1 files changed, 103 insertions, 0 deletions
diff --git a/pyecsca/sca/process.py b/pyecsca/sca/process.py
new file mode 100644
index 0000000..8e983b2
--- /dev/null
+++ b/pyecsca/sca/process.py
@@ -0,0 +1,103 @@
+import numpy as np
+from copy import copy
+from public import public
+
+from .trace import Trace
+
+
+@public
+def absolute(trace: Trace) -> Trace:
+    """
+    Apply absolute value to samples of `trace`.
+
+    :param trace:
+    :return:
+    """
+    return Trace(copy(trace.title), copy(trace.data), np.absolute(trace.samples))
+
+
+@public
+def invert(trace: Trace) -> Trace:
+    """
+    Invert(negate) the samples of `trace`.
+
+    :param trace:
+    :return:
+    """
+    return Trace(copy(trace.title), copy(trace.data), np.negative(trace.samples))
+
+
+@public
+def threshold(trace: Trace, value) -> Trace:
+    """
+    Map samples of the `trace` to 1 if they are above `value` or to 0.
+
+    :param trace:
+    :param value:
+    :return:
+    """
+    result_samples = trace.samples.copy()
+    result_samples[result_samples <= value] = 0
+    result_samples[np.nonzero(result_samples)] = 1
+    return Trace(copy(trace.title), copy(trace.data), result_samples)
+
+
+def rolling_window(samples: np.ndarray, window: int) -> np.ndarray:
+    shape = samples.shape[:-1] + (samples.shape[-1] - window + 1, window)
+    strides = samples.strides + (samples.strides[-1],)
+    return np.lib.stride_tricks.as_strided(samples, shape=shape, strides=strides)
+
+
+@public
+def rolling_mean(trace: Trace, window: int) -> Trace:
+    """
+    Compute the rolling mean of `trace` using `window`. Shortens the trace by `window` - 1.
+
+    :param trace:
+    :param window:
+    :return:
+    """
+    return Trace(copy(trace.title), copy(trace.data),
+                 np.mean(rolling_window(trace.samples, window), -1).astype(
+                         dtype=trace.samples.dtype))
+
+
+@public
+def offset(trace: Trace, offset) -> Trace:
+    """
+    Offset samples of `trace` by `offset`, sample-wise (Adds `offset` to all samples).
+
+    :param trace:
+    :param offset:
+    :return:
+    """
+    return Trace(copy(trace.title), copy(trace.data), trace.samples + offset)
+
+
+def root_mean_square(trace: Trace):
+    return np.sqrt(np.mean(np.square(trace.samples)))
+
+
+@public
+def recenter(trace: Trace) -> Trace:
+    """
+    Subtract the root mean square of the `trace` from its samples, sample-wise.
+
+    :param trace:
+    :return:
+    """
+    around = root_mean_square(trace)
+    return offset(trace, -around)
+
+
+@public
+def normalize(trace: Trace) -> Trace:
+    return Trace(copy(trace.title), copy(trace.data),
+                 (trace.samples - np.mean(trace.samples)) / np.std(trace.samples))
+
+
+@public
+def normalize_wl(trace: Trace) -> Trace:
+    return Trace(copy(trace.title), copy(trace.data),
+                 (trace.samples - np.mean(trace.samples)) / (
+                         np.std(trace.samples) * len(trace.samples)))