- Add link to the proper build instructions on MediaWiki (remove existing content)
- Merge build instructions on Github wiki
- Update build instructions to use brew MantidDeveloper package.
- Move Github wiki build instructions into the
mantid/docs
. - Create bottles for packages we manage
- Converting script to python or cmake.
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import matplotlib.pyplot as plt | |
from pathlib import Path, PurePath | |
from image import ImageLoader, Regrid | |
from skimage.transform import resize | |
from skimage.exposure import exposure | |
import numpy as np | |
import sys | |
from PIL import Image as PillowImage | |
from PIL import ImageEnhance | |
import skimage |
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diff --git a/MantidPlot/make_package.rb.in b/MantidPlot/make_package.rb.in | |
index acdb31e30f..672bf3f3b6 100755 | |
--- a/MantidPlot/make_package.rb.in | |
+++ b/MantidPlot/make_package.rb.in | |
@@ -72,7 +72,7 @@ library_filenames = ["libboost_regex-mt.dylib", | |
"libTKGeomBase.dylib", | |
"libqwt.dylib", | |
"libqwtplot3d.dylib", | |
- "libqscintilla2.dylib", | |
+ "libqscintilla2_qt4.dylib", |
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def printname(func): | |
""" | |
Prints the name of a decorated method | |
This can be useful for debugging unit tests which | |
interfere with each other. | |
""" | |
def wrapper(self): | |
print func.__name__ | |
return func(self) |
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#!/usr/bin/env python | |
import sys | |
import subprocess | |
import os | |
import re | |
import tempfile | |
def run_command(command): | |
try: |
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QPainterPath path; | |
std::sort(points.begin(), points.end(), | |
[](const QPointF& p1, const QPointF& p2) -> bool | |
{ | |
return p1.x() < p2.x(); | |
}); | |
constexpr auto step = 100.0; |
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#!/usr/bin/env python | |
import requests | |
import sys | |
import subprocess | |
import os | |
import tempfile | |
def get_build_list(): | |
contents = get_json_data("http://builds.mantidproject.org/job/pull_requests-clang-format/api/json?pretty=true") | |
if 'builds' in contents.keys(): |
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from sklearn import cross_validation | |
from sklearn import metrics | |
from sklearn.pipeline import Pipeline | |
import numpy as np | |
import collections | |
def repeated_cross_fold_validation(models, X, y, n=10, k=5, cv=None, | |
score_function=metrics.accuracy_score): | |
""" Run cross validation on a set of models n times |
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