Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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9,900 | 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', 'hammoz-consortium', 'sandbox-2', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: HAMMOZ-CONSORTIUM
Source ID: SANDBOX-2
Topic: Landice
Sub-To... |
9,901 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Non-parametric between conditions cluster statistic on single trial power
This script shows how to compare clusters in time-frequency
power estimates between conditions. It uses a non-parame... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.time_frequency import tfr_morlet
from mne.stats import permutation_cluster_test
from mne.datasets import sample
print(__doc__)
Explanati... |
9,902 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GCE Lab 3 - Constrain Galaxy Model
This notebook presents how to plot the basic galaxy evolution properties of your simple Milky Way model. Those plots will allow you to calibrate your model... | Python Code:
# Import the standard Python packages
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
# Two-zone galactic chemical evolution code
import JINAPyCEE.omega_plus as omega_plus
# Matplotlib option
%matplotlib inline
Explanation: GCE Lab 3 - Constrain Galaxy Model
This notebook presents how ... |
9,903 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<small><i>This notebook was prepared by Donne Martin. Source and license info is on GitHub.</i></small>
Challenge Notebook
Problem
Step1: Unit Test
The following unit test is expected to fa... | Python Code:
%run ../../stacks_queues/stack/stack.py
%load ../../stacks_queues/stack/stack.py
def hanoi(num_disks, src, dest, buff):
# TODO: Implement me
pass
Explanation: <small><i>This notebook was prepared by Donne Martin. Source and license info is on GitHub.</i></small>
Challenge Notebook
Problem: Implemen... |
9,904 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import Modules
Step1: Import Scrapped Reviews
Step2: Import Hu & Liu (2004) Word Dictionary and Wrangled Large Users
Step3: Connect to the AWS Instance and get the restaurant reviews from... | Python Code:
import json
import pandas as pd
import re
import random
import matplotlib.pyplot as plt
%matplotlib inline
from ast import literal_eval as make_tuple
from scipy import sparse
import numpy as np
from pymongo import MongoClient
from nltk.corpus import stopwords
from sklearn import svm
from sklearn.decompos... |
9,905 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: Task
Include the curvature as an extra parameter to your likelihood
Step4: Now let's analize the chains
First just an histogram
Step5: How to obtain the confidence regions of a vari... | Python Code:
import numpy as np
import scipy.integrate as integrate
def E(z,OmDE,OmM):
This function computes the integrand for the computation of the luminosity distance for a flat universe
z -> float
OmDE -> float
OmM -> float
gives
E -> float
Omk=1-OmDE-OmM
return 1/np.sqrt(... |
9,906 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GMaps on Android
The goal of this experiment is to test out GMaps on a Pixel device running Android and collect results.
Step1: Test environment setup
For more details on this please check ... | Python Code:
from conf import LisaLogging
LisaLogging.setup()
%pylab inline
import json
import os
# Support to access the remote target
import devlib
from env import TestEnv
# Import support for Android devices
from android import Screen, Workload
# Support for trace events analysis
from trace import Trace
# Suport for... |
9,907 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Detección de caras mediante Machine Learning
Previamente a utilizar esta técnica para reconocer los fitolitos en nuestras imagenes, utilizaremos esta técnica para reconocer caras en diversas... | Python Code:
#Imports
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Explanation: Detección de caras mediante Machine Learning
Previamente a utilizar esta técnica para reconocer los fitolitos en nuestras imagenes, utilizaremos esta técnica para reconocer caras en diversas imagenes. Si el reconoci... |
9,908 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DiscreteDP Example
Step1: We follow the state-action pairs formulation approach.
We let the state space consist of the possible values of the asset price
and the state indicating that "the ... | Python Code:
%matplotlib inline
import numpy as np
from scipy import sparse
import matplotlib.pyplot as plt
import quantecon as qe
from quantecon.markov import DiscreteDP, backward_induction, sa_indices
T = 0.5 # Time expiration (years)
vol = 0.2 # Annual volatility
r = 0.05 # Annual interest rate
strike... |
9,909 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Base Question Visualization
Step1: Reading data back from npz file
Step2: I use interact on my plotter function to plot the positions of the stars and galaxies in my system at every time v... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import YouTubeVideo
from plotting_function import plotter,static_plot,com_plot,static_plot_com
Explanation: Base Questi... |
9,910 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Committees
Step1: Party
Step2: [
{
"id" | Python Code:
#List all committees
query = 'classification:Committee'
r = requests.get('http://api.openhluttaw.org/en/search/organizations?q='+query)
pages = r.json()['num_pages']
committees = []
for page in range(1,pages+1):
r = requests.get('http://api.openhluttaw.org/en/search/organizations?q='+query+'&page='+str... |
9,911 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Feature Reduction For Training Data
Select the top 10%, 20%, 30%, 40% and 50% of features with the most variance. Starting with 1006 ASM features
the process will select about 100,... | Python Code:
train_data = pd.read_csv('data/train-malware-features-asm.csv')
labels = pd.read_csv('data/trainLabels.csv')
sorted_train_data = train_data.sort(columns='filename', axis=0, ascending=True, inplace=False)
sorted_train_labels = labels.sort(columns='Id', axis=0, ascending=True, inplace=False)
X = sorted_train... |
9,912 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Running a Hyperparameter Tuning Job with Vertex Training
Learning objectives
In this notebook, you learn how to
Step1: Restart the kernel
After you install the additional packages, you need... | Python Code:
import os
# The Google Cloud Notebook product has specific requirements
IS_GOOGLE_CLOUD_NOTEBOOK = os.path.exists("/opt/deeplearning/metadata/env_version")
# Google Cloud Notebook requires dependencies to be installed with '--user'
USER_FLAG = ""
if IS_GOOGLE_CLOUD_NOTEBOOK:
USER_FLAG = "--user"
# Inst... |
9,913 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting
There are several plotting modules in python. Matplolib is the most complete/versatile package for all 2D plotting. The easiest way to construct a new plot is to have a look at http... | Python Code:
%matplotlib
import numpy as np
import matplotlib.pyplot as plt
# To get interactive plotting (otherwise you need to
# type plt.show() at the end of the plotting commands)
plt.ion()
x = np.linspace(0, 10)
y = np.sin(x)
# basic X/Y line plotting with '--' dashed line and linewidth of 2
plt.plot(x, y, '--',... |
9,914 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of discrete and inverse discrete Fourier transform
Step1: In this notebook, we provide examples of the discrete Fourier transform (DFT) and its inverse, and how xrft automatically h... | Python Code:
import numpy as np
import numpy.testing as npt
import xarray as xr
import xrft
import numpy.fft as npft
import scipy.signal as signal
import dask.array as dsar
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Example of discrete and inverse discrete Fourier transform
End of explanation
k0 = ... |
9,915 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning Engineer Nanodegree
Deep Learning
Project
Step5: Using MNIST dataset
Loading pickled MNIST dataset
Step6: Question 1
What approach did you take in coming up with a solutio... | Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import random
import os
import sys
import tarfile
import cPickle
import gzip
import theano
import theano.tens... |
9,916 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this tutorial, you will learn how to use cross-validation for better measures of model performance.
