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5,300 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Note
Step1: The ImageCollection class provides an easy way of
loading and representing multiple images. Images are not
read from disk until accessed.
Step2: Credit
Step3: For this demo, ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from skimage import io, transform
from skimage.color import rgb2gray
from skdemo import imshow_all
ic = io.ImageCollection('../images/pano/DFM_*')
Explanation: Note: This example has been significantly expanded and enhanced. The new, recommended version is... |
5,301 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2.3 Python语言基础
1 语言语义（Language Semantics）
缩进，而不是括号
Python使用空格（tabs or spaces)来组织代码结构，而不是像R，C++，Java那样用括号。
建议使用四个空格来作为默认的缩进，设置tab键为四个空格
另外可以用分号隔开多个语句：
Step1: 所有事物都是对象（object）
在python中，number... | Python Code:
a = 5; b = 6; c = 7
Explanation: 2.3 Python语言基础
1 语言语义（Language Semantics）
缩进，而不是括号
Python使用空格（tabs or spaces)来组织代码结构，而不是像R，C++，Java那样用括号。
建议使用四个空格来作为默认的缩进，设置tab键为四个空格
另外可以用分号隔开多个语句：
End of explanation
result = f(x, y, z)
Explanation: 所有事物都是对象（object）
在python中，number，string，data structure，function，class，mo... |
5,302 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Variables and 3D Shapes
In the last class we used functions and arguments to build circles, spheres and hollow spheres of different radii. Lets go ahead and build some 3D solid shapes as wel... | Python Code:
import sys
sys.path.append('/home/pi/minecraft-programming')
import mcpi.block as block
import time
import drawings
Explanation: Variables and 3D Shapes
In the last class we used functions and arguments to build circles, spheres and hollow spheres of different radii. Lets go ahead and build some 3D solid s... |
5,303 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sta 663 Final Project
by Hao Sheng, Xiaozhou Wang
netid
Step1: Benchmark of vectorization
Step2: As for the optimization, we employed vectorization to avoid the use of triple for-loops und... | Python Code:
import numpy as np
from numpy import random
from collections import deque
import matplotlib.pyplot as plt
import HMM
import pandas as pd
from hmmlearn import hmm
Explanation: Sta 663 Final Project
by Hao Sheng, Xiaozhou Wang
netid: hs220, xw106
email: {hao.sheng,xiaozhou.wang}@duke.edu
Please make sure you... |
5,304 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
用ConfigParser模块读写conf配置文件
ConfigParser是Python内置的一个读取配置文件的模块，用它来读取和修改配置文件非常方便，本文介绍一下它的基本用法。
数据准备
假设当前目录下有一个名为sys.conf的配置文件，其内容如下：
```bash
[db]
db_host=127.0.0.1
db_port=22
db_user=root
db_pas... | Python Code:
import ConfigParser
cf = ConfigParser.ConfigParser()
cf.read('./sys.conf')
Explanation: 用ConfigParser模块读写conf配置文件
ConfigParser是Python内置的一个读取配置文件的模块，用它来读取和修改配置文件非常方便，本文介绍一下它的基本用法。
数据准备
假设当前目录下有一个名为sys.conf的配置文件，其内容如下：
```bash
[db]
db_host=127.0.0.1
db_port=22
db_user=root
db_pass=root123
[concurrent]
thread... |
5,305 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Interrupts and asyncio for Buttons and Switches
This notebook provides a simple example for using asyncio I/O to interact asynchronously with multiple input devices. A task is created ... | Python Code:
from pynq import PL
from pynq.overlays.base import BaseOverlay
base = BaseOverlay("base.bit")
Explanation: Using Interrupts and asyncio for Buttons and Switches
This notebook provides a simple example for using asyncio I/O to interact asynchronously with multiple input devices. A task is created for each i... |
5,306 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building a System
Setup
Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to u... | Python Code:
!pip install -I "phoebe>=2.0,<2.1"
Explanation: Building a System
Setup
Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
End of explanation
import phoebe
from p... |
5,307 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Implicit generative model
An implicit generative model only provides us with samples. Here for simplicity, we use a different set of samples obtained from the data dis... | Python Code:
import random
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import scipy
sns.set(rc={"lines.linewidth": 2.8}, font_scale=2)
sns.set_style("whitegrid")
# We implement our own very simple mixture, relying on scipy for the mixture
# components.
class SimpleGaussianMixture(object):
... |
5,308 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Função para codificar rótulos inteiros na codificação one-hot
Esta função é também chamada de conversão para dados categóricos. Temos 3 classes de
flores
Step1: Primeira solução
Step2: Seg... | Python Code:
import numpy as np
Explanation: Função para codificar rótulos inteiros na codificação one-hot
Esta função é também chamada de conversão para dados categóricos. Temos 3 classes de
flores: Iris setosa, Iris virginica and Iris versicolor. Estas classes podem ser codificadas
como classes 0, 1 e 2 (rótulos numé... |
5,309 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Andreas Alexopoulos
30 / 08 / 2016
Introduction
The Beam Loss Monitoring system of the Large Hadron Collider close to the interaction points contains mostly gas ionization chambers working a... | Python Code:
from __future__ import print_function, division
import warnings
from collections import deque
from datetime import datetime, timedelta
from time import ctime
from os.path import abspath, join
from itertools import cycle
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Patch... |
5,310 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using the trained weights in an ensemble of neurons
On the function points branch of nengo
On the vision branch of nengo_extras
Step1: Load the MNIST database
Step2: Each digit is represen... | Python Code:
import nengo
import numpy as np
import cPickle
from nengo_extras.data import load_mnist
from nengo_extras.vision import Gabor, Mask
from matplotlib import pylab
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import scipy.ndimage
from scipy.ndimage.interpolation import rotate
Expla... |
5,311 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Useful Scripts
Location of the scripts
Here are some scripts that you may find useful. They are in the folder "./eppy/useful_scripts"
And now for some housekeeping before we start off
Step1:... | Python Code:
import os
os.chdir("../eppy/useful_scripts")
# changes directory, so we are where the scripts are located
# you would normaly install eppy by doing
# python setup.py install
# or
# pip install eppy
# or
# easy_install eppy
# if you have not done so, the following three lines are needed
import sys
# pathnam... |
5,312 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Smart Underwriter!
Step1: Underwrting
Step2: Let's take a peek at the data.
Step3: How many morgages have been prepaid in these three years?
