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8,600 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transfer Learning
Most of the time you won't want to train a whole convolutional network yourself. Modern ConvNets training on huge datasets like ImageNet take weeks on multiple GPUs. Instea... | Python Code:
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
vgg_dir = 'tensorflow_vgg/'
# Make sure vgg exists
if not isdir(vgg_dir):
raise Exception("VGG directory doesn't exist!")
class DLProgress(tqdm):
last_block = 0
def hook(self, block_num=1, block_size=... |
8,601 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Collecting Tweets
This notebook shows how to collect tweets. For analyzing words you want to collect by search term, but collecting tweets from a specific user is also possible.
Step1: Coll... | Python Code:
import sys
sys.path.append('..')
from twords.twords import Twords
import matplotlib.pyplot as plt
%matplotlib inline
import pandas as pd
# this pandas line makes the dataframe display all text in a line; useful for seeing entire tweets
pd.set_option('display.max_colwidth', -1)
twit_mars = Twords()
# set p... |
8,602 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Nonequilibrium Switching Free Energy Analysis
This notebook is useful for examining the results of nonequilibrium switching calculations performed with the Perses tool. It enables examinatio... | Python Code:
import numpy as np
import nglview
from bokeh.plotting import figure, output_notebook, show
from bokeh.layouts import row, column
import simtk.unit as unit
import mdtraj as md
import plotting_tools
output_notebook()
Explanation: Nonequilibrium Switching Free Energy Analysis
This notebook is useful for exami... |
8,603 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kernel Density Estimation for outlier detection
Motivation
A common assumption in pattern recognition is that all classes are known. This assumption does not hold in many real-world applicat... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import metrics
from sklearn.neighbors.kde import KernelDensity
%matplotlib inline
Explanation: Kernel Density Estimation for outlier detection
Motivation
A common assumption in pattern recognition is that all classes are kn... |
8,604 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
# Getting Started with gensim
The goal of this tutorial is to get a new user up-and-running with gensim. This notebook covers the following objectives.
## Objectives
Installing gensim.
Acce... | Python Code:
raw_corpus = ["Human machine interface for lab abc computer applications",
"A survey of user opinion of computer system response time",
"The EPS user interface management system",
"System and human system engineering testing of EPS",
"Relati... |
8,605 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
8,606 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Scraping the web is fun
Step1: Let's scrape the daily crime log from Cambridge, Massachusetts!
The most powerful web-scraping Python library is lxml...
Step2: Wow that's ugly. Wait, can't ... | Python Code:
import requests
r = requests.get("http://berkeley.edu")
r
dir(r)
r.encoding
Explanation: Scraping the web is fun:
Do-goodery
Making much money
Amusing much people
End of explanation
import lxml.html as LH
url = "http://www.cambridgema.gov/cpd/newsandalerts/Archives/detail.aspx?path=%2fsitecore%2fcontent%2f... |
8,607 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Graph attributes can be manipulated through the set_*() and get_*() methods.
Step1: Defaults can be set for nodes and edges.
Step2: Nodes, edges and subgraphs are added and deleted through... | Python Code:
graph.set_fontsize('12')
graph.get_fontsize()
Explanation: Graph attributes can be manipulated through the set_*() and get_*() methods.
End of explanation
graph.set_node_defaults(fillcolor='blue', style='filled')
graph.get_node_defaults()
Explanation: Defaults can be set for nodes and edges.
End of explana... |
8,608 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training at scale with AI Platform Training Service
Learning Objectives
Step1: Change your project name and bucket name in the cell below if necessary.
Step2: Confirm below that the bucket... | Python Code:
from google import api_core
from google.cloud import bigquery
Explanation: Training at scale with AI Platform Training Service
Learning Objectives:
1. Learn how to organize your training code into a Python package
1. Train your model using cloud infrastructure via Google Cloud AI Platform Training Serv... |
8,609 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 24
Modeling and Simulation in Python
Copyright 2021 Allen Downey
License
Step1: In this chapter we model systems that involve rotating objects.
Rotation
Rotation is complicated
Ste... | Python Code:
# install Pint if necessary
try:
import pint
except ImportError:
!pip install pint
# download modsim.py if necessary
from os.path import exists
filename = 'modsim.py'
if not exists(filename):
from urllib.request import urlretrieve
url = 'https://raw.githubusercontent.com/AllenDowney/ModSim/... |
8,610 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Options Widgets
Herein, we present the widgets that can be used as components in order to assemble higher level widgets, such as the ones presented in Menpo Widgets.ipynb and MenpoFit Widget... | Python Code:
from menpowidgets.options import (AnimationOptionsWidget, ChannelOptionsWidget, PatchOptionsWidget,
LandmarkOptionsWidget, RendererOptionsWidget, PlotOptionsWidget,
LinearModelParametersWidget, TextPrintWidget, FeatureOptionsWidget,
... |
8,611 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<p>
<img src="http
Step1: <center><img src="https
Step2: By convention, you'll find that most people in the SciPy/PyData world will import NumPy using np as an alias
Step3: Throughout thi... | Python Code:
__AUTHORS__ = {'am': ("Andrea Marino",
"andrea.marino@unifi.it",),
'mn': ("Massimo Nocentini",
"massimo.nocentini@unifi.it",
"https://github.com/massimo-nocentini/",)}
__KEYWORDS__ = ['Python', 'numpy', 'numerical', 'data',... |
8,612 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generating Features from GeoTiff Files
From GeoTiff Files available for India over a period of more than 20 years, we want to generate features from those files for the problem of prediction... | Python Code:
from osgeo import ogr, osr, gdal
import fiona
from shapely.geometry import Point, shape
import numpy as np
import pandas as pd
import os
import sys
import tarfile
import timeit
Explanation: Generating Features from GeoTiff Files
From GeoTiff Files available for India over a period of more than 20 years, we... |
8,613 | Given the following text description, write Python code to implement the functionality described.
Description:
Significant Inversions in an Array
Function that sorts the input array and returns the number of inversions in the array ; Recursive function that sorts the input array and returns the number of inversions in ... | Python Code:
def mergeSort(arr , array_size ) :
temp =[0 for i in range(array_size ) ]
return _mergeSort(arr , temp , 0 , array_size - 1 )
def _mergeSort(arr , temp , left , right ) :
mid , inv_count = 0 , 0
if(right > left ) :
mid =(right + left ) // 2
inv_count = _mergeSort(arr , temp , left , mid ... |
8,614 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!--BOOK_INFORMATION-->
<a href="https
Step1: Exercise 1
Step2: Code up your own SVM solution below
Step3: Code up your own SVM solution below
Step4: Code up your own solution | Python Code:
import numpy as np
np.random.seed(4242)
Explanation: <!--BOOK_INFORMATION-->
<a href="https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-opencv" target="_blank"><img align="left" src="data/cover.jpg" style="width: 76px; height: 100px; background: white; padding: 1px; border: 1px s... |
8,615 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This example demonstrates using a network pretrained on ImageNet for classification. The model used was converted from the VGG_CNN_S model (http
Step1: Setup
Step2: Define the... | Python Code:
!wget https://s3.amazonaws.com/lasagne/recipes/pretrained/imagenet/vgg_cnn_s.pkl
Explanation: Introduction
This example demonstrates using a network pretrained on ImageNet for classification. The model used was converted from the VGG_CNN_S model (http://arxiv.org/abs/1405.3531) in Caffe's Model Zoo.
For d... |
8,616 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Path Loss Models
This notebook illustrates some path loss models.
Initializations
First we set the Python path and import some libraries.
Step1: Now we import some pyphysim stuff
Step2: Pa... | Python Code:
%matplotlib inline
import numpy as np
from matplotlib import pyplot as plt
Explanation: Path Loss Models
This notebook illustrates some path loss models.
Initializations
First we set the Python path and import some libraries.
End of explanation
from pyphysim.channels import pathloss
Explanation: Now we imp... |
8,617 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Funciones
Una función es una sección de código reutilizable, escrita para realizar una tarea específica en un programa.
¿Por qué son útiles las funciones? Fíjate en los siguientes ejemplos.... | Python Code:
# necesito calcular el cuadrado de un número
# defino una variable asignándole el valor 6
n = 6
# calculo el cuadrado y lo imprimo por pantalla
cuadrado = n**2
print(cuadrado)
# ahora me piden que calcule otro cuadrado, en este caso de 8
# repito el proceso
n = 8
cuadrado = n**2
print(cuadrado)
Explanation... |
8,618 | 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: 与之前章节一样，本节示例的相关性分析只限制在abupy内置沙盒数据中，和上一节一样首先将内置沙盒中美股，A股，港股, 比特币，莱特币，期货市场中的symbol都列出来，然后组成训练集和... | Python Code:
# 基础库导入
from __future__ import print_function
from __future__ import division
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abupy，导致的版本不一致问题
sys.path.insert(0, os.path.abspath('../'))
import abupy
# 使用沙盒数据，... |
8,619 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Station Plot with Layout
Make a station plot, complete with sky cover and weather symbols, using a
station plot layout built into MetPy.
The station plot itself is straightforward, but there... | Python Code:
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
import pandas as pd
from metpy.calc import get_wind_components
from metpy.cbook import get_test_data
from metpy.plots import (add_metpy_logo, simple_layout, StationPlot,
StationPlotLayout,... |
8,620 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1.0 Load data from http
Step1: 1.2 Calculate Actual Profit
Step2: 1.3 Load data from 'Calories' worksheet and plot
Step3: 1.4 add calorie data to sales worksheet
Step4: 1.5 pivot table
S... | Python Code:
# code written in python_3. (for py_2.7 users some changes may be required)
import pandas # load pandas dataframe lib
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
# find path to your Concessions.xlsx
# df = short for dataframe == excel worksheet
# zero indexing in python, so f... |
8,621 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Now that we have created and saved a configuration file, let’s read it back and explore the data it holds.
Step1: Please note that default values have precedence over fallback values. For i... | Python Code:
config = configparser.ConfigParser()
config.sections()
config.read('example.ini')
config.sections()
'bitbucket.org' in config
'bytebong.com' in config
config['bitbucket.org']['User']
config['DEFAULT']['Compression']
topsecret = config['topsecret.server.com']
topsecret['ForwardX11']
topsecret['Port']
for ke... |
8,622 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Python PCA - Plotting Explained Variance Ratio with Matplotlib
| Python Code::
import matplotlib.pyplot as plt
plt.figure(figsize=(10,6))
plt.bar(x=range(0,len(X_train.columns)),
height=pca.explained_variance_ratio_,
tick_label=X_train.columns)
plt.title('Explained Variance Ratio')
plt.ylabel('Explained Variance Ratio')
plt.xlabel('Component')
plt.show()
|
8,623 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
8,624 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Heatmap
The HeatMap mark represents a 2d matrix of values as a color image. It can be used to visualize a 2d function, or a grayscale image for instance.
HeatMap is very similar to the GridH... | Python Code:
import numpy as np
from bqplot import Figure, LinearScale, ColorScale, Color, Axis, HeatMap, ColorAxis
from ipywidgets import Layout
Explanation: Heatmap
The HeatMap mark represents a 2d matrix of values as a color image. It can be used to visualize a 2d function, or a grayscale image for instance.
HeatMap... |
8,625 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Customization basics
Step2: Import TensorFlow
To get started, import the tensorflow module. As of TensorFlow 2.0, eager execution is turned on... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
8,626 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
레버리지와 아웃라이어
레버리지 (Leverage)
개별적인 데이터 표본이 회귀 분석 결과에 미치는 영향은 레버리지(leverage)분석을 통해 알 수 있다.
레버리지는 target value $y$가 예측된(predicted) target $\hat{y}$에 미치는 영향을 나타낸 값이다. self-influence, self-sensiti... | Python Code:
from sklearn.datasets import make_regression
X0, y, coef = make_regression(n_samples=100, n_features=1, noise=20, coef=True, random_state=1)
# add high-leverage points
X0 = np.vstack([X0, np.array([[4], [3]])])
X = sm.add_constant(X0)
y = np.hstack([y, [300, 150]])
plt.scatter(X0, y)
plt.show()
model = sm.... |
8,627 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Run the CCF analysis
You should have already cross-correlated all your spectra against a suitable model using Search.py. This notebook goes through the shifting and subtracting of the averag... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import CombineCCFs
import numpy as np
from astropy import units as u, constants
from HelperFunctions import Gauss, integral
import os
import lmfit
import emcee
import triangle
from scipy.interpolate import Interpol... |
8,628 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using the SIAF class
The Science Instrument Aperture File, or SIAF, provides approximate conversions of sky positions to detector positions in support of operations. (More sophisticated corr... | Python Code:
%pylab inline --no-import-all
plt.style.use('ggplot')
Explanation: Using the SIAF class
The Science Instrument Aperture File, or SIAF, provides approximate conversions of sky positions to detector positions in support of operations. (More sophisticated corrections, e.g. for correcting and analyzing science... |
8,629 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
OpenMP example
In this example we illustrate how OpenMP can be used to speedup the calculation of the likelihood.
First we set the number of openmp threads. This is done via an environmental... | Python Code:
import os
os.environ['OMP_NUM_THREADS'] = '4'
Explanation: OpenMP example
In this example we illustrate how OpenMP can be used to speedup the calculation of the likelihood.
First we set the number of openmp threads. This is done via an environmental variable called OMP_NUM_THREADS. In this example we set t... |
8,630 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 编写自己的回调函数
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: Keras 回调函数概述
所有回调函数都将 keras.callb... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
8,631 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this short tutorial, we will compute the static connectivity of the EEG singals.
Load data
Step1: Static connectivity
As a first example, we are going to compute the static connectivity ... | Python Code:
import numpy as np
import scipy
from scipy import io
eeg = np.load("data/eeg_eyes_opened.npy")
num_trials, num_channels, num_samples = np.shape(eeg)
eeg_ts = np.squeeze(eeg[0, :, :])
Explanation: In this short tutorial, we will compute the static connectivity of the EEG singals.
Load data
End of explanatio... |
8,632 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Control Structures
Simple for loop
Write a for loop which iterates over the list of breakfast items "sausage", "eggs", "bacon" and "spam" and prints out the name of item
Step1: Write then a... | Python Code:
breakfast = ["sausage", "eggs", "bacon", "spam"]
for item in breakfast:
print(item)
Explanation: Control Structures
Simple for loop
Write a for loop which iterates over the list of breakfast items "sausage", "eggs", "bacon" and "spam" and prints out the name of item
End of explanation
squares = []
for ... |
8,633 | 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:
import os
import numpy as np
import matplotlib.pyplot as plt
import shogun as sg
%matplotlib inline
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
Explanation: Multiple Kernel Learning
By Saurabh Mahindre - <a href="https://github.com/Saurabh7">github.com/Saurabh7</a>
This notebook is about ... |
8,634 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="static/pybofractal.png" alt="Pybonacci" style="width
Step1: Note
Step2: The declaration of a model is also required. The use of the name <span style="color
Step3: We declare the... | Python Code:
!cat abstract1.py
Explanation: <img src="static/pybofractal.png" alt="Pybonacci" style="width: 200px;"/>
<img src="static/cacheme_logo.png" alt="CAChemE" style="width: 300px;"/>
1. Pyomo Overview
Note: Adapted from https://github.com/Pyomo/PyomoGettingStarted, by William and Becca Hart
1.1 Mathematical Mod... |
8,635 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Filtering and resampling data
This tutorial covers filtering and resampling, and gives examples of how
filtering can be used for artifact repair.
Step1: Background on filtering
A filter... | Python Code:
import os
import numpy as np
import matplotlib.pyplot as plt
import mne
sample_data_folder = mne.datasets.sample.data_path()
sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
'sample_audvis_raw.fif')
raw = mne.io.read_raw_fif(sample_data_raw_file)
... |
8,636 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 2
Work on this before the next lecture on 24 April. We will talk about questions, comments, and solutions during the exercise after the third lecture.
Please do form study groups! W... | Python Code:
%config InlineBackend.figure_format='retina'
%matplotlib inline
import numpy as np
np.random.seed(123)
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = (8, 8)
plt.rcParams["font.size"] = 14
from sklearn.utils import check_random_state
Explanation: Exercise 2
Work on this before the next lec... |
8,637 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook Tour
Step1: The Jupyter Notebook is a web-based application that enables users to create documents that combine live code wth narrative next, equations, images, visualizations and ... | Python Code:
from IPython.display import display, Image, HTML
from talktools import website, nbviewer
Explanation: Notebook Tour
End of explanation
2+2
import math
math.atan?
Explanation: The Jupyter Notebook is a web-based application that enables users to create documents that combine live code wth narrative next, eq... |
8,638 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Netscan
Here is a sample of some the capabilities of the netscan library.
Step1: Get host info
On macOS or Linux, GetHostName should be able to resolve a computer's IP address to a hostname... | Python Code:
from __future__ import print_function
from netscan.lib import WhoIs, GetHostName, MacLookup, Commands
import pprint as pp
Explanation: Netscan
Here is a sample of some the capabilities of the netscan library.
End of explanation
print(GetHostName('192.168.1.13').name)
print(GetHostName('127.0.0.1').name)
Ex... |
8,639 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Learning word embeddings - word2vec
- Saurabh Mathur
The aim of this experiment is to use the algorithm developed by Tomas Mikolov et al. to learn high quality vector representations of text... | Python Code:
import tensorflow as tf
Explanation: Learning word embeddings - word2vec
- Saurabh Mathur
The aim of this experiment is to use the algorithm developed by Tomas Mikolov et al. to learn high quality vector representations of text.
The skip-gram model
Given,
a sequence of words $ w_1, w_2, .., w_T $, predict ... |
8,640 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sliding Windows
Many applications require computations on sliding windows of streams. A sliding window is specified by a window size and a step size, both of which are positive integers. Sli... | Python Code:
import os
import sys
sys.path.append("../")
from IoTPy.core.stream import Stream, run
from IoTPy.agent_types.op import map_window
from IoTPy.helper_functions.recent_values import recent_values
def example():
x, y = Stream(), Stream()
map_window(func=sum, in_stream=x, out_stream=y, window_size=2, st... |
8,641 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 2
Step1: A function in PyRTL is nothing special -- it just so happens that the statements
it encapsulate tell PyRTL to build some hardware.
Step2: If we call one_bit_add
above with... | Python Code:
import pyrtl
pyrtl.reset_working_block()
Explanation: Example 2: A Counter with Ripple Carry Adder.
This next example shows how you make stateful things with registers
and more complex hardware structures with functions. We generate
a 3-bit ripple carry adder building off of the 1-bit adder from
the prio... |
8,642 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Export epochs to Pandas DataFrame
In this example the pandas exporter will be used to produce a DataFrame
object. After exploring some basic features a split-apply-combine
work flow will be ... | Python Code:
# Author: Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import mne
import matplotlib.pyplot as plt
import numpy as np
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif'
event_fname = dat... |
8,643 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Numpy has many built-in functions and capabilities. We won't cover them all but instead we will focus on some of the most important aspects of Numpy
Step2: Built-in Me... | Python Code:
import numpy as np
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
<center>Copyright Pierian Data 2017</center>
<center>For more information, visit us at www.pieriandata.com</center>
NumPy
NumPy (or Numpy) is a Linear Algebra Library for Python, the reason it i... |
8,644 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.1 - Calculer un chi 2 sur un tableau de contingence
$\chi_2$ et tableau de contingence, avec numpy, avec scipy ou sans.
Step1: formule
Le test du $\chi_2$ (wikipedia) sert à comparer deu... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.1 - Calculer un chi 2 sur un tableau de contingence
$\chi_2$ et tableau de contingence, avec numpy, avec scipy ou sans.
End of explanation
import numpy
M = numpy.array([[4, 5, 2, 1],
[6, 3, 1, 7],
... |
8,645 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This document demonstrate how to use the library to define a "density dependent population process" and to compute its mean-field approximation and refined mean-field approximation
Step1: E... | Python Code:
# To load the library
import rmftool as rmf
import importlib
importlib.reload(rmf)
# To plot the results
import numpy as np
import matplotlib.pyplot as plt
# %matplotlib inline
%matplotlib notebook
Explanation: This document demonstrate how to use the library to define a "density dependent population proce... |
8,646 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Trajectory equations
Step1: The equation of motion
Step2: For the case of a uniform magnetic field
along the $z$-axis
Step3: Assuming $E_z = 0$ and $E_y = 0$
Step4: Motion is uniform al... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from sympy import *
init_printing()
Ex, Ey, Ez = symbols("E_x, E_y, E_z")
Bx, By, Bz, B = symbols("B_x, B_y, B_z, B")
x, y, z = symbols("x, y, z")
vx, vy, vz, v = symbols("v_x, v_y, v_z, v")
t = symbols("t")
q, m = symbols("q, m")
c, eps0 = symbols("c, eps... |
8,647 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<small><i>This notebook was put together by Jake Vanderplas. Source and license info is on GitHub.</i></small>
Dimensionality Reduction
Step1: Introducing Principal Component Analysis
Princ... | Python Code:
from __future__ import print_function, division
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
plt.style.use('seaborn')
Explanation: <small><i>This notebook was put together by Jake Vanderplas. Source and license info is on GitHub.</i></small>
Dimensionality R... |
8,648 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
If I plan to run the scorer every batch to select loans, I should have a minimum score that a loan must receive to even be considered for investing in, and the remaining loans can be selecte... | Python Code:
import modeling_utils.data_prep as data_prep
from sklearn.externals import joblib
import time
platform = 'lendingclub'
store = pd.HDFStore(
'/Users/justinhsi/justin_tinkering/data_science/lendingclub/{0}_store.h5'.
format(platform),
append=True)
Explanation: If I plan to run the scorer every ba... |
8,649 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Download the list of occultation periods from the MOC at Berkeley.
Note that the occultation periods typically only are stored at Berkeley for the future and not for the past. So this is onl... | Python Code:
fname = io.download_occultation_times(outdir='../data/')
print(fname)
Explanation: Download the list of occultation periods from the MOC at Berkeley.
Note that the occultation periods typically only are stored at Berkeley for the future and not for the past. So this is only really useful for observation pl... |
8,650 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training on an Advanced Standard CNN Architecture
https
Step1: Preparation
Step2: Uncomment next three cells if you want to train on augmented image set
Otherwise Overfitting can not be av... | Python Code:
import warnings
warnings.filterwarnings('ignore')
%matplotlib inline
%pylab inline
import matplotlib.pylab as plt
import numpy as np
from distutils.version import StrictVersion
import sklearn
print(sklearn.__version__)
assert StrictVersion(sklearn.__version__ ) >= StrictVersion('0.18.1')
import tensorflow ... |
8,651 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
K-Nearest Neighbors (KNN)
by Chiyuan Zhang and Sören Sonnenburg
This notebook illustrates the <a href="http
Step1: Let us plot the first five examples of the train data (first row) and... | Python Code:
import numpy as np
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
from scipy.io import loadmat, savemat
from numpy import random
from os import path
import matplotlib.pyplot as plt
%matplotlib inline
import shogun as sg
mat = loadmat(os.path.join(SHOGUN_DATA_DIR, 'multicl... |
8,652 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Screenshots and Movies with WebGL
One can use the REBOUND WebGL ipython widget to capture screenshots of a simualtion. These screenshots can then be easily compiled into a movie.
The widget ... | Python Code:
import rebound
sim = rebound.Simulation()
sim.add(m=1) # add a star
for i in range(10):
sim.add(m=1e-3,a=0.4+0.1*i,inc=0.03*i,omega=5.*i) # Jupiter mass planets on close orbits
sim.move_to_com() # Move to the centre of mass frame
w = sim.getWidget()
w
Explanation: Screenshots and Movies with WebGL
One ... |
8,653 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stockmarket analysis with pmdarima
This example follows the post on Towards Data Science (TDS), demonstrating the use of pmdarima to simplify time series analysis.
Step1: Import the data
pm... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import pmdarima as pm
print(f"Using pmdarima {pm.__version__}")
Explanation: Stockmarket analysis with pmdarima
This example follows the post on Towards Data Science (TDS), demonstrating the use of pmdarima to simpl... |
8,654 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Source
Step1: Elements Are Lists
Step2: Attributes Are Dictonaries
Step3: Searching
Step4: Generating XML | Python Code:
#import lxml.etree as etree
try:
from lxml import etree as etree
except ImportError:
import xml.etree.ElementTree as etree
tree = etree.parse('feed.xml')
root = tree.getroot()
root
Explanation: Source : Dive Into Python - Chapter 12 XML by Mark Pilgrim
XML overview
XML is a generalized way of descr... |
8,655 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ZPIC Python interface
This notebook illustrates the use of the ZPIC Python interface to run a simulation and save the results to disk.
Calling ZPIC from Python requires importing the appropr... | Python Code:
import em1d
Explanation: ZPIC Python interface
This notebook illustrates the use of the ZPIC Python interface to run a simulation and save the results to disk.
Calling ZPIC from Python requires importing the appropriate ZPIC module. For this example we will be using the EM1D code, so we need to import the ... |
8,656 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Какво е "цикъл"?
В програмирането често се налага многократно изпълнение на дадена
последователност от операции.
Цикъл (loop) е основна конструкция в програмирането, която позволява
многокра... | Python Code:
counter = 1
while counter <= 10:
print(counter)
counter = counter + 1
print("end")
Explanation: Какво е "цикъл"?
В програмирането често се налага многократно изпълнение на дадена
последователност от операции.
Цикъл (loop) е основна конструкция в програмирането, която позволява
многократно изпъ... |
8,657 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vehicle Data
Data1.txt
Dies sind die Werte aus der Datei "data1.txt". Hierbei hatten wir einen folgende Startwerte
Step1: Da wir nun die entsprechenden Werte in numpy importiert haben, könn... | Python Code:
#Create Lists
time = [233.32,198.92,184.7,168.18,148.22,138.88,151.76,127.48,119.12,115.24,110.7,104.28,105.52,109.2,120.7401,147.027]
motorTorque = [100,110,121,133.1,146.41,161.051,161.051,177.1561,194.8717,214.3589,235.7948,259.3743,285.3117,313.8429,345.2272,379.74992]
print(time)
print('elements in ti... |
8,658 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nasa-giss', 'sandbox-1', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: NASA-GISS
Source ID: SANDBOX-1
Topic: Aerosol
Sub-Topics: Transport,... |
8,659 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Halo Scattering
v1 -- Mainly in the context of the FRB 181112 paper
Step1: Kolmogorov estimate
Equation 1 of Prochaska et al. 2019 by JP Macquart
Step2: $\tau = 1 $ms, $z_{\rm FRB} = 1$, $... | Python Code:
# imports
import numpy as np
from importlib import reload
from astropy import units
from astropy import constants
from frb import turb_scattering as frb_scatt
Explanation: Halo Scattering
v1 -- Mainly in the context of the FRB 181112 paper
End of explanation
reload(frb_scatt)
z_FRB = 0.4755
z_halo = 0.367
... |
8,660 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gaussian Process Regression in Pytorch
Thomas Viehmann, tv@lernapparat.de
Modelled after GPFlow Regression not... | Python Code:
from matplotlib import pyplot
%matplotlib inline
import IPython
import torch
import numpy
import sys, os
sys.path.append(os.path.join(os.getcwd(),'..'))
pyplot.style.use('ggplot')
import candlegp
import candlegp.training.hmc
Explanation: Gaussian Process Regression in Pytorch
Thomas Viehmann, tv&... |
8,661 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Todo
Step1: Rel risk. P(gender|misaligned)/P(gender)
What proportion of the misaligned dataset is about women?
For each gender, what proportion of the each misalignment group do the represe... | Python Code:
bigdf = pandas.read_csv('/media/notconfusing/9d9b45fc-55f7-428c-a228-1c4c4a1b728c/home/maximilianklein/snapshot_data/2016-01-03/gender-index-data-2016-01-03.csv')
gender_qid_df = bigdf[['qid','gender']]
def map_gender(x):
if isinstance(x,float):
return 'no gender'
else:
gen = x.spli... |
8,662 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data SITREP
redshiftzero, January 26, 2017
We've been collecting traces from crawling onion services, this notebook contains a brief SITREP of the status of the data collection.
Step1: Numb... | Python Code:
import os
import pandas as pd
import sqlalchemy
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('ggplot')
with open(os.environ["PGPASS"], "rb") as f:
content = f.readline().decode("utf-8").replace("\n", "").split(":")
engine = sqlalchemy.create_engine("postgresql:... |
8,663 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex client library
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Once you've installed the Vertex client library and Google clo... | Python Code:
import os
import sys
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install -U google-cloud-aiplatform $USER_FLAG
Explanation: Vertex client library: Local text binary classification model for online prediction
<... |
8,664 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FAQ
This document will address frequently asked questions not addressed in other pages of the documentation.
How do I install cobrapy?
Please see the INSTALL.rst file.
How do I cite cobrapy?... | Python Code:
from cobra.io import load_model
model = load_model("iYS1720")
for metabolite in model.metabolites:
metabolite.id = f"test_{metabolite.id}"
try:
model.metabolites.get_by_id(model.metabolites[0].id)
except KeyError as e:
print(repr(e))
Explanation: FAQ
This document will address frequently asked ... |
8,665 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
8,666 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocean
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cmcc', 'cmcc-cm2-hr5', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: CMCC
Source ID: CMCC-CM2-HR5
Topic: Ocean
Sub-Topics: Timestepping Framewo... |
8,667 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modifying Rates
Sometimes we want to change the nuclei involved in rates to simplify our network. Currently,
pynucastro supports changing the products. Here's an example.
Step1: We want t... | Python Code:
import pynucastro as pyna
reaclib_library = pyna.ReacLibLibrary()
Explanation: Modifying Rates
Sometimes we want to change the nuclei involved in rates to simplify our network. Currently,
pynucastro supports changing the products. Here's an example.
End of explanation
filter = pyna.RateFilter(reactants=[... |
8,668 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
_ doesn't look like much, but as part of a name in Python it has a surprising amount of different meanings.
Make names more readable
We all know that we should use good names. This often mak... | Python Code:
def spam(a, _, b):
return a + b
spam(1, 2, 3)
Explanation: _ doesn't look like much, but as part of a name in Python it has a surprising amount of different meanings.
Make names more readable
We all know that we should use good names. This often makes it necessary to use more than one word to describe ... |
8,669 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Video using the Base Overlay
The PYNQ-Z1 board contains a HDMI input port, and a HDMI output port connected to the FPGA fabric of the Zynq® chip. This means to use the HDMI ports, HDMI contr... | Python Code:
from pynq import Overlay
from pynq.drivers.video import HDMI
# Download bitstream
Overlay("base.bit").download()
# Initialize HDMI as an input device
hdmi_in = HDMI('in')
Explanation: Video using the Base Overlay
The PYNQ-Z1 board contains a HDMI input port, and a HDMI output port connected to the FPGA fab... |
8,670 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 Google LLC.
Licensed under the Apache License, Version 2.0 (the "License")
Step1: On Variational Bounds of Mutual Information
Ben Poole, Sherjil Ozair, Aäron van den Oor... | Python Code:
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distribute... |
8,671 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Scapy in 15 minutes (or longer)
Guillaume Valadon & Pierre Lalet
Scapy is a powerful Python-based interactive packet manipulation program and library. It can be used to forge or decode packe... | Python Code:
send(IP(dst="1.2.3.4")/TCP(dport=502, options=[("MSS", 0)]))
Explanation: Scapy in 15 minutes (or longer)
Guillaume Valadon & Pierre Lalet
Scapy is a powerful Python-based interactive packet manipulation program and library. It can be used to forge or decode packets for a wide number of protocols, send the... |
8,672 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
数据科学
数据科学问题解决流程 workflow stage
问题定义
获取训练和测试数据
数据清洗 预处理
分析数据
建模 预测 解决问题
可视化解决问题流程
提交结果到Kaggle
workflow 七大目标
数据科学workflow解决七大问题
1. 分类
1. 相关性 发现特征和结果之前的相关性 或者发现特征之前的相关性
1. 转换 建模阶段根据模型的不同可能需要将... | Python Code:
# 数据分析和预处理
import pandas as pd
import numpy as np
import random as rnd
# 数据可视化
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
# 机器学习算法
from sklearn.linear_model import LogisticRegression # logstic回归
from sklearn.linear_model import Perceptron # 感知机
from sklearn.linear_model impor... |
8,673 | Given the following text description, write Python code to implement the functionality described.
Description:
Search , insert and delete in a sorted array
function to implement binary search ; low + ( high - low ) / 2 ; Driver program to check above functions Let us search 3 in below array
| Python Code:
def binarySearch(arr , low , high , key ) :
mid =(low + high ) / 2
if(key == arr[int(mid ) ] ) :
return mid
if(key > arr[int(mid ) ] ) :
return binarySearch(arr ,(mid + 1 ) , high , key )
if(key < arr[int(mid ) ] ) :
return binarySearch(arr , low ,(mid - 1 ) , key )
return 0
a... |
8,674 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmos
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-3', 'sandbox-1', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: TEST-INSTITUTE-3
Source ID: SANDBOX-1
Topic: Atmos
Sub-Topics: Dy... |
8,675 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MLE with Normal distribution
Step1: Draw normal density
$$f\left(y_{i};\mu,\sigma\right)=\frac{1}{\sqrt{2\pi\sigma^{2}}}\exp\left(-\frac{\left(y_{i}-\mu\right)^{2}}{2\sigma^{2}}\right)$$
St... | Python Code:
import numpy as np
import matplotlib.pylab as plt
import seaborn as sns
np.set_printoptions(precision=4, suppress=True)
sns.set_context('notebook')
%matplotlib inline
Explanation: MLE with Normal distribution
End of explanation
theta = [[0., 1.], [.5, .5], [-.25, 2.]]
f = lambda x, mu, sigma: 1 / np.sqrt(2... |
8,676 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 2
Step1: If you get an error stating that database "homework2" does not exist, make sure that you followed the instructions above exactly. If necessary, drop the database you creat... | Python Code:
import pg8000
conn = pg8000.connect(database="homework2")
Explanation: Homework 2: Working with SQL (Data and Databases 2016)
This homework assignment takes the form of an IPython Notebook. There are a number of exercises below, with notebook cells that need to be completed in order to meet particular crit... |
8,677 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SVN Reports Dashboard
Reporting import/upload pipelines
Import Libraries
Libraries necessary to parse through each dashboard
Step1: Parametrization
Adding parameters for Papermill
Step2: S... | Python Code:
import datetime
from IPython.display import display, Markdown, Latex
import json
import numpy as np
import pandas as pd
Explanation: SVN Reports Dashboard
Reporting import/upload pipelines
Import Libraries
Libraries necessary to parse through each dashboard
End of explanation
site: str
Explanation: Paramet... |
8,678 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Unicode 文字列
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: tf.string データ型
標準的な TensorFlow ... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
8,679 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convolutional variational autoencoder with PyMC3 and Keras
In this document, I will show how autoencoding variational Bayes (AEVB) works in PyMC3's automatic differentiation variational infe... | Python Code:
#!pip install --upgrade git+https://github.com/Theano/Theano.git#egg=Theano
#!pip install --upgrade keras
#!pip install --upgrade pymc3
#!conda install -y mkl-service
%autosave 0
%matplotlib inline
import sys, os
os.environ['KERAS_BACKEND'] = 'theano'
from theano import config
config.floatX = 'float32'
con... |
8,680 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
¿Cómo vibra un tambor cuando lo golpeas?
Analizar el problema de la membrana vibrante permite entender el funcionamiento de instrumentos de percusión tales como los tambores, timbales e incl... | Python Code:
# Importamos todas las librerías que usaremos. Explicación...
%matplotlib inline
import matplotlib.pyplot as plt
from scipy import special
import numpy as np
from ipywidgets import *
# Graficamos funciones de Bessel de orden n = 0,1,...,4
r = np.linspace(0, 10,100)
for n in range(5):
plt.plot(r, specia... |
8,681 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Given a pandas DataFrame, how does one convert several binary columns (where 0 denotes the value exists, 1 denotes it doesn't) into a single categorical column? | Problem:
import pandas as pd
df = pd.DataFrame({'A': [0, 1, 1, 1, 0, 1],
'B': [1, 0, 1, 1, 1, 0],
'C': [1, 1, 0, 1, 1, 1],
'D': [1, 1, 1, 0, 1, 1]})
df["category"] = df.idxmin(axis=1) |
8,682 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center> Python and MySQL tutorial </center>
<center> Author
Step1: Calculator
Step2: Strings
Step3: show ' and " in a string
Step4: span multiple lines
Step5: slice and index
Step6: I... | Python Code:
width = 20
height = 5*9
width * height
Explanation: <center> Python and MySQL tutorial </center>
<center> Author: Cheng Nie </center>
<center> Check chengnie.com for the most recent version </center>
<center> Current Version: Feb 18, 2016</center>
Python Setup
Since most students in this class use Windows ... |
8,683 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ch 05
Step1: Define a class called SOM. The constructor builds a grid of nodes, and also defines some helper ops
Step2: Time to use our newfound powers. Let's test it out on some data | Python Code:
%matplotlib inline
import tensorflow as tf
import numpy as np
Explanation: Ch 05: Concept 03
Self-organizing map
Import TensorFlow and NumPy:
End of explanation
class SOM:
def __init__(self, width, height, dim):
self.num_iters = 100
self.width = width
self.height = height
... |
8,684 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 2
Step1: Example 1
Step2: Example 2
Step3: Example 3
Step4: Example 4
Step5: Example 5
Step6: Example 6 | Python Code:
# Import relevant modules
%matplotlib inline
%load_ext autoreload
%autoreload 2
import numpy as np
import healpy as hp
from NPTFit import create_mask as cm # Module for creating masks
Explanation: Example 2: Creating Masks
In this example we show how to create masks using create_mask.py.
Often it is conven... |
8,685 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classifying Risky P2P Loans
Abstract
The prevalence of a global Peer-to-Peer (P2P) economy, coupled with the recent deregulation of financial markets, has lead to the widespread adoption of ... | Python Code:
from IPython.display import display
from IPython.core.display import HTML
import warnings
warnings.filterwarnings('ignore')
import os
if os.getcwd().split('/')[-1] == 'notebooks':
os.chdir('../')
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import seaborn as ... |
8,686 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TODO
Step1: Коэффициент для учета вклада гелия в массу газа (см. Notes)
Step2: Для большой оси
Step3: Для случая бесконечного тонкого диска
Step4: Два других механизма из http
Step5: Hu... | Python Code:
%run ../../utils/load_notebook.py
from instabilities import *
import numpy as np
Explanation: TODO: сделать так, чтобы можно было импортировать
End of explanation
He_coeff = 1.34
def flat_end(argument):
'''декоратор для того, чтобы продолжать функцию на уровне последнего значения'''
def real_decora... |
8,687 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
JSON examples and exercise
get familiar with packages for dealing with JSON
study examples with JSON strings and files
work on exercise to be completed and submitted
reference
Step1: impo... | Python Code:
import pandas as pd
Explanation: JSON examples and exercise
get familiar with packages for dealing with JSON
study examples with JSON strings and files
work on exercise to be completed and submitted
reference: http://pandas.pydata.org/pandas-docs/stable/io.html#io-json-reader
data source: http://jsonstud... |
8,688 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Recursive Implementation of Minimax
This notebook implements the minimax algorithm in a pure form, i.e. it does not employ any memoization techniques.
In order to have some variation in ou... | Python Code:
import random
random.seed(1)
Explanation: A Recursive Implementation of Minimax
This notebook implements the minimax algorithm in a pure form, i.e. it does not employ any memoization techniques.
In order to have some variation in our games, we use random numbers to choose between different optimal moves.
E... |
8,689 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Caso de uso 1 - Validación, transformación y harvesting con el catálogo del Ministerio de Justicia
Caso 1
Step1: Declaración de variables y paths
Step2: Validación del archivo xlsx y trans... | Python Code:
import arrow
import os, sys
sys.path.insert(0, os.path.abspath(".."))
from pydatajson import DataJson #lib y clase
from pydatajson.readers import read_catalog # lib, modulo ... metodo Lle el catalogo -json o xlsx o (local o url) dicc- y lo transforma en un diccionario de python
from pydatajson.writers impo... |
8,690 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: モジュール、レイヤー、モデルの概要
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: TensorFlow におけるモデルとレイヤーの定... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
8,691 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
What is an efficient way of splitting a column into multiple rows using dask dataframe? For example, let's say I have a csv file which I read using dask to produce the following das... | Problem:
import pandas as pd
df = pd.DataFrame([["A", "Z-Y"], ["B", "X"], ["C", "W-U-V"]], index=[1,2,3], columns=['var1', 'var2'])
def g(df):
return df.join(pd.DataFrame(df.var2.str.split('-', expand=True).stack().reset_index(level=1, drop=True),columns=['var2 '])).\
drop('var2',1).rename(columns=str.strip... |
8,692 | 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: Authentication
Step2: Install the h5py to prepare sample dataset, and the grpcio-tools for querying against the index.
Step3: Restart... | Python Code:
PROJECT_ID = "<your_project_id>" # @param {type:"string"}
NETWORK_NAME = "ucaip-haystack-vpc-network" # @param {type:"string"}
PEERING_RANGE_NAME = "ucaip-haystack-range"
# Create a VPC network
! gcloud compute networks create {NETWORK_NAME} --bgp-routing-mode=regional --subnet-mode=auto --project={PROJE... |
8,693 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ch 02
Step1: The moving average is defined as follows
Step2: Here's what we care to visualize
Step3: Time to compute the moving averages. We'll also run the merged op to track how the val... | Python Code:
import tensorflow as tf
import numpy as np
raw_data = np.random.normal(10, 1, 100)
Explanation: Ch 02: Concept 08
Using TensorBoard
TensorBoard is a great way to visualize what's happening behind the code.
In this example, we'll loop through some numbers to improve our guess of the average value. Then we ... |
8,694 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Grove Gesture Example
This example shows how to use the
Grove gesture sensor on the board.
The gesture sensor can detect 10 gestures as follows
Step1: 1. Instantiate the sensor object
Step... | Python Code:
from pynq.overlays.base import BaseOverlay
base = BaseOverlay("base.bit")
Explanation: Grove Gesture Example
This example shows how to use the
Grove gesture sensor on the board.
The gesture sensor can detect 10 gestures as follows:
| Raw value read by sensor | Gesture |
|-----------------------... |
8,695 | Given the following text description, write Python code to implement the functionality described.
Description:
Sum of the series 1 + ( 1 + 2 ) + ( 1 + 2 + 3 ) + ( 1 + 2 + 3 + 4 ) + ... ... + ( 1 + 2 + 3 + 4 + ... + n )
Function to find sum of series ; Driver Code
| Python Code:
def sumOfSeries(n ) :
return sum([ i *(i + 1 ) / 2 for i in range(1 , n + 1 ) ] )
if __name__== "__main __":
n = 10
print(sumOfSeries(n ) )
|
8,696 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ClarityViz Tutorial
Overview
claritybase
Step1: 2) local histogram equilization
local histogram equilization is the process of enhancing low contrast images, and makes the pixel values easi... | Python Code:
from clarityviz import claritybase
token = 'Fear199'
source_directory = '/cis/home/alee/claritycontrol/code/data/raw'
# Initialize the claritybase object, the initial basis for all operations.
# After you initialize with a token and source directory, a folder will be created in your current directory
# wit... |
8,697 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Temporary notebook to get the parameters for the MICE sims for the data ismael sent me.
Step1: mean number of central/satellites per bin. read with pd.read_csv(‘hod_redmagicMICE.csv’, sep='... | Python Code:
import pandas as pd
import numpy as np
#fit given by Andres
#CENTRALS
def f_cen(logmhalo,logmmin,siglogm,fmaxcen,fmincen,k,logmdrop):
ncen = 0.5*( 1. + ss.erf((logmhalo[0,:] - logmmin)/siglogm) )
ncen = fmaxcen * ncen
ncen = ncen * (1.0 - (1.0-fmincen/fmaxcen)/(1.0 + 10**((2.0/k)*(logmha... |
8,698 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Survival Analysis
Think Bayes, Second Edition
Copyright 2020 Allen B. Downey
License
Step1: This chapter introduces "survival analysis", which is a set of statistical methods used to answer... | 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(... |
8,699 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load the relevant libraries
Step1: set the stage for data visualization
Step2: Load the dataset and make a copy of it
Step3: List all the variables in the dataset
Step4: Data standardisa... | Python Code:
import pandas as pd # for data import and dissection
import numpy as np # for data analysis
import statsmodels.formula.api as smf
import statsmodels.api as sm
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
Explanation: Load the relevant libraries
End of explanation
plt.interactive... |
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