Introduction
Machine learning is an iterative process.
You will face choices about wha... | Python Code:
#$HIDE$
import pandas as pd
# Read the data
data = pd.read_csv('../input/melbourne-housing-snapshot/melb_data.csv')
# Select subset of predictors
cols_to_use = ['Rooms', 'Distance', 'Landsize', 'BuildingArea', 'YearBuilt']
X = data[cols_to_use]
# Select target
y = data.Price
Explanation: In this tutorial, ... |
9,917 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Burst statistics of 5 smFRET samples
Step1: 8-spot paper plot style
Step2: Compute Burst Data
Burst Search Parameters
Step3: Multispot
Correction Factors
Load the leakage coefficient from... | Python Code:
from fretbursts import *
sns = init_notebook()
import os
from glob import glob
import pandas as pd
from IPython.display import display
%config InlineBackend.figure_format='retina' # for hi-dpi displays
import lmfit
print('lmfit version:', lmfit.__version__)
figure_size = (5, 4)
default_figure = lambda: pl... |
9,918 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Atomic Charge Prediction
Introduction
In this notebook we will machine-learn the relationship between an atomic descriptor and its electron density using neural networks.
The atomic descript... | Python Code:
# --- INITIAL DEFINITIONS ---
from sklearn.neural_network import MLPRegressor
import numpy, math, random
from scipy.sparse import load_npz
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from ase import Atoms
from visualise import view
Explanation: Atomic Charge Prediction
Introduct... |
9,919 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 5
CHE 116
Step1: $$2^{10} \approx 10^3$$
$$2^{20} \approx 10^6$$
$$2^{10n} \approx 10^{3n}$$
1.2 Answer
Step2: 1.3 Answer
Step3: 1.4 Answer
Step4: 2. Watching Youtube with the G... | Python Code:
import numpy as np
ints = np.arange(1,21)
pows = 2**ints
print(pows)
print(pows[9], pows[19])
Explanation: Homework 5
CHE 116: Numerical Methods and Statistics
Prof. Andrew White
Version 1.1 (2/9/2016)
1. Python Practice (20 Points)
Answer the following problems in Python
[4 points] Using Numpy, create the... |
9,920 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mean field inference for $\mathbb{Z}_2$ Syncronization
We illustrate the $\mathbb{Z}_2$ syncronization inference problem using pyro.
Step1: The model
Our model is
$$
Y_{ij} = \frac{\lambda}... | Python Code:
# import some dependencies
import torch
from torch.autograd import Variable
import numpy as np
import pyro
import pyro.distributions as dist
import pyro
from pyro.infer import SVI
Explanation: Mean field inference for $\mathbb{Z}_2$ Syncronization
We illustrate the $\mathbb{Z}_2$ syncronization inference p... |
9,921 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: <h1 align="center">Visualizing TensorFlow
Step2: The TensorFlow Execution Graph
If we now launch tensorboard and navigate to http
Step3: After re-running with the loss function summ... | Python Code:
%pylab inline
pylab.style.use('ggplot')
import numpy as np
import tensorflow as tf
import os
import shutil
from contextlib import contextmanager
@contextmanager
def event_logger(logdir, session):
Hands out a managed tensorflow summary writer.
Cleans up the event log directory before every run... |
9,922 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PANDAS
Module 1
Step1: Overview
Two primary data structures of pandas
* Series (1-dimensional) array
* DataFrame (tabular, spreadsheet)
Indexing and slicing of pandas objects
Arithmetic op... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: PANDAS
Module 1: Data Structure and Applications
pandas is an open source, BSD-licensed Python library providing fast, flexible, easy-to-use, data structures and data analysis tools for working with “rela... |
9,923 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
===========================================================
Plot single trial activity, grouped by ROI and sorted by RT
===========================================================
This will ... | Python Code:
# Authors: Jona Sassenhagen <jona.sassenhagen@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne.datasets import testing
from mne import Epochs, io, pick_types
from mne.event import define_target_events
print(__doc__)
Explanation: ===========================================================
Plot sin... |
9,924 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!-- dom
Step1: Here follows a simple example where we set up an array of ten elements, all determined by random numbers drawn according to the normal distribution,
Step2: We defined a vec... | Python Code:
import numpy as np
Explanation: <!-- dom:TITLE: Data Analysis and Machine Learning: Getting started, our first data and Machine Learning encounters -->
Data Analysis and Machine Learning: Getting started, our first data and Machine Learning encounters
<!-- dom:AUTHOR: Morten Hjorth-Jensen at Department of ... |
9,925 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gaussian Process Regression
Gaussian Process regression is a non-parametric approach to regression or data fitting that assumes that observed data points $y$ are generated by some unknown la... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.cm as cmap
cm = cmap.inferno
import numpy as np
import scipy as sp
import theano
import theano.tensor as tt
import theano.tensor.nlinalg
import sys
sys.path.insert(0, "../../..")
import pymc3 as pm
Explanation: Gaussian Process Regressio... |
9,926 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Class 26
Step1: Define a log likelihood function for the vertex degree distribution
Step2: Define a vectorized log-factorial function, since it doesn't seem to be a builtin in python
Step3... | Python Code:
import pandas
g_discret_data = pandas.read_csv("shared/sachs_data_discretized.txt",
sep="\t")
g_discret_data.head(n=6)
Explanation: Class 26: Bayesian Networks
Infer a Bayesian network from a matrix of discretized phospho-flow cytometry data.