Step4: Remember prepay includes a common case... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
import seaborn as sns
pd.options.display.max_columns = 999
%matplotlib inline
matplotlib.rcParams['savefig.dpi'] = 1.5 * matplotlib.rcParams['savefig.dpi']
Explanation: Smart Underwriter!
End of explanation
# Read the ... |
5,313 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<H1>Pattern similarities</H1>
<P>We will compare similarities between the patterns in a network before (input) and after (output) the effect of inhibition.</P>
<P> If patterns of activity ar... | Python Code:
# load necessary modules
%pylab inline
import numpy as np
np.random.seed(0)
from __future__ import division
from inet import __version__
from inet.plots import separation_plot
print(__version__)
Explanation: <H1>Pattern similarities</H1>
<P>We will compare similarities between the patterns in a network be... |
5,314 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2A.ML101.1
Step1: Numpy Arrays
Manipulating numpy arrays is an important part of doing machine learning
(or, really, any type of scientific computation) in Python. This will likely
be revi... | Python Code:
# Start pylab inline mode, so figures will appear in the notebook
%matplotlib inline
Explanation: 2A.ML101.1: Introduction to data manipulation with scientific Python
In this section we'll go through the basics of the scientific Python stack for data manipulation: using numpy and matplotlib.
Source: Course... |
5,315 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Slider Example
This example will allow the user to use sliders to interact with the ISR spectra. Currently this notebook creates two images. The first is a dual plot of the ACF and Po... | Python Code:
import numpy as np
import matplotlib as mpl
import scipy.fftpack as scfft
import scipy.constants as spconst
import matplotlib.pylab as plt
import seaborn as sns
sns.set_style("white")
sns.set_context("notebook")
#
from ISRSpectrum import Specinit
import ipywidgets
from IPython.display import display
#%mat... |
5,316 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning Engineer Nanodegree
Unsupervised Learning
Project 3
Step1: Data Exploration
In this section, you will begin exploring the data through visualizations and code to understand... | Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
import renders as rs
from IPython.display import display # Allows the use of display() for DataFrames
# Show matplotlib plots inline (nicely formatted in the notebook)
%matplotlib inline
# Load the wholesale customers data... |
5,317 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy Exercise 4
Imports
Step1: Complete graph Laplacian
In discrete mathematics a Graph is a set of vertices or nodes that are connected to each other by edges or lines. If those edges don... | Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
Explanation: Numpy Exercise 4
Imports
End of explanation
import networkx as nx
K_5=nx.complete_graph(5)
nx.draw(K_5)
Explanation: Complete graph Laplacian
In discrete mathematics a Graph is a set of vertices or node... |
5,318 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
WARNING
It is a non-public API. It may change with no previous notice
We are going to show how to work with the CARTO custom visualizations (aka Kuviz).
We are going to start creating tje Au... | Python Code:
USERNAME = ""
BASE_URL = "https://{u}.carto.com".format(u=USERNAME)
API_KEY = ""
from carto.auth import APIKeyAuthClient
auth_client = APIKeyAuthClient(api_key=API_KEY, base_url=BASE_URL)
Explanation: WARNING
It is a non-public API. It may change with no previous notice
We are going to show how to work wit... |
5,319 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Xhistogram Tutorial
Histograms are the foundation of many forms of data analysis.
The goal of xhistogram is to make it easy to calculate weighted histograms in multiple dimensions over n-dim... | Python Code:
import xarray as xr
import numpy as np
%matplotlib inline
nt, nx = 100, 30
da = xr.DataArray(np.random.randn(nt, nx), dims=['time', 'x'],
name='foo') # all inputs need a name
display(da)
da.plot()
Explanation: Xhistogram Tutorial
Histograms are the foundation of many forms of data analysi... |
5,320 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Project Euler
Step2: I realize this probably isn't the fastest or most concise code, but it works.
Now write a set of assert tests for your number_to_words function that verifies tha... | Python Code:
def number_to_words(n):
Given a number n between 1-1000 inclusive return a list of words for the number.
words = {0:'',1:'one',2:'two',3:'three',4:'four',5:'five',6:'six',7:'seven',8:'eight',9:'nine',10:'ten',11:'eleven',12:'twelve',13:'thirteen',14:'fourteen',15:'fifteen',16:'sixteen',17:'seventee... |
5,321 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="http
Step1: Pick the initial and run conditions
Step2: Elapsed time starts at 1 second. This prevents errors when setting our boundary conditions.
Step3: Use Landlab methods to i... | Python Code:
from landlab.components.overland_flow import OverlandFlow
from landlab.plot.imshow import imshow_grid
from landlab.plot.colors import water_colormap
from landlab import RasterModelGrid
from landlab.io.esri_ascii import read_esri_ascii
from matplotlib.pyplot import figure
import numpy as np
from time import... |
5,322 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Umbrella sampling simulations
The bias is computed via a harmonic potential based on the deviation of a frame from a reference structure. In the usual one-dimensional case, this reads
$$b^{(... | Python Code:
adw_x, adw_f, adw_pi = shortcuts.adw_reference(-1, 5, 100)
fig, ax = plt.subplots(1, 2, figsize=(2 * pw, ph))
ax[0].plot(adw_x, adw_pi, linewidth=3, color='black')
ax[0].set_ylabel(r"$\pi(x)$", fontsize=20)
ax[0].semilogy()
ax[1].plot(adw_x, adw_f, linewidth=3, color='black')
ax[1].set_ylabel(r"$f(x)$ / kT... |
5,323 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TinyDB
TinyDB is a small and lightweight NoSQL database framework based on simple JSON files.
Source
Official Website
Step1: Insert some data into db.
Step2: Fill with some data (iris).
St... | Python Code:
path = './testData.json'
from tinydb import TinyDB, where
db = TinyDB(path)
Explanation: TinyDB
TinyDB is a small and lightweight NoSQL database framework based on simple JSON files.
Source
Official Website:
- getting started
- advanced usage
Code
Some examples to create a database and insert, delete and s... |
5,324 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Variational Autoencoder
Step5: Task
Step6: Visualize reconstruction quality
Step7: Illustrating latent space
Next, we train a VAE with 2d latent space and illustrates how the encoder (the... | Python Code:
import numpy as np
import tensorflow as tf
import tensorflow.contrib.slim as slim
from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
import matplotlib.pyplot as plt
%matplotlib inline
import input_data
mnist = input_data.read_data_sets('fashion-mnist/data/fashion', one_hot=True... |
5,325 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial 2
Step1: Parametrization (recap of Tutorial 1)
We'll rerun the parametrization performed in Tutorial 1.
