert tr2.stats.endtime == UTC(40)
def test_trim_floating_point(self):
"""
Tests the slicing of trace objects.
"""
# Create test array that allows for easy testing.
tr = Trace(data=np.arange(11))
org_stats = deepcopy(tr.stats)
org_data = deepcopy(tr.data)
# Save memory position of array.
mem_pos = tr.data.ctypes.data
# Just some sanity tests.
assert tr.stats.starttime == UTC(0)
assert tr.stats.endtime == UTC(10)
# Create temp trace object used for testing.
st = tr.stats.starttime
# This is supposed to include the start and end times and should
# therefore cut right at 2 and 8.
temp = deepcopy(tr)
temp.trim(st + 2.1, st + 7.1)
# Should be identical.
temp2 = deepcopy(tr)
temp2.trim(st + 2.0, st + 8.0)
assert temp.stats.starttime == UTC(2)
assert temp.stats.endtime == UTC(7)
assert temp.stats.npts == 6
assert temp2.stats.npts == 7
# self.assertEqual(temp.stats, temp2.stats)
np.testing.assert_array_equal(temp.data, temp2.data[:-1])
# Create test array that allows for easy testing.
# Check if the data is the same.
assert temp.data.ctypes.data != tr.data[2:9].ctypes.data
np.testing.assert_array_equal(tr.data[2:8], temp.data)
# Using out of bounds times should not do anything but create
# a copy of the stats.
temp = deepcopy(tr)
temp.trim(st - 2.5, st + 200)
# The start and end times should not change.
assert temp.stats.starttime == UTC(0)
assert temp.stats.endtime == UTC(10)
assert temp.stats.npts == 11
# Alter the new stats to make sure the old one stays intact.
temp.stats.starttime = UTC(1000)
assert org_stats == tr.stats
# Check if the data address is not the same, that is it is a copy
assert temp.data.ctypes.data != tr.data.ctypes.data
np.testing.assert_array_equal(tr.data, temp.data)
# Make sure the original Trace object did not change.
np.testing.assert_array_equal(tr.data, org_data)
assert tr.data.ctypes.data == mem_pos
assert tr.stats == org_stats
# Use more complicated times and sampling rate.
tr = Trace(data=np.arange(111))
tr.stats.starttime = UTC(111.11111)
tr.stats.sampling_rate = 50.0
org_stats = deepcopy(tr.stats)
org_data = deepcopy(tr.data)
# Save memory position of array.
mem_pos = tr.data.ctypes.data
# Create temp trace object used for testing.
temp = deepcopy(tr)
temp.trim(UTC(111.22222), UTC(112.99999),
nearest_sample=False)
# Should again be identical. XXX NOT!
temp2 = deepcopy(tr)
temp2.trim(UTC(111.21111), UTC(113.01111),
nearest_sample=False)
np.testing.assert_array_equal(temp.data, temp2.data[1:-1])
# Check stuff.
assert temp.stats.starttime == UTC(111.23111)
assert temp.stats.endtime == UTC(112.991110)
# Check if the data is the same.
temp = deepcopy(tr)
temp.trim(UTC(0), UTC(1000 * 1000))
assert temp.data.ctypes.data != tr.data.ctypes.data
# starttime must be in conformance with sampling rate
t = UTC(111.11111)
assert temp.stats.starttime == t
delta = int((tr.stats.starttime - t) * tr.stats.sampling_rate + .5)
np.testing.assert_array_equal(tr.data, temp.data[delta:delta + 111])
# Make sure the original Trace object did not change.
np.testing.assert_array_equal(tr.data, org_data)
assert tr.data.ctypes.data == mem_pos
assert tr.stats == org_stats
def test_trim_floating_point_with_padding_1(self):
"""
Tests the slicing of trace objects with the use of the padding option.
"""
# Create test array that allows for easy testing.
tr = Trace(data=np.arange(11))
org_stats = deepcopy(tr.stats)
org_data = deepcopy(tr.data)
# Save memory position of array.
mem_pos = tr.data.ctypes.data
# Just some sanity tests.
assert tr.stats.starttime == UTC(0)
assert tr.stats.endtime == UTC(10)
# Create temp trace object used for testing.
st = tr.stats.starttime
# Using out of bounds times should not do anything but create
# a copy of the stats.
temp = deepcopy(tr)
temp.trim(st - 2.5, st + 200, pad=True)
assert temp.stats.starttime.timestamp == -2.0
assert temp.stats.endtime.timestamp == 200
assert temp.stats.npts == 203
mask = np.zeros(203).astype(np.bool_)
mask[:2] = True
mask[13:] = True
np.testing.assert_array_equal(temp.data.mask, mask)
# Alter the new stats to make sure the old one stays intact.
temp.stats.starttime = UTC(1000)
assert org_stats == tr.stats
# Check if the data address is not the same, that is it is a copy
assert temp.data.ctypes.data != tr.data.ctypes.data
np.testing.assert_array_equal(tr.data, temp.data[2:13])
# Make sure the original Trace object did not change.
np.testing.assert_array_equal(tr.data, org_data)
assert tr.data.ctypes.data == mem_pos
assert tr.stats == org_stats
def test_trim_floating_point_with_padding_2(self):
"""
Use more complicated times and sampling rate.