Based on supplementary data fr... |
9,927 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Denoising Autoencoder
Sticking with the MNIST dataset, let's add noise to our data and see if we can define and train an autoencoder to de-noise the images.
<img src='notebook_ims/autoencode... | Python Code:
import torch
import numpy as np
from torchvision import datasets
import torchvision.transforms as transforms
# convert data to torch.FloatTensor
transform = transforms.ToTensor()
# load the training and test datasets
train_data = datasets.MNIST(root='data', train=True,
do... |
9,928 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Template matching
Let's first download an image and a template to search for. The template is a smaller part of the original image.
Step2: Both the image used for pro... | Python Code:
import glob # to extend file name pattern to list
import cv2 # OpenCV for image processing
from cv2 import aruco # to find ArUco markers
import numpy as np # for matrices
import matplotlib.pyplot as plt # to show images
Exp... |
9,929 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Likelihood of a coin being fair
$$
P(\theta|X) = \frac{P(X|\theta)P(\theta)}{P(X)}
$$
Here, $P(X|\theta)$ is the likelihood, $P(\theta)$ is the prior on theta, $P(X)$ is the evidence, while ... | Python Code:
def get_likelihood(theta, n, k, normed=False):
ll = (theta**k)*((1-theta)**(n-k))
if normed:
num_combs = comb(n, k)
ll = num_combs*ll
return ll
get_likelihood(0.5, 2, 2, normed=True)
get_likelihood(0.5, 10, np.arange(10), normed=True)
N = 100
plt.plot(
np.arange(N),
get_... |
9,930 | 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="#Searching,-Hashing,-Sorting" data-toc-modified-id="Searching,-Hashing,-Sorti... | Python Code:
from jupyterthemes import get_themes
from jupyterthemes.stylefx import set_nb_theme
themes = get_themes()
set_nb_theme(themes[1])
%load_ext watermark
%watermark -a 'Ethen' -d -t -v -p jupyterthemes
Explanation: <h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><l... |
9,931 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework assignment #3
These problem sets focus on using the Beautiful Soup library to scrape web pages.
Problem Set #1
Step1: Now, in the cell below, use Beautiful Soup to write an express... | Python Code:
from bs4 import BeautifulSoup
from urllib.request import urlopen
html_str = urlopen("http://static.decontextualize.com/widgets2016.html").read()
document = BeautifulSoup(html_str, "html.parser")#python读取html里所有代码，用beautifulsoup
Explanation: Homework assignment #3
These problem sets focus on using the Beaut... |
9,932 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bombora Topic Interest Datasets
Explaining Bombora topic interest score datasets.
0. Surge vs Interest?
As a matter of clarification, topic surge as a product is generated from topic interes... | Python Code:
!ls -lh ../../data/topic-interest-score/
Explanation: Bombora Topic Interest Datasets
Explaining Bombora topic interest score datasets.
0. Surge vs Interest?
As a matter of clarification, topic surge as a product is generated from topic interest models. In technical discussions, we'll refer to both the pro... |
9,933 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Errors, or bugs, in your software
Today we'll cover dealing with errors in your Python code, an important aspect of writing software.
What is a software bug?
According to Wikipedia (accessed... | Python Code:
import numpy as np
Explanation: Errors, or bugs, in your software
Today we'll cover dealing with errors in your Python code, an important aspect of writing software.
What is a software bug?
According to Wikipedia (accessed 16 Oct 2018), a software bug is an error, flaw, failure, or fault in a computer prog... |
9,934 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: <table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Vectorize an example sentence
Consider the ... | 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... |
9,935 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
plot_sky_brightness_model
Visualizing the machine-learned (PTF) sky brightness model
Step1: Let's look at the range of the data
Step2: So there are clearly outliers. Let's look at histogr... | Python Code:
# hack to get the path right
import sys
sys.path.append('..')
from ztf_sim.SkyBrightness import SkyBrightness
from ztf_sim.magnitudes import limiting_mag
import astropy.units as u
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
sns.set_style('... |
9,936 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 変数の概要
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 変数の作成
変数を作成するには、初期値を指定します。tf.Variable は、初期... | 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... |
9,937 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Labeled Data
Labeled Data - contains the features and target attribute with correct answer
Training Set
Part of labeled data that is used for training the model. 60-70% of the labeled data i... | Python Code:
# read the bike train csv file
df = pd.read_csv(regression_example)
df.head()
df.corr()
df['count'].describe()
df.season.value_counts()
df.holiday.value_counts()
df.workingday.value_counts()
df.weather.value_counts()
df.temp.describe()
Explanation: Labeled Data
Labeled Data - contains the features and targ... |
9,938 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<hr>
Patrick BROCKMANN - LSCE (Climate and Environment Sciences Laboratory)<br>
<img align="left" width="40%" src="http
Step1: "Classic" use with cell magic
Step2: Explore interactive widg... | Python Code:
%load_ext ferretmagic
Explanation: <hr>
Patrick BROCKMANN - LSCE (Climate and Environment Sciences Laboratory)<br>
<img align="left" width="40%" src="http://www.lsce.ipsl.fr/Css/img/banniere_LSCE_75.png" ><br><br>
<hr>
Updated: 2019/11/13
Load the ferret extension
End of explanation
%%ferret -s 600,400
set... |
9,939 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recommender Engine
Perhaps the most famous example of a recommender engine in the Data Science world was the Netflix competition started in 2006, in which teams from all around the world c... | Python Code:
# Importing the data
import pandas as pd
import numpy as np
header = ['user_id', 'item_id', 'rating', 'timestamp']
data_movie_raw = pd.read_csv('../data/ml-100k/u.data', sep='\t', names=header)
data_movie_raw.head()
Explanation: Recommender Engine
Perhaps the most famous example of a recommender engine i... |
9,940 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Geo Query Dataset Analysis
Step1: Do some cleanup
Step2: Query Frequency Analysis
Let's take a look
Step3: The frequency of queries drops off pretty quickly, suggesting a long tail of low... | Python Code:
import os
import sys
import pandas as pd
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
import utils
%matplotlib inline
%load_ext autoreload
%autoreload 2
CSV_PATH = '../../data/unique_counts_semi.csv'
# load data
initial_df = utils.load_queries(CSV_PATH)
Explanation: Geo Query Dat... |
9,941 | 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', 'pcmdi', 'pcmdi-test-1-0', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: PCMDI
Source ID: PCMDI-TEST-1-0
Topic: Atmos
Sub-Topics: Dynamical Core... |
9,942 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
When life was easy
At some point in my calculus education I developed a simple rule, when in doubt set the derivative equal to zero and solve for x. You might recall doing this,... | Python Code:
#load all the things!
