Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
7,100 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Quality Measures
Step1: <a id='pain'></a>
Pain
Step2: <a id='dyspnea'></a>
Dyspnea
Step3: <a id='constipation'></a>
Constipation Screening
Step4: <a id='opiod'></a>
Opiod bowel regimen
C... | Python Code:
import pandas as pd
import pickle
import numpy as np
import matplotlib.pyplot as plt
from textwrap import wrap
#from matplotlib import rcParams
#rcParams.update({'figure.autolayout': True})
%matplotlib inline
dd = pickle.load(open("./python_scripts/02_data_dictionary_dict.p", "rb" ))
voi = ['ESASPain','ES... |
7,101 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generative Adversarial Network
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten d... | Python Code:
%matplotlib inline
import pickle as pkl
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data')
Explanation: Generative Adversarial Network
In this notebook, we'll be building a gen... |
7,102 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deputado Histogramado
expressao.xyz/deputado/
Como processar as sessões do parlamento Português
Índice
Reunír o dataset
Contando as palavras mais comuns
Fazendo histogramas
Representações ge... | Python Code:
%matplotlib inline
import pylab
import matplotlib
import pandas
import numpy
dateparse = lambda x: pandas.datetime.strptime(x, '%Y-%m-%d')
sessoes = pandas.read_csv('sessoes_democratica_org.csv',index_col=0,parse_dates=['data'], date_parser=dateparse)
Explanation: Deputado Histogramado
expressao.xyz/deputa... |
7,103 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 8 – Fit an Hubble Diagram
The SN Ia Science in short
The Type Ia Supernova event is the thermonuclear runaway of a white dwarf. This bright event is extremely stable and the maximum... | Python Code:
import warnings
# No annoying warnings
warnings.filterwarnings('ignore')
# Because we always need that
# plot within the notebook
%matplotlib inline
import numpy as np
import matplotlib.pyplot as mpl
Explanation: Exercise 8 – Fit an Hubble Diagram
The SN Ia Science in short
The Type Ia Supernova event is t... |
7,104 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The network directory in this share (which is still uploading, btw) contains a pickle (data.pkl) and the code used to generate it (network.py). The lfdr_pcor object in the pickle has the par... | Python Code:
! ls -lh ../waffle_network_dir/*.tsv
! wc -l ../waffle_network_dir/network.py.tsv
! head -n 5 ../waffle_network_dir/network.py.tsv | csvlook -t
! ls -lh ../waffle_network_dir/network.py.tsv
Explanation: The network directory in this share (which is still uploading, btw) contains a pickle (data.pkl) and th... |
7,105 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example Usage
Step1: pandas-learn has an identical module structure to scikit-learn, so you already know where to find all the models you already use
Step2: You can use pandas to manipulat... | Python Code:
import pandas as pd
%matplotlib inline
Explanation: Example Usage: Titanic Dataset
An example of training a model on the titanic dataset.
The name of the package is pandas-learn, a mixing pandas into scikit-learn. Therefore, you should always use pandas to handle your data if you are using the package(!):... |
7,106 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Keras での重みクラスタリングの例
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: クラスタを使用せずに、MNIST の tf.keras ... | 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... |
7,107 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gravity Brightening/Darkening (gravb_bol)
Setup
Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your install... | Python Code:
!pip install -I "phoebe>=2.0,<2.1"
Explanation: Gravity Brightening/Darkening (gravb_bol)
Setup
Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
End of explanat... |
7,108 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Object-Oriented Programming
We've talked about how everyting in Python is an object. In addition, we've come to use many objects. However, we have not created any objects. In this lecture, w... | Python Code:
# Creating a class called Bike
class Bike:
pass
Explanation: Object-Oriented Programming
We've talked about how everyting in Python is an object. In addition, we've come to use many objects. However, we have not created any objects. In this lecture, we will discuss object-oriented programming, and what... |
7,109 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Como usar com o Pandas
Os catálogos de dados abertos podem ser consultados facilmente com a ferramenta
Pandas, com ou sem Jupyter Notebook.