"""
tr = Trace(data=np.arange(111))
tr.stats.starttime = UTC(111.11111)
tr.stats.sampling_rate = 50.0
org_stats = deepcopy(tr.stats)
org_data = deepcopy(tr.data)
# Save memory position of array.
mem_pos = tr.data.ctypes.data
# Create temp trace object used for testing.
temp = deepcopy(tr)
temp.trim(UTC(111.22222), UTC(112.99999),
nearest_sample=False)
# Should again be identical.#XXX not
temp2 = deepcopy(tr)
temp2.trim(UTC(111.21111), UTC(113.01111),
nearest_sample=False)
np.testing.assert_array_equal(temp.data, temp2.data[1:-1])
# Check stuff.
assert temp.stats.starttime == UTC(111.23111)
assert temp.stats.endtime == UTC(112.991110)
# Check if the data is the same.
temp = deepcopy(tr)
temp.trim(UTC(0), UTC(1000 * 1000), pad=True)
assert temp.data.ctypes.data != tr.data.ctypes.data
# starttime must be in conformance with sampling rate
t = UTC(1969, 12, 31, 23, 59, 59, 991110)
assert temp.stats.starttime == t
delta = int((tr.stats.starttime - t) * tr.stats.sampling_rate + .5)
np.testing.assert_array_equal(tr.data, temp.data[delta:delta + 111])
# Make sure the original Trace object did not change.
np.testing.assert_array_equal(tr.data, org_data)
assert tr.data.ctypes.data == mem_pos
assert tr.stats == org_stats
def test_add_sanity(self):
"""
Test sanity checks in __add__ method of the Trace object.
"""
tr = Trace(data=np.arange(10))
# you may only add a Trace object
with pytest.raises(TypeError):
tr.__add__(1234)
with pytest.raises(TypeError):
tr.__add__('1234')
with pytest.raises(TypeError):
tr.__add__([1, 2, 3, 4])
# trace id
tr2 = Trace()
tr2.stats.station = 'TEST'
with pytest.raises(TypeError):
tr.__add__(tr2)
# sample rate
tr2 = Trace()
tr2.stats.sampling_rate = 20
with pytest.raises(TypeError):
tr.__add__(tr2)
# calibration factor
tr2 = Trace()
tr2.stats.calib = 20
with pytest.raises(TypeError):
tr.__add__(tr2)
# data type
tr2 = Trace()
tr2.data = np.arange(10, dtype=np.float32)
with pytest.raises(TypeError):
tr.__add__(tr2)
def test_add_overlaps_default_method(self):
"""
Test __add__ method of the Trace object.
"""
# 1
# overlapping trace with differing data
# Trace 1: 0000000
# Trace 2: 1111111
tr1 = Trace(data=np.zeros(7))
tr2 = Trace(data=np.ones(7))
tr2.stats.starttime = tr1.stats.starttime + 5
# 1 + 2 : 00000--11111
tr = tr1 + tr2
assert isinstance(tr.data, np.ma.masked_array)
assert tr.data.tolist() == [0, 0, 0, 0, 0, None, None, 1, 1, 1, 1, 1]
# 2 + 1 : 00000--11111
tr = tr2 + tr1
assert isinstance(tr.data, np.ma.masked_array)
assert tr.data.tolist() == [0, 0, 0, 0, 0, None, None, 1, 1, 1, 1, 1]
# 2
# overlapping trace with same data
# Trace 1: 0000000
# Trace 2: 0000000
tr1 = Trace(data=np.zeros(7))
tr2 = Trace(data=np.zeros(7))
tr2.stats.starttime = tr1.stats.starttime + 5
# 1 + 2 : 000000000000
tr = tr1 + tr2
assert isinstance(tr.data, np.ndarray)
np.testing.assert_array_equal(tr.data, np.zeros(12))
# 2 + 1 : 000000000000
tr = tr2 + tr1
assert isinstance(tr.data, np.ndarray)
np.testing.assert_array_equal(tr.data, np.zeros(12))
# 3
# contained trace with same data
# Trace 1: 1111111111
# Trace 2: 11
tr1 = Trace(data=np.ones(10))
tr2 = Trace(data=np.ones(2))
tr2.stats.starttime = tr1.stats.starttime + 5
# 1 + 2 : 1111111111
tr = tr1 + tr2
assert isinstance(tr.data, np.ndarray)
np.testing.assert_array_equal(tr.data, np.ones(10))
# 2 + 1 : 1111111111
tr = tr2 + tr1
assert isinstance(tr.data, np.ndarray)
np.testing.assert_array_equal(tr.data, np.ones(10))
# 4
# contained trace with differing data
# Trace 1: 0000000000
# Trace 2: 11
tr1 = Trace(data=np.zeros(10))
tr2 = Trace(data=np.ones(2))
tr2.stats.starttime = tr1.stats.starttime + 5
# 1 + 2 : 00000--000
tr = tr1 + tr2
assert isinstance(tr.data, np.ma.masked_array)
assert tr.data.tolist() == [0, 0, 0, 0, 0, None, None, 0, 0, 0]
# 2 + 1 : 00000--000
tr = tr2 + tr1
assert isinstance(tr.data, np.ma.masked_array)
assert tr.data.tolist() == [0, 0, 0, 0, 0, None, None, 0, 0, 0]
# 5
# completely contained trace with same data until end
# Trace 1: 1111111111
# Trace 2: 1111111111
tr1 = Trace(data=np.ones(10))
tr2 = Trace(data=np.ones(10))
# 1 + 2 : 1111111111
tr = tr1 + tr2
assert isinstance(tr.data, np.ndarray)
np.testing.assert_array_equal(tr.data, np.ones(10))
# 6
# completely contained trace with differing data
# Trace 1: 0000000000
# Trace 2: 1111111111
tr1 = Trace(data=np.zeros(10))
tr2 = Trace(data=np.ones(10))
# 1 + 2 : ----------
tr = tr1 + tr2
assert isinstance(tr.data, np.ma.masked_array)
assert tr.data.tolist() == [None] * 10