次のものがインストールされているPCを用意してください。
- OSはWindows/Mac/Ubuntuのいずれか(それ以外のものは講師が対応出来ない可能性がありますので、自己責任でお願いします)
- Python3.4.0以降のバージョン
- NumPy, SciPy, matplotlib, scikit-learn
- テキストエディタやIDEでPythonに対応したもの
# ランダムに円を100個描いたSVGファイルを作成します。 | |
import svgwrite | |
import random | |
drawing = svgwrite.Drawing("a.svg", size=("400px", "400px")) | |
s = dict(stroke=svgwrite.rgb(0,0,0,"%"), fill="white") | |
for _ in range(100): | |
x = random.randrange(0,400) |
import bottle | |
app = bottle.Bottle() | |
s = """<p>名前は?</p> | |
<p> | |
<form method="GET" action="/get""> | |
<input type="text" name="a" /> | |
<input type="submit" /> | |
</form> | |
</p>""" |
# Reuters-21578 dataset downloader and parser | |
# | |
# Author: Eustache Diemert <eustache@diemert.fr> | |
# http://scikit-learn.org/stable/auto_examples/applications/plot_out_of_core_classification.html | |
# | |
# Modified by @herrfz, get pandas DataFrame from the orig SGML | |
# License: BSD 3 clause | |
from __future__ import print_function |
#!/usr/bin/env python | |
import numpy as np | |
import mcpi | |
import mcpi.block | |
import mcpi.minecraft | |
def line(mc, v1, v2): | |
v = v2 - v1 | |
norm = np.sqrt((v**2).sum()) |
#!/usr/bin/env python | |
"This program draws a Koch curve in Minecraft" | |
import mcpi | |
import mcpi.block | |
import mcpi.minecraft | |
import numpy as np | |
LIMIT = 7 |
#!/usr/bin/env python | |
"This program makes a cone in Minecraft" | |
import mcpi | |
import mcpi.block | |
import mcpi.minecraft | |
import numpy as np | |
def disk(mc, cx, cy, cz, r): |
{ | |
"metadata": { | |
"name": "", | |
"signature": "sha256:89cf919bf95aa5890f6bfdfaeb3326b0387784bdc70d5b96e515bfffdae2d9ab" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ |
{ | |
"metadata": { | |
"name": "" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ |
diff -u -r cnn_orig/convolutional_mlp.py cnn/convolutional_mlp.py | |
--- cnn_orig/convolutional_mlp.py 2014-08-08 12:15:47.412611962 +0900 | |
+++ cnn/convolutional_mlp.py 2014-08-08 12:18:02.684614501 +0900 | |
@@ -37,6 +37,18 @@ | |
from logistic_sgd import LogisticRegression, load_data | |
from mlp import HiddenLayer | |
+from PIL import Image | |
+ | |
+def pack(m,n,a): |