Esse tutorial inspirado na
demonstração
do Open Kn... | Python Code:
import pandas as pd
# Para trabalhar com Frictionless Data – frictionlessdata.io
from tableschema import Storage
from datapackage import Package
# Para visualização
import plotly_express as px
import plotly as py, plotly.graph_objects as go
Explanation: Como usar com o Pandas
Os catálogos de dados abertos ... |
7,110 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
build a neural network to predict the magnitude of an Earthquake given the date, time, Latitude, and Longitude as features. This is the dataset. Optimize at least 1 hyperparameter using Rand... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
df = pd.read_csv("data/earthquake-database.csv")
print(df.shape)
df.head()
Explanation: build a neural network to predict the magnitude of an Earthquake given the date, time, Latitude, and Longitude as features. This ... |
7,111 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to the TensorFlow computation graph
When I started with deep learning, one of the concepts that took me quite a while to wrap my head around was the use of a computation graph w... | Python Code:
import tensorflow as tf
assert tf.__version__=="1.2.0" # we want that version
Explanation: Introduction to the TensorFlow computation graph
When I started with deep learning, one of the concepts that took me quite a while to wrap my head around was the use of a computation graph within code. Furthermore, ... |
7,112 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Masking and padding with Keras
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Introduction... | 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... |
7,113 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This is the notebook for the python pandas dataframe course
The idea of this notebook is to show the power of working with pandas dataframes
Motivation
We usually work with tabular data
We s... | Python Code:
# Import libraries
import pandas as pd
import numpy as np
Explanation: This is the notebook for the python pandas dataframe course
The idea of this notebook is to show the power of working with pandas dataframes
Motivation
We usually work with tabular data
We should not handle them with bash commands like:... |
7,114 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Computing various MNE solutions
This example shows example fixed- and free-orientation source localizations
produced by MNE, dSPM, sLORETA, and eLORETA.
Step1: Fixed orientation
First let's... | Python Code:
# Author: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne.datasets import sample
from mne.minimum_norm import make_inverse_operator, apply_inverse
print(__doc__)
data_path = sample.data_path()
subjects_dir = data_path + '/subjects'
# Read data
fname_evoked = data_path ... |
7,115 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting started in scikit-learn with the famous iris dataset
From the video series
Step1: Machine learning on the iris dataset
Framed as a supervised learning problem
Step2: Machine learni... | Python Code:
from IPython.display import IFrame
IFrame('http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data', width=300, height=200)
Explanation: Getting started in scikit-learn with the famous iris dataset
From the video series: Introduction to machine learning with scikit-learn
Agenda
What is the ... |
7,116 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy Exercise 3
Imports
Step2: Geometric Brownian motion
Here is a function that produces standard Brownian motion using NumPy. This is also known as a Wiener Process.
Step3: Call the bro... | Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import antipackage
import github.ellisonbg.misc.vizarray as va
Explanation: Numpy Exercise 3
Imports
End of explanation
def brownian(maxt, n):
Return one realization of a Brownian (Wiener) process with n steps a... |
7,117 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hydropy-package
Step1: We have a Dataframe with river discharge at different locations in the Maarkebeek basin (Belgium)
Step2: Data downloaded from http
Step3: Converting the dataframe t... | Python Code:
#Loading the hydropy package
import hydropy as hp
Explanation: Hydropy-package
End of explanation
HTML('<iframe src=http://biomath.ugent.be/~stvhoey/maarkebeek_data/ width=700 height=350></iframe>')
Explanation: We have a Dataframe with river discharge at different locations in the Maarkebeek basin (Belgiu... |
7,118 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this exercise, you will use your new knowledge to propose a solution to a real-world scenario. To succeed, you will need to import data into Python, answer questions using the data, and ... | Python Code:
import pandas as pd
pd.plotting.register_matplotlib_converters()
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
print("Setup Complete")
Explanation: In this exercise, you will use your new knowledge to propose a solution to a real-world scenario. To succeed, you will need to impo... |
7,119 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transliteration
Transliteration is the conversion of a text from one script to another.
