swayson

10 Rules of Good Studying:

• Use recall. After you read a page, look away and recall the main ideas. Highlight very little, and never highlight anything you haven’t put in your mind first by recalling. Try recalling main ideas when you are walking to class or in a different room from where you originally learned it. An ability to recall—to generate the ideas from inside yourself—is one of the key indicators of good learning.
• Test yourself. On everything. All the time. Flash cards are your friend.
• Chunk your problems. Chunking is understanding and practicing with a problem solution so that it can all come to mind in a flash. After you solve a problem, rehearse it. Make sure you can solve it cold—every step. Pretend it’s a song and learn to play it over and over again in your mind, so the information combines into one smooth chunk you can pull up whenever you want.
• Space your repetition. Spread out your learning in any subject a little every day, just like an athlete. Your brain is like a muscle—it ca

swayson

You are a helpful assistant who follow instructions. Assume you are working with an adult.

To replicate the process of "Dialectic into Dia-logos" as outlined by John Vervaeke and Guy Sengstock, here’s a step-by-step guide:

1. Set the Foundation: Establish a Safe and Open Space
   Begin by creating a space where participants feel safe, vulnerable, and open to sharing. This is crucial because Dialectic into Dia-logos requires a high level of trust, curiosity, and authenticity. Encourage participants to leave behind any need to "win" arguments or persuade others. The goal is to seek understanding, not resolution​(

2. Engage in Dialectic
   The process starts with a Socratic dialectic: a structured dialogue where participants collaboratively investigate a question or idea. Each participant tracks the flow of the conversation (the logos), allowing new insights to emerge naturally rather than forcing conclusions. In this stage, virtues such as humility, courage, and openness to change

swayson

library(tidyverse)
airquality %>%
  group_by(Month) %>%
  summarise(average_temperature = mean(Temp)) %>%
  ggplot(aes(x=Month, y=average_temperature)) +
  geom_bar(stat='identity', position = 'dodge') + 
  geom_text(aes(label=round(average_temperature, 0)), position=position_dodge(width=0.9), vjust=-0.5) + 
  labs(x='Month', y='Average temperature', title='Average temperature per month') + 
  theme_minimal() + 
  theme(plot.background = element_blank(),

swayson

Map	Action
<F1>	Causes Netrw to issue help
<cr>	Netrw will enter the directory or read the file
<del>	Netrw will attempt to remove the file/directory
-	Makes Netrw go up one directory
a	Toggles between normal display, hiding (suppress display of files matching g:netrw_list_hide) showing (display only files which match g:netrw_list_hide)
c	Make browsing directory the current directory
C	Setting the editing window
d	Make a directory

swayson

"""
Simple utility command line tool to list the sheet names of an Excel workbook.
"""
import argparse
from xlrd import open_workbook


def get_args():
    """This function parses and return command line arguments"""
    parser = argparse.ArgumentParser(description='List sheetnames in Excel workbook.')

swayson

# Ask for the user password
# Script only works if sudo caches the password for a few minutes
sudo true

# Install kernel extra's to enable docker aufs support
# sudo apt-get -y install linux-image-extra-$(uname -r)

# Add Docker PPA and install latest version
# sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 36A1D7869245C8950F966E92D8576A8BA88D21E9
# sudo sh -c "echo deb https://get.docker.io/ubuntu docker main > /etc/apt/sources.list.d/docker.list"

swayson

files = [path/to/file, path/to/file2, path/to/file3]
with zipfile.ZipFile('/tmp/test.zip', 'w', zipfile.ZIP_DEFLATED) as out_file:
    for rel_filename in files:
        absname = os.path.abspath(rel_filename)
        root = os.path.dirname(absname)
        filename  = os.path.relpath(rel_filename, root)
        out_file.write(rel_filename, filename)
        print(absname, root, filename)

swayson

import os
import click


def read_file(filename):
    with open(filename) as in_file:
         for line in in_file:
             if line.strip() != '':
                 yield line.strip()

swayson

"""
Specifically, the Kullback–Leibler divergence from Q to P, denoted DKL(P‖Q), is
a measure of the information gained when one revises one's beliefs from the
prior probability distribution Q to the posterior probability distribution P. In
other words, it is the amount of information lost when Q is used to approximate
P.
"""
import numpy as np
from scipy.stats import entropy

swayson

import numpy as np
from numpy.lib.stride_tricks import as_strided


def rolling_block(A, block=(3, 3)):
    shape = (A.shape[0] - block[0] + 1, A.shape[1] - block[1] + 1) + block
    strides = (A.strides[0], A.strides[1]) + A.strides
    return as_strided(A, shape=shape, strides=strides)

X = np.random.randint(0, 200, (10, 10))