Step2: Highlighting atoms and CG beads
To link atoms to coarse-grained bead... | Python Code:
import auto_martini as am
import numpy as np
from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from IPython.display import Image
import rdkit
from rdkit.Chem import Draw
from rdkit.Chem import AllChem
from rdkit.Chem import rdDepictor
from rdkit.Chem.Draw import rdMolDraw2D
print(rdkit.__ve... |
5,326 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exact solution used in MES runs
We would like to MES the operation
$$
\partial_\theta f^2
$$
Using cylindrical geometry.
Step1: Initialize
Step2: Define the variables
Step3: Define the fu... | Python Code:
%matplotlib notebook
from sympy import init_printing
from sympy import S
from sympy import sin, cos, tanh, exp, pi, sqrt
from boutdata.mms import x, y, z, t
from boutdata.mms import DDZ
import os, sys
# If we add to sys.path, then it must be an absolute path
common_dir = os.path.abspath('./../../../../comm... |
5,327 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial Brief
numpy is a powerful set of tools to perform mathematical operations of on lists of numbers. It works faster than normal python lists operations and can manupilate high dimenti... | Python Code:
import numpy as np
Explanation: Tutorial Brief
numpy is a powerful set of tools to perform mathematical operations of on lists of numbers. It works faster than normal python lists operations and can manupilate high dimentional arrays too.
Finding Help:
http://wiki.scipy.org/Tentative_NumPy_Tutorial
http://... |
5,328 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Video 1
Step1: Simply printing out the DataFrame will give us similar information to R's str()
Step2: And for the summary we'll use an equivalent method, DataFrame.describe()
Step3: Video... | Python Code:
NBA = pd.read_csv("NBA_train.csv")
Explanation: Video 1
End of explanation
NBA
Explanation: Simply printing out the DataFrame will give us similar information to R's str():
End of explanation
NBA.describe()
Explanation: And for the summary we'll use an equivalent method, DataFrame.describe():
End of explan... |
5,329 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Rydberg Pair Potentials Near Surfaces
This tutorial is based on results that were published by J. Block and S. Scheel, "van der Waals interaction potential between Rydberg atoms near surface... | Python Code:
%matplotlib inline
# Arrays
import numpy as np
# Plotting
import matplotlib.pyplot as plt
from itertools import product
# Operating system interfaces
import os, sys
# Parallel computing
from multiprocessing import Pool
# pairinteraction :-)
from pairinteraction import pireal as pi
# Create cache for matrix... |
5,330 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 14 (or so)
Step1: You can explore the files if you'd like, but we're going to get the ones from convote_v1.1/data_stage_one/development_set/. It's a bunch of text files.
Step2: So... | Python Code:
# If you'd like to download it through the command line...
!curl -O http://www.cs.cornell.edu/home/llee/data/convote/convote_v1.1.tar.gz
# And then extract it through the command line...
!tar -zxf convote_v1.1.tar.gz
Explanation: Homework 14 (or so): TF-IDF text analysis and clustering
Hooray, we kind of f... |
5,331 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Decorator Pattern 1
Step2: Tip. 튜플 결합
Step3: Decorator
Step4: 중첩된 decorator
python
@decorator3
@decorator2
@decorator1
[function, method, class]
적용순서 | Python Code:
def mean(first, second, *rest):
평균값 반환 함수
numbers = (first, second) + rest
return sum(numbers) / len(numbers)
Explanation: Decorator Pattern 1
End of explanation
(1, 2) + (3,)
Explanation: Tip. 튜플 결합
End of explanation
def float_args_and_return(function):
def wrapper(*args, **kwargs):
... |
5,332 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Submit Structures to MPComplete
This notebook documents the process of
1. Taking and validating a collection of CIFs (e.g. in a ZIP file), creating pymatgen Structure objects
3. Filtering fo... | Python Code:
zipfilename = '/Users/dwinston/Dropbox/best/structures/ever.zip'
Explanation: Submit Structures to MPComplete
This notebook documents the process of
1. Taking and validating a collection of CIFs (e.g. in a ZIP file), creating pymatgen Structure objects
3. Filtering for structures that are submittable to MP... |
5,333 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Source alignment and coordinate frames
This tutorial shows how to visually assess the spatial alignment of MEG sensor
locations, digitized scalp landmark and sensor locations, and MRI volume... | Python Code:
import os.path as op
import numpy as np
import nibabel as nib
from scipy import linalg
import mne
from mne.io.constants import FIFF
data_path = mne.datasets.sample.data_path()
subjects_dir = op.join(data_path, 'subjects')
raw_fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis_raw.fif')
trans_fname ... |
5,334 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: The Fashion MNIST data is available directly in the tf.keras datasets API. You load it like this
Step2: Calling load_data on this object will give you two sets of two... | Python Code:
import tensorflow as tf
print(tf.__version__)
Explanation: <a href="https://colab.research.google.com/github/leopardbruce/FileFun/blob/master/%E2%80%9CCourse_1_Part_4_Lesson_2_Notebook_ipynb%E2%80%9D.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Co... |
5,335 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spatiotemporal permutation F-test on full sensor data
Tests for differential evoked responses in at least
one condition using a permutation clustering test.
The FieldTrip neighbor templates ... | Python Code:
# Authors: Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
from mne.viz import plot_topomap
import mne
from mne.stats import spatio_temporal_cluster_test
from mne.datasets import... |
5,336 | Given the following text description, write Python code to implement the functionality described.
