From b5093c94cef0c77aa62b85f0a2e0518e7e7a7c20 Mon Sep 17 00:00:00 2001
From: Leo Fang <leofang@bnl.gov>
Date: Mon, 18 May 2020 16:10:39 -0400
Subject: [PATCH 1/6] fix NEP-18
---
autocorr/multitau.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/autocorr/multitau.py b/autocorr/multitau.py
index 1b0bd1cd..17594edb 100644
--- a/autocorr/multitau.py
+++ b/autocorr/multitau.py
@@ -44,8 +44,8 @@ def even(x):
# calculate levels
levels = np.int_(np.log2(N / m)) + 1
dims = (a.shape[0], (levels + 1) * (m // 2))
- g2 = np.zeros(dims, dtype=np.float32)
- tau = np.zeros(dims[1], dtype=np.float32)
+ g2 = np.zeros_like(a, shape=dims, dtype=np.float32)
+ tau = np.zeros_like(a, shape=(dims[1],), dtype=np.float32)
# zero level
delta_t = 1
From 6da3e063ba15c0b83fe9c5e7b1c06d3138d021f3 Mon Sep 17 00:00:00 2001
From: Leo Fang <leofang@bnl.gov>
Date: Mon, 18 May 2020 23:41:22 -0400
Subject: [PATCH 2/6] Use recent NumPy to support NEP-18
---
requirements.txt | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/requirements.txt b/requirements.txt
index 163fdd06..1b4707e5 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,2 +1,2 @@
-numpy
+numpy >=1.17
pybind11
From 3181e20c338bbb0a172438321d9e4694171a6336 Mon Sep 17 00:00:00 2001
From: tankonst <tatiana.v.konst@gmail.com>
Date: Sun, 16 Aug 2020 12:12:31 -0400
Subject: [PATCH 3/6] adding function for calculating the entire ROI
---
autocorr/multitau_roi.py | 78 ++++++++++++++++++++++++++++++++++++++++
1 file changed, 78 insertions(+)
create mode 100755 autocorr/multitau_roi.py
diff --git a/autocorr/multitau_roi.py b/autocorr/multitau_roi.py
new file mode 100755
index 00000000..d3318a95
--- /dev/null
+++ b/autocorr/multitau_roi.py
@@ -0,0 +1,78 @@
+import numpy as np
+
+
+def multitau(signal, lags_per_level=16):
+ """Autocorrelation of a signal using multi-tau method.
+
+ For details, please refer to D. Magatti and F. Ferri doi:10.1364/ao.40.004011
+
+ Parameters
+ ----------
+ signal: 2-D array
+ input signal, autocorrlation is calulated along `1-axis`
+ lags_per_level: integer, optional
+ number of lag-times per level, 16 is a as good number as any other
+
+ Returns:
+ --------
+ autocorrelations: numpy.ndarray
+ should be self-explanatory
+ lag-times: numpy.ndarray
+ lag times in log2, corresponding to autocorrelation values
+ """
+ # if N is add subtract 1
+ def even(x):
+ return x if x % 2 == 0 else x - 1
+
+ # 1-D data hack
+ if signal.ndim == 1:
+ N = even(signal.shape[0])
+ a = signal[np.newaxis, :N]
+ elif signal.ndim == 2:
+ # copy data a local array
+ N = even(signal.shape[1])
+ a = signal[:, :N]
+ elif signal.ndim > 2:
+ raise ValueError('Flatten the [2,3,..] dimensions before passing to autocorrelate.')
+
+ if N < lags_per_level:
+ raise ValueError('Lag times per level must be greater than length of signal.')