from pulp import *
Explanation: Introduction
When life was easy
At some point in my calculus education I developed a simple rule, when in doubt set the derivative equal to zero and solve for x. You might recall doing this, and the reason for doing it is because for a smooth function ... |
9,943 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Build local cache file from Argo data sources - first in a series of Notebooks
Execute commands to pull data from the Internet into a local HDF cache file so that we can better interact with... | Python Code:
from biofloat import ArgoData
ad = ArgoData(verbosity=2)
Explanation: Build local cache file from Argo data sources - first in a series of Notebooks
Execute commands to pull data from the Internet into a local HDF cache file so that we can better interact with the data
Import the ArgoData class and instati... |
9,944 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Data Analysis, 3rd ed
Chapter 4, demo 1
Normal approximaton for Bioassay model.
Step1: The following demonstrates an alternative "bad" way of calcuting the posterior density p in a... | Python Code:
import numpy as np
from scipy import optimize, stats
%matplotlib inline
import matplotlib.pyplot as plt
import os, sys
# add utilities directory to path
util_path = os.path.abspath(os.path.join(os.path.pardir, 'utilities_and_data'))
if util_path not in sys.path and os.path.exists(util_path):
sys.path.i... |
9,945 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Flopy MODFLOW Boundary Conditions
Flopy has a new way to enter boundary conditions for some MODFLOW packages. These changes are substantial. Boundary condtions can now be entered as a list... | Python Code:
#begin by importing flopy
import os
import sys
import numpy as np
#flopypath = '../..'
#if flopypath not in sys.path:
# sys.path.append(flopypath)
import flopy
workspace = os.path.join('data')
#make sure workspace directory exists
if not os.path.exists(workspace):
os.makedirs(workspace)
Explanation:... |
9,946 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Programming with Escher
This notebook is a collection of preliminary notes about a "code camp" (or a series of lectures) aimed at young students inspired by the fascinating Functional Geomet... | Python Code:
f
Explanation: Programming with Escher
This notebook is a collection of preliminary notes about a "code camp" (or a series of lectures) aimed at young students inspired by the fascinating Functional Geometry paper of Peter Henderson.
In such work the Square Limit woodcut by Maurits Cornelis Escher is recon... |
9,947 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Supervised Learning
learn the link between two datasets
Step1: 2 Linear regression
linear models
Step2: shrinkage
Step3: An example of bias/variance tradeoff, the larger the ridge $\alpha... | Python Code:
import numpy as np
from sklearn import datasets
iris = datasets.load_iris()
iris_X = iris.data
iris_y = iris.target
np.random.seed(0)
indices = np.random.permutation(len(iris_X))
iris_X_train = iris_X[indices[:-10]]
iris_y_train = iris_y[indices[:-10]]
iris_X_test = iris_X[indices[-10:]]
iris_y_test = iris... |
9,948 | 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', 'sandbox-1', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: MIROC
Source ID: SANDBOX-1
Topic: Seaice
Sub-Topics: Dynamics, Thermodynam... |
9,949 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TensorFlow Basics
Step1: Constants
Step2: Operations
Step3: Placeholders
Instead of using a constant, we can define a placeholder that allows us to provide the value at the time of execut... | Python Code:
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
tf.__version__
Explanation: TensorFlow Basics
End of explanation
h = tf.constant('Hello World')
h
h.graph is tf.get_default_graph()
x = tf.constant(100)
x
# Create Session object in which we can run operations.
# ... |
9,950 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Learning
Assignment 1
The objective of this assignment is to learn about simple data curation practices, and familiarize you with some of the data we'll be reusing later.
This notebook ... | Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
import matplotlib.pyplot as plt
import numpy as np
import os
import tarfile
import urllib
from IPython.display import display, Image
from scipy import ndimage
from sklearn.linear_model import Logist... |
9,951 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Planet OS API demo for GEFS
<font color=red>This notebook is not working right now as GEFS Ensambled forecast is updating only by request! Let us know if you would like to use it</fon... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import dateutil.parser
import datetime
from urllib.request import urlopen, Request
import simplejson as json
import pandas as pd
def extract_reference_time(API_data_loc):
Find reference time that corresponds to most complete forecast... |
9,952 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Magics to Access the JVM Kernels from Python
BeakerX has magics for Python so you can run cells in the other languages.