Description:
Arrangement of the characters of a word such that all vowels are at odd places
Python3 program to find the number of ways in which the characters of the word can be arranged such that the vowels occupy only th... | Python Code:
import math
def fact(n ) :
f = 1 ;
for i in range(2 , n + 1 ) :
f = f * i ;
return f ;
def npr(n , r ) :
return fact(n ) / fact(n - r ) ;
def countPermutations(str ) :
even = math . floor(len(str ) / 2 ) ;
odd = len(str ) - even ;
ways = 0 ;
freq =[0 ] * 26 ;
for i in ra... |
5,337 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
With this post I explore an alternative to ol' numpy; xarray. Numpy is still running under the hood but this very handy library applies the pandas concept of labeled dimension to large N-dim... | Python Code:
import xarray as xr
import os
import seaborn
from matplotlib import rcParams
import matplotlib.pyplot as pl
%matplotlib inline
rcParams['font.size']=16
rcParams['xtick.labelsize']=14
rcParams['ytick.labelsize']=14
rcParams['legend.fontsize']=14
rcParams['axes.formatter.limits'] = (-3,3)
Explanation: With t... |
5,338 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ABU量化系统使用文档
<center>
<img src="./image/abu_logo.png" alt="" style="vertical-align
Step1: 算法交易之父托马斯•彼得菲最成功的一段经历是利用当时最快的计算机，租赁独享电话线以保证数据传输畅通无阻，甚至超越时代定制平叛电脑，使用统计套利在不同市场进行对冲策略。
这是最有保证的一... | Python Code:
# 基础库导入
from __future__ import print_function
from __future__ import division
import warnings
warnings.filterwarnings('ignore')
warnings.simplefilter('ignore')
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import os
import sys
# 使用insert 0即只使用github，避免交叉使用了pip安装的... |
5,339 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook to retrieve gridded climate time-series data sets
Case study
Step1: Establish a secure connection with HydroShare by instantiating the hydroshare class that is defined within hs_ut... | Python Code:
# data processing
import os
import pandas as pd, numpy as np, dask, json
import ogh
import geopandas as gpd
# data migration library
from utilities import hydroshare
# plotting and shape libraries
%matplotlib inline
import warnings
warnings.filterwarnings("ignore")
Explanation: Notebook to retrieve gridded... |
5,340 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
独立成分分析 Lab
在此 notebook 中，我们将使用独立成分分析方法从三个观察结果中提取信号，每个观察结果都包含不同的原始混音信号。这个问题与 ICA 视频中解释的问题一样。
数据集
首先看看手头的数据集。我们有三个 WAVE 文件，正如我们之前提到的，每个文件都是混音形式。如果你之前没有在 python 中处理过音频文件，没关系，它们实际上就是浮点数列表。
首先加载第... | Python Code:
import numpy as np
import wave
# Read the wave file
mix_1_wave = wave.open('ICA_mix_1.wav','r')
Explanation: 独立成分分析 Lab
在此 notebook 中，我们将使用独立成分分析方法从三个观察结果中提取信号，每个观察结果都包含不同的原始混音信号。这个问题与 ICA 视频中解释的问题一样。
数据集
首先看看手头的数据集。我们有三个 WAVE 文件，正如我们之前提到的，每个文件都是混音形式。如果你之前没有在 python 中处理过音频文件，没关系，它们实际上就是浮点数列表。
首先加载第一个音频文件 I... |
5,341 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
M-Estimators for Robust Linear Modeling
Step1: An M-estimator minimizes the function
$$Q(e_i, \rho) = \sum_i~\rho \left (\frac{e_i}{s}\right )$$
where $\rho$ is a symmetric function of the... | Python Code:
%matplotlib inline
from statsmodels.compat import lmap
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import statsmodels.api as sm
Explanation: M-Estimators for Robust Linear Modeling
End of explanation
norms = sm.robust.norms
def plot_weights(support, weights_func, xlabels, xti... |
5,342 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Problem setup
Step1: Traditional model-fitting explanation
Step2: Here a polynomial won't be look great, but it's relatively stable in the region around the data.
However, the fit becomes ... | Python Code:
X_MAX = 2 * np.pi
def make_data(m):
# Make Xs scattered on interval [0, 2pi]
X = X_MAX * np.random.rand(m,)
# Y's are all zero (1e-10 for plotting purposes)
Y = 1e-9 + np.zeros((m,))
# ...except for one noise point
Y[m//2] = 1
return X, Y
Explanation: Problem setup:
We're going ... |
5,343 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multiple Kernel Learning
By Saurabh Mahindre - <a href="https
Step1: Introduction
<em>Multiple kernel learning</em> (MKL) is about using a combined kernel i.e. a kernel consisting of a line... | Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
# import all shogun classes
from modshogun import *
Explanation: Multiple Kernel Learning
By Saurabh Mahindre - <a href="https://github.com/Saurabh7">github.com/Saurabh7</a>
This notebook is about multi... |
5,344 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ant Colony Optimization for Energy Systems Research
This notebook explores using Ant Colony Optimization to solve the combinatorial optimization problem of optimally configuring a branch of ... | Python Code:
a, b, P_el = sympy.symbols("a b P_el ")
eta_el = a * sympy.log(P_el) + b
t_op, E_th, eta_th = sympy.symbols("t_op E_th eta_th")
P_th = P_el / eta_el * (1 - eta_el) * eta_th
sols = sympy.solve(sympy.Eq(P_th, E_th/t_op), sympy.log(P_el))
assert len(sols) == 1
sols[0]
Explanation: Ant Colony Optimization for ... |
5,345 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Period Change (dpdt)
Setup
Let's first make sure we have the latest version of PHOEBE 2.4 installed (uncomment this line if running in an online notebook session such as colab).
Step1: As a... | Python Code:
#!pip install "phoebe>=2.4,<2.5"
Explanation: Period Change (dpdt)
Setup
Let's first make sure we have the latest version of PHOEBE 2.4 installed (uncomment this line if running in an online notebook session such as colab).
End of explanation
import phoebe
from phoebe import u # units
import numpy as np
im... |
5,346 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Rechunker Tutorial
This tutorial notebook explains how to use rechunker with real datasets. We will also use xarray to make some things easier and prettier, but we note that xarray is not a ... | Python Code:
import xarray as xr
xr.set_options(display_style='text')
import zarr
import dask.array as dsa
ds = xr.tutorial.open_dataset("air_temperature")
# create initial chunk structure
ds = ds.chunk({'time': 100})
ds.air.encoding = {} # helps when writing to zarr
ds
Explanation: Rechunker Tutorial
This tutorial not... |
5,347 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Taxi Fare Prediction Using Realtime Traffic Data
This will be the same as our previous taxi fare model, but with the addition of ‘trips_last_5min’ data as a feature. This is our proxy for tr... | Python Code:
import tensorflow as tf
import numpy as np
import shutil
print(tf.__version__)
Explanation: Taxi Fare Prediction Using Realtime Traffic Data
This will be the same as our previous taxi fare model, but with the addition of ‘trips_last_5min’ data as a feature. This is our proxy for traffic
End of explanation
... |
5,348 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table align="left">
<td>
<a href="https
Step3: Clone and build tensorflow_enterprise_addons
To use the latest version of the tensorflow_enterprise_addons, we will clone and bui... | Python Code:
import sys
# If you are running this notebook in Colab, run this cell and follow the
# instructions to authenticate your Google Cloud account. This provides access
# to your Cloud Storage bucket and lets you submit training jobs and prediction
# requests.
if 'google.colab' in sys.modules:
from google.c... |
5,349 | Given the following text description, write Python code to implement the functionality described.
