| import numpy as np | |
| def clean_cholesky(chi): | |
| """Converts a random complex-valued matrix which has a shape | |
| (N, N) to a Hermitian matrix. | |
| Args: | |
| chi (array (complex)): A matrix of shape (N, N). |
| import numpy as np | |
| from qutip.wigner import wigner | |
| from qutip import coherent, squeeze, destroy, displace | |
| import matplotlib.pyplot as plt | |
| from matplotlib import colors | |
| def cubic(initial_state, squeezing, gamma): |
| " Use vim-plug | |
| call plug#begin('~/.local/share/nvim/plugged') | |
| Plug 'Shougo/deoplete.nvim', { 'do': ':UpdateRemotePlugins' } | |
| Plug 'zchee/deoplete-jedi' | |
| Plug 'Shougo/echodoc.vim' | |
| Plug 'junegunn/fzf', { 'dir': '~/.fzf', 'do': './install --all' } | |
| Plug 'junegunn/fzf.vim' | |
| Plug 'scrooloose/nerdcommenter' | |
| Plug 'vim-airline/vim-airline' | |
| Plug 'vim-airline/vim-airline-themes' |
-Shahnawaz Ahmed ([email protected])
Dipy is a python library for analysis of diffusion-weighted MRI (dMRI). Diffusion patterns can reveal microscopic details about tissue architecture and is used in clinical as well as neuroscience research. The intra-voxel incoherent motion (IVIM) model describes diffusion and perfusion in the signal acquired with diffusion MRI as :