The first few cells below show how complete the implementation is with... | Python Code:
%%groovy
println("stdout works")
f = {it + " work"}
f("results")
%%groovy
new Plot(title:"plots work", initHeight: 200)
%%groovy
[a:"tables", b:"work"]
%%groovy
"errors work"/1
%%groovy
HTML("<h1>HTML works</h1>")
%%groovy
def p = new Plot(title : 'Plots Work', xLabel: 'Horizontal', yLabel: 'Vertical');
p ... |
9,953 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
K-means clustering
Authors
Ndèye Gagnessiry Ndiaye and Christin Seifert
License
This work is licensed under the Creative Commons Attribution 3.0 Unported License https
Step1: We load the ... | Python Code:
import pandas as pd
import numpy as np
import pylab as plt
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
import sklearn.metrics as sm
Explanation: K-means clustering
Authors
Ndèye Gagnessiry Ndiaye and Christin Seifert
License
This work is licensed under the Creative Commons Attribut... |
9,954 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plots
Entropy vs langton
blue = all, red = our random
Step1: Chi-square vs langton
blue = all, red = our random
Step2: Mean vs langton
blue = all, red = our random
Step3: Monte-Carlo-Pi v... | Python Code:
# Plot Entropy of all rules against the langton parameter
ax1 = plt.gca()
d_five.plot("langton", "Entropy", ax=ax1, kind="scatter", marker='o', alpha=.5, s=40)
d_five_p10_90.plot("langton", "Entropy", ax=ax1, kind="scatter", color="r", marker='o', alpha=.5, s=40)
plt.show()
ax1 = plt.gca()
d_five.plot("lan... |
9,955 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Least squares fitting of models to data
This is a quick introduction to statsmodels for physical scientists (e.g. physicists, astronomers) or engineers.
Why is this needed?
Because most of s... | Python Code:
import numpy as np
import pandas as pd
import statsmodels.api as sm
Explanation: Least squares fitting of models to data
This is a quick introduction to statsmodels for physical scientists (e.g. physicists, astronomers) or engineers.
Why is this needed?
Because most of statsmodels was written by statistici... |
9,956 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Understanding Electronic Health Records with BigQuery ML
This tutorial introduces
BigQuery ML (BQML) in the
context of working with the MIMIC3
dataset.
BigQuery ML adds only a few statements... | Python Code:
from __future__ import print_function
from google.colab import auth
from google.cloud import bigquery
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
auth.authenticate_user()
Explanation: Understanding Electronic Health Records with BigQuery ML
This tutorial int... |
9,957 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
W7 Lab Assignment
Step1: Cumulative histogram and CDF
How can we plot a cumulative histogram?
Step2: Does it reach 1.0? Why should it become 1.0 at the right end? Also you can do the plot ... | Python Code:
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import numpy as np
import random
sns.set_style('white')
%matplotlib inline
Explanation: W7 Lab Assignment
End of explanation
# TODO: Load IMDB data into movie_df using pandas
movie_df = pd.read_csv('imdb.csv', delimiter='\t')
movie_d... |
9,958 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
On-Axis Field of a Finite Solenoid
This formula uses the formula for the field due to a thin shell solenoid, integrated over a range of radii to obtain the magnetic field at any point on th... | Python Code:
%matplotlib inline
from scipy.special import ellipk, ellipe, ellipkm1
from numpy import pi, sqrt, linspace, log
from pylab import plot, xlabel, ylabel, suptitle, legend, show
uo = 4E-7*pi # Permeability constant - units of H/m
# Compute G Factor from unitless parameters
def GFactorUnitless(a, b, g=0.0)... |
9,959 | Given the following text description, write Python code to implement the functionality described.
Description:
Number of n digit numbers that do not contain 9
function to find number of n digit numbers possible ; driver function
| Python Code:
def totalNumber(n ) :
return 8 * pow(9 , n - 1 ) ;
n = 3
print(totalNumber(n ) )
|
9,960 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CSV 파일 다루기와 데이터 시각화
수정 사항
좀 더 복잡한 csv 데이터 활용 예제 추가 필요
주요 내용
데이터 분석을 위해 가장 기본적으로 할 수 있고, 해야 하는 일이 데이터 시각화이다.
데이터를 시각화하는 것은 어렵지 않지만, 적합한 시각화를 만드는 일은 매우 어려우며,
많은 훈련과 직관이 요구된다.
여기서는 데이터를 탐색하여 얻... | Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: CSV 파일 다루기와 데이터 시각화
수정 사항
좀 더 복잡한 csv 데이터 활용 예제 추가 필요
주요 내용
데이터 분석을 위해 가장 기본적으로 할 수 있고, 해야 하는 일이 데이터 시각화이다.
데이터를 시각화하는 것은 어렵지 않지만, 적합한 시각화를 만드는 일은 매우 어려우며,
많은 훈련과 직관이 요구된다.
여기서는 데이터를 탐색하여 얻어진 데이터를 시각화하는 기본적인 방법 네 가지를 배운다.
선그래프
막대그래프
히스토그램
산점도... |
9,961 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Obtaining the first trajectories for a Toy Model
Tasks covered in this notebook
Step1: Basic system setup
First we set up our system
Step2: Set up the toy system
For the toy model, we need... | Python Code:
# Basic imports
from __future__ import print_function
import openpathsampling as paths
import numpy as np
%matplotlib inline
# used for visualization of the 2D toy system
# we use the %run magic because this isn't in a package
%run ../resources/toy_plot_helpers.py
Explanation: Obtaining the first trajector... |
9,962 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Maxwell filter data with movement compensation
Demonstrate movement compensation on simulated data. The simulated data
contains bilateral activation of auditory cortices, repeated over 14
di... | Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
from os import path as op
import mne
from mne.preprocessing import maxwell_filter
print(__doc__)
data_path = op.join(mne.datasets.misc.data_path(verbose=True), 'movement')
head_pos = mne.chpi.read_head_pos(op.join(data_path, 'simula... |
9,963 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PUMP IT
Using data from Taarifa and the Tanzanian Ministry of Water, can you predict which pumps are functional, which need some repairs, and which don't work at all? This is an intermediate... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
np.random.seed(69572)
%matplotlib inline
%load_ext writeandexecute
# plt.figure(figsize=(120,10))
small = (4,3)
mid = (10, 8)
large = (12, 8)
Explanation: PUMP IT
Using data from Taarifa a... |
9,964 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple RL
Welcome! Here we'll showcase some basic examples of typical RL programming tasks.