Description:
Remove recurring digits in a given number
Removes recurring digits in num [ ] ; Index in modified string ; Traverse digits of given number one by one ; Copy the first occurrence of new digit ; Remove repeating... | Python Code:
def removeRecurringDigits(num ) :
l = len(num )
(i , j ) =(0 , 0 )
str = ' '
while i < l :
str += num[i ]
j += 1
while(i + 1 < l and num[i ] == num[i + 1 ] ) :
i += 1
i += 1
return str
if __name__== ' __main __' :
num = '1299888833'
print(' Modified ▁ number ▁ is ▁ { } ' ... |
5,350 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clustering comparison
Generate datasets
We choose the size big enough to see the scalability of the algorithms, but we don't want the example to take too long.
Step1: Enumerate clustering c... | Python Code:
import numpy as np
from sklearn import datasets
from collections import OrderedDict
np.random.seed(0)
n_samples = 2500
ds = OrderedDict()
ds['noisy_circles'] = datasets.make_circles(
n_samples=n_samples, factor=.5, noise=.05)
ds['noisy_moons'] = datasets.make_moons(
n_samples=n_samples, noise=.05)
... |
5,351 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1H Magnetic Resonance Spectroscopy (1H-MRS)
Measuring GABA concentrations in vivo in human
Principles of MRS measurement
Following a $90^\circ$ square (broadband) pulse
Step1: Fourier trans... | Python Code:
def FID(t, M0=1, omega_0=128, omega=150, phi=0, T2_star=1.0):
Mx = M0 * np.sin((omega_0 - omega) * t + phi) * np.exp(-(t / T2_star))
My = M0 * np.cos((omega_0 - omega) * t + phi) * np.exp(-(t / T2_star))
return Mx, My
def plot_fid(t, FID, omega=None, omega_0=None):
fig = plt.figure()
ax... |
5,352 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sensivity analysis with python using SALib
Written by Sarah Juricic
September 21st 2018
Step1: Objectives
Step2: Draw a number of samples from your problem definition
Step4: Run your own... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Sensivity analysis with python using SALib
Written by Sarah Juricic
September 21st 2018
End of explanation
# STATE THE PROBLEM DICTIONNARY
# what will be varying (=inputs) ? in what bounds ?
problem = {
'num_vars': 3,
... |
5,353 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Currenlty the market basket analysis we are performing is only looking within a time slice to determin if thigs are occuring at the same time, not if they can be used to predict what is in t... | Python Code:
import itertools
for p in procLine:
l = p.split(' ')
if len(l) > 1:
comb = itertools.combinations(l, 2)
for start,finish in comb:
val = (start,finish)
edgeDict[val] += 1
edgeSet.add(val)
Explanation: Currenlty the market basket analysis we are... |
5,354 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: We import all the necessary packages. We are going to work with the fastai V1 library which sits on top of Pytorch 1.0. The fastai library provides many useful functio... | Python Code:
%reload_ext autoreload
%autoreload 2
%matplotlib inline
Explanation: <a href="https://colab.research.google.com/github/astronstar/astronstar.github.io/blob/master/%E2%80%9Clesson1_pets_ipynb%E2%80%9D%E7%9A%84%E5%89%AF%E6%9C%AC.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab... |
5,355 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Példa 1
Step1: A stack egymásra rakja az oszlopokat.
Step2: Most nem teljesen jó, mert előbb az országot és a tevékenységet ki kellene ragadjuk onnan. Ezért indexet csinálunk belőlük.
Step... | Python Code:
df=pd.read_excel('formazottbi2.xlsx')
df
Explanation: Példa 1
End of explanation
pd.DataFrame(df.stack()).head()
Explanation: A stack egymásra rakja az oszlopokat.
End of explanation
df.columns
df.set_index(['Tevékenység','Ország']).head(2)
Explanation: Most nem teljesen jó, mert előbb az országot és a tev... |
5,356 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 2
This chapter introduces more PyMC syntax and design patterns, and ways to think about how to model a system from a Bayesian perspective. It also contains tips and data visualizatio... | Python Code:
import pymc as pm
parameter = pm.Exponential("poisson_param", 1)
data_generator = pm.Poisson("data_generator", parameter)
data_plus_one = data_generator + 1
Explanation: Chapter 2
This chapter introduces more PyMC syntax and design patterns, and ways to think about how to model a system from a Bayesian per... |
5,357 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Neighborhood Structures in the ArcGIS Spatial Statistics Library
Spatial Weights Matrix
On-the-fly Neighborhood Iterators [GA Table]
Contructing PySAL Spatial Weights
Spatial Weight Matrix ... | Python Code:
import Weights as WEIGHTS
import os as OS
inputFC = r'../data/CA_Polygons.shp'
fullFC = OS.path.abspath(inputFC)
fullPath, fcName = OS.path.split(fullFC)
masterField = "MYID"
Explanation: Neighborhood Structures in the ArcGIS Spatial Statistics Library
Spatial Weights Matrix
On-the-fly Neighborhood Iterato... |
5,358 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python Metaprogramming (the sometimes useful but often interesting)
Why?
Repetative code is an excuse to waste time?
Might allow you to control functions, classes behavior at a higher level ... | Python Code:
from functools import wraps
def debug_on(func):
@wraps(func) #preserving the metadata for func
def debugging(*args,**kwargs):
retval = func(*args,**kwargs);
print('Scope: debugging %s:%s:%s'%(func,func.__name__,retval));
return retval;
print('Scope: debug_on',debugging)
... |
5,359 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Create a classifier to predict the wine color from wine quality attributes using this dataset
Step1: Split the data into features (x) and target (y, the last column in the table)
Remember y... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import dateutil.parser
import pg8000
from pandas import DataFrame
from sklearn.externals.six import StringIO
import pydotplus
from sklearn import tree
from sklearn.cross_validation import train_test_split
from sklearn... |
5,360 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TO DO
Step1: This notebook calculates and plots the theoretical tilt angles. It will also plot the alpha and p0 factors vs temperature that are given in the cell below this.
