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13,700 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Quickstart
This notebook was made with the following version of emcee
Step1: The easiest way to get started with using emcee is to use it for a project. To get you started, here’s an annota... | Python Code:
import emcee
emcee.__version__
Explanation: Quickstart
This notebook was made with the following version of emcee:
End of explanation
import numpy as np
Explanation: The easiest way to get started with using emcee is to use it for a project. To get you started, here’s an annotated, fully-functional example... |
13,701 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1 Make a request from the Forecast.io API for where you were born (or lived, or want to visit!)
Tip
Step1: 2. What's the current wind speed? How much warmer does it feel than it actually is... | Python Code:
#https://api.forecast.io/forecast/APIKEY/LATITUDE,LONGITUDE,TIME
response = requests.get('https://api.forecast.io/forecast/4da699cf85f9706ce50848a7e59591b7/12.971599,77.594563')
data = response.json()
#print(data)
#print(data.keys())
print("Bangalore is in", data['timezone'], "timezone")
timezone_find = da... |
13,702 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matplotlib Exercise 2
Imports
Step1: Exoplanet properties
Over the past few decades, astronomers have discovered thousands of extrasolar planets. The following paper describes the propertie... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Explanation: Matplotlib Exercise 2
Imports
End of explanation
!head -n 30 open_exoplanet_catalogue.txt
Explanation: Exoplanet properties
Over the past few decades, astronomers have discovered thousands of extrasolar planets. The followin... |
13,703 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
======================================================... | Python Code:
print(__doc__)
import numpy as np
from sklearn.svm import SVR
import matplotlib.pyplot as plt
Explanation: ===================================================================
Support Vector Regression (SVR) using linear and non-linear kernels
================================================================... |
13,704 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stock Prices
Step1: Ridge as Linear Regressor | Python Code:
from sklearn.linear_model import RidgeCV
from sklearn.model_selection import train_test_split
from sklearn.externals import joblib
import numpy as np
import matplotlib.pyplot as plt
import os
data = np.loadtxt(fname = 'data.txt', delimiter = ',')
X, y = data[:,:5], data[:,5]
print("Features sample: {}".for... |
13,705 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GLM
Step1: Generating data
Create some toy data to play around with and scatter-plot it.
Essentially we are creating a regression line defined by intercept and slope and add data points by... | Python Code:
%matplotlib inline
from pymc3 import *
import numpy as np
import matplotlib.pyplot as plt
Explanation: GLM: Linear regression
Author: Thomas Wiecki
This tutorial is adapted from a blog post by Thomas Wiecki called "The Inference Button: Bayesian GLMs made easy with PyMC3".
This tutorial appeared as a post... |
13,706 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interactive Network Exploration with pynucastro
This notebook shows off the interactive RateCollection network plot.
You must have widgets enabled.
Jupyter notebook
Step1: This collection o... | Python Code:
%matplotlib inline
import pynucastro as pyrl
Explanation: Interactive Network Exploration with pynucastro
This notebook shows off the interactive RateCollection network plot.
You must have widgets enabled.
Jupyter notebook:
jupyter nbextension enable --py --user widgetsnbextension
for a user install or... |
13,707 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Calculate terminated results Exiobase v.3.3.11b1 exc. iLUC, electricity markets and social extensions
Investments are not integrated in the MR_HIOT table. They are accounted for in the Final... | Python Code:
HIOT_FD = "/Users/marie/Desktop/MR_HIOT_2011_v3.3.11.xlsx"
import pandas as pd
import csv
### MR-HIOT.csv is created because the excel is too heavy
data_xls = pd.read_excel(HIOT_FD, 'HIOT', index_col=None)
data_xls.to_csv('MR_HIOT.csv', encoding='utf-8')
### FD.csv is created because the excel is too heavy... |
13,708 | 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="#Generating-synthetic-data" data-toc-modified-id="Generating-synthetic-data-1"><span class="toc-item-num">1 </span>Generat... | Python Code:
# important stuff:
import os
import pandas as pd
import numpy as np
import statsmodels.tools.numdiff as smnd
import scipy
# Graphics
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib import rc
rc('text', usetex=True)
rc('text.latex', preamble=r'\usepackage{cmbri... |
13,709 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Image Classification
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. You'll preprocess the images... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if present
floyd_cifa... |
13,710 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Imaging Cortical Layers
Step1: Extract images from the imaging site of our proposed cortical layers | Python Code:
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
#%matplotlib inline
import numpy as np
import urllib2
import scipy.stats as stats
np.set_printoptions(precision=3, suppress=True)
url = ('https://raw.githubusercontent.com/Upward-Spiral-Science'
'/data/master/syn-density/output... |
13,711 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Revised version
Step1: Step 4a
Step2: Step 4b
Step3: Step 5
Step4: Apply to data | Python Code:
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import itertools
import urllib2
import scipy.stats as stats
%matplotlib inline
np.set_printoptions(precision=3, threshold=1000000, suppress=True)
np.random.seed(1)
alpha = .025
url = ('https://raw.githubusercontent.com/Upward-Spiral... |
13,712 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualizing MusicBrainz data with Python/JS, an introduction
This introductory notebook will explain how I get database from MusicBrainz and how I transform it to Python format for display i... | Python Code:
%load_ext watermark
%watermark --python -r
%watermark --date --updated
Explanation: Visualizing MusicBrainz data with Python/JS, an introduction
This introductory notebook will explain how I get database from MusicBrainz and how I transform it to Python format for display in tables or plots.