Example 1
Step1: Next, we make an MDP and a few agents
Step2: The real meat of <i>simple_rl</i> ... | Python Code:
# Add simple_rl to system path.
import os
import sys
parent_dir = os.path.abspath(os.path.join(os.getcwd(), os.pardir))
sys.path.insert(0, parent_dir)
from simple_rl.agents import QLearningAgent, RandomAgent
from simple_rl.tasks import GridWorldMDP
from simple_rl.run_experiments import run_agents_on_mdp
Ex... |
9,965 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python and Friends
This is a very quick run-through of some python syntax
Step1: The Python Language
Lets talk about using Python as a calculator...
Step2: Notice integer division and floa... | Python Code:
# The %... is an iPython thing, and is not part of the Python language.
# In this case we're just telling the plotting library to draw things on
# the notebook, instead of on a separate window.
%matplotlib inline
#this line above prepares IPython notebook for working with matplotlib
# See all the "as ..."... |
9,966 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
XID+ Example Run Script
(This is based on a Jupyter notebook, available in the XID+ package and can be interactively run and edited)
XID+ is a probababilistic deblender for confusion dominat... | Python Code:
import numpy as np
from astropy.io import fits
from astropy import wcs
import pickle
import dill
import sys
import os
import xidplus
import copy
from xidplus import moc_routines, catalogue
from xidplus import posterior_maps as postmaps
from builtins import input
Explanation: XID+ Example Run Script
(This i... |
9,967 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook demonstrates how to use the Python MagicDataFrame object. A MagicDataFrame contains the data from one MagIC-format table and provides functionality for accessing and editing t... | Python Code:
from pmagpy import new_builder as nb
from pmagpy import ipmag
import os
import json
import numpy as np
import sys
import pandas as pd
from pandas import DataFrame
from pmagpy import pmag
working_dir = os.path.join("..", "3_0", "Osler")
Explanation: This notebook demonstrates how to use the Python MagicData... |
9,968 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Frame Plots
documentation
Step1: The plot method on Series and DataFrame is just a simple wrapper around plt.plot()
If the index consists of dates, it calls gcf().autofmt_xdate() to tr... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
Explanation: Data Frame Plots
documentation: http://pandas.pydata.org/pandas-docs/stable/visualization.html
End of explanation
ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
... |
9,969 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Soring, searching, and counting
Step1: Sorting
Q1. Sort x along the second axis.
Step2: Q2. Sort pairs of surnames and first names and return their indices. (first by surname, then by name... | Python Code:
import numpy as np
np.__version__
author = 'kyubyong. longinglove@nate.com'
Explanation: Soring, searching, and counting
End of explanation
x = np.array([[1,4],[3,1]])
out = np.sort(x, axis=1)
x.sort(axis=1)
assert np.array_equal(out, x)
print out
Explanation: Sorting
Q1. Sort x along the second axis.
End ... |
9,970 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.soft - Calcul numérique et Cython
Python est très lent. Il est possible d'écrire certains parties en C mais le dialogue entre les deux langages est fastidieux. Cython propose un mélange d... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.soft - Calcul numérique et Cython
Python est très lent. Il est possible d'écrire certains parties en C mais le dialogue entre les deux langages est fastidieux. Cython propose un mélange de C et Python qui accélère la conception... |
9,971 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nasa-giss', 'sandbox-3', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: NASA-GISS
Source ID: SANDBOX-3
Topic: Ocnbgchem
Sub-Topics: Trac... |
9,972 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Adding river levels
Developed by R.A. Collenteur & D. Brakenhoff
In this example it is shown how to create a Pastas model that not only includes precipitation and evaporation, but also obser... | Python Code:
import pandas as pd
import pastas as ps
import matplotlib.pyplot as plt
ps.show_versions()
ps.set_log_level("INFO")
Explanation: Adding river levels
Developed by R.A. Collenteur & D. Brakenhoff
In this example it is shown how to create a Pastas model that not only includes precipitation and evaporation, bu... |
9,973 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Grand Canonical Monte Carlo of atomic species using tabulated pair potentials
Step1: Download and build faunus
Step2: Generate an artificial, tabulated potential
This is just a damped sinu... | Python Code:
from __future__ import division, unicode_literals, print_function
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np, pandas as pd
import os.path, os, sys, json, filecmp, copy
plt.rcParams.update({'font.size': 16, 'figure.figsize': [8.0, 6.0]})
try:
workdir
e... |
9,974 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
OP-WORKFLOW-CAGEscan-short-reads-v2.0
This document is an example of how to process a C1 CAGE library with a Jupyter notebook from raw reads to single molecule count. All the steps are descr... | Python Code:
import subprocess, os, csv, signal, pysam
Explanation: OP-WORKFLOW-CAGEscan-short-reads-v2.0
This document is an example of how to process a C1 CAGE library with a Jupyter notebook from raw reads to single molecule count. All the steps are described in the tutorial section of this repository. In the follow... |
9,975 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotly and Cufflinks for plotting with Pandas
Get cufflinks
Cufflinks integrates plotly with pandas to allow plotting right from pandas dataframes. Install using pip
pip install cufflinks
St... | Python Code:
import numpy as np
import pandas as pd
import cufflinks as cf
from plotly.offline import download_plotlyjs, init_notebook_mode
from plotly.offline import plot, iplot
#set notebook mode
init_notebook_mode(connected=True)
cf.go_offline()
df = pd.DataFrame(np.random.randn(100,4),
columns='A... |
9,976 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
门面模式(Facade Pattern)
1 代码
假设有一组火警报警系统，由三个子元件构成：一个警报器，一个喷水器，一个自动拨打电话的装置。其抽象如下：
Step1: 在业务中如果需要将三个部件启动，例如，如果有一个烟雾传感器，检测到了烟雾。在业务环境中需要做如下操作：
Step2: 但如果在多个业务场景中需要启动三个部件，怎么办？Ctrl+C加上Ctrl+V么？当然... | Python Code:
class AlarmSensor:
def run(self):
print ("Alarm Ring...")
class WaterSprinker:
def run(self):
print ("Spray Water...")
class EmergencyDialer:
def run(self):
print ("Dial 119...")
