4 files changed, 20 insertions, 21 deletions

diff --git a/pyecsca/sca/trace/align.py b/pyecsca/sca/trace/align.py
index f1bf259..dc246eb 100644
--- a/pyecsca/sca/trace/align.py
+++ b/pyecsca/sca/trace/align.py
@@ -191,8 +191,8 @@ def align_dtw_scale(reference: Trace, *traces: Trace, radius: int = 1,
             dist, path = fastdtw(reference_samples, trace.samples, radius=radius)
         else:
             dist, path = dtw(reference_samples, trace.samples)
-        result_samples = np.zeros(len(trace.samples), dtype=trace.samples.dtype)
-        scale = np.ones(len(trace.samples), dtype=trace.samples.dtype)
+        result_samples = np.zeros(max((len(trace.samples), len(reference_samples))), dtype=trace.samples.dtype)
+        scale = np.ones(max((len(trace.samples), len(reference_samples))), dtype=trace.samples.dtype)
         for x, y in path:
             result_samples[x] = trace.samples[y]
             scale[x] += 1
@@ -225,7 +225,7 @@ def align_dtw(reference: Trace, *traces: Trace, radius: int = 1, fast: bool = Tr
             dist, path = fastdtw(reference_samples, trace.samples, radius=radius)
         else:
             dist, path = dtw(reference_samples, trace.samples)
-        result_samples = np.zeros(len(trace.samples), dtype=trace.samples.dtype)
+        result_samples = np.zeros(max((len(trace.samples), len(reference_samples))), dtype=trace.samples.dtype)
         pairs = np.array(np.array(path, dtype=np.dtype("int,int")),
                          dtype=np.dtype([("x", "int"), ("y", "int")]))
         result_samples[pairs["x"]] = trace.samples[pairs["y"]]
diff --git a/pyecsca/sca/trace/trace.py b/pyecsca/sca/trace/trace.py
index 6ba70bc..764dada 100644
--- a/pyecsca/sca/trace/trace.py
+++ b/pyecsca/sca/trace/trace.py
@@ -64,7 +64,7 @@ class Trace(object):
         return np.array_equal(self.samples, other.samples) and self.meta == other.meta
 
     def with_samples(self, samples: ndarray) -> "Trace":
-        return Trace(samples, deepcopy(self.meta), deepcopy(self.trace_set))
+        return Trace(samples, deepcopy(self.meta))
 
     def __copy__(self):
         return Trace(copy(self.samples), copy(self.meta), copy(self.trace_set))
diff --git a/pyecsca/sca/trace_set/hdf5.py b/pyecsca/sca/trace_set/hdf5.py
index 6f676ff..b610735 100644
--- a/pyecsca/sca/trace_set/hdf5.py
+++ b/pyecsca/sca/trace_set/hdf5.py
@@ -8,6 +8,7 @@ from typing import Union, Optional, Dict, Any, List
 import h5py
 import numpy as np
 from public import public
+from copy import deepcopy
 
 from .base import TraceSet
 from .. import Trace
@@ -16,27 +17,27 @@ from .. import Trace
 @public
 class HDF5Meta(MutableMapping):
     _dataset: h5py.AttributeManager
-    _cache: Dict[str, Any]
 
     def __init__(self, attrs: h5py.AttributeManager):
         self._attrs = attrs
-        self._cache = {}
         super().__init__()
 
     def __getitem__(self, item):
         if item not in self._attrs:
             raise KeyError
-        if item not in self._cache:
-            self._cache[item] = pickle.loads(self._attrs[item])
-        return self._cache[item]
+        return pickle.loads(self._attrs[item])
 
     def __setitem__(self, key, value):
         self._attrs[key] = np.void(pickle.dumps(value))
 
     def __delitem__(self, key):
         del self._attrs[key]
-        if key in self._cache:
-            del self._cache[key]
+
+    def __copy__(self):
+        return deepcopy(self)
+
+    def __deepcopy__(self, memodict={}):
+        return dict(self)
 
     def __iter__(self):
         yield from self._attrs
@@ -69,7 +70,7 @@ class HDF5TraceSet(TraceSet):
         else:
             raise ValueError
         kwargs = dict(hdf5.attrs)
-        kwargs["_ordering"] = list(kwargs["_ordering"])
+        kwargs["_ordering"] = list(kwargs["_ordering"]) if "_ordering" in kwargs else list(hdf5.keys())
         traces = []
         for k in kwargs["_ordering"]:
             meta = dict(HDF5Meta(hdf5[k].attrs))
@@ -87,7 +88,7 @@ class HDF5TraceSet(TraceSet):
         else:
             raise ValueError
         kwargs = dict(hdf5.attrs)
-        kwargs["_ordering"] = list(kwargs["_ordering"])
+        kwargs["_ordering"] = list(kwargs["_ordering"]) if "_ordering" in kwargs else list(hdf5.keys())
         traces = []
         for k in kwargs["_ordering"]:
             meta = HDF5Meta(hdf5[k].attrs)
diff --git a/test/sca/test_align.py b/test/sca/test_align.py
index 8aa489b..c36cff0 100644
--- a/test/sca/test_align.py
+++ b/test/sca/test_align.py
@@ -1,5 +1,3 @@
-from unittest import TestCase
-
 import numpy as np
 from pyecsca.sca import align_correlation, align_peaks, align_sad, align_dtw_scale,\
     align_dtw, Trace, InspectorTraceSet
@@ -10,7 +8,7 @@ class AlignTests(Plottable):
 