A static HTML ... |
13,713 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Class 01
Big Data Ingesting
Step1: The next step will be to copy the data file that we will be using for this tutorial into the same folder as these notes. We will be looking at a couple of... | Python Code:
import pandas as pd
Explanation: Class 01
Big Data Ingesting: CSVs, Data frames, and Plots
Welcome to PHY178/CSC171. We will be using the Python language to import data, run machine learning, visualize the results, and communicate those results.
Much of the data that we will use this semester is stored in ... |
13,714 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to PyTorch
Introduction to Torch's tensor library
All of deep learning is computations on tensors, which are
generalizations of a matrix that can be indexed in more than 2
dimen... | Python Code:
# Author: Robert Guthrie
import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
torch.manual_seed(1)
Explanation: Introduction to PyTorch
Introduction to Torch's tensor library
All of deep learning is computations on tensors, which a... |
13,715 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute source power estimate by projecting the covariance with MNE
We can apply the MNE inverse operator to a covariance matrix to obtain
an estimate of source power. This is computationall... | Python Code:
# Author: Denis A. Engemann <denis-alexander.engemann@inria.fr>
# Luke Bloy <luke.bloy@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
import mne
from mne.datasets import sample
from mne.minimum_norm import make_inverse_operator, apply_inverse_cov
data_path = sample.d... |
13,716 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The objective of this notebook is to show how to read and plot data from a mooring (time series).
Step1: Data reading
The data file is located in the datafiles directory.
Step2: As the pla... | Python Code:
%matplotlib inline
import netCDF4
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import rcParams
from matplotlib import colors
from mpl_toolkits.basemap import Basemap
Explanation: The objective of this notebook is to show how to read and plot data from a moorin... |
13,717 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CCSDT theory for a closed-shell reference
This notebook extends the spinorbital-CCSD notebook to compute CCSDT
Step1: Read calculation information (integrals, number of orbitals)
We start b... | Python Code:
import time
import wicked as w
import numpy as np
from examples_helpers import *
Explanation: CCSDT theory for a closed-shell reference
This notebook extends the spinorbital-CCSD notebook to compute CCSDT
End of explanation
molecule = "sr-h6-sto-3g"
with open(f"{molecule}.npy", "rb") as f:
Eref = np.lo... |
13,718 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook, I will show how to train the TensorFlow version of Sketch-RNN on a new dataset, and convert the weights of the TF model to a JSON format that is usable by Sketch-RNN-JS so ... | Python Code:
# import the required libraries
import numpy as np
import time
import random
import codecs
import collections
import os
import math
import json
import tensorflow as tf
from six.moves import xrange
# libraries required for visualisation:
from IPython.display import SVG, display
import svgwrite # conda insta... |
13,719 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Demo for NitroML on Cloud using KubeFlow
Step 1
Step1: Step 2
Step2: Step 3
Step3: Step 4
Step4: Step 5
Step5: Step 6 | Python Code:
import sys
# install kfp (https://kubeflow-pipelines.readthedocs.io/en/latest/source/kfp.html)
!{sys.executable} -m pip install --user --upgrade -q kfp==1.0.0
!{sys.executable} -m pip install --user --upgrade -q kfp-server-api==1.0.0
# Download skaffold and set it executable.
# !curl -Lo skaffold https://s... |
13,720 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Polara for custom evaluation scenarios
Polara is designed to automate the process of model prototyping and evaluation as much as possible. As a part of it,
<div class="alert alert-bloc... | Python Code:
import numpy as np
from polara.datasets.movielens import get_movielens_data
seed = 0
def random_state(seed=seed): # to fix random state in experiments
return np.random.RandomState(seed=seed)
Explanation: Using Polara for custom evaluation scenarios
Polara is designed to automate the process of model pr... |
13,721 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
4.2 サードパーティ製パッケージを使ってスクレイピングに挑戦
Requests http
Step1: RequestsでWebページを取得
Step2: Requestsを使いこなす
connpass APIリファレンス https
Step3: httpbin(1)
Step4: Beautiful Soup 4を使いこなす | Python Code:
import requests
import bs4
Explanation: 4.2 サードパーティ製パッケージを使ってスクレイピングに挑戦
Requests http://docs.python-requests.org/
Beautiful Soup http://www.crummy.com/software/BeautifulSoup/
End of explanation
# Requestsでgihyo.jpのページのデータを取得
import requests
r = requests.get('http://gihyo.jp/lifestyle/clip/01/everyday-cat')... |
13,722 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matrices de Transformación
Las matrices de rotación y traslación nos sirven para transformar una coordenada entre diferentes sistemas coordenados, pero tambien lo podemos ver, como la transf... | Python Code:
from math import pi, sin, cos
from numpy import matrix
from matplotlib.pyplot import figure, plot, style
from mpl_toolkits.mplot3d import Axes3D
style.use("ggplot")
%matplotlib notebook
τ = 2*pi
Explanation: Matrices de Transformación
Las matrices de rotación y traslación nos sirven para transformar una co... |
13,723 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
II. Numpy and Scipy
Numpy contains core routines for doing fast vector, matrix, and linear algebra-type operations in Python. Scipy contains additional routines for optimization, special fun... | Python Code:
%pylab inline
import numpy as np
# Import pylab to provide scientific Python libraries (NumPy, SciPy, Matplotlib)
%pylab --no-import-all
#import pylab as pl
# import the Image display module
from IPython.display import Image
import math
np.array([1,2,3,4,5,6])
Explanation: II. Numpy and Scipy
Numpy contain... |
13,724 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An example packet from ESEO.