For instance, a Latin transliteration of the Greek phrase "Ελληνική Δημοκρατία", usually translated as... | Python Code:
from polyglot.transliteration import Transliterator
Explanation: Transliteration
Transliteration is the conversion of a text from one script to another.
For instance, a Latin transliteration of the Greek phrase "Ελληνική Δημοκρατία", usually translated as 'Hellenic Republic', is "Ellēnikḗ Dēmokratía".
End ... |
7,120 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modeling the X-ray image data
In this notebook, we'll take a closer look at the X-ray image data products, and build a simple generative model for the observed data.
Step1: A closer look at... | Python Code:
import astropy.io.fits as pyfits
import astropy.visualization as viz
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 10.0)
Explanation: Modeling the X-ray image data
In this notebook, we'll take a closer look at the X-ray image data products, an... |
7,121 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic reading and visualization of radar data with Py-ART
Introduction to Jupyter
What you are looking at is a Jupyter Notebook, a web-based interactive computation enviroment well suited fo... | Python Code:
# This is a Python comment
# the next line is a line of Python code
print("Hello World!")
Explanation: Basic reading and visualization of radar data with Py-ART
Introduction to Jupyter
What you are looking at is a Jupyter Notebook, a web-based interactive computation enviroment well suited for creating and... |
7,122 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classifying Images using Dropout and Batchnorm Layer
Introduction
In this notebook, you learn how to build a neural network to classify the tf-flowers dataset using dropout and batchnorm lay... | Python Code:
import tensorflow as tf
print(tf.version.VERSION)
Explanation: Classifying Images using Dropout and Batchnorm Layer
Introduction
In this notebook, you learn how to build a neural network to classify the tf-flowers dataset using dropout and batchnorm layer.
Learning objectives
Define Helper Functions.
Apply... |
7,123 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Prediction
For investors it's interesting to know which characteristics of a loan are predictive of a loan ending in charged off. Lending club has its own algorithms beforehand that they use... | Python Code:
loans = pd.read_csv('../data/loan.csv')
closed_loans = loans[loans['loan_status'].isin(['Fully Paid', 'Charged Off'])]
print(closed_loans.shape)
round(sum(closed_loans['loan_status']=='Charged Off')/len(closed_loans['loan_status'])*100)
Explanation: Prediction
For investors it's interesting to know which c... |
7,124 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The basic imports and the variables we'll be using
Step1: Examples and tests
Step2: Sympy can be a little tricky because it caches things, which means that the first implementation of this... | Python Code:
from __future__ import division
import sympy
from sympy import *
from sympy import Rational as frac
import simpletensors
from simpletensors import Vector, TensorProduct, SymmetricTensorProduct, Tensor
init_printing()
var('vartheta, varphi')
var('nu, m, delta, c, t')
# These are related scalar functions of ... |
7,125 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Resumen de NLTK
Step2: Gramáticas Independientes del Contexto (CFG)
Noam Chmosky definió una jerarquía de lenguajes y gramáticas que se utiliza habitualmente en Lingüística e Informática pa... | Python Code:
from __future__ import print_function
from __future__ import division
import nltk
Explanation: Resumen de NLTK: Análisis sintáctico
Este resumen se corresponde con el capítulo 8 del NLTK Book Analyzing Sentence Structure. La lectura del capítulo es muy recomendable.
En este resumen vamos a repasar cómo cre... |
7,126 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute ICA on MEG data and remove artifacts
ICA is fit to MEG raw data.
The sources matching the ECG and EOG are automatically found and displayed.
Subsequently, artifact detection and reje... | Python Code:
# Authors: Denis Engemann <denis.engemann@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne.preprocessing import ICA
from mne.preprocessing import create_ecg_epochs, create_eog_epochs
from mne.datasets impor... |
7,127 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CUSTOMER CHURN
Credits
Step1: We'll be keeping the statistical model pretty simple for this example so the feature space is almost unchanged from what you see above. The following code simp... | Python Code:
from __future__ import division
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import json
from sklearn.cross_validation import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.cross_validation import train_test_split
from sklearn.svm import SVC
from sklearn.ensem... |
7,128 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example jupyter_spark notebook
This is an example notebook to demonstrate the jupyter_spark notebook plugin.
