From 442559ae50633bbead9ca7638607ecf2d01f3ba8 Mon Sep 17 00:00:00 2001 From: Pierre Raybaut Date: Fri, 2 Aug 2024 14:30:27 +0200 Subject: [PATCH] Remove unnecessary warning catch following plotpy verrsion upgrade --- CHANGELOG.md | 1 - cdl/computation/image/__init__.py | 8 +------- 2 files changed, 1 insertion(+), 8 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 018e1424..009854e7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -33,7 +33,6 @@ See DataLab [roadmap page](https://datalab-platform.com/en/contributing/roadmap. * Intensity profile / Segment profile extraction: * When extracting a profile on an image with a ROI defined, the associated PlotPy feature show a warning message ('UserWarning: Warning: converting a masked element to nan.') but the profile is correctly extracted and displayed, with NaN values where the ROI is not defined. - * This warning message will persist until PlotPy v2.5.2 is released * NaN values are now removed from the profile before plotting it * Simple processing features with a one-to-on mapping with a Python function (e.g. `numpy.absolute`, `numpy.log10`, etc.) and without parameters: fix result object title which was systematically ending with "|" (the character that usually precedes the list of parameters) * Butterworth filter: fix cutoff frequency ratio default value and valid range diff --git a/cdl/computation/image/__init__.py b/cdl/computation/image/__init__.py index 45fe93d0..26740325 100644 --- a/cdl/computation/image/__init__.py +++ b/cdl/computation/image/__init__.py @@ -12,7 +12,6 @@ from __future__ import annotations -import warnings from collections.abc import Callable from typing import Any, Literal @@ -867,12 +866,7 @@ def compute_segment_profile(src: ImageObj, p: SegmentProfileParam) -> ImageObj: p.row2 = min(p.row2, data.shape[0] - 1) p.col2 = min(p.col2, data.shape[1] - 1) suffix = f"({p.row1}, {p.col1})-({p.row2}, {p.col2})" - - # TODO: Remove the warning catch when upgrading to PlotPy >= 2.5.2 - with warnings.catch_warnings(): - warnings.simplefilter("ignore", UserWarning) - x, y = csline(data, p.row1, p.col1, p.row2, p.col2) - + x, y = csline(data, p.row1, p.col1, p.row2, p.col2) x, y = x[~np.isnan(y)], y[~np.isnan(y)] # Remove NaN values dst = dst_11_signal(src, "segment_profile", suffix) dst.set_xydata(np.array(x, dtype=float), np.array(y, dtype=float))