Step1: Trim the data between the 0x7e7e flags. We skip Reed-Solomon decoding, since we are confident that there are no bit errors. We remove the 16 Reed-Solomon... | Python Code:
bits = np.array([0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0,... |
13,725 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Core vision
Basic image opening/processing functionality
Helpers
Step1: Image.n_px
Image.n_px (property)
Number of pixels in image
Step2: Image.shape
Image.shape (property)
Image (height,w... | Python Code:
#|export
imagenet_stats = ([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
cifar_stats = ([0.491, 0.482, 0.447], [0.247, 0.243, 0.261])
mnist_stats = ([0.131], [0.308])
im = Image.open(TEST_IMAGE).resize((30,20))
#|export
if not hasattr(Image,'_patched'):
_old_sz = Image.Image.size.fget
@patch(... |
13,726 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Eager Execution
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Now you can run TensorFlow ... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
13,727 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MRI intensity normalization
Intensity normalization of multi-channel MRI images using the method proposed by Nyul et al. 2000.
In the original paper, the authors suggest a method where a set... | Python Code:
import os
import numpy as np
import nibabel as nib
from nyul import nyul_train_standard_scale
DATA_DIR = 'data_examples'
T1_name = 'T1.nii.gz'
MASK_name = 'brainmask.nii.gz'
# generate training scans
train_scans = [os.path.join(DATA_DIR, folder, T1_name)
for folder in os.listdir(DATA_DIR)... |
13,728 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Latent Dirichlet Allocation applied to real data
Step1: Data fetching and preprocessing
Building sample dataset
We are considering a collection of English news articles about the case relat... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: Latent Dirichlet Allocation applied to real data
End of explanation
#get raw data
import xml.etree.ElementTree as ET
tree = ET.parse('../dataset/nysk.xml')
root = tree.getroot()
root1 = root.getchildren()[150].getchildren()
texts=... |
13,729 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tests of PySpark UDF with mapInArrow vs. mapInPandas
Step1: Dataset preparation
Step2: mapInPAndas tests
Test 1 - dummy UDF
Step3: Test 2
Step4: mapInArrow tests
Test 3
Step5: Test 5
St... | Python Code:
# This is a new feature, candidate from Spark 3.3.0
# See https://issues.apache.org/jira/browse/SPARK-37227
import findspark
findspark.init("/home/luca/Spark/spark-3.3.0-SNAPSHOT-bin-spark_21220128")
# use only 1 core to make performance comparisons easier/cleaner
from pyspark.sql import SparkSession
spark... |
13,730 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1、随机生成1万个整数，范围在0-10万之间，分别进行简单选择排序、快速排序（自行递归实现的）以及内置sort函数3种排序，打印出3种排序的运行时间。
假设有快速排序算法quick_sort(seq)，可以实现快速排序。
令left_seq = [], right_seq = []
令待排序序列区间的第一个元素为p，即p=seq[0]
对seq的[start+1,end... | Python Code:
import random
import time
def simple_sort(numbers):
for i in range(len(numbers)):
for j in range(i+1,len(numbers)):
min=i
if numbers[min]>numbers[j]:
min=j
numbers[i],numbers[min]=numbers[min],numbers[i]
def quick_sort(seq):
left_seq=[]
ri... |
13,731 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
United States carries most of the weight of the total electricity consumption in the household market in N. America in the perdio 1990-2014. US is followed in consumption by Canada and Mexic... | Python Code:
#Europe
df5 = df4.loc[df4.index.isin(['Austria', 'Belgium', 'Bulgaria','Croatia', 'Cyprus', 'Czechia','Denmark', 'Estonia','Finland','France','Germany','Greece','Hungary','Ireland','Italy','Latvia','Lithuania','Luxembourg','Malta','Netherlands','Poland','Portugal','Romania','Slovakia', 'Slovenia','Spain', ... |
13,732 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hyper-study
The time series models built with the help of bayesloop are called hierarchical models, since the parameters of the observation model are in turn controlled by hyper-parameters t... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt # plotting
import seaborn as sns # nicer plots
sns.set_style('whitegrid') # plot styling
import numpy as np
import bayesloop as bl
S = bl.HyperStudy()
S.loadExampleData()
L = bl.om.Poisson('accident_rate', bl.oint(0, 6, 1000))
T = bl.tm.Seri... |
13,733 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Functions
1. pairwise_correlation( df )
Step3: 2. corr_rowi_rowj( df , i , j )
Step5: 3. corr_rowi_vs_all1( df )
Step7: 4. corr_rowi_vs_all2( df , i )
Step8: Test
1. pairwise_corr... | Python Code:
#Try now
def pairwise_correlation(df):
#Print data first to make it easy to check.
print("data:")
print(df,"\n\nP value:")
metrix = pd.DataFrame()
labels=[]
#Use 'iterrows()' to get rows repeatedly.
#There are two for loops.
The outer for loop is used to get... |
13,734 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 2
Step1: Note
Step2: Problem set 1
Step3: Problem set 2
Step4: Nicely done. Now, in the cell below, fill in the indicated string with a SQL statement that returns all occupation... | Python Code:
import pg8000
conn = pg8000.connect(database="homework2")
Explanation: Homework 2: Working with SQL (Data and Databases 2016)
This homework assignment takes the form of an IPython Notebook. There are a number of exercises below, with notebook cells that need to be completed in order to meet particular crit... |
13,735 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A simple example on how to use jQAssistant with Python Pandas
I'm a huge fan of the software analysis framework jQAssistant (http
Step1: Step 2
Step2: Step 3
Step3: Step 4
Step4: Step 5
... | Python Code:
import py2neo
import pandas as pd
Explanation: A simple example on how to use jQAssistant with Python Pandas
I'm a huge fan of the software analysis framework jQAssistant (http://www.jqassistant.org). It's a great tool for scanning and validating various software artifacts (get a glimpse at https://buschma... |
13,736 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocean
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'niwa', 'sandbox-2', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: NIWA
Source ID: SANDBOX-2
Topic: Ocean
Sub-Topics: Timestepping Framework, Ad... |
13,737 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmoschem
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', 'mri', 'sandbox-3', 'atmoschem')
Explanation: ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era: CMIP6
Institute: MRI
Source ID: SANDBOX-3
Topic: Atmoschem
Sub-Topics: Transport, Emiss... |
13,738 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Decoding sensor space data with generalization across time and conditions
This example runs the analysis described in
Step1: We will train the classifier on all left visual vs auditory tri... | Python Code:
# Authors: Jean-Remi King <jeanremi.king@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD-3-Clause
import matplotlib.pyplot as plt
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import Standar... |
13,739 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing surrogate models
Tim Head, July 2016.