It is based on the approximating pi example in the pyspark documentation. This w... | Python Code:
import sys
from random import random
from operator import add
from pyspark.sql import SparkSession
Explanation: Example jupyter_spark notebook
This is an example notebook to demonstrate the jupyter_spark notebook plugin.
It is based on the approximating pi example in the pyspark documentation. This works ... |
7,129 | Given the following text description, write Python code to implement the functionality described.
Description:
Everyone knows Fibonacci sequence, it was studied deeply by mathematicians in
the last couple centuries. However, what people don't know is Tribonacci sequence.
Tribonacci sequence is defined by the r... | Python Code:
def tri(n):
if n == 0:
return [1]
my_tri = [1, 3]
for i in range(2, n + 1):
if i % 2 == 0:
my_tri.append(i / 2 + 1)
else:
my_tri.append(my_tri[i - 1] + my_tri[i - 2] + (i + 3) / 2)
return my_tri |
7,130 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
RCM modeling with varying reactor volume
This example is available as an ipynb (Jupyter Notebook) file in the main GitHub repository at https
Step1: Next, we have to load the ChemKED file a... | Python Code:
import cantera as ct
import numpy as np
from pyked import ChemKED
Explanation: RCM modeling with varying reactor volume
This example is available as an ipynb (Jupyter Notebook) file in the main GitHub repository at https://github.com/pr-omethe-us/PyKED/blob/master/docs/rcm-example.ipynb
The ChemKED file th... |
7,131 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction au Streaming adaptatif
Luc Trudeau
Au menu
Step1: Llama Drama Low (1920x1080)
256 kbits/secondes
Step2: Llama Drama Medium (1920x1080)
512 kbits/secondes
Step3: Llama Drama H... | Python Code:
!ffmpeg -i LlamaDrama.mp4 -movflags faststart -b:v 256000 -maxrate 256000 -x264opts "fps=24:keyint=48:min-keyint=48:no-scenecut" -hls_list_size 0 -hls_time 4 -hls_base_url http://192.168.3.14:8000/low/ low/LlamaDrama.m3u8
Explanation: Introduction au Streaming adaptatif
Luc Trudeau
Au menu:
Implémentation ... |
7,132 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image classification with Convolutional Neural Networks
Welcome to the first week of the second deep learning certificate! We're going to use convolutional neural networks (CNNs) to allow ou... | Python Code:
# Put these at the top of every notebook, to get automatic reloading and inline plotting
%reload_ext autoreload
%autoreload 2
%matplotlib inline
Explanation: Image classification with Convolutional Neural Networks
Welcome to the first week of the second deep learning certificate! We're going to use convolu... |
7,133 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Get the data
2MASS => J, H K, angular resolution ~4"
WISE => 3.4, 4.6, 12, and 22 μm (W1, W2, W3, W4) with an angular resolution of 6.1", 6.4", 6.5", & 12.0"
GALEX imaging => Five imaging s... | Python Code:
#obj = ["3C 454.3", 343.49062, 16.14821, 1.0]
obj = ["PKS J0006-0623", 1.55789, -6.39315, 1.0]
#obj = ["M87", 187.705930, 12.391123, 1.0]
#### name, ra, dec, radius of cone
obj_name = obj[0]
obj_ra = obj[1]
obj_dec = obj[2]
cone_radius = obj[3]
obj_coord = coordinates.SkyCoord(ra=obj_ra, dec=obj_dec, u... |
7,134 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DAT210x - Programming with Python for DS
Module3 - Lab1
Step1: Load up the wheat seeds dataset into a dataframe. We've stored a copy in the Datasets directory.