Explanation: 门面模式(Facade Pattern)
1 代码
假设有一组火警报警系统，由三个子元件构成：一个警报器，一个喷水器，一个自动拨打电话的装置。其抽象如下：... |
9,977 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A decomposition of spatial forecast errors for wildfires using a modification of the contiguous rain area (CRA) method.
Copyright Bureau Of Meteorology.
This software is provided under licen... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from shapely import geometry, ops
from scipy import optimize
from skimage import transform
from IPython import display
%matplotlib inline
Explanation: A decomposition of spatial forecast errors for wildfires using a modification of the ... |
9,978 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2A.data - Classification, régression, anomalies - énoncé
Le jeu de données Wine Quality Data Set contient 5000 vins décrits par leurs caractéristiques chimiques et évalués par un expert. Peu... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 2A.data - Classification, régression, anomalies - énoncé
Le jeu de données Wine Quality Data Set contient 5000 vins décrits par leurs caractéristiques chimiques et évalués par un ... |
9,979 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src='https
Step1: Customizing matplotlib
http
Step2: Quick, easy, simple plots.
Object-oriented pyplot interface
No global variables
Separates style from graph
Can easily have multipl... | Python Code:
#inline to use with notebook (from pylab import *)
%pylab inline
Explanation: <img src='https://www.rc.colorado.edu/sites/all/themes/research/logo.png'>
Introduction to Data Visualization with matplotlib
Thomas Hauser
<img src='https://s3.amazonaws.com/research_computing_tutorials/mpl-overview.png'>
Obje... |
9,980 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Path function
The goal of the MADlib path function is to perform regular pattern matching over a sequence of rows, and to extract useful information about the pattern matches. The useful inf... | Python Code:
%load_ext sql
# %sql postgresql://gpdbchina@10.194.10.68:55000/madlib
%sql postgresql://fmcquillan@localhost:5432/madlib
%sql select madlib.version();
Explanation: Path function
The goal of the MADlib path function is to perform regular pattern matching over a sequence of rows, and to extract useful inform... |
9,981 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Networks
author
Step1: The Monty Hall Gameshow
The Monty Hall problem arose from the gameshow <i>Let's Make a Deal</i>, where a guest had to choose which one of three doors had a p... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn; seaborn.set_style('whitegrid')
import numpy
from pomegranate import *
numpy.random.seed(0)
numpy.set_printoptions(suppress=True)
%load_ext watermark
%watermark -m -n -p numpy,scipy,pomegranate
Explanation: Bayesian Networks
author: Jacob Sc... |
9,982 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dynamic factors and coincident indices
Factor models generally try to find a small number of unobserved "factors" that influence a subtantial portion of the variation in a larger number of o... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
np.set_printoptions(precision=4, suppress=True, linewidth=120)
from pandas_datareader.data import DataReader
# Get the datasets from FRED
start = '1979-01-01'
end = '2014-12-01'
indprod = ... |
9,983 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
计算传播与机器学习
王成军
wangchengjun@nju.edu.cn
计算传播网 http
Step1: 使用sklearn做logistic回归
王成军
wangchengjun@nju.edu.cn
计算传播网 http
Step2: 使用sklearn实现贝叶斯预测
王成军
wangchengjun@nju.edu.cn
计算传播网 http
Step3: n... | Python Code:
%matplotlib inline
from sklearn import datasets
from sklearn import linear_model
import matplotlib.pyplot as plt
import sklearn
print sklearn.__version__
# boston data
boston = datasets.load_boston()
y = boston.target
' '.join(dir(boston))
boston['feature_names']
regr = linear_model.LinearRegression()
lm =... |
9,984 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Load and prepare the dataset
You will use the MNIST dataset to train the generator and the discriminator. The generator will generate handwritten digits resembling the... | Python Code:
from __future__ import absolute_import, division, print_function, unicode_literals
try:
# %tensorflow_version only exists in Colab.
%tensorflow_version 2.x
except Exception:
pass
import tensorflow as tf
tf.__version__
import glob
import imageio
import matplotlib.pyplot as plt
import numpy as np... |
9,985 | 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', 'dwd', 'sandbox-1', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: DWD
Source ID: SANDBOX-1
Sub-Topics: Radiative Forcings.
Properties: 85... |
9,986 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Downloaded a few comma-delimited data from the <b>United States Department of Transportation, Bureau of Transportation Statistics website.</b> <br>
This data ranges from the months of <b>Jan... | Python Code:
# Assign a list of available files in my data directory (../data/2016/) to a variable
files = os.listdir("data/2016");