Step1: Bayesian optimization or sequential model-based optimization uses a surrogate model
to model the expensive to evaluate function func. ... | Python Code:
import numpy as np
np.random.seed(123)
%matplotlib inline
import matplotlib.pyplot as plt
plt.set_cmap("viridis")
Explanation: Comparing surrogate models
Tim Head, July 2016.
End of explanation
from skopt.benchmarks import branin as _branin
def branin(x, noise_level=0.):
return _branin(x) + noise_level... |
13,740 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
travelTime Analysis
Different analyses of data collected using https
Step1: Load data
Step2: Convert the unix timestamp to a datetime object
Step3: Add a new column with the duration in h... | Python Code:
%matplotlib inline
import pandas as pd, matplotlib.pyplot as plt, matplotlib.dates as dates, math
from datetime import datetime
from utils import find_weeks, find_days # custom
from pytz import timezone
from detect_peaks import detect_peaks
from ipywidgets import interact, interactive, fixed, interact_manu... |
13,741 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Evolution of sequence, structure and dynamics with Evol and SignDy
This tutorial has two parts, focusing on two related parts of ProDy for studying evolution
Step1: We also configure ProDy ... | Python Code:
from prody import *
from pylab import *
%matplotlib inline
confProDy(auto_show=False)
Explanation: Evolution of sequence, structure and dynamics with Evol and SignDy
This tutorial has two parts, focusing on two related parts of ProDy for studying evolution:
The sequence sub-package Evol is for fetching, p... |
13,742 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
convert an BGR image to RGB image
| Python Code::
import cv2
import numpy as np
array_of_image = np.array(image)
image_rgb = cv2.cvtColor(array_of_image, cv2.COLOR_BGR2RGB)
cv2.imshow('image', image_rgb)
|
13,743 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
K-nearest neighbors
Step1: Let's imagine we measure 2 quantities, $x_1$ and $x_2$ for some objects, and we know the classes that these objects belong to, e.g., "star", 0, or "galaxy", 1 (ma... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('notebook.mplstyle')
%matplotlib inline
from scipy.stats import mode
Explanation: K-nearest neighbors
End of explanation
a = np.random.multivariate_normal([1., 0.5],
[[4., 0.],
... |
13,744 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Text generation using an RNN
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Download the Shak... | 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... |
13,745 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What is NLP?
NLP is a field of linguistics and machine learning focused on understanding everything related to human language. The aim of NLP tasks is not only to understand single words ind... | Python Code:
from transformers import pipeline
classifier = pipeline('sentiment-analysis')
classifier("I've been waiting for a HuggingFace course my whole life.")
## passing multiple sentences
classifier([
"I've been waiting for a HuggingFace course my whole life.",
"I hate this so much!"
])
Explanation: What ... |
13,746 | 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="#Instantiate-CPPN" data-toc-modified-id="Instantiate-CPPN-1"><span class="toc... | Python Code:
import numpy as np
import yaml
import os
import cv2
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import animation
from datetime import datetime
from pathlib import Path
plt.rcParams['animation.ffmpeg_path'] = str(Path.home() / "anaconda3/envs/image-processing/bi... |
13,747 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 2
Step1: 1. Load trajectory
Read the heat current from a simple column-formatted file. The desired columns are selected based on their header (e.g. with LAMMPS format).
For other in... | Python Code:
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
try:
import sportran as st
except ImportError:
from sys import path
path.append('..')
import sportran as st
c = plt.rcParams['axes.prop_cycle'].by_key()['color']
%matplotlib notebook
Explanation: Example 2: Cepstral Analy... |
13,748 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Jupyter Notebooks on Navigating Complexity
<img src="http
Step1: Or how many unique words are there.
Step2: Or something more complicated, such as defining how a graph is p... | Python Code:
len("in all honesty, counting all the words in a sentence is best done in a computers mind. It doesn't mind counting at all".split())
Explanation: Introduction to Jupyter Notebooks on Navigating Complexity
<img src="http://jupyter.org/assets/jupyterpreview.png" style="height: 300px; float: right;"> </img>
... |
13,749 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Linear Regression
Simple Linear Regression
Running a SLR in Python is fairly simple once you know how to use the relevant functions. What might be confusing is that there exist several packa... | Python Code:
# Load relevant packages
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')
plt.rcParams['font.size'] = 14
Explanation: Linear Regression
Simple Linear Regression
Running a SLR in Python is fairly simple ... |
13,750 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Variable pitch solenoid model
A.M.C. Dawes - 2015
A model to design a variable pitch solenoid and calculate the associated on-axis B-field.