Step2: Create a slice from y... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
# Look pretty...
# matplotlib.style.use('ggplot')
plt.style.use('ggplot')
Explanation: DAT210x - Programming with Python for DS
Module3 - Lab1
End of explanation
# .. your code here ..
Explanation: Load up the wheat seeds dataset into a ... |
7,135 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 1.1 Trim sequence to multiples of three characters
Write a function trim(s) that trims the sequence s (which is a Seq object) to a multiple of three characters so that its translati... | Python Code:
def trim(s):
# implement this function
pass
# test case
import Bio.Seq as BS
s = BS.Seq("ACGCGGCGTG")
print(s, "has length", len(s))
# write a piece of code here which will
# print the translated sequence 'TRR'
# without any errors
Explanation: Exercise 1.1 Trim sequence to multiples of three chara... |
7,136 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Since the annotation channel of this data is somewhat suspect, I decided to load some alternate annoation files to compare
Interestingly, the labels are exactly 3 times the z span of the p1 ... | Python Code:
def otsuVox(argVox):
probVox = np.nan_to_num(argVox)
bianVox = np.zeros_like(probVox)
for zIndex, curSlice in enumerate(probVox):
#if the array contains all the same values
if np.max(curSlice) == np.min(curSlice):
#otsu thresh will fail here, leave bianVox as all 0's... |
7,137 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Libraries
Step1: NOTE
Step2: Analysis
RASLseqAnalysis_STAR
Step3: Demultiplexing and Aligning FASTQ Reads
Step4: SUMMARY REPORT | Python Code:
import pandas as pd
import os, sys, time, random
import numpy as np
from scipy import stats
sys.path.append('../')
from RASLseqTools import *
sys.path.append('../RASLseqTools')
import RASLseqAnalysis_STAR
import seaborn
%pylab inline
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
Explana... |
7,138 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
So in numpy arrays there is the built in function for getting the diagonal indices, but I can't seem to figure out how to get the diagonal ending at bottom left rather than botton r... | Problem:
import numpy as np
a = np.array([[ 0, 1, 2, 3, 4, 5],
[ 5, 6, 7, 8, 9, 10],
[10, 11, 12, 13, 14, 15],
[15, 16, 17, 18, 19, 20],
[20, 21, 22, 23, 24, 25]])
dim = min(a.shape)
b = a[:dim,:dim]
result = np.vstack((np.diag(b), np.diag(np.fliplr(b)))) |
7,139 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sigma to Pressure Interpolation
By using metpy.calc.log_interp, data with sigma as the vertical coordinate can be
interpolated to isobaric coordinates.
Step1: Data
The data for this example... | Python Code:
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
from netCDF4 import Dataset, num2date
from metpy.cbook import get_test_data
from metpy.interpolate import log_interpolate_1d
from metpy.plots import add_metpy_logo, add_timestamp
from metpy.units import units
Expl... |
7,140 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple charts in pandas
In this session, we're gonna revisit our MLB data to rock a quick chart in pandas. Our goal
Step1: Let Jupyter know that you're gonna be charting inline
(Don't worry... | Python Code:
# import a ticker formatting class from matplotlib
Explanation: Simple charts in pandas
In this session, we're gonna revisit our MLB data to rock a quick chart in pandas. Our goal: A horizontal bar chart of the top 10 teams by payroll.
Import pandas and a some chart formatting help
End of explanation
# cre... |
7,141 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Function definitions and some other parameters
Step1: Load a mean pulse profile for B1957+20, and fit a gaussian to the main pulse
Step2: Isolate the main pulse, sqrt it, and center
Step3:... | Python Code:
res = 10000 # 1 sample is 1/res*1.6ms, 1e7 to resolve 311Mhz
n = 40 * res # grid size, total time
n = n-1 # To get the wave periodicity edge effects to work out
#freq = 311.25 # MHz, observed band
freq = 0.5 # Test, easier on computation
p_spin = 1.6 # ms, spin period
freq *= 1e6 #MHz to Hz
p_spin *= 1e-3 ... |
7,142 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example implementation of the ESU subgraph enumeration algorithm in python
Load the packages that we will need
Step1: Set the random number seed to 1337
Step2: Define the extend_subgraph f... | Python Code:
import igraph
import random
import collections
Explanation: Example implementation of the ESU subgraph enumeration algorithm in python
Load the packages that we will need
End of explanation
def exclusive_neighborhood(graph, v, Vp):
assert type(graph)==igraph.Graph
assert type(v)==int
assert typ... |
7,143 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Giới thiệu
Trong notebook này, mình sẽ trình bày cách giải quyết đề tài tuyển dụng của VinID. Mô hình CNN được sử dụng để phân loại 10 số viết tay trong bộ MNIST. Trong notebook này,bao g... | Python Code:
!pip install hyperas
# Basic compuational libaries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import seaborn as sns
%matplotlib inline
np.random.seed(2)
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_ma... |
7,144 | Given the following text description, write Python code to implement the functionality described.