Material Charac... | Python Code:
import numpy as np
from scipy.integrate import quad, dblquad
%matplotlib inline
import matplotlib.pyplot as plt
import scipy.optimize as opt
Explanation: TO DO:
Need to be able to scatter plot measured values of Psi on top of the current Psi plot.
Alpha and rho LaTeX not working in plots.
Legend needs to b... |
5,361 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
One vs All
Step1: Loading and visualizing training data
The training data is 5000 digit images of digits of size 20x20. We will display a random selection of 25 of them.
Step2: Part 2
Step... | Python Code:
import pandas
import numpy as np
import scipy.io
import scipy.optimize
import functools
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: One vs All
End of explanation
ex3data1 = scipy.io.loadmat("./ex3data1.mat")
X = ex3data1['X']
y = ex3data1['y'][:,0]
y[y==10] = 0
m, n = X.shape
m, n
fig =... |
5,362 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table align="left">
<td>
<a href="https
Step1: Restart the kernel
After you install the additional packages, you need to restart the notebook kernel so it can find the packages.
Step... | Python Code:
import os
# The Vertex AI Workbench Notebook product has specific requirements
IS_WORKBENCH_NOTEBOOK = os.getenv("DL_ANACONDA_HOME")
IS_USER_MANAGED_WORKBENCH_NOTEBOOK = os.path.exists(
"/opt/deeplearning/metadata/env_version"
)
# Vertex AI Notebook requires dependencies to be installed with '--user'
U... |
5,363 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent neural network that performs sentiment analysis. Using an RNN rather than a feedfoward network is more accurate ... | Python Code:
import numpy as np
import tensorflow as tf
with open('../sentiment-network/reviews.txt', 'r') as f:
reviews = f.read()
with open('../sentiment-network/labels.txt', 'r') as f:
labels = f.read()
reviews[:2000]
Explanation: Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent ... |
5,364 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step 0 - hyperparams
vocab_size is all the potential words you could have (classification for translation case)
and max sequence length are the SAME thing
decoder RNN hidden units are usuall... | Python Code:
input_len = 60
target_len = 30
batch_size = 50
with_EOS = False
csv_in = '../price_history_03_seq_start_suddens_trimmed.csv'
Explanation: Step 0 - hyperparams
vocab_size is all the potential words you could have (classification for translation case)
and max sequence length are the SAME thing
decoder RNN hi... |
5,365 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Estimators
Most of sklearn is designed around the concept of "estimators", which are objects that can transform data. That is, we can think of an estimator as a functi... | Python Code:
# Standard Python libraries
from __future__ import absolute_import, division, print_function, unicode_literals
import os
import time
import numpy as np
import glob
import matplotlib.pyplot as plt
import PIL
import imageio
from IPython import display
import sklearn
import seaborn as sns
sns.set(style="ticks... |
5,366 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 1 Least squares and linear basis functions models
1.1 Least squares
Step2: Load the data
Here we will reuse the dataset height_weight_genders.csv from previous exercise section to ch... | Python Code:
def least_squares(y, tx):
calculate the least squares solution.
a = tx.T.dot(tx)
b = tx.T.dot(y)
return np.linalg.solve(a, b)
Explanation: 1 Least squares and linear basis functions models
1.1 Least squares
End of explanation
from helpers import *
def test_your_least_squares():
height, ... |
5,367 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LeNet Lab Solution
Source
Step1: Basic Info of the Dataset
Step2: Visualize Data
View a sample from the dataset.
You do not need to modify this section.
Step3: Preprocess Data
Shuffle the... | Python Code:
# Load pickled data
import pickle
# TODO: Fill this in based on where you saved the training and testing data
training_file = 'train.p'
validation_file= 'valid.p'
testing_file = 'test.p'
with open(training_file, mode='rb') as f:
train = pickle.load(f)
with open(validation_file, mode='rb') as f:
val... |
5,368 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
In the exercise, you will work with data from the TalkingData AdTracking competition. The goal of the competition is to predict if a user will download an app after clicking th... | Python Code:
# Set up code checking
from learntools.core import binder
binder.bind(globals())
from learntools.feature_engineering.ex1 import *
Explanation: Introduction
In the exercise, you will work with data from the TalkingData AdTracking competition. The goal of the competition is to predict if a user will downloa... |
5,369 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex pipelines
Learning Objectives
Step1: Restart the kernel
After you install the additional packages, you need to restart the notebook kernel so it can find the packages.
Import librari... | Python Code:
!pip3 install --user google-cloud-pipeline-components==0.1.1 --upgrade
Explanation: Vertex pipelines
Learning Objectives:
Use components from google_cloud_pipeline_components to create a Vertex Pipeline which will
1. train a custom model on Vertex AI
1. create an endpoint to host the model
1. upload... |
5,370 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DAY 11 - Mar 7, 2017
Today I'll do something a little different. This morning I tweeted something along the lines of "will be working with matplotlib." In terms of visualization, I'm more fa... | Python Code:
website_base_stats = "http://leagueoflegends.wikia.com/wiki/Base_champion_statistics"
# Save HTML to soup
html_data = requests.get(website_base_stats).text
soup = BeautifulSoup(html_data, "html5lib")
# Parse table
table = soup.find('table', attrs={'class' : 'wikitable'})
# Parse table header
lol_thead = [h... |
5,371 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matrix Factorization
In a recommendation system, there is a group of users and a set of items. Given that each users have rated some items in the system, we would like to predict how the use... | Python Code:
class Batch(object):
def __init__(self, data_names, data, label_names, label):
self.data = data
self.label = label
self.data_names = data_names
self.label_names = label_names
@property
def provide_data(self):
return [(n, x.shape) for n, x in zip(... |
5,372 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Making New Layers and Models via Subclassing
Learning Objectives
Use Layer class as the combination of state (weights) and computation.
Defer weight creation until the shape of the inputs is... | Python Code:
# Import necessary libraries
import tensorflow as tf
from tensorflow import keras
Explanation: Making New Layers and Models via Subclassing
Learning Objectives
Use Layer class as the combination of state (weights) and computation.
Defer weight creation until the shape of the inputs is known.