Step2: Parameters
Step3: Design discussion and c... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
mpl.rcParams['legend.fontsize'] = 10
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
I = 10 #amps
mu = 4*np.pi*1e-7 #This gives B in units of Tesla
Explanation: Variable pitch solenoid model
A.M.C. Dawes - 2015
A model t... |
13,751 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Stats Quality for 2016 College Nationals
As one of the biggest tournaments hosted by USAU, the Club Nationals is one of the few tournaments where player statistics are relatively reli... | Python Code:
import usau.reports
import usau.fantasy
from IPython.display import display, HTML
import pandas as pd
pd.options.display.width = 200
pd.options.display.max_colwidth = 200
pd.options.display.max_columns = 200
def display_url_column(df):
Helper for formatting url links
df.url = df.url.apply(lambda url: "... |
13,752 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
下載 ETC M06A 資料
<a href="http
Step1: 基本的資料
Step2: 反過來由檔名找日期，可以用 regexp 或者 datetime
Step3: 抓所有的壓縮檔案
Step4: 將 .tar.gz 重新打包成 .tar.xz | Python Code:
from urllib.request import urlopen, urlretrieve
import tqdm
Explanation: 下載 ETC M06A 資料
<a href="http://www.freeway.gov.tw/UserFiles/File/TIMCCC/TDCS%E4%BD%BF%E7%94%A8%E6%89%8B%E5%86%8A(tanfb)v3.0-1.pdf">國道高速公路電子收費交通資料蒐集支援系統(Traffic Data Collection System,TDCS)使用手冊</a>
End of explanation
# 歷史資料網址
data_base... |
13,753 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Test DFA-2-RegExp
Step1: As this regular expression is nearly unreadable, The notebook Rewrite.ipynb contains the definition of the function simplify that can be used to simplify this expr... | Python Code:
%run DFA-2-RegExp.ipynb
%run FSM-2-Dot.ipynb
delta = { (0, 'a'): 0,
(0, 'b'): 1,
(1, 'a'): 1
}
A = {0, 1}, {'a', 'b'}, delta, 0, {1}
g, _ = dfa2dot(A)
g
r = dfa_2_regexp(A)
r
Explanation: Test DFA-2-RegExp
End of explanation
%run Rewrite.ipynb
s = simplify(r, Rules)
s
Explanatio... |
13,754 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h3 STYLE="background
Step1: <h3 STYLE="background
Step2: <h3 STYLE="background
Step3: <h4 style="border-bottom
Step4: 上図のように、qualityが６未満のワインと６以上のワインは volatile acidity の分布が異なるように見えます。その差... | Python Code:
# 数値計算やデータフレーム操作に関するライブラリをインポートする
import numpy as np
import pandas as pd
import scipy as sp
from scipy import stats
# URL によるリソースへのアクセスを提供するライブラリをインポートする。
# import urllib # Python 2 の場合
import urllib.request # Python 3 の場合
# 図やグラフを図示するためのライブラリをインポートする。
%matplotlib inline
import matplotlib.pyplot as plt
# 機... |
13,755 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
XGBoost模型调优
加载要用的库
Step1: 载入数据
上一个ipython notebook已经做了下面这些数据特征预处理
1. City因为类别太多丢掉
2. DOB生成Age字段，然后丢掉原字段
3. EMI_Loan_Submitted_Missing 为1(EMI_Loan_Submitted) 为0(EMI_Loan_Submitted缺省) EMI_Loa... | Python Code:
import pandas as pd
import numpy as np
import xgboost as xgb
from xgboost.sklearn import XGBClassifier
from sklearn import cross_validation, metrics
from sklearn.grid_search import GridSearchCV
import matplotlib.pylab as plt
%matplotlib inline
from matplotlib.pylab import rcParams
rcParams['figure.figsize'... |
13,756 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
13,757 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spatial Model fitting in GLS
In this exercise we will fit a linear model using a Spatial structure as covariance matrix.
We will use GLS to get better estimators.
As always we will need to ... | Python Code:
# Load Biospytial modules and etc.
%matplotlib inline
import sys
sys.path.append('/apps')
sys.path.append('..')
sys.path.append('../spystats')
import django
django.setup()
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
## Use the ggplot style
plt.style.use('ggplot')
import tools
Exp... |
13,758 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
13,759 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
cs231n case study toy NN example
http
Step1: Training a softmax linear classifier
Step2: Softmax loss using cross-entropy
keepdims variable forces the matrix shape !!
- else np.sum result... | Python Code:
import numpy as np
# for quick visualization in notebook
import matplotlib.pyplot as plt
%matplotlib inline
N = 100 # number of points per class
D = 2 # dimensionality
K = 3 # number of classes
X = np.zeros((N*K,D)) # data matrix (each row = single example)
y = np.zeros(N*K, dtype='uint8') # class labels
f... |
13,760 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Transformation
This exploratory analysis takes into account how long does it take to a given open case to be closed.
Step1: Transforming Column Names
Step2: Transforming Open and Clos... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import bokeh
from bokeh.io import output_notebook
output_notebook()
import os
DATA_STREETLIGHT_CASES_URL = 'https://data.sfgov.org/api/views/c53t-rr3f/rows.json?accessType=DOWNLOAD'
DATA_STREETLI... |
13,761 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analysis of large set of Abl simulations on Folding@home (project 10468), one starting configuration
May 1, 2015
This is some initial MSM building Abl simulations.
Section 0
Step1: The time... | Python Code:
#Import libraries
import matplotlib.pyplot as plt
import mdtraj as md
import glob
import numpy as np
from msmbuilder.dataset import dataset
%pylab inline
#Import longest trajectory.
t = md.load("run0-clone35.h5")
Explanation: Analysis of large set of Abl simulations on Folding@home (project 10468), one sta... |
13,762 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recovering rotation periods in simulated LSST data
Step1: Randomly select targets from a TRILEGAL output.