Description:
Program to find the smallest element among three elements
Python implementation to find the smallest of three elements
| Python Code:
a , b , c = 5 , 7 , 10
if(a <= b and a <= c ) :
print(a , "is ▁ the ▁ smallest ")
elif(b <= a and b <= c ) :
print(b , "is ▁ the ▁ smallest ")
else :
print(c , "is ▁ the ▁ smallest ")
|
7,145 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: Testing the Numerial Gradient
This notebook explores the assess the differences and validity in calculating the spectral slope using finite differences or np.gradient().
In Figueira e... | Python Code:
import matplotlib
matplotlib.rcParams["text.usetex"] = False
matplotlib.rcParams["text.latex.unicode"] = True
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
from eniric.utilities import load_aces_spectrum
# from eniric.precision import slope, slope_grad
def slope(wavelength, flux):
... |
7,146 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ensemble of Decision Trees
By Parijat Mazumdar (GitHub ID
Step1: Next, we decide the parameters of our Random Forest.
Step2: In the above code snippet, we decided to create a forest using ... | Python Code:
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../../data')
import shogun as sg
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
def load_file(feat_file,label_file):
feats=sg.create_features(sg.read_csv(feat_file))
labels=sg.create_labels(sg.read_csv(label_file))... |
7,147 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step1: We define the model, adapted from the Keras CIFAR-10 example
Step2: We train the model us... | Python Code:
import tensorflow as tf
# Check that GPU is available: cf. https://colab.research.google.com/notebooks/gpu.ipynb
assert(tf.test.is_gpu_available())
tf.keras.backend.clear_session()
tf.config.optimizer.set_jit(False) # Start with XLA disabled.
def load_data():
(x_train, y_train), (x_test, y_test) = tf.ker... |
7,148 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: tf.data を使ったテキストの読み込み
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 例 1
Step3: train/csharp、t... | 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... |
7,149 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Φ<sub>Flow</sub> Math
The phi.math module provides abstract access to tensor operations.
It internally uses NumPy/SciPy, TensorFlow or PyTorch to execute the actual operations, depending on ... | Python Code:
from phi import math
Explanation: Φ<sub>Flow</sub> Math
The phi.math module provides abstract access to tensor operations.
It internally uses NumPy/SciPy, TensorFlow or PyTorch to execute the actual operations, depending on which backend is selected (see below).
This ensures that code written against phi.m... |
7,150 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Number of papers over time
data source
We load the data from the Competence Centre for Bibliometrics
Step1: set parameter
Step24: load data from SQL database
Step25: merging data
Step26: ... | Python Code:
import cx_Oracle #ensure that OS, InstantClient (Basic, ODBC, SDK) and cx_Oracle are all 64 bit. Install with "pip install cx_Oracle". Add link to InstantClient in Path variable!
import pandas as pd
import re
import plotly.plotly as py
import plotly.graph_objs as go
Explanation: Number of papers over time
... |
7,151 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
syncID
Step1: First we will define the extents of the rectangular array containing the section from each BRDF flightline.