# Display
files
# Read through all files and concat all df into a single dataframe, df.
framelist = []
for file in files:
tempdf = pd.read_csv("data/2016/" + file)
framelist.append... |
9,987 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: ServerSim Overview and Tutorial
Introduction
This is an overview and tutorial about ServerSim, a framework for the creation of discrete event simulation models to analyze the performa... | Python Code:
# %load simulate_deployment_scenario.py
from __future__ import print_function
from typing import List, Tuple, Sequence
from collections import namedtuple
import random
import simpy
from serversim import *
def simulate_deployment_scenario(num_users, weight1, weight2, server_range1,
... |
9,988 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introdução à Programação em Python
Nesse Notebook aprenderemos
Step1: A ordem que as operações são executadas seguem uma ordem de precedência
Step2: A ordem pode ser alterada com o uso de ... | Python Code:
# todo texto escrito após "#" é um comentário e não é interpretado pelo Python
1+2 # realiza a operação 1+2 e imprime na tela
2-1
3*5
7/2
7//2
2**3
5%2
Explanation: Introdução à Programação em Python
Nesse Notebook aprenderemos:
operações básicas do Python,
tipos básicos de variáveis,
entrada e saída de ... |
9,989 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kaggle Dogs Vs. Cats Using LeNet on Google Colab TPU
Required setup
Update api_token with kaggle api key for downloading dataset
- Login to kaggle
- My Profile > Edit Profile > Cr... | Python Code:
!pip install kaggle
api_token = {"username":"xxxxx","key":"xxxxxxxxxxxxxxxxxxxxxxxx"}
import json
import zipfile
import os
os.mkdir('/root/.kaggle')
with open('/root/.kaggle/kaggle.json', 'w') as file:
json.dump(api_token, file)
!chmod 600 /root/.kaggle/kaggle.json
# !kaggle config path -p /root
!kaggl... |
9,990 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Four Axes
This notebook demonstrates the use of Cube Browser to produce multiple plots using only the code (i.e. no selection widgets).
Step1: Load and prepare your cubes
Step2: Set up you... | Python Code:
import iris
import iris.plot as iplt
import matplotlib.pyplot as plt
from cube_browser import Contour, Browser, Contourf, Pcolormesh
Explanation: Four Axes
This notebook demonstrates the use of Cube Browser to produce multiple plots using only the code (i.e. no selection widgets).
End of explanation
air_po... |
9,991 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Whiskey Data
This data set contains data on a small number of whiskies
Step1: Summaries
Shown below are the following charts
Step2: Some Analysis
Here we use the sci-kit decision tree regr... | Python Code:
import pandas as pd
from numpy import log, abs, sign, sqrt
import brunel
whiskey = pd.read_csv("data/whiskey.csv")
print('Data on whiskies:', ', '.join(whiskey.columns))
Explanation: Whiskey Data
This data set contains data on a small number of whiskies
End of explanation
%%brunel data('whiskey') x(country... |
9,992 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interpolation Exercise 2
Step1: Sparse 2d interpolation
In this example the values of a scalar field $f(x,y)$ are known at a very limited set of points in a square domain
Step2: The follow... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
sns.set_style('white')
from scipy.interpolate import griddata
Explanation: Interpolation Exercise 2
End of explanation
x = np.empty((1,),dtype=int)
x[0] = 0
for i in range(-4,5):
x = np.hstack((x,np.array((i,i))... |
9,993 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hands-on Tutorial
Step1: Install library and data dependencies
Load and pre-process data sets
Step2: Let's examine some rows in these datasets.
Step3: Understanding the data
There are man... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn import metrics
from keras.preprocessing.text import Tokenizer
from tensorflow.keras.utils import to_categorical
from keras.preprocessing.sequence import pad_sequences
from keras.layers import Embedding... |
9,994 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pandas 数据类型
Step1: 数据丢弃
Step2: 排序
Step3: 获取数据信息
Step4: 数据摘要
Step5: 选择
Step6: 数据聚合
Step7: 帮助
help(pd.Series.loc)
使用函数
Step8: 数据对齐
Step9: 输入输出
读取和写入csv
pd.read_csv('file.csv', header=... | Python Code:
s = pd.Series([3, -5, 7, 4], index=['a', 'b', 'c', 'd'])
data = {'Country': ['Belgium', 'India', 'Brazil'],
'Capital': ['Brussels', 'New Delhi', 'Brasília'],
'Population': [11190846, 1303171035, 207847528]}
df = pd.DataFrame(data,
columns=['Country', 'Capital', 'Population'])
#Pivvot,
data = {'Date': ['201... |
9,995 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Finding Sprints, Formally
We present an example use of Montre on a data set obtained by tracking positions of players in a real soccer match. In this example, we find all sprints performed b... | Python Code:
# Speed (m/s) and acceleration (m/s^2) categories
accel_desc = ['nhigh','nmedium', 'nlow','around_zero', 'low', 'medium', 'high']
accel_syms = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
accel_bins = [-100, -1.60, -1.17,-0.57, 0.57, 1.17, 1.60, 100]
speed_desc = ['low', 'medium', 'high', 'very_high']
speed_syms =... |
9,996 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
QuTiP Example
Step1: Overview
Here we aim to reproduce the experimental results from
Step2: Run Simulation
Step3: Plot Results
Step4: Versions | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from qutip import *
Explanation: QuTiP Example: Birth and Death of Photons in a Cavity
J.R. Johansson and P.D. Nation
For more information about QuTiP see http://qutip.org
End of explanation
N=5
a=destroy(N)
H=a.dag()*a # Simple osc... |
9,997 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyScopus
Step1: <hr>
General Search
Step2: Full text link
Step3: For those with full text links, you are able to get all the text by calling scopus.retrieve_full_text()
Step4: <hr>
Searc... | Python Code:
import pyscopus
pyscopus.__version__
from pyscopus import Scopus
key = 'YOUR_OWN_API'
scopus = Scopus(key)
Explanation: PyScopus: Quick Start
PyScopus is a Python wrapper of Elsevier Scopus API. More details of this Python package can be found here.
<hr>
Import Scopus class and initialize with your own API... |
9,998 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preprocessing and Pipelines
Step1: Cross-validated pipelines including scaling, we need to estimate mean and standard deviation separately for each fold.
To do that, we build a pipeline.
St... | Python Code:
from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split
digits = load_digits()
X_train, X_test, y_train, y_test = train_test_split(digits.data,
digits.target)
Explanation: Preprocessing and Pipelines
End of explanati... |
9,999 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Aprendizado Supervisionado
Vamos começar o estudo da aprendizagem de máquina com o tipo de aprendizado denominado de Supervisionado.
Aprendizado Supervisionado (Supervised Learning)
Step1: ... | Python Code:
# Imports necessários para a parte de Regressão Linear
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import cross_val_score
%matplotlib inline
Explanation: Aprendizado Supervisionado
Vamos começar o estudo da aprendizagem ... |
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