Step2: Calculate periods from ages and colours for cool stars
Step3: Draw from a ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from gatspy.periodic import LombScargle
import sys
%matplotlib inline
from toy_simulator import simulate_LSST
from trilegal_models import random_stars
import simple_gyro as sg
import pandas as pd
Explanation: Recovering rotation periods in simulated LSST d... |
13,763 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create dataframe
Step2: Make plot | Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
Explanation: Title: Scatterplot In MatPlotLib
Slug: matplotlib_stacked_bar_plot
Summary: Scatterplot In MatPlotLib
Date: 2016-05-01 12:00
Category: Python
Tags: Data Visualization
Authors: Chris Albon
Based on: Seb... |
13,764 | Given the following text description, write Python code to implement the functionality described.
Description:
Number of subarrays have bitwise OR >= K
Function to return the count of required sub - arrays ; Traverse sub - array [ i . . j ] ; Driver code
| Python Code:
def countSubArrays(arr , n , K ) :
count = 0 ;
for i in range(n ) :
for j in range(i , n ) :
bitwise_or = 0
for k in range(i , j + 1 ) :
bitwise_or = bitwise_or | arr[k ]
if(bitwise_or >= K ) :
count += 1
return count
if __name__== "__main __":
arr =[3 , 4 , 5 ]
n = ... |
13,765 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DTOcean Electrical Sub-Systems Example
Note, this example assumes the Electrical Sub-Systems Module has been installed
Step1: Create the core, menus and pipeline tree
The core object carrys... | Python Code:
%matplotlib inline
from IPython.display import display, HTML
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (14.0, 8.0)
import numpy as np
from dtocean_core import start_logging
from dtocean_core.core import Core
from dtocean_core.menu import ModuleMenu, ProjectMenu
from dtocean_core.pipe... |
13,766 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex AI Pipelines
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Install the latest GA version of google-cloud-pipeline-components library as well.
... | Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
Explanation: Vertex AI Pipelines: AutoML image classification pipelines using google-cloud-pipeline-co... |
13,767 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting Data and Preprocessing
Step1: factorplot and FacetGrid | Python Code:
names = [
'mpg'
, 'cylinders'
, 'displacement'
, 'horsepower'
, 'weight'
, 'acceleration'
, 'model_year'
, 'origin'
, 'car_name'
]
# reading the file and assigning the header
df = pd.read_csv("http://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/a... |
13,768 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Question 1
Step1: On vérifie en utilisant sympy que le calcul est correct
Step2: Question 2
Step3: On vérifie en utilisant sympy que ce calcul est correct
Step4: Question 3
Step5: On vé... | Python Code:
def somme(A, B):
C = []
for i in range(4):
Ai = A[i]
Bi = B[i]
row = [Ai[j]+Bi[j] for j in range(4)]
C.append(row)
return C
X = [[56, 39, 3, 41],
[23, 78, 11, 62],
[61, 26, 65, 51],
[80, 98, 9, 68]]
Y = [[51, 52, 53, 15],
[ 1, 71, 46, 31],
... |
13,769 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1 Creating an instance of the solow.Model class
In this notebook I will walk you through the creation of an instance of the solow.Model class. To create an instance of the solow.Model we mus... | Python Code:
solow.Model.output?
Explanation: 1 Creating an instance of the solow.Model class
In this notebook I will walk you through the creation of an instance of the solow.Model class. To create an instance of the solow.Model we must define two primitives: an aggregate production function and a dictionary of model ... |
13,770 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Initialize PySpark
First, we use the findspark package to initialize PySpark.
Step1: Hello, World!
Loading data, mapping it and collecting the records into RAM...
Step2: Creating Objects f... | Python Code:
from pyspark.sql import SparkSession
# Initialize PySpark with MongoDB support
APP_NAME = "Introducing PySpark"
spark = (
SparkSession.builder.appName(APP_NAME)
# Load support for MongoDB and Elasticsearch
.config("spark.jars.packages", "org.mongodb.spark:mongo-spark-connector_2.12:3.0.1,org.el... |
13,771 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SETI Test Set Classification Accuracy
This notebook provides the code needed to calculate the performance of your signal classification models using the PREVIEW test set (see Step 1. Get Dat... | Python Code:
from sklearn.metrics import classification_report
from sklearn.model_selection import train_test_split
import numpy as np
import sklearn
import csv
import operator
class_list = ['brightpixel', 'narrowband', 'narrowbanddrd', 'noise', 'squarepulsednarrowband', 'squiggle', 'squigglesquarepulsednarrowband']
fi... |
13,772 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Practice with galaxy photometry and shape measurement
To accompany galaxy-measurement lecture from the LSSTC Data Science Fellowship Program, July 2020.