     def test_align(self):
         first_arr = np.array([10, 64, 120, 64, 10, 10, 10, 10, 10], dtype=np.dtype("i1"))
-        second_arr = np.array([10, 10, 10, 10, 50, 80, 50, 20, 10], dtype=np.dtype("i1"))
+        second_arr = np.array([10, 10, 10, 10, 50, 80, 50, 20], dtype=np.dtype("i1"))
         third_arr = np.array([70, 30, 42, 35, 28, 21, 15, 10, 5], dtype=np.dtype("i1"))
         a = Trace(first_arr)
         b = Trace(second_arr)
@@ -19,7 +17,7 @@ class AlignTests(Plottable):
         self.assertIsNotNone(result)
         self.assertEqual(len(result), 2)
         np.testing.assert_equal(result[0].samples, first_arr)
-        np.testing.assert_equal(result[1].samples, np.array([10, 50, 80, 50, 20, 10, 0, 0, 0], dtype=np.dtype("i1")))
+        np.testing.assert_equal(result[1].samples, np.array([10, 50, 80, 50, 20, 0, 0, 0], dtype=np.dtype("i1")))
 
     @slow
     def test_large_align(self):
@@ -35,7 +33,7 @@ class AlignTests(Plottable):
 
     def test_peak_align(self):
         first_arr = np.array([10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10], dtype=np.dtype("i1"))
-        second_arr = np.array([10, 10, 10, 10, 90, 40, 50, 20, 10, 17, 16, 10, 10], dtype=np.dtype("i1"))
+        second_arr = np.array([10, 10, 10, 10, 90, 40, 50, 20, 10, 17, 16, 10], dtype=np.dtype("i1"))
         a = Trace(first_arr)
         b = Trace(second_arr)
         result = align_peaks(a, b, reference_offset=2, reference_length=5, max_offset=3)
@@ -43,7 +41,7 @@ class AlignTests(Plottable):
 
     def test_sad_align(self):
         first_arr = np.array([10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10], dtype=np.dtype("i1"))
-        second_arr = np.array([10, 10, 10, 10, 90, 40, 50, 20, 10, 17, 16, 10, 10], dtype=np.dtype("i1"))
+        second_arr = np.array([10, 10, 90, 40, 50, 20, 10, 17, 16, 10, 10], dtype=np.dtype("i1"))
         a = Trace(first_arr)
         b = Trace(second_arr)
         result = align_sad(a, b, reference_offset=2, reference_length=5, max_offset=3)
@@ -51,7 +49,7 @@ class AlignTests(Plottable):
 
     def test_dtw_align_scale(self):
         first_arr = np.array([10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10, 8, 10, 12, 10, 13, 9], dtype=np.dtype("i1"))
-        second_arr = np.array([10, 10, 10, 10, 60, 40, 90, 20, 10, 17, 16, 10, 10, 10, 10, 10, 17, 12, 10], dtype=np.dtype("i1"))
+        second_arr = np.array([10, 10, 60, 40, 90, 20, 10, 17, 16, 10, 10, 10, 10, 10, 17, 12, 10], dtype=np.dtype("i1"))
         third_arr = np.array([10, 30, 20, 21, 15, 8, 10, 37, 21, 77, 20, 28, 25, 10, 9, 10, 15, 9, 10], dtype=np.dtype("i1"))
         a = Trace(first_arr)
         b = Trace(second_arr)
@@ -64,7 +62,7 @@ class AlignTests(Plottable):
 
     def test_dtw_align(self):
         first_arr = np.array([10, 64, 14, 120, 15, 30, 10, 15, 20, 15, 15, 10, 10, 8, 10, 12, 10, 13, 9], dtype=np.dtype("i1"))
-        second_arr = np.array([10, 10, 10, 10, 60, 40, 90, 20, 10, 17, 16, 10, 10, 10, 10, 10, 17, 12, 10], dtype=np.dtype("i1"))
+        second_arr = np.array([10, 10, 60, 40, 90, 20, 10, 17, 16, 10, 10, 10, 10, 10, 17, 12, 10], dtype=np.dtype("i1"))
         third_arr = np.array([10, 30, 20, 21, 15, 8, 10, 47, 21, 77, 20, 28, 25, 10, 9, 10, 15, 9, 10], dtype=np.dtype("i1"))
         a = Trace(first_arr)
         b = Trace(second_arr)