benjaminhwilliams

hdf5_in_memory = {"driver": "core", "backing_store": False}

with h5py.File(" ", mode="w", **hdf5_in_memory) as f:
    ...

benjaminhwilliams

import math

from dxtbx.format.FormatNXmxDLSI19_2 import FormatNXmxDLSI19_2
from dxtbx.masking import GoniometerMaskerFactory


class FormatNXmxDLSI19_2_CustomDAC(FormatNXmxDLSI19_2):
    """
    Read NXmx-flavour data from beamline I19-2 at Diamond Light Source.

benjaminhwilliams

#!/bin/bash
#SBATCH --nodes=1
#SBATCH --cpus-per-task=20
#SBATCH --time=04:00:00
#SBATCH --error=job-%J.err
#SBATCH --output=job-%J.out
#SBATCH -A i19-1
#SBATCH -p cs05r
echo "Hello world!"

benjaminhwilliams

"""
Create a conical shadow mask for NXmx-flavour NeXus image data.

From a NXmx NeXus-format HDF5 data file, compute a stack of mask frames corresponding
to the shadow on the detector of a circular object or aperture that rotates with the
sample.  This might be used to mask the anvils of a diamond anvil pressure cell or
the sample mount assembly in a complex goniometer apparatus.

It is assumed that the shadowed region is bounded by a double cone, with the apex at
the lab frame origin.  You must specify the cones' axis as a vector, and aperture (twice

benjaminhwilliams

from tqdm import tqdm
from dask import diagnostics


class TqdmLikeDask(tqdm):
    """A tqdm progress bar with a format that mimics Dask Distributed's 'progress'."""

    @staticmethod
    def format_interval(t):
        return diagnostics.progress.format_time(t)

benjaminhwilliams

#!dials.python
# -*- coding:utf-8 -*-

# The lines above just let your computer know how to read this file and
# that this program should be run with the in-built dials python distribution.

u"""
Filter background pixels from signal pixels

This program separates pixels that are likely to be part of reflections