Build recursiv... |
5,373 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Algorithm comparison
This notebook contains the algorithm comparison for the measurements done with the DySpan 2017 testbed
N_FRAMES = 50
comparison is based on different aspects, such as
St... | Python Code:
%load_ext autoreload
%autoreload 2
import sys
print(sys.version)
import sys
sys.path.append("../python")
import setup_dataset
data, labels = setup_dataset.setup_simple_iterables("with_dc")
X_train, X_test, y_train, y_test = setup_dataset.slice_data(data, labels)
# Setting up various complexities for the di... |
5,374 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
User Defined Materials
Overview
Materials are implemented by subclassing the matmodlab.core.Material base class. The user material is called at each frame of every step. It is provided with... | Python Code:
%pycat ../matmodlab2/materials/elastic3.py
%pylab inline
from matmodlab2 import *
Explanation: User Defined Materials
Overview
Materials are implemented by subclassing the matmodlab.core.Material base class. The user material is called at each frame of every step. It is provided with the material state at... |
5,375 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
列表生成式和生成式表达式
我们可以用 map 和 filter 达到 列表生成式的效果
Step1: 对于上面的例子来说， filter/map 并不比 listcomp(列表生成式) 快, 后面的章节我们进一步讨论
列表生成式的多层循环
假如我们要制作两种颜色三种大小组成的 T 恤, 下面的代码是生成 T 恤的序列
Step2: Python中，[], {}, () 内的... | Python Code:
symbols = "a%b&c$de$"
beyond_ascii = [ord(s) for s in symbols if ord(s) > 50]
beyond_ascii
beyond_ascii = list(filter(lambda c: c > 50, map(ord, symbols)))
beyond_ascii
Explanation: 列表生成式和生成式表达式
我们可以用 map 和 filter 达到 列表生成式的效果
End of explanation
colors = ['black', 'white']
sizes = ['S', 'M', 'L']
tshirts = ... |
5,376 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Traveling Salesman problem
Names of group members
// put your names here!
Goals of this assignment
The main goal of this assignment is to use Monte Carlo methods to find the shortest pat... | Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
from IPython.display import display, clear_output
def calc_total_distance(table_of_distances, city_order):
'''
Calculates distances between a sequence of cities.
Inputs: N x N table containing distances between each pair... |
5,377 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cmcc', 'cmcc-cm2-hr5', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: CMCC
Source ID: CMCC-CM2-HR5
Topic: Land
Sub-Topics: Soil, Snow, Vegetation,... |
5,378 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Imports
Step1: Useful functions
Step2: Reading the data
Step3: Analysis of coverage
Step4: Diversity plot
Step5: Positions that increase in frequency in the different replicates and con... | Python Code:
from collections import Counter
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
from pylab import rcParams
import seaborn as sns
from array import array
import numpy as np
from scipy.stats import ttest_ind
from scipy.stats import linregress
from scipy.stats import ma... |
5,379 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
COLOP in Spectral Blueing Mode
IPython notebook to calculate operator for spectral blueing using seismic amplitude spectrum and well AI spectrum exported from OpendTect.
First sample of the ... | Python Code:
import sys
import numpy as np
from scipy.stats import linregress
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: COLOP in Spectral Blueing Mode
IPython notebook to calculate operator for spectral blueing using seismic amplitude spectrum and well AI spectrum exported from OpendTect.
First sa... |
5,380 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modeling and Simulation in Python
Case Study
Step1: One queue or two?
This notebook presents a solution to an exercise from Modeling and Simulation in Python. It uses features from the fir... | Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import functions from the modsim.py module
from modsim import *
# set the random number gene... |
5,381 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This will lean heavily on Tom Augspurger's excellent series on Modern Pandas.
Quote
Step2: In the original example from Tom, the code is written out as such
Step3: Our function may be a bi... | Python Code:
import os
import zipfile
import requests
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
Explanation: This will lean heavily on Tom Augspurger's excellent series on Modern Pandas.
Quote:
Method chaining, where you call methods on an object one after another, is ... |
5,382 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Step1: In this chapter, we will look at the relationship between graphs and linear algebra.
The deep connection between these two topics is super interesting,
and I'd like to s... | Python Code:
from IPython.display import YouTubeVideo
YouTubeVideo(id="uTHihJiRELc", width="100%")
Explanation: Introduction
End of explanation
import networkx as nx
nodes = list(range(4))
G1 = nx.Graph()
G1.add_nodes_from(nodes)
G1.add_edges_from(zip(nodes, nodes[1:]))
Explanation: In this chapter, we will look at the... |
5,383 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Filtering and resampling data
Some artifacts are restricted to certain frequencies and can therefore
be fixed by filtering. An artifact that typically affects only some
frequencies is due to... | Python Code:
import numpy as np
import mne
from mne.datasets import sample
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif'
proj_fname = data_path + '/MEG/sample/sample_audvis_eog_proj.fif'
tmin, tmax = 0, 20 # use the first 20s of data
# Setup for reading the raw data (save m... |
5,384 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Train Model with XLA_GPU (and CPU*)
Some operations do not have XLA_GPU equivalents, so we still need to use CPU.
IMPORTANT
Step1: Reset TensorFlow Graph
Useful in Jupyter Notebooks
Step2: ... | Python Code:
import tensorflow as tf
from tensorflow.python.client import timeline
import pylab
import numpy as np
import os
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
tf.logging.set_verbosity(tf.logging.INFO)
Explanation: Train Model with XLA_GPU (and CPU*)
Some operations do not have XLA_GPU eq... |
5,385 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Please find jax implementation of this notebook here
Step2: Implementation
Utility functions.
Step6: Main function.
Step7: Example
The shape of the multi-head attention output is (batch_s... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(seed=1)
import math
import collections
try:
import torch
except ModuleNotFoundError:
%pip install -qq torch
import torch
from torch import nn
from torch.nn import functional as F
!mkdir figures # for saving plots
Explanation: Ple... |
5,386 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Softmax exercise
Adapt from the Stanford CS231n assignment1, find the original version on the course website.