Step2: Next we will define the coordinates of the target of intere... | Python Code:
import h5py
import csv
import numpy as np
import os
import gdal
import matplotlib.pyplot as plt
import sys
from math import floor
import time
import warnings
warnings.filterwarnings('ignore')
def h5refl2array(h5_filename):
hdf5_file = h5py.File(h5_filename,'r')
#Get the site name
file_attrs_str... |
7,152 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Index - Back - Next
Widget List
Step1: Numeric widgets
There are many widgets distributed with IPython that are designed to display numeric values. Widgets exist for displaying integers an... | Python Code:
import ipywidgets as widgets
Explanation: Index - Back - Next
Widget List
End of explanation
widgets.IntSlider(
value=7,
min=0,
max=10,
step=1,
description='Test:',
disabled=False,
continuous_update=False,
orientation='horizontal',
readout=True,
readout_format='d'
)
... |
7,153 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Decision Tree of Observable Operators
Part 3
Step1: ...by emitting all of the items emitted by corresponding Observables
flat_map(flat_map)
Step2: flat_map_latest(select_switch)
Step3: ... | Python Code:
reset_start_time(O.map, title='map') # alias is "select"
# warming up:
d = subs(O.from_((1, 2 , 3)).map(lambda x: x * 2))
rst(O.pluck, title='pluck')
d = subs(O.from_([{'x': 1, 'y': 2}, {'x': 3, 'y': 4}]).pluck('y'))
class Coord:
def __init__(self, x, y):
self.x = x
self.y = y
rst(titl... |
7,154 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Solving the HJB
The HJB equation, is used in dynamic programming to solve optimisation problem. Optimisation problems occur in all walks of life and some can even be solved. And some of thos... | Python Code:
import numpy as np
import time
import matplotlib.pyplot as plt
Explanation: Solving the HJB
The HJB equation, is used in dynamic programming to solve optimisation problem. Optimisation problems occur in all walks of life and some can even be solved. And some of those that can be solved are best solved with... |
7,155 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Working with Graphs using Networkx Intro
When creating a graph object, it can either be empty (default) or you can pass data as an argument. The data can take multiple forms
Step1: Notice t... | Python Code:
# isntantiate a graph object
G = nx.Graph()
# add a single node
G.add_node(1)
# add multiple nodes from a list
G.add_nodes_from([2,3,5])
# return lists of nodes and edges in the graph
G.nodes(), G.edges()
Explanation: Working with Graphs using Networkx Intro
When creating a graph object, it can either be e... |
7,156 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ATM 623
Step1: Contents
The ice ages
Introducing the astronomical theory of the ice ages
Ellipses and orbits
Past orbital variations
Using climlab to calculate insolation for arbitrary orbi... | Python Code:
# Ensure compatibility with Python 2 and 3
from __future__ import print_function, division
Explanation: ATM 623: Climate Modeling
Brian E. J. Rose, University at Albany
Lecture 16: Orbital variations, insolation, and the ice ages
Warning: content out of date and not maintained
You really should be looking... |
7,157 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Random forest regression example
As an experiment, we'll look at a dataset uniquely well suited to modeling with random forest regression.
Step1: Generate fake data
Step2: The target varia... | Python Code:
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import r2_score
import matplotlib.pyplot as plt
Explanation: Random forest regression example
As an experiment, we'll look at a dataset uniquely well suited to modeling with random forest regressi... |
7,158 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent neural network that performs sentiment analysis. Using an RNN rather than a feedfoward network is more accurate ... | Python Code:
import numpy as np
import tensorflow as tf
with open('../sentiment-network/reviews.txt', 'r') as f:
reviews = f.read()
with open('../sentiment-network/labels.txt', 'r') as f:
labels_orig = f.read()
reviews[:2000]
Explanation: Sentiment Analysis with an RNN
In this notebook, you'll implement a recur... |
7,159 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Logistic Regression
cf. sklearn.linear_model.LogisticRegression documentation
Let's take a look at the examples in the LogisticRegression documentation of sklearn.