+
+ # shorthand for long names
+ m = lags_per_level
+
+ # calculate levels
+ levels = np.int_(np.log2(N / m)) + 1
+ dims = (a.shape[0], (levels + 1) * (m // 2))
+ g2 = np.zeros_like(a, shape=(dims[1],), dtype=np.float32)
+ tau = np.zeros_like(a, shape=(dims[1],), dtype=np.float32)
+
+ # zero level
+ delta_t = 1
+ for i in range(m):
+ tau[i] = i * delta_t
+ d = a.shape[0]
+ t1 = np.mean(a[:, :N - i])
+ t2 = np.mean(a[:, i:])
+ cov = np.diagonal(a[:, :-i].T @ a[:, i:])
+ g2[i] = np.mean(cov) / t1 / t2/ d
+ a = (a[:, :N:2] + a[:, 1:N:2]) / 2
+ N = even(N // 2)
+
+ for level in range(1, levels):
+ delta_t *= 2
+ for n in range(m // 2):
+ idx = m + (level - 1) * (m // 2) + n
+ shift = m // 2 + n
+ tau[idx] = tau[idx - 1] + delta_t
+ d = a.shape[0]
+ t1 = np.mean(a[:, :-shift])
+ t2 = np.mean(a[:, shift:])
+ cov = np.diagonal(a[:, :-shift].T @ a[:, shift:])
+ g2[idx] = np.mean(cov) / t1 / t2/ d
+ a = (a[:, :N:2] + a[:, 1:N:2]) / 2
+ N = even(N // 2)
+ if N < lags_per_level:
+ break
+
+ return g2, tau
From a59fca9cc36d7cd160a94691db41cc626c7be39f Mon Sep 17 00:00:00 2001
From: tankonst <tatiana.v.konst@gmail.com>
Date: Sun, 16 Aug 2020 12:34:40 -0400
Subject: [PATCH 4/6] fixing __init__.py
---
autocorr/__init__.py | 1 +
1 file changed, 1 insertion(+)
diff --git a/autocorr/__init__.py b/autocorr/__init__.py
index 36d6c5a7..4911847f 100644
--- a/autocorr/__init__.py
+++ b/autocorr/__init__.py
@@ -3,6 +3,7 @@
from .multitau import multitau
+from .multitau_roi import multitau_roi
from .fftautocorr import fftautocorr # noqa
from .cAutocorr import fftautocorr as fftautocorr_mt # noqa
try:
From ce452918279e04cbce88ef7aadafd76c357761d4 Mon Sep 17 00:00:00 2001
From: tankonst <tatiana.v.konst@gmail.com>
Date: Sun, 16 Aug 2020 12:46:51 -0400
Subject: [PATCH 5/6] fixing __init__.py and multitau_roi.py
---
autocorr/__init__.py | 2 +-
autocorr/multitau_roi.py | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/autocorr/__init__.py b/autocorr/__init__.py
index 4911847f..745636c3 100644
--- a/autocorr/__init__.py
+++ b/autocorr/__init__.py
@@ -5,7 +5,7 @@
from .multitau import multitau
from .multitau_roi import multitau_roi
from .fftautocorr import fftautocorr # noqa
-from .cAutocorr import fftautocorr as fftautocorr_mt # noqa
+# from .cAutocorr import fftautocorr as fftautocorr_mt # noqa
try:
from .cAutocorr import multitau_mt
except ImportError:
diff --git a/autocorr/multitau_roi.py b/autocorr/multitau_roi.py
index d3318a95..09dc332e 100755
--- a/autocorr/multitau_roi.py
+++ b/autocorr/multitau_roi.py
@@ -1,7 +1,7 @@
import numpy as np
-def multitau(signal, lags_per_level=16):
+def multitau_roi(signal, lags_per_level=16):
"""Autocorrelation of a signal using multi-tau method.
For details, please refer to D. Magatti and F. Ferri doi:10.1364/ao.40.004011
From aac84eb5bb8eb637d8af106515c34bf94185390f Mon Sep 17 00:00:00 2001
From: tankonst <tatiana.v.konst@gmail.com>
Date: Sun, 16 Aug 2020 14:38:28 -0400
Subject: [PATCH 6/6] Corrected zero-sized arrays warning
---
autocorr/multitau_roi.py | 10 ++++++----
1 file changed, 6 insertions(+), 4 deletions(-)
diff --git a/autocorr/multitau_roi.py b/autocorr/multitau_roi.py
index 09dc332e..4ab6245c 100755
--- a/autocorr/multitau_roi.py
+++ b/autocorr/multitau_roi.py
@@ -52,10 +52,11 @@ def even(x):
for i in range(m):
tau[i] = i * delta_t
d = a.shape[0]
- t1 = np.mean(a[:, :N - i])
+ t1 = np.mean(a[:, : N - i])
t2 = np.mean(a[:, i:])
- cov = np.diagonal(a[:, :-i].T @ a[:, i:])
+ cov = np.diagonal(a[:, :N-i].T @ a[:, i:])
g2[i] = np.mean(cov) / t1 / t2/ d
+
a = (a[:, :N:2] + a[:, 1:N:2]) / 2
N = even(N // 2)
@@ -66,10 +67,11 @@ def even(x):
shift = m // 2 + n
tau[idx] = tau[idx - 1] + delta_t
d = a.shape[0]
- t1 = np.mean(a[:, :-shift])
+ t1 = np.mean(a[:, : N -shift])
t2 = np.mean(a[:, shift:])
- cov = np.diagonal(a[:, :-shift].T @ a[:, shift:])
+ cov = np.diagonal(a[:, : N-shift].T @ a[:, shift:])
g2[idx] = np.mean(cov) / t1 / t2/ d
+
a = (a[:, :N:2] + a[:, 1:N:2]) / 2
N = even(N // 2)
if N < lags_per_level: