Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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12,400 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using subset-selector
Create SubsetSelector with data and plot. y should be a multidimensional array. Each sample from a subset of y is graphed. You can scroll through subsets using the figu... | Python Code:
from subset_selector import SubsetSelector
ss = SubsetSelector(x, y)
ss.plot()
Explanation: Using subset-selector
Create SubsetSelector with data and plot. y should be a multidimensional array. Each sample from a subset of y is graphed. You can scroll through subsets using the figure's toolbar, select grap... |
12,401 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Keras でマスキングとパディングをする
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: はじめに
マスキングは、シーケンス処理レイヤーに入力... | 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... |
12,402 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
See quick reference at the bottom
See full module reference section for full details
In the begining of each analysis, the first step is to load ReproPhylo and its dependencies with the comm... | Python Code:
from reprophylo import *
Explanation: See quick reference at the bottom
See full module reference section for full details
In the begining of each analysis, the first step is to load ReproPhylo and its dependencies with the command
End of explanation
coi = Locus(char_type='dna',
feature_type='... |
12,403 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 3
Step1: if ... else statement
python
if <condition>
Step2: if ...elif ... else statement
python
if <condition>
Step3: Imagine that in the above program, 23 is the tem... | Python Code:
password = input("Please enter the password:")
if password == "Simsim":
print("\t> Welcome to the cave")
x = "Mayank"
y = "TEST"
if y == "TEST":
print(x)
if y:
print("Hello World")
z = None
if z:
print("TEST")
x = 11
if x > 10:
print("Hello")
if x > 10.999999999999:
print("H... |
12,404 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This IPython Notebook is for integrating filter curves with the spectra to show the Si gap's effect size on tranmission in IR imaging.
Author
Step1: From the Thorlabs website
Step2: Normal... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
Explanation: This IPython Notebook is for integrating filter curves with the spectra to show the Si gap's effect size on tranmission in IR imaging.
Author: Michael Gully-Santiago, gully@astro.as.... |
12,405 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spark + Python = PySpark
Esse notebook introduz os conceitos básicos do Spark através de sua interface com a linguagem Python. Como aplicação inicial faremos o clássico examplo de contador d... | Python Code:
from pyspark import SparkContext
sc =SparkContext()
ListaPalavras = ['gato', 'elefante', 'rato', 'rato', 'gato']
palavrasRDD = sc.parallelize(ListaPalavras, 4)
print type(palavrasRDD)
Explanation: Spark + Python = PySpark
Esse notebook introduz os conceitos básicos do Spark através de sua interface com a l... |
12,406 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Source localization with MNE/dSPM/sLORETA/eLORETA
The aim of this tutorial is to teach you how to compute and apply a linear
inverse method such as MNE/dSPM/sLORETA/eLORETA on evoked/raw/epo... | Python Code:
# sphinx_gallery_thumbnail_number = 10
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample
from mne.minimum_norm import make_inverse_operator, apply_inverse
Explanation: Source localization with MNE/dSPM/sLORETA/eLORETA
The aim of this tutorial is to teach you how ... |
12,407 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CrowdTruth for Multiple Choice Tasks
Step1: Declaring a pre-processing configuration
The pre-processing configuration defines how to interpret the raw crowdsourcing input. To do this, we ne... | Python Code:
import pandas as pd
test_data = pd.read_csv("../data/relex-multiple-choice.csv")
test_data.head()
Explanation: CrowdTruth for Multiple Choice Tasks: Relation Extraction
In this tutorial, we will apply CrowdTruth metrics to a multiple choice crowdsourcing task for Relation Extraction from sentences. The wor... |
12,408 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GitHub Analiza
iz
V tem projektu bomo analizirali najpopularnejše odprte repozitorije na priljubljeni strani GitHub. Podatki so bili zajeti iz https
Step1: Naložimo zajete podatke in si ogl... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
pd.options.display.max_rows = 20
Explanation: GitHub Analiza
iz
V tem projektu bomo analizirali najpopularnejše odprte repozitorije na priljubljeni strani GitHub. Podatki so bili zajeti iz https://api.github.com, kar ... |
12,409 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How many movies are listed in the titles dataframe?
Step1: What are the earliest two films listed in the titles dataframe?
Step2: How many movies have the title "Hamlet"?
Step3: How many ... | Python Code:
titles.tail()
len(titles)
Explanation: How many movies are listed in the titles dataframe?
End of explanation
titles.sort(columns='year', ascending=True).head()[:2]
Explanation: What are the earliest two films listed in the titles dataframe?
End of explanation
titles[titles['title'].str.contains('Hamlet')]... |
12,410 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Conventional "dB-differencing" analysis
Step1: Set params and load clean MVBS data
Step2: dB-differencing operation
Here I used the criteria from Sato et al. 2015 for dB-differencing. The ... | Python Code:
import os, sys, glob, re
import datetime as dt
import numpy as np
from matplotlib.dates import date2num,num2date
import h5py
sys.path.insert(0,'..')
sys.path.insert(0,'../mi_instrument/')
import db_diff
import decomp_plot
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatab... |
12,411 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DATA 643 - Final Project
Sreejaya Nair and Suman K Polavarapu
Description
Step1: Prepare the pySpark Environment
Step2: Initialize Spark Context
Step3: Load and Analyse Data
Step4: Ratin... | Python Code:
import os
import sys
import urllib2
import collections
import matplotlib.pyplot as plt
import math
from time import time, sleep
%pylab inline
Explanation: DATA 643 - Final Project
Sreejaya Nair and Suman K Polavarapu
Description:
Explore the Apache Spark Cluster Computing Framework by analysing the moviele... |
12,412 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Contents
Step1: 2. Millionaires
What country are most billionaires from? For the top ones, how many billionaires per billion people?
Step2: What's the average wealth of a billionaire? Male... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv("07-hw-animals.csv")
df.columns
df.head(3)
df.sort_values(by='length', ascending=False).head(3)
df['animal'].value_counts()
dogs = df[df['animal']=='dog']
dogs
df[df['length'] > 40]
df['inches'] = .393701 * df['length']... |
12,413 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div class="alert alert-block alert-info" style="margin-top
Step1: <a id="ref0"></a>
<h2> Helper Functions </h2>
Functions used to plot
Step2: dataset object
Step3: <a id='ref1'> </a>
<h2... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from matplotlib.colors import ListedColormap
torch.manual_seed(1)
Explanation: <div class="alert alert-block alert-info" style="margin-top: 20px">
<a href="http://cocl.us/NotebooksPython1... |
12,414 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Face Generation
In this project, you'll use generative adversarial networks to generate new images of faces.
Get the Data
You'll be using two datasets in this project
Step3: Explore ... | Python Code:
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input/R5KrjnANiKVhLWAkpXhNBe'
import time
import pylab as pl
from IPython import display
DON'T MODIFY ANYTHING IN THIS CELL
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', dat... |
12,415 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hadamard Multitask GP Regression
Introduction
This notebook demonstrates how to perform "Hadamard" multitask regression.
This differs from the multitask gp regression example notebook in on... | Python Code:
import math
import torch
import gpytorch
from matplotlib import pyplot as plt
%matplotlib inline
%load_ext autoreload
%autoreload 2
Explanation: Hadamard Multitask GP Regression
Introduction
This notebook demonstrates how to perform "Hadamard" multitask regression.
This differs from the multitask gp regre... |
12,416 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinary Differential Equations Exercise 3
Imports
Step1: Damped, driven nonlinear pendulum
The equations of motion for a simple pendulum of mass $m$, length $l$ are
Step4: Write a functio... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
Explanation: Ordinary Differential Equations Exercise 3
Imports
End of explanation
g = 9.81 # m/s^2
l = 0.5 # length of pendul... |
12,417 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Astropy quantities
Astropy quantitites are a great way to handle all sorts of messy unit conversions. Careful unit conversions save lives! https
Step1: A brief word of warning, the pretty... | Python Code:
print(type(u.Msun))
u.Msun
Explanation: Astropy quantities
Astropy quantitites are a great way to handle all sorts of messy unit conversions. Careful unit conversions save lives! https://en.wikipedia.org/wiki/Gimli_Glider
The simplest way to create a new quantity object is multiply or divide a number by ... |
12,418 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
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', 'fio-ronm', 'sandbox-1', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: FIO-RONM
Source ID: SANDBOX-1
Topic: Landice
Sub-Topics: Glaciers, Ic... |
12,419 | 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>
Density Estimation
Step1: Introducing Gaussian Mixture Models
We previously sa... | Python Code:
%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>
Density Estimation: Gaussian Mixture Models
Here we'll explore G... |
12,420 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Model Complexity, Overfitting and Underfitting
Step1: Validation Curves
Step2: Exercise
Plot the validation curve on the digit dataset for | Python Code:
from plots import plot_kneighbors_regularization
plot_kneighbors_regularization()
Explanation: Model Complexity, Overfitting and Underfitting
End of explanation
from sklearn.datasets import load_digits
from sklearn.ensemble import RandomForestClassifier
from sklearn.learning_curve import validation_curve
d... |
12,421 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A class to represent Phase Noise
imports
Step1: Introduction
This document present a class in the plldesinger python module used to represent phase noise. The class have methods to compute... | Python Code:
from __future__ import division
# Matrix computation
import numpy as np
from numpy import sqrt, diff, conj
from numpy.random import randn
# Signal processing routines
import scipy.signal as sig
# Symbolic math
import sympy as sym
sym.init_printing(use_latex='mathjax')
# Plotting
import matplotlib
import ma... |
12,422 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Rabi model fitting
Step1: The model
According to the Rabi model, the probability of being in the excited state, $p_e$ is given by,
\begin{equation}
P_e = a_0 + a_1 \frac{\Omega^2}{W^2} ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats
from scipy.optimize import curve_fit
%matplotlib inline
Explanation: Rabi model fitting
End of explanation
def rabiModel(time, rabiFreq, T1, Tdec, phi, a0, a1, a2, detuning=0.0):
phi_deg = phi*(np.pi/180)
W = np.sqrt(rab... |
12,423 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Encontro 03
Step1: Carregando e visualizando o grafo | Python Code:
import sys
sys.path.append('..')
import socnet as sn
Explanation: Encontro 03: Grafos Reais
Importando a biblioteca:
End of explanation
sn.node_size = 3
sn.node_color = (0, 0, 0)
sn.edge_width = 1
sn.edge_color = (192, 192, 192)
sn.node_label_position = 'top center'
g = sn.load_graph('twitter.gml')
sn.show... |
12,424 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Network Analysis
This group exercise is designed to develop an understanding of basic network measures and to start participants thinking about interesting research questions that can be ena... | Python Code:
with open('karate_edges_77.txt', 'rb') as file:
karate_club = nx.read_edgelist(file) # Read in the edges
groups = {}
with open('karate_groups.txt', 'r') as file:
for line in file:
[node, group] = re.split(r'\t+', line.strip())
groups[node] = int(group)
nx.set_node_attributes(karate... |
12,425 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute iterative reweighted TF-MxNE with multiscale time-frequency dictionary
The iterative reweighted TF-MxNE solver is a distributed inverse method
based on the TF-MxNE solver, which prom... | Python Code:
# Author: Mathurin Massias <mathurin.massias@gmail.com>
# Yousra Bekhti <yousra.bekhti@gmail.com>
# Daniel Strohmeier <daniel.strohmeier@tu-ilmenau.de>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD-3-Clause
import os.path as op
import mne
from mne.datasets impo... |
12,426 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reproducing "Observations on the statistical iterations of matrices" by J.H. Hetherington*
I. Introduction
We can use stochastic iteration to effect the power method for sampling the extrema... | Python Code:
# construct an exemplary non-negative matrix
A = zeros([2,2])
A[0,0] = 2.0
A[1,1] = 1.0
A[1,0] = 3.0
A[0,1] = 4.0
print 'Matrix A: \n', A
# verify that columns do not sum to 1
print 'Column 0 sum: ', sum(A[:,0])
print 'Column 1 sum: ', sum(A[:,1])
print 'Matrix A is non-negative but the columns do not sum ... |
12,427 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Week 4
Step1: If we want to do any "feature engineering" like creating new features or adjusting existing ones we should do this directly using the SFrames as seen in the first n... | Python Code:
import graphlab
import numpy as np
import pandas as pd
from sklearn import linear_model
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('darkgrid')
%matplotlib inline
Explanation: Regression Week 4: Ridge Regression (gradient descent)
In this notebook, we will i... |
12,428 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Azimuthal Integral
Introduction
This tutorial demonstrates how to acquire an azimuthal integral profile from a multidimensional data set in pyXem.
The data set is a 10x10x256x256 data set o... | Python Code:
%matplotlib inline
import hyperspy.api as hs
import numpy as np
import matplotlib.pyplot as plt
Explanation: Azimuthal Integral
Introduction
This tutorial demonstrates how to acquire an azimuthal integral profile from a multidimensional data set in pyXem.
The data set is a 10x10x256x256 data set of a poly... |
12,429 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parameter selection, Validation & Testing
Most models have parameters that influence how complex a model they can learn. Remember using KNeighborsRegressor.
If we change the number of neighb... | Python Code:
from figures import plot_kneighbors_regularization
plot_kneighbors_regularization()
Explanation: Parameter selection, Validation & Testing
Most models have parameters that influence how complex a model they can learn. Remember using KNeighborsRegressor.
If we change the number of neighbors we consider, we ... |
12,430 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create The Data
The dataset used in this tutorial is the famous iris dataset. The Iris target data contains 50 samples from three species of Iris, y and four feature variables,... | Python Code:
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.feature_selection import SelectFromModel
from sklearn.metrics import accuracy_score
Explanation: Title: Feature Selection Using Random Forest... |
12,431 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Lime with Pytorch
In this tutorial we will show how to use Lime framework with Pytorch. Specifically, we will use Lime to explain the prediction generated by one of the pretrained Imag... | Python Code:
import matplotlib.pyplot as plt
from PIL import Image
import torch.nn as nn
import numpy as np
import os, json
import torch
from torchvision import models, transforms
from torch.autograd import Variable
import torch.nn.functional as F
Explanation: Using Lime with Pytorch
In this tutorial we will show how t... |
12,432 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training a better model
Step1: Are we underfitting?
Our validation accuracy so far has generally been higher than our training accuracy. That leads to two obvious questions
Step2: ...and l... | Python Code:
from theano.sandbox import cuda
%matplotlib inline
import utils; reload(utils)
from utils import *
from __future__ import division, print_function
#path = os.path.join('input','sample')
path = os.path.join('input','sample-10')
#path = os.path.join('input')
output_path = os.path.join('output','sample')
mode... |
12,433 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NormMUSIC Demo
The goal of this notebook is to demonstrate the effect of frequency normalization when MUSIC is applied on broadband signals
The notebook is structured as follows
Step1: <a i... | Python Code:
# imports
import pickle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.signal import stft
from random import uniform, sample
from pyroomacoustics import doa, Room, ShoeBox
Explanation: NormMUSIC Demo
The goal of this notebook is to demonstrate the ef... |
12,434 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overview
Contents
Introduction to Python
The Python Interpreter
First Steps with Python
Importing Libraries
About the Data
Arrays and their Attributes
Getting Help
More on Arrays
Basic Data ... | Python Code:
import glob
filenames = glob.glob('*.csv')
filenames
Explanation: Overview
Contents
Introduction to Python
The Python Interpreter
First Steps with Python
Importing Libraries
About the Data
Arrays and their Attributes
Getting Help
More on Arrays
Basic Data Visualization
Repeating Tasks with Loops
Sequences
... |
12,435 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Visualizing eclipse data
Let us find some interesting data to generate elements from, before we consider how to customize them. Here is a dataset containing information... | Python Code:
import pandas as pd
import holoviews as hv
hv.extension('bokeh', 'matplotlib')
Explanation: <a href='http://www.holoviews.org'><img src="assets/hv+bk.png" alt="HV+BK logos" width="40%;" align="left"/></a>
<div style="float:right;"><h2>02. Customizing Visual Appearance</h2></div>
Section 01 focused on speci... |
12,436 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Review from the previous lecture
In yesterday's Lecture 2, you learned how to use the numpy module, how to make your own functions, and how to import and export data. Below is a quick review... | Python Code:
import numpy as np
Explanation: Review from the previous lecture
In yesterday's Lecture 2, you learned how to use the numpy module, how to make your own functions, and how to import and export data. Below is a quick review before we move on to Lecture 3.
Remember, to use the numpy module, first it must be ... |
12,437 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I'm using tensorflow 2.10.0. | Problem:
import tensorflow as tf
A = tf.constant([-0.5, -0.1, 0, 0.1, 0.5, 2], dtype=tf.float32)
def g(A):
return tf.math.reciprocal(A)
result = g(A.__copy__()) |
12,438 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time Maps
inspiration from https
Step1: the example in the blog post is for a heat map of the amount of time in between events in a sequence.
Step2: Our data file includes equal intervals,... | Python Code:
import os; os.sys.path.append(os.path.dirname(os.path.abspath('.'))) # for relative imports
from utils.nab_data import NABData
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
data = NABData()
data.summary().head()
data.data.keys()
data.plot('nyc_taxi')
Explanation:... |
12,439 | 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', 'ncc', 'noresm2-mh', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: NCC
Source ID: NORESM2-MH
Topic: Atmos
Sub-Topics: Dynamical Core, Radiation,... |
12,440 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Agents
Step2: Conway's Game of Life
A simple agent model is Conway's Game of Life, which is an example of Cellular automota. A two-dimensional square grid of cells are either "dead" or "ali... | Python Code:
from IPython.core.display import HTML
css_file = 'https://raw.githubusercontent.com/ngcm/training-public/master/ipython_notebook_styles/ngcmstyle.css'
HTML(url=css_file)
Explanation: Agents: Lab 1
End of explanation
%matplotlib inline
import numpy
from matplotlib import pyplot, animation
from matplotlib im... |
12,441 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook shows the how tallies can be combined (added, subtracted, multiplied, etc.) using the Python API in order to create derived tallies. Since no covariance information is obtained... | Python Code:
import glob
from IPython.display import Image
import numpy as np
import openmc
Explanation: This notebook shows the how tallies can be combined (added, subtracted, multiplied, etc.) using the Python API in order to create derived tallies. Since no covariance information is obtained, it is assumed that tall... |
12,442 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fantasy (first steps)
This shows how to use Pandas to manipulate roster data.
$\rightarrow$ Use [Control] + [Enter] to evaluate a cell. (Check the 'Help' menu above for more.)
Step1: First ... | Python Code:
##
# Setup -- import the modules we want and set up inline plotting
#
from __future__ import print_function
import datetime
import matplotlib
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
# Bigger fonts and figures for the demo
matplotlib.rcParams.update({
... |
12,443 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Oregon Curriculum Network <br />
Discovering Math with Python
Crystal Ball Sequence
The face-centered cubic (FCC) lattice is not always presented in this simplest form, ditto the cubi... | Python Code:
from itertools import accumulate, islice
def cubocta():
Classic Generator: Cuboctahedral / Icosahedral #s
https://oeis.org/A005901
yield 1 # nuclear ball
f = 1
while True:
elem = 10 * f * f + 2 # f for frequency
yield elem # <--- pause / resume here
... |
12,444 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Description
Step1: Time to equilibrium
Step2: sigma as a function of time & fragment length
Step3: Graphing sigma as a function of time & fragment length
Step4: Low GC
Step5: High GC
St... | Python Code:
%load_ext rpy2.ipython
%%R
library(dplyr)
library(tidyr)
library(ggplot2)
library(gridExtra)
%%R
GC2MW = function(x){
A = 313.2
T = 304.2
C = 289.2
G = 329.2
GC = G + C
AT = A + T
x = x / 100
x*GC + (1-x)*AT
}
GC2BD = function(GC){
# GC = percentage
BD = GC / 100 ... |
12,445 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
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', 'miroc', 'nicam16-7s', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: MIROC
Source ID: NICAM16-7S
Topic: Seaice
Sub-Topics: Dynamics, Thermodyn... |
12,446 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting the location of the North Sea Harding Oil and Gas field
This example is taken out of my Ph.D. thesis. It shows the North Sea bathymetry and the topography of the surrounding countri... | Python Code:
import shapefile
import numpy as np
from matplotlib import cm, rcParams
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
rcParams.update({'font.size': 16}) # Increase font-size
Explanation: Plotting the location of the North Sea Harding Oil and Gas field
This example is taken out of... |
12,447 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading data from Excel
Let's get some data. Download Sample Superstore Sales .xls file or my local copy and open it in Excel to see what it looks like.
Data of interest that we want to proc... | Python Code:
with open('data/SampleSuperstoreSales.xls', "rb") as f:
txt = f.read()
print(txt[0:100])
Explanation: Reading data from Excel
Let's get some data. Download Sample Superstore Sales .xls file or my local copy and open it in Excel to see what it looks like.
Data of interest that we want to process in ... |
12,448 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 勾配の計算
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: TensorFlow Quantum をインストールします。
Step3:... | 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... |
12,449 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
prelim_month - create Reliability_Names data
2016.12.04 - work log - prelim_month - create Reliability_Names
original file name
Step1: Setup - virtualenv jupyter kernel
Back to Table of Con... | Python Code:
import datetime
print( "packages imported at " + str( datetime.datetime.now() ) )
Explanation: prelim_month - create Reliability_Names data
2016.12.04 - work log - prelim_month - create Reliability_Names
original file name: 2016.12.04-work_log-prelim_month-create_Reliability_Names.ipynb
This is the noteboo... |
12,450 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Resonances of Jupiter's moons, Io, Europa, and Ganymede
Example provided by Deborah Lokhorst. In this example, the four Galilean moons of Jupiter are downloaded from HORIZONS and their orbit... | Python Code:
import rebound
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
sim = rebound.Simulation()
sim.units = ('AU', 'days', 'Msun')
# We can add Jupiter and four of its moons by name, since REBOUND is linked to the HORIZONS database.
labels = ["Jupiter", "Io", "Europa","Ganymede","Callisto"]... |
12,451 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Annotation
Consider a binary classification problem. We will fit a predictor and use it to assign a weight score to each node in each instance; this operation is referred to as "annotation".... | Python Code:
pos = 'bursi.pos.gspan'
neg = 'bursi.neg.gspan'
from eden.converter.graph.gspan import gspan_to_eden
iterable_pos = gspan_to_eden( pos )
iterable_neg = gspan_to_eden( neg )
#split train/test
train_test_split=0.9
from eden.util import random_bipartition_iter
iterable_pos_train, iterable_pos_test = random_bi... |
12,452 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1 toc-item"><a href="#Booleans" data-toc-modified-id="Booleans-1"><span class="toc-item-num">1 </span>Booleans</a></div><div class="lev2 toc-it... | Python Code:
mybool_1 = True
print(mybool_1)
mybool_2 = False
print(mybool_2)
Explanation: Table of Contents
<p><div class="lev1 toc-item"><a href="#Booleans" data-toc-modified-id="Booleans-1"><span class="toc-item-num">1 </span>Booleans</a></div><div class="lev2 toc-item"><a href="#Not-True-/-Not-False?" da... |
12,453 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recently, I’ve become quite interested in fandoms. In particular, I’m curious about the process through which characters become the collective property of amateur writers.
With multiple auth... | Python Code:
#1. import
from bs4 import BeautifulSoup
import nltk
with open ('stopwords_names.txt') as f:
stopwords_string = f.read()
names_tokenizer = nltk.word_tokenize(stopwords_string)
names_tokens = [word.lower() for word in names_tokenizer if word[0].isalpha()]
stop_words = nltk.corpus.stopwords.words("... |
12,454 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Domestic Load Research Programme Social Survey Exploration
This notebook requires access to a data directory with DLR survey data saved as feather objects. The data files must be saved in /d... | Python Code:
import processing.procore as pcore
import features.socios as s
tbls = pcore.loadTables()
print("Stored Data Tables\n")
for k in sorted(list(tbls.keys())):
print(k)
Explanation: Domestic Load Research Programme Social Survey Exploration
This notebook requires access to a data directory with DLR survey d... |
12,455 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CMEMS Visualization
Import packages
For this visualization of a sample <i>index_latest.txt</i> dataset of the Copernicus Marine Environment Monitoring Service, we use the two packages
Step1:... | Python Code:
import numpy as np
import folium
Explanation: CMEMS Visualization
Import packages
For this visualization of a sample <i>index_latest.txt</i> dataset of the Copernicus Marine Environment Monitoring Service, we use the two packages:
* <a href="https://github.com/python-visualization/folium">folium</a> for th... |
12,456 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a network written with ... | Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
Explanation: Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a n... |
12,457 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Start with our simple example
Let's start with $f(x) = x^2$
Step1: Let's assume we start at the top of the curve, at x = -4, and want to get down to x=0.
Step2: In this algorithm, alpha is... | Python Code:
# make our x array
x = np.linspace(-4, 4, 801)
# f(x) = x^2
def f(x):
return x**2
# derivative of x^2 is 2x
def f_prime(x):
return 2*x
# take a look at the curve
plt.plot(x, f(x), c='black')
sns.despine();
Explanation: Start with our simple example
Let's start with $f(x) = x^2$:
End of explanation
... |
12,458 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: A Primer
Finding Hyperparameters
Grid Search?
python
param_grid = [
{'C'
Step4: Setup
Assumptions
search space for each parameter is random uniform between 0 and 1
200 iterations f... | Python Code:
def smbo(generator_fn,
score_fn,
evaluation_fn,
num_dims,
num_initial_points=10,
num_iter=200,
num_generated=10000):
general sequential model based optimization to minimize the result
of some presumably expensive function
generator_fn:
... |
12,459 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dual CRISPR Screen Analysis
Step 1
Step1: Automated Set-Up
Step2: Scaffold Trimming Functions
Step3: Gzipped FASTQ Filenames
Step4: FASTQ Gunzip Execution
Step5: FASTQ Filenames
Step6: ... | Python Code:
g_num_processors = 3
g_fastqs_dir = '~/dual_crispr/test_data/test_set_1'
g_trimmed_fastqs_dir = '~/dual_crispr/test_outputs/test_set_1'
g_full_5p_r1 = 'TATATATCTTGTGGAAAGGACGAAACACCG'
g_full_5p_r2 = 'CCTTATTTTAACTTGCTATTTCTAGCTCTAAAAC'
g_full_3p_r1 = 'GTTTCAGAGCTATGCTGGAAACTGCATAGCAAGTTGAAATAAGGCTAGTCCGTTA... |
12,460 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What are the ten most common movie names of all time?
Step1: Which three years of the 1930s saw the most films released?
Step2: Plot the number of films that have been released each decade... | Python Code:
titles['title'].value_counts()[:10]
Explanation: What are the ten most common movie names of all time?
End of explanation
titles[(titles['year']<1940)&(titles['year']>=1930)]['year'].value_counts()
Explanation: Which three years of the 1930s saw the most films released?
End of explanation
dec=((titles['yea... |
12,461 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Exercises
Recreate the plots below using the titanic dataframe. There are very few hints since most of the plots can be done with just one or two lines of code and a h... | Python Code:
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
sns.set_style('whitegrid')
titanic = sns.load_dataset('titanic')
titanic.head()
titanic.shape
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
Seaborn Exercises
Time to practice your new se... |
12,462 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework Part 1
Step1: that is a cue to use a particular command, in this case, plot. Run the cell to see documentation for that command. (To quickly close the Help window, press q.)
For m... | Python Code:
plt.plot?
Explanation: Homework Part 1: Understanding Audio Features through Sonification
There is no written component to be submitted for this part, Part 1. This section is intended to acquaint you with Python, the IPython notebook, and librosa.
When you see a cell that looks like this:
End of explanatio... |
12,463 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Feature engineering on NCAA data
Domain knowledge is critical to getting the best out of data analysis and machine learning.
In the case of basketball, Dean Oliver identified four factors th... | Python Code:
%%bigquery df1
SELECT
team_code,
AVG(SAFE_DIVIDE(fgm + 0.5 * fgm3,fga)) AS offensive_shooting_efficiency,
AVG(SAFE_DIVIDE(opp_fgm + 0.5 * opp_fgm3,opp_fga)) AS opponents_shooting_efficiency,
AVG(win) AS win_rate,
COUNT(win) AS num_games
FROM lab_dev.team_box
WHERE fga IS NOT NULL
GROUP BY team_c... |
12,464 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matplotlib Exercise 3
Imports
Step2: Contour plots of 2d wavefunctions
The wavefunction of a 2d quantum well is
Step3: The contour, contourf, pcolor and pcolormesh functions of Matplotlib ... | Python Code:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
Explanation: Matplotlib Exercise 3
Imports
End of explanation
def well2d(x, y, nx, ny, L=1):
Compute the 2d quantum well wave function.
return (2.0/L*np.sin((nx*np.pi*x)/L)*np.sin((ny*np.pi*y)/L))
?np.zeros
psi ... |
12,465 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Big Data Applications and Analytics
Step1: Explore data frames to check headers
Look at columns headers, variable information, type, etc.
Step2: Explore data frames to check headers and da... | Python Code:
import seaborn as sns
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv('~/project-data.csv')
df.drop(df.columns[[0,1]], axis=1, inplace=True)
df.shape
Explanation: Big Data Applications and Analytics: Term Project
Sean M. Shiverick Fall 2017
D... |
12,466 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Profiling
Step2: timeit module
Step3: cProfile
Step4: Use pstats.Stats to parse and print cProfile output
You can sort the records
Step5: Networking
Standard library provides some module... | Python Code:
# EXERCISE:
# Execute the following command:
!python -m timeit '"-".join([str(n) for n in range(100)])'
# Now execute the following:
!python -m timeit '"-".join(map(str, range(100)))'
# Now execute:
!python -m timeit --setup 'func = lambda n: "-".join(map(str, range(n)))' 'func(100)'
# And finally:
!python... |
12,467 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CNN transfer learning - Keras+TensorFlow
This is for CNN models transferred from pretrained model, using Keras based on TensorFlow. First, some preparation work.
Step1: Read the MNIST data.... | Python Code:
from keras.layers import Conv2D, MaxPooling2D, Input, Dense, Flatten, Activation, add, Lambda
from keras.layers.normalization import BatchNormalization
from keras.layers.pooling import GlobalAveragePooling2D
from keras.optimizers import RMSprop
from keras.backend import tf as ktf
from keras.models import M... |
12,468 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'inpe', 'sandbox-3', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: INPE
Source ID: SANDBOX-3
Sub-Topics: Radiative Forcings.
Properties: ... |
12,469 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data pre-processing in python, using Pima Indians diabetes dataset from National Institute of Diabetes and Digestive and Kidney Diseases
Citation
Step1: 2.0 Split data into feature (input) ... | Python Code:
import pandas as pd
from pandas import read_csv
pd.set_option('precision', 3) # set display precision to 3 significant figures
filename = 'C:/Users/craigrshenton/Desktop/Dropbox/python/python_pro/machine_learning_mastery_with_python/machine_learning_mastery_with_python_code/chapter_07/pima-indians-diabetes... |
12,470 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implementing logistic regression from scratch
The goal of this notebook is to implement your own logistic regression classifier. You will
Step1: Load review dataset
For this assignment, we ... | Python Code:
import graphlab
Explanation: Implementing logistic regression from scratch
The goal of this notebook is to implement your own logistic regression classifier. You will:
Extract features from Amazon product reviews.
Convert an SFrame into a NumPy array.
Implement the link function for logistic regression.
Wr... |
12,471 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<p><font size="6"><b>03 - Pandas
Step1: <div class="alert alert-info" style="font-size
Step2: Reversing this operation, is reset_index
Step3: Selecting data based on the index
<div class=... | Python Code:
import pandas as pd
# redefining the example dataframe
data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],
'population': [11.3, 64.3, 81.3, 16.9, 64.9],
'area': [30510, 671308, 357050, 41526, 244820],
'capital': ['Brussels', 'Paris', 'Berlin', 'Amst... |
12,472 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
High Schools dataset cleaning and exploration
In this notebook we will clean and explore the 2017 High Schools dataset by the NYC Department of Education.
Let's start by opening and examinin... | Python Code:
import pandas as pd
all_high_schools = pd.read_csv('data/DOE_High_School_Directory_2017.csv')
all_high_schools.shape
pd.set_option('display.max_columns', 453)
all_high_schools.head(3)
Explanation: High Schools dataset cleaning and exploration
In this notebook we will clean and explore the 2017 High Schools... |
12,473 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cônicas na forma polar
A forma geral de uma cônica na forma polar é
$$ r = \frac{de}{e\cos{\theta} + 1} $$
Vamos fazer dois exemplos
Step1: A Hipérbole
Note que na definição de uma hipérb... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
theta = np.arange(-1.7,1.7,0.1)
r = lambda x: 2.0/(1+np.cos(x))
theta
rho =r(theta)
rho
## primeiro vou tentar um grafico polar
ax=plt.subplot(111,projection='polar')
ax.plot(theta,rho)
ponto = lambda x: [r(x)*np.cos(x) , r(x)*np.sin(x)]... |
12,474 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: 1. Data Manipulation and Cleaning
1.1 Data Ingestion
We read the file 'data/vgsales.csv' using the pandas read_csv() function, and store it into the variable data.
Ste... | Python Code:
# IF YOU ARE RUNNING THIS NOTEBOOK VIA GOOGLE COLAB, PLEASE UNCOMMENT and RUN THIS CELL
# from google.colab import drive
# drive.mount('/content/drive')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
pd.s... |
12,475 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
VARMAX models
This is a notebook stub for VARMAX models. Full development will be done after impulse response functions are available.
Step1: Model specification
The VARMAX class in Statsmo... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
dta = sm.datasets.webuse('lutkepohl2', 'http://www.stata-press.com/data/r12/')
dta.index = dta.qtr
endog = dta.ix['1960-04-01':'1978-10-01', ['dln_inv', 'dln_inc', 'dln_consump']]
Explanat... |
12,476 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
List comprehensions
Jedná se o zápis s Pythonu s jehož pomocí se dají jednoduše vytvářet seznamy.
Step1: Tabulka s hracím polem
Řešení 1
Step2: Řešení 2
Step3: Správné řešení
Step4: Krát... | Python Code:
[x for x in range(10)]
[x**2 for x in range(10)]
[x**2 for x in range(10) if x % 2 == 0]
[(x, x**2) for x in range(10)]
[[y for y in range(3)] for x in range(10)]
Explanation: List comprehensions
Jedná se o zápis s Pythonu s jehož pomocí se dají jednoduše vytvářet seznamy.
End of explanation
def vytvor_tab... |
12,477 | 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: past and present
From https
Step3: For a nicer description evaluate the following cell
Step4: %%bash
To start a Jupyter process t... | Python Code:
__AUTHORS__ = {'am': ("Andrea Marino",
"andrea.marino@unifi.it",),
'mn': ("Massimo Nocentini",
"massimo.nocentini@unifi.it",
"https://github.com/massimo-nocentini/",)}
__KEYWORDS__ = ['Python', 'Jupyter', 'notebooks', 'keyn... |
12,478 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Demonstration for setting up an ODE system
PyGOM — A Python Package for Simplifying Modelling with Systems of Ordinary Differential Equations https
Step1: The following parameterization, ru... | Python Code:
# import required packages
from pygom import DeterministicOde, Transition, SimulateOde, TransitionType
import os
from sympy import symbols, init_printing
import numpy as np
import matplotlib.pyplot as mpl
import sympy
import itertools
# Add graphvis path (N.B. set to your local circumstances)
graphvis_pat... |
12,479 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create Data
Step2: Detect Outliers
EllipticEnvelope assumes the data is normally distributed and based on that assumption "draws" an ellipse around the data, classifying any o... | Python Code:
# Load libraries
import numpy as np
from sklearn.covariance import EllipticEnvelope
from sklearn.datasets import make_blobs
Explanation: Title: Detecting Outliers
Slug: detecting_outliers
Summary: How to detect outliers for machine learning in Python.
Date: 2016-09-06 12:00
Category: Machine Learning
T... |
12,480 | 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="#Raw-data-stats" data-toc-modified-id="Raw-data-stats-1"><span class="toc-ite... | Python Code:
%matplotlib ipympl
import seaborn as sns
sns.set()
sns.set_context('paper')
sns.set_palette('colorblind')
from planet4 import io, stats, markings, plotting, region_data
from planet4.catalog_production import ReleaseManager
fans = pd.read_csv("/Users/klay6683/Dropbox/data/planet4/p4_analysis/P4_catalog_v1.0... |
12,481 | 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', 'cmcc', 'cmcc-esm2-sr5', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: CMCC
Source ID: CMCC-ESM2-SR5
Topic: Aerosol
Sub-Topics: Transport, E... |
12,482 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
# Getting Started with gensim
This section introduces the basic concepts and terms needed to understand and use gensim and provides a simple usage example.
Core Concepts and Simple Example
A... | 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... |
12,483 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> Text Classification using TensorFlow/Keras on AI Platform </h1>
This notebook illustrates
Step1: Note
Step2: We will look at the titles of articles and figure out whether the article ... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
!pip install --user google-cloud-bigquery==1.25.0
Explanation: <h1> Text Classification using TensorFlow/Keras on AI Platform </h1>
This notebook illustrates:
<ol>
<li> Creating datasets for AI Platform using BigQuery
<li> Creating a text c... |
12,484 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Efficient programming for parallel computing
Timing and profiling
Step11: Profiling your code
Step12: Not covered
Step13: Pointers versus copies
Step14: Choosing the right contain... | Python Code:
%%file timing.py
some simple things to time
import time
def _list_comprehension(N):
return [x*x for x in xrange(N)]
def _for_append(N):
L = []
for x in xrange(N):
L.append(x*x)
return L
def _for_setitem(N):
L = [None]*N
i = 0
for x in xrange(N):
L[i] = x*x
... |
12,485 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Python and Natural Language Technologies
Lecture 04, Week 04
February 28, 2018
List comprehension
transform any iterable into a list in one line
syntactic sugar
example
Step1... | Python Code:
l = []
for i in range(10):
l.append(2*i+1)
l
Explanation: Introduction to Python and Natural Language Technologies
Lecture 04, Week 04
February 28, 2018
List comprehension
transform any iterable into a list in one line
syntactic sugar
example: create a list of the first N odd numbers starting from 1
En... |
12,486 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Network analysis of the data.
The goal of this notebook is to uncover several constructions inside the dataset which may help us to uncover fraud. With that, we can see whether we can create... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
Explanation: Network analysis of the data.
The goal of this notebook is to uncover several constructions inside the dataset which may help us to uncover fraud. With that, we can see whether we ca... |
12,487 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cropping2D
[convolutional.Cropping2D.0] cropping ((1,1),(1,1)) on 3x5x4 input, data_format='channels_last'
Step1: [convolutional.Cropping2D.1] cropping ((1,1),(1,1)) on 3x5x4 input, data_fo... | Python Code:
data_in_shape = (3, 5, 4)
L = Cropping2D(cropping=((1,1),(1, 1)), data_format='channels_last')
layer_0 = Input(shape=data_in_shape)
layer_1 = L(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
# set weights to random (use seed for reproducibility)
np.random.seed(250)
data_in = 2 * np.random.random(d... |
12,488 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Some Basic Statistics
This module will cover the calculation of some basic statistical parameters using numpy and scipy, starting with a 'by hand' or from textbook formulas and using built-i... | Python Code:
from numpy.random import normal,rand
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats
%matplotlib inline
Explanation: Some Basic Statistics
This module will cover the calculation of some basic statistical parameters using numpy and scipy, starting with a 'by hand' or from text... |
12,489 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> 2. Creating a sampled dataset </h1>
This notebook illustrates
Step2: <h2> Create ML dataset by sampling using BigQuery </h2>
<p>
Let's sample the BigQuery data to create smaller datase... | Python Code:
# change these to try this notebook out
BUCKET = 'cloud-training-demos-ml'
PROJECT = 'cloud-training-demos'
REGION = 'us-central1'
import os
os.environ['BUCKET'] = BUCKET
os.environ['PROJECT'] = PROJECT
os.environ['REGION'] = REGION
%%bash
if ! gsutil ls | grep -q gs://${BUCKET}/; then
gsutil mb -l ${REG... |
12,490 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction tutorial
In this tutorial we will perform handwriting recognition by training a
multilayer perceptron (MLP)
on the MNIST handwritten digit database.
