90 lines
3.6 KiB
Diff
90 lines
3.6 KiB
Diff
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From 740fcd0da87d3aefa41aa3962cc8f1ddb7ab3cab Mon Sep 17 00:00:00 2001
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From: Doug Burke <dburke@cfa.harvard.edu>
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Date: Tue, 20 Jun 2023 15:31:55 -0400
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Subject: [PATCH] NumPy 1.25 support
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NumPy 1.25 deprecates converting a ndarray that is not a 0d value,
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so for our cases this is
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int(value)
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info("message %g", value)
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where value is a ndarray of length 1. The simple fix is to explictly
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access the first element - so
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answer = int(value[0])
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info("message %g", value[0])
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although for the int case (in the PSF convolution instrument code) I
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have not looked through to determine if value is always guaranteed to
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be a ndarray, so it is more like
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if np.isscalar(value):
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newval = value
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else:
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newval = value[0]
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answer = int(newval)
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---
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sherpa/fit.py | 13 +++++++++----
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sherpa/instrument.py | 12 ++++++++++--
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2 files changed, 19 insertions(+), 6 deletions(-)
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Index: sherpa-4.15.1/sherpa/fit.py
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===================================================================
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--- sherpa-4.15.1.orig/sherpa/fit.py
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+++ sherpa-4.15.1/sherpa/fit.py
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@@ -1258,8 +1258,13 @@ class Fit(NoNewAttributesAfterInit):
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def get_par_name(ii):
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return self.model.pars[self.thaw_indices[ii]].fullname
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- # Call from a parameter estimation method, to report
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- # that limits for a given parameter have been found
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+ # Call from a parameter estimation method, to report that
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+ # limits for a given parameter have been found At present (mid
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+ # 2023) it looks like lower/upper are both single-element
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+ # ndarrays, hence the need to convert to a scalar by accessing
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+ # the first element (otherwise there's a deprecation warning
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+ # from NumPy 1.25).
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+ #
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def report_progress(i, lower, upper):
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if i < 0:
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pass
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@@ -1268,11 +1273,11 @@ class Fit(NoNewAttributesAfterInit):
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if isnan(lower) or isinf(lower):
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info("%s \tlower bound: -----" % name)
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else:
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- info("%s \tlower bound: %g" % (name, lower))
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+ info("%s \tlower bound: %g" % (name, lower[0]))
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if isnan(upper) or isinf(upper):
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info("%s \tupper bound: -----" % name)
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else:
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- info("%s \tupper bound: %g" % (name, upper))
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+ info("%s \tupper bound: %g" % (name, upper[0]))
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# If starting fit statistic is chi-squared or C-stat,
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# can calculate reduced fit statistic -- if it is
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Index: sherpa-4.15.1/sherpa/instrument.py
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===================================================================
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--- sherpa-4.15.1.orig/sherpa/instrument.py
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+++ sherpa-4.15.1/sherpa/instrument.py
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@@ -357,9 +357,17 @@ class PSFKernel(Kernel):
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# and Python 3.8 - causes a TypeError with the message
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# "only integer scalar arrays can be converted to a scalar index"
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# to be thrown here if sent directly to set_origin. So
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- # we convert to a Python integer type.
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+ # we convert to a Python integer type. In NumPy 1.25 it became
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+ # a deprecation error to call int on an array with ndim > 0.
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#
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- origin = set_origin(kshape, int(brightPixel))
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+ # assume there is only one element in brightPixel if not
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+ # a scalar
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+ #
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+ if not numpy.isscalar(brightPixel):
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+ loc = brightPixel[0]
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+ else:
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+ loc = brightPixel
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+ origin = set_origin(kshape, int(loc))
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if self.origin is None:
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self.origin = origin
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