In this exercise we will
Step5: Load CIFAR-10 data
Load the data and split into... | Python Code:
import random
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.data_utils import load_CIFAR10
from cs231n.gradient_check import grad_check_sparse
# plotting setting
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.inte... |
5,387 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preparing the data
Data loading and putting it into a suitable format
Parsing chord labels to binary pitch class sets
for chord label dataset
[x] see tools/add_pitch_class_sets.sh
Joining Da... | Python Code:
def impute_missing_key_files():
path = 'data/beatles/keylab/The_Beatles/10CD2_-_The_Beatles/CD2_-_12_-_Revolution_9.lab'
if not os.path.exists(path):
df = pd.DataFrame.from_records(
[("0.0", "502.204082", "Silence", None)],
columns=['start', 'end', 'key_indicator', '... |
5,388 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Исследование поведения предложенного функционала. Часть I.
Возьмем в качестве базисных функций $\cos(x)$, $\sin(x)$, $\cos(2x)$, $\sin(2x)$.
Стоит посмотреть, как будет вести себя предлженна... | Python Code:
import numpy as np
import tensorflow as tf
from matplotlib import pylab as plt
%matplotlib inline
m = 4500
M = 4
a = -10
b = 10
x_grid = np.linspace(a, b, m, endpoint=True)
sess = tf.Session()
x = tf.placeholder(tf.double)
trial_func = [tf.sin(x), tf.cos(x), tf.sin(2*x), tf.cos(2*x)]
alpha = tf.Variable(... |
5,389 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Estimating Counts
Think Bayes, Second Edition
Copyright 2020 Allen B. Downey
License
Step1: In the previous chapter we solved problems that involve estimating proportions.
In the Euro probl... | Python Code:
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install empiricaldist
# Get utils.py
from os.path import basename, exists
def download(url):
filename = basename(url)
if not exists(... |
5,390 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright (c) 2015, 2016 Sebastian Raschka
<br>
2016 Li-Yi Wei
https
Step1: The use of watermark is optional. You can install this IPython extension via "pip install watermark". For more in... | Python Code:
%load_ext watermark
%watermark -a '' -u -d -v -p numpy,pandas,matplotlib,scipy,sklearn
Explanation: Copyright (c) 2015, 2016 Sebastian Raschka
<br>
2016 Li-Yi Wei
https://github.com/1iyiwei/pyml
MIT License
Python Machine Learning - Code Examples
Chapter 7 - Combining Different Models for Ensemble Learning... |
5,391 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Please find torch implementation of this notebook here
Step4: Basics
This section is based on sec 8.2 of http
Step6: Tokenization
Step9: Vocabulary
We map each word to a unique int... | Python Code:
import os
import numpy as np
import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import math
try:
import torch
except ModuleNotFoundError:
%pip install -qq torch
import torch
from torch.utils import data
if not os.path.exists("figures"):
os.makedirs("figures") # for saving p... |
5,392 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Machine-Translation-with-Huggingface-Transformer" data-toc-modified-id="Mach... | Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', '..', 'notebook_format'))
from formats import load_style
load_style(css_style='custom2.css', plot_style=False)
os.chdir(path)
# 1. magic for in... |
5,393 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Self-Driving Car Engineer Nanodegree
Project
Step1: Read in an Image
Step10: Ideas for Lane Detection Pipeline
Some OpenCV functions (beyond those introduced in the lesson) that might be u... | Python Code:
#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
%matplotlib inline
Explanation: Self-Driving Car Engineer Nanodegree
Project: Finding Lane Lines on the Road
In this project, you will use the tools you learned about in the lesson... |
5,394 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Resources
http
Step1: Compute the traces of cross-sections | Python Code:
fin = open('./../data/trench.xy', 'r')
trench = []
for line in fin:
aa = re.split('\s+', re.sub('^\s+', '', line))
trench.append((float(aa[0]), float(aa[1])))
fin.close()
trench = Trench(numpy.array(trench))
cat = pickle.load(open("./../data/catalogue_ext_cac.p", "rb" ))
Explanation: Resources
htt... |
5,395 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook shows how to extract information from a spectral line using the weak-field approximation. It uses a Bayesian approach to the problem.
Index
Simple case
Biases
Errors in both co... | Python Code:
lambda0 = 6301.5080
JUp = 2.0
JLow = 2.0
gUp = 1.5
gLow = 1.833
lambdaStart = 6300.8
lambdaStep = 0.03
nLambda = 50
lineInfo = np.asarray([lambda0, JUp, JLow, gUp, gLow, lambdaStart, lambdaStep])
s = pymilne.milne(nLambda, lineInfo)
stokes = np.zeros((4,nLambda))
BField = 100.0
BTheta = 20.0
BChi = 0.0
VMa... |
5,396 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'fio-ronm', 'sandbox-2', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: FIO-RONM
Source ID: SANDBOX-2
Topic: Ocnbgchem
Sub-Topics: Tracer... |
5,397 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook a simple Q learner will be trained and evaluated. The Q learner recommends when to buy or sell shares of one particular stock, and in which quantity (in fact it determines t... | Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
from multiprocessing import Pool
%matplotlib inline
%pylab inline
... |
5,398 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: റെൻസോർഫ്ളോ വിളിക്കുന്നു
tf എന്നു പേരിടുന്നു
Step2: ഡേറ്റയെ വിളിക്കുന്നു....
ചിത്രങ്ങൾ ...കൈയ്യെഴുത്ത് അക്കങ്ങളുടെ മെനിസ്റ്റ് ഡാറ്റാബേസ്,
60,000 ഉദാഹരണങ്ങൾ, ഒപ്പം 10... | Python Code:
print ("Gods name is Jehova")
Explanation: <a href="https://colab.research.google.com/github/Graphitenet/Fun-CSS-Java-Clock/blob/master/%E0%B4%B1%E0%B5%86%E0%B5%BB%E0%B4%B8%E0%B5%8B%E0%B5%BC%E0%B4%AB%E0%B5%8D%E0%B4%B3%E0%B5%8B_.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/cola... |
5,399 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 15. 다중 회귀 분석
Step3: 14장의 내용을 추가 데이터를 사용해 모델의 성능을 높이기 위해,
더 많은 독립 변수를 사용하는 선형 모델을 시험
14장에서 다뤘던 모델
$y_i=\alpha+\beta x_i+\epsilon_i$
여기에 독립 변수를 추가하면
$\Rightarrow$시간(분)= $\alpha+\beta_1... | Python Code:
from __future__ import division
from collections import Counter
from functools import partial
from linear_algebra import dot, vector_add
from stats import median, standard_deviation, de_mean
from probability import normal_cdf
from gradient_descent import minimize_stochastic
#from simple_linear_regression i... |
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