dangom

;; modify ob-js to redirect to skewer if it is currently connected
;; this code can go in an emacs settings file

(require 'ob-js)
(require 'cl)
(advice-add 'org-babel-execute:js :around 'bill/org-babel-execute:skewer)
;;(advice-remove 'org-babel-execute:js #'bill/org-babel-execute:skewer)
(defun bill/org-babel-execute:skewer (oldFunc body params)
  (if (skewer-ping)
      (lexical-let* ((result-type (cdr (assoc :result-type params)))

dangom

Keybase proof

I hereby claim:

• I am dangom on github.
• I am dangom (https://keybase.io/dangom) on keybase.
• I have a public key ASBKgWA4c8boXP8dXRDZtHTRQ9v9JGGiwsVY8x8Dg1br3Qo

To claim this, I am signing this object:

dangom

#! /usr/bin/python
#
# Author: Gaute Hope ([email protected]) / 2015
#
# based on example from matlab sinc function and
# interpolate.m by H. Hobæk (1994).
#
# this implementation is similar to the matlab sinc-example, but
# calculates the values sequentially and not as a single matrix
# matrix operation for all the values.

dangom

How to install Matlab Engine on Python 3.6

Preparation

If you’ve tried recently to install matlab engine on a Python 3.6, you’ve seen a message saying that the platform is not supported. That doesn’t make any sense, since Python 3.5 is supported, right?

The problem is that Mathworks hardcodes a list with valid versions, I guess to reduce pressure on their customer service in case something goes wrong with untested versions. Well, that doesn’t mean that we shouldn’t be allowed to try it anyway, right?

dangom

#!/bin/bash
# Time-stamp: <2017-07-19 15:06:39 dangom>
# Script for installing BART and dependencies from source on a CentOS machine without admin rights.

# Steps:
# 1. Build OpenBLAS from source to enable support for LAPACKE C API.
# 2. Build FFTW3 from source to enable float32 support (fftw defaults to double precision. BART doesn't)
# 3. Link against Matlab2016, because something changed in Matlab2017 and the BART build breaks.
# 4. Download Cmake >= 3 since cluster ships with old cmake 2.8

dangom

"""
Partial Correlation in Python (clone of Matlab's partialcorr)

This uses the linear regression approach to compute the partial 
correlation (might be slow for a huge number of variables). The 
algorithm is detailed here:

    http://en.wikipedia.org/wiki/Partial_correlation#Using_linear_regression

Taking X and Y two variables of interest and Z the matrix with all the variable minus {X, Y},

dangom

#!/bin/bash

## cf from http://programster.blogspot.com/2014/05/ubuntu-14-desktop-install-fira-sans-and.html

cd /tmp

# install unzip just in case the user doesn't already have it.
if [[ `uname` = Linux ]]; then
    sudo apt-get install unzip -y
    wget "http://www.carrois.com/downloads/fira_4_1/FiraFonts4106.zip"

dangom

# Add field
echo '{"hello": "world"}' | jq --arg foo bar '. + {foo: $foo}'
# {
#   "hello": "world",
#   "foo": "bar"
# }

# Override field value
echo '{"hello": "world"}' | jq --arg foo bar '. + {hello: $foo}'
{

dangom

import subprocess
import io
import pandas as pd

# The fslcc binary to use
FSLCC = '/opt/fsl/5.0.11/bin/fslcc'

# Parameters for the command line. No thresholding, report 4 digits.
FSLCC_PARAMS = ['-t', '0', '-p', '4']

dangom

# By Jake VanderPlas
# License: BSD-style

import matplotlib.pyplot as plt
import numpy as np


def discrete_cmap(N, base_cmap=None):
    """Create an N-bin discrete colormap from the specified input map"""