All questions and corrections can be ... | Python Code:
# Load the packages we will use
import numpy as np
import astropy.io.fits as pf
import astropy.coordinates as co
from matplotlib import pyplot as pl
import scipy.fft as fft
%matplotlib inline
Explanation: Practice with galaxy photometry and shape measurement
To accompany galaxy-measurement lecture from the... |
13,773 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'pcmdi', 'sandbox-2', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: PCMDI
Source ID: SANDBOX-2
Topic: Land
Sub-Topics: Soil, Snow, Vegetation, Ene... |
13,774 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Now create the DrawControl and add it to the Map using add_control. We also register a handler for draw events. This will fire when a drawn path is created, edited or deleted (there are the ... | Python Code:
dc = DrawControl(marker={'shapeOptions': {'color': '#0000FF'}},
rectangle={'shapeOptions': {'color': '#0000FF'}},
circle={'shapeOptions': {'color': '#0000FF'}},
circlemarker={},
)
def handle_draw(self, action, geo_json):
print(action)
... |
13,775 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
(📗) ipyrad Cookbook
Step1: Connect to cluster
The code can be easily parallelized across cores on your machine, or many nodes of an HPC cluster using the ipyparallel library (see ou... | Python Code:
import ipyrad.analysis as ipa
import ipyparallel as ipp
import toytree
import toyplot
print ipa.__version__
print toyplot.__version__
print toytree.__version__
Explanation: (📗) ipyrad Cookbook: abba-baba admixture tests
The ipyrad.analysis Python module includes functions to calculate abba-baba adm... |
13,776 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'niwa', 'sandbox-3', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: NIWA
Source ID: SANDBOX-3
Topic: Land
Sub-Topics: Soil, Snow, Vegetation, Energ... |
13,777 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Installation instructions
First, clone cmac2.0 into your own directory
Step2: This will start a distributed cluster on the arm_high_mem queue. I have set it to have 6 adi_cmac2 proce... | Python Code:
import subprocess
import os
import sys
from dask_jobqueue import PBSCluster
from distributed import Client, progress
from datetime import datetime, timedelta
from pkg_resources import load_entry_point
from distributed import progress
def exec_adi(info_dict):
This function will call adi_cmac2 from ... |
13,778 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matrix generation
Init symbols for sympy
Step1: Lame params
Step2: Metric tensor
${\displaystyle \hat{G}=\sum_{i,j} g^{ij}\vec{R}_i\vec{R}_j}$
Step3: ${\displaystyle \hat{G}=\sum_{i,j} g_... | Python Code:
from sympy import *
from geom_util import *
from sympy.vector import CoordSys3D
N = CoordSys3D('N')
alpha1, alpha2, alpha3 = symbols("alpha_1 alpha_2 alpha_3", real = True, positive=True)
init_printing()
%matplotlib inline
%reload_ext autoreload
%autoreload 2
%aimport geom_util
Explanation: Matrix generati... |
13,779 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook
Step1: Download or use cached file oecd-canada.json. Caching file on disk permits to work off-line and to speed up the exploration of the data.
Step2: Initialize JsonStatCollectio... | Python Code:
# all import here
from __future__ import print_function
import os
import pandas as ps # using panda to convert jsonstat dataset to pandas dataframe
import jsonstat # import jsonstat.py package
import matplotlib as plt # for plotting
%matplotlib inline
Explanation: Notebook: using jsonstat.py python l... |
13,780 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples of plots and calculations using the tmm package
Imports
Step1: Set up
Step2: Sample 1
Here's a thin non-absorbing layer, on top of a thick absorbing layer, with
air on both sides.... | Python Code:
from __future__ import division, print_function, absolute_import
from tmm import (coh_tmm, unpolarized_RT, ellips,
position_resolved, find_in_structure_with_inf)
from numpy import pi, linspace, inf, array
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
%matplot... |
13,781 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Our Mission
Spam detection is one of the major applications of Machine Learning in the interwebs today. Pretty much all of the major email service providers have spam detection systems built... | Python Code:
'''
Solution
'''
import pandas as pd
# Dataset from - https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection
df = pd.read_table('smsspamcollection/SMSSpamCollection',
sep='\t',
header=None,
names=['label', 'sms_message'])
# Output printing out... |
13,782 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fractal Dimension and Lacunarity
Much of the code/theory is from
Step1: Generate Data
Generate a random walk of length n in d dimensions and plot it if it is 1, 2, or 3 dimensional.
Step2: ... | Python Code:
import scipy.optimize
from pandas import Series, DataFrame
import statsmodels.formula.api as sm
import numpy as np, scipy, scipy.stats
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
Explanation: Fractal Dimension and Lacunarity
Much of the code/theory is from: http://connor-johnson... |
13,783 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to the dmdd tutorial!
A python package that enables simple simulation and Bayesian posterior analysis
of nuclear-recoil data from dark matter direct detection experiments
for a wide... | Python Code:
I. Nuclear-recoil rates
-----
______
`dmdd` has three modules that let you calculate differential rate $\frac{dR}{dE_R}$ and total rate $R(E_R)$ of nuclear-recoil events:
I) `rate_UV`: rates for a variety of UV-complete theories (from Gresham & Zurek, 2014)
II) `rate_genNR`: rates for all non-relativis... |
13,784 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generate test data for SASS implementation of the Gibson-Lanni PSF.
This Python algorithm has been verified against the original MATLAB code from the paper Li, J., Xue, F., & Blu, T. (2017).... | Python Code:
import sys
%pylab inline
import scipy.special
from scipy.interpolate import interp1d
from scipy.interpolate import RectBivariateSpline
print('Python {}\n'.format(sys.version))
print('NumPy\t\t{}'.format(np.__version__))
print('matplotlib\t{}'.format(matplotlib.__version__))
print('SciPy\t\t{}'.format(scipy... |
13,785 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
观测者模式(Observer Pattern)
1 代码
在门面模式中，我们提到过火警报警器。在当时，我们关注的是通过封装减少代码重复。而今天，我们将从业务流程的实现角度，来再次实现该火警报警器。
Step1: 以上是门面模式中的三个传感器类的结构。仔细分析业务，报警器、洒水器、拨号器都是“观察”烟雾传感器的情况来做反应的。因而，他们三个都是观察者，而烟雾传感器则是被观察对象... | 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: 观测者模式(Observer Pattern)
1 代码
在门面模式中，我们提到过火警报警器。在当时，我们关注的是通过封装减少代码重复。而今天，我们将从业务流... |
13,786 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this example, we'e going to actually run a short simulation with OpenMM
saving the results to disk with MDTraj's HDF5 reporter
Obviously, running this example calculation on your machine ... | Python Code:
import os
import mdtraj
import mdtraj.reporters
Explanation: In this example, we'e going to actually run a short simulation with OpenMM
saving the results to disk with MDTraj's HDF5 reporter
Obviously, running this example calculation on your machine requires
having OpenMM installed. OpenMM can be download... |
13,787 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Tutorial
Step1: We will try summarizing a small toy example; later we will use a larger piece of text. In reality, the text is too small, but it suffices as an illustrative example.