The Task
MNIST is a dataset ... | Python Code:
from theano import tensor
x = tensor.matrix('features')
Explanation: Introduction tutorial
In this tutorial we will perform handwriting recognition by training a
multilayer perceptron (MLP)
on the MNIST handwritten digit database.
The Task
MNIST is a dataset which consists of 70,000 handwritten digits. Ea... |
12,491 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Manual Commands Workbook
This notebook is a workbook for testing hardware with manual FPE commands, and general empirical testing. It turns out that it's also a handy command reference.
Sta... | Python Code:
from tessfpe.dhu.fpe import FPE
from tessfpe.dhu.unit_tests import check_house_keeping_voltages
fpe1 = FPE(1, debug=False, preload=True, FPE_Wrapper_version='6.1.1')
print fpe1.version
fpe1.cmd_start_frames()
fpe1.cmd_stop_frames()
if check_house_keeping_voltages(fpe1):
print "Wrapper load complete. In... |
12,492 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Named Entity Recognition using Transformers
Author
Step1: We will be using the transformer implementation from this fantastic
example.
Let's start by defining a TransformerBlock layer
Step2... | Python Code:
!pip3 install datasets
!wget https://raw.githubusercontent.com/sighsmile/conlleval/master/conlleval.py
import os
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from datasets import load_dataset
from collections import Counter
from conlleval impor... |
12,493 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutor Magic in IPython
This notebook demonstrates the %%tutor magic as used in IPython notebook.
First, you'll need the following installed
Step1: Finally, put a %%tutor at the top of any c... | Python Code:
from metakernel import register_ipython_magics
register_ipython_magics()
Explanation: Tutor Magic in IPython
This notebook demonstrates the %%tutor magic as used in IPython notebook.
First, you'll need the following installed:
IPython/Jupyter
Metakernel
Next, you'll need to use the magics in IPython:
End o... |
12,494 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Supervised learning for classification
給一堆 $x$, 和他的分類，我們找出計算 x 的分類的方式
One hot encoding
如果我們有三類種類別， 我們可以來編碼這三個類別
* $(1,0,0)$
* $(0,1,0)$
* $(0,0,1)$
問題
為什麼不直接用 1,2,3 這樣的編碼呢？
Softmax Regressio... | Python Code:
# Weight
W = Matrix([1,2],[3,4], [5,6])
W
# Bias
b = Vector(1,0,-1)
b
# 輸入
x = Vector(2,-1)
x
Explanation: Supervised learning for classification
給一堆 $x$, 和他的分類，我們找出計算 x 的分類的方式
One hot encoding
如果我們有三類種類別， 我們可以來編碼這三個類別
* $(1,0,0)$
* $(0,1,0)$
* $(0,0,1)$
問題
為什麼不直接用 1,2,3 這樣的編碼呢？
Softmax Regression 的模型是這樣的
... |
12,495 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Detección de anomalías
La detección de anomalías (anomaly detection, AD) es una tarea de aprendizaje automático que consiste en detectar outliers o datos fuera de rango.
An outlier is an obs... | Python Code:
%matplotlib inline
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
Explanation: Detección de anomalías
La detección de anomalías (anomaly detection, AD) es una tarea de aprendizaje automático que consiste en detectar outliers o datos fu... |
12,496 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The $k$-Nearest Neighbor Classification Algorithm
Notebook version
Step1: 1. The binary classification problem.
In a binary classification problem, we are given an observation vector ${\bf ... | Python Code:
# To visualize plots in the notebook
%matplotlib inline
# Import some libraries that will be necessary for working with data and displaying plots
import csv # To read csv files
import random
import matplotlib.pyplot as plt
import numpy as np
from scipy import spatial
from sklearn import neighbors, dat... |
12,497 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Converting on OSX Keychain into Text Notes
The purpose of this notebook is to export the secured notes from an Apple keychain into separate files. It is pretty rough, but generally this only... | Python Code:
path = '/Volumes/---/keychains'
#!ls -l $path
Explanation: Converting on OSX Keychain into Text Notes
The purpose of this notebook is to export the secured notes from an Apple keychain into separate files. It is pretty rough, but generally this only needs to be done once (at least for me this was the case... |
12,498 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src='https
Step1: Locally and Remote
Run locally
Connect to the cloud (e.g AWS)
Connect to supercomputer (e.g. XSEDE Resource)
Add compute power
Step2: Plot a Histogram of x
Step3: N... | Python Code:
2+4
print("hello")
a=2
print("Hello world!")
Explanation: <img src='https://raw.githubusercontent.com/scientific-visualization-2016/ClassMaterials/master/Images/rc_logo.png' style="height:75px">
Data Analysis and Visualization with the IPython Notebook
<img src='https://raw.githubusercontent.com/scientific... |
12,499 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parameter Estimation of RIG Roll Experiments
Setup and descriptions
Without ACM model
Turn on wind tunnel
Only 1DoF for RIG roll movement
Use small-amplitude aileron command of CMP as inputs... | Python Code:
%run matt_startup
%run -i matt_utils
button_qtconsole()
#import other needed modules in all used engines
#with dview.sync_imports():
# import os
Explanation: Parameter Estimation of RIG Roll Experiments
Setup and descriptions
Without ACM model
Turn on wind tunnel
Only 1DoF for RIG roll movement
Use small... |
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