StephenSmith25

from distutils.core import setup

setup(name='versionupdater',
      version='1.0',
      description='Updatess',
      author='Me',
      author_email='..',
      license='BSD-3'
      entry_points={
        'console_scripts': [

StephenSmith25

name: mantid-python

channels:
  - conda-forge

dependencies:
  - euphonic=0.6.*
  - h5py>=2.10.0,<3 
  - ipykernel<6 
  - numpy>=1.20.2

StephenSmith25

# Implementation of searching for QScintilla. It contains a function
# parameterized by the major version of Qt to be linked against.
#
# The function creates an imported target prefixed in a similar manner
# to the Qt4/Qt5 targets.

if ( NOT Qt5_FOUND)
    message ( FATAL_ERROR "find_package ( Qt5 ...) must be called first" )
endif()
    set ( _qsci_lib_names

StephenSmith25

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
import numpy as np
import scipy as sp


def residual(a, b):
   x, y = data
   f = y-a+b*x

StephenSmith25

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
import numpy as np
import lmfit

# create decaying exponential data
x = np.linspace(1, 10, 250)
np.random.seed(0)
y = 3.0*np.exp(-x/2) + 0.1*np.random.randn(x.size)

StephenSmith25

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
import numpy as np
import lmfit

# create decaying exponential data
x = np.linspace(1, 10, 250)
np.random.seed(0)
y = 3.0*np.exp(-x/2) + 0.1*np.random.randn(x.size)

StephenSmith25

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
from scipy import stats
import numpy as np
import lmfit

np.random.seed(10)
x = np.linspace(0, 10, 100)
y = 2*x + 1 + 0.2*np.random.randn(x.size)

StephenSmith25

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
import numpy as np
from numpy import exp, loadtxt, pi, sqrt
from lmfit import Model

def gaussian(x, amp, cen, wid):
    return amp * exp(-0.5*(x-cen)**2 / wid**2)

StephenSmith25

Minutes

Mantid PMB Meeting 17

Minutes of: 2020-08-24 UTC12:00-14:00

In Attendance:

* CSNS - Junrong Zhang