Ste... | Python Code:
import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
from gensim.summarization import summarize
Explanation: <h1>Tutorial: automatic summarization using Gensim</h1>
This module automatically summarizes the given text, by extracting one or more important... |
13,788 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Create Space from an already existing .json input file
Step1: Probe group information and get particle index
Step2: Extract positions etc from a group
Step3: Calculate center of mass for ... | Python Code:
jsoninput = mc.InputMap('../src/examples/minimal.json')
space = mc.Space(jsoninput)
print(space.info())
print 'system volume = ',space.geo.getVolume()
Explanation: Create Space from an already existing .json input file:
End of explanation
groups = space.groupList()
for group in groups:
print group.name... |
13,789 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Biosignals Processing in Python
Welcome to the course for biosignals processing using NeuroKit and python. You'll find the necessary files to run this example in the examples section.
Import... | Python Code:
# Import packages
import neurokit as nk
import pandas as pd
import numpy as np
import matplotlib
import seaborn as sns
# Plotting preferences
%matplotlib inline
matplotlib.rcParams['figure.figsize'] = [14.0, 10.0] # Bigger figures
sns.set_style("whitegrid") # White background
sns.set_palette(sns.color_pa... |
13,790 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy random snippets
Most comments are taken from the Numpy documentation.
Import directive
Step1: Tool functions
Step2: Discrete distributions
Bernoulli distribution
Step3: Binomial dis... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
Explanation: Numpy random snippets
Most comments are taken from the Numpy documentation.
Import directive
End of explanation
def plot(data, bins=30):
plt.hist(data, bins)
plt.show()
Explanation: Tool functions
End of explanation
... |
13,791 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Custom training and online prediction
<table align="left">
<td>
<a href="https
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Install the pillow... | 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"
! pip ... |
13,792 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recurrent Neural Networks in Theano
Credits
Step1: We now define a class that uses scan to initialize an RNN and apply it to a sequence of data vectors. The constructor initializes the shar... | Python Code:
%matplotlib inline
from synthetic import mackey_glass
import matplotlib.pyplot as plt
import theano
import theano.tensor as T
import numpy
floatX = theano.config.floatX
Explanation: Recurrent Neural Networks in Theano
Credits: Forked from summerschool2015 by mila-udem
First, we import some dependencies:
En... |
13,793 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matplotlib
This notebook is (will be) a small crash course on the functionality of the Matplotlib Python module for creating graphs (and embedding it in notebooks). It is of course no substi... | Python Code:
%matplotlib inline
Explanation: Matplotlib
This notebook is (will be) a small crash course on the functionality of the Matplotlib Python module for creating graphs (and embedding it in notebooks). It is of course no substitute for the proper Matplotlib thorough documentation.
Initialization
We need to add ... |
13,794 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
As always, we load things from files so we don't have to set them up again.
Step1: The flux_pairs variable is a list of 2-tuples, where the first element is the state we're calculating the ... | Python Code:
old = paths.Storage("mistis.nc", 'r')
engine = old.engines[0]
network = old.networks[0]
states = set(network.initial_states + network.final_states)
# must ensure that the diskcache is disabled in order to save,
# otherwise it looks for things that aren't there!
cvs = old.cvs[:]
for cv in cvs:
cv.disabl... |
13,795 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
how to delete a particular row in dataframe using python
| Python Code::
dataFrame = dataFrame.drop(columns)
|
13,796 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This notebook demonstrates pymatgen's functionality in terms of creating and editing molecules, as well as its integration with OpenBabel. For the latter, please note that you w... | Python Code:
from pymatgen import Molecule
# Create a methane molecule.
coords = [[0.000000, 0.000000, 0.000000],
[0.000000, 0.000000, 1.089000],
[1.026719, 0.000000, -0.363000],
[-0.513360, -0.889165, -0.363000],
[-0.513360, 0.889165, -0.363000]]
mol = Molecule(["C", "H", "H", "... |
13,797 | 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', 'miroc', 'nicam16-9s', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: MIROC
Source ID: NICAM16-9S
Topic: Aerosol
Sub-Topics: Transport, Emiss... |
13,798 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploration of a problem interpreting binary test results
Copyright 2015 Allen Downey
MIT License
Step1: p is the prevalence of a condition
s is the sensititivity of the test
The false posi... | Python Code:
from __future__ import print_function, division
import thinkbayes2
from sympy import symbols
Explanation: Exploration of a problem interpreting binary test results
Copyright 2015 Allen Downey
MIT License
End of explanation
p, q, s, t1, t2 = symbols('p q s t1 t2')
Explanation: p is the prevalence of a condi... |
13,799 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Récupération des données
Ce notebook donne quelques exemples de codes qui permettent de récupérer les données utilisées par d'autres notebooks. Le module actuariat_python est implémenté avec... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('ggplot')
# le code qui suit n'est pas indispensable, il génère automatiquement un menu
# dans le notebook
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: Récupération des données
Ce notebook donne quelques exempl... |
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