The Logistic Regression ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model, datasets
# import some data to play with
iris = datasets.load_iris()
X = iris.data[:, :2] # take the first two features. # EY : 20160503 type(X) is numpy.ndarray
Y = iris.target # EY : 20160503 type(Y) is numpy.ndarray
h ... |
7,160 | 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... |
7,161 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Filter Design Using the Helper Modules
The Scipy package signal assists with the design of many digital filter types. As an alternative, here we explore the use of the filter design modules ... | Python Code:
Image('300ppi/FIR_Lowpass_Highpass_Bandpass_Bandstop@300ppi.png',width='90%')
Explanation: Filter Design Using the Helper Modules
The Scipy package signal assists with the design of many digital filter types. As an alternative, here we explore the use of the filter design modules found in scikit-dsp-comm
(... |
7,162 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
When we cannot afford to sample the quantity of interest many times at every design within an optimization, we can use surrogate models instead. Here we will show you how to use third party ... | Python Code:
from horsetailmatching import HorsetailMatching, UniformParameter
from horsetailmatching.demoproblems import TP2
from horsetailmatching.surrogates import PolySurrogate
import numpy as np
uparams = [UniformParameter(), UniformParameter()]
Explanation: When we cannot afford to sample the quantity of interest... |
7,163 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Note that job 2 has not executed because it is waiting for job 4, which has not run yet
Step3: Here is how to make a dependency queue with pool
We have to sleep a lot in this script to allo... | Python Code:
queue.put([jon, 'done', None])
myjobs = update_jobs(myjobs, outqueue)
myjobs
runner.is_alive()
outqueue.empty()
myjobs = update_jobs(myjobs, outqueue)
myjobs
Explanation: Note that job 2 has not executed because it is waiting for job 4, which has not run yet
End of explanation
def job_runner(cores, jobqueu... |
7,164 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Программирование на Python
Дзен Python
Step1: Красивое лучше, чем уродливое.<br>
Явное лучше, чем неявное.<br>
Простое лучше, чем сложное.<br>
Сложное лучше, чем запутанное.<br>
Плоское луч... | Python Code:
%pylab inline
import this
Explanation: Программирование на Python
Дзен Python
End of explanation
import numpy as np
np.array([1,2,3])
a = np.array([[1,2,3], [4,5,6]])
a = np.array([1,2,3])
b = np.array([4,5,6])
a+b
a*b
a/b
a**b
Explanation: Красивое лучше, чем уродливое.<br>
Явное лучше, чем неявное.<br>
П... |
7,165 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Text Analysis with NLTK
Author
Step1: 1. Corpus acquisition.
In these notebooks we will explore some tools for text analysis and two topic modeling algorithms available from Python toolboxe... | Python Code:
# %matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# import pylab
# Required imports
from wikitools import wiki
from wikitools import category
import nltk
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
from time import ... |
7,166 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Review from the previous lecture
In yesterday's Lecture 2, you learned how to use the numpy module, how to make your own functions, and how to import and export data. Below is a quick review... | Python Code:
import numpy as np
Explanation: Review from the previous lecture
In yesterday's Lecture 2, you learned how to use the numpy module, how to make your own functions, and how to import and export data. Below is a quick review before we move on to Lecture 3.
Remember, to use the numpy module, first it must be ... |
7,167 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 Google LLC
Licensed under the Apache License, Version 2.0 (the "License")
Step1: Retrain a classification model for Edge TPU using post-training quantization (with TF2)
In th... | Python Code:
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distribute... |
7,168 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Python basics
This chapter only gives a short introduction to Python to make the explanations in the following chapters more understandable. A detailed description would be too extensive ... | Python Code:
print('Hello World')
Explanation: 1. Python basics
This chapter only gives a short introduction to Python to make the explanations in the following chapters more understandable. A detailed description would be too extensive and would go beyond the scope of this tutorial. Take a look at https://docs.python.... |
7,169 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
=====================================================================
Spectro-temporal receptive field (STRF) estimation on continuous data
==================================================... | Python Code:
# Authors: Chris Holdgraf <choldgraf@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.decoding import ReceptiveField, TimeDelayingRidge
from scipy.stats import multivariate_normal
from scipy.io imp... |
7,170 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>CAR Classic predictor - Regressor</h1>
<hr style="border
Step1: <span>
Build a processor.
</span>
<br>
<span>
This is required by the regressor in order to parse the input raw data.<br>... | Python Code:
import sys
#sys.path.insert(0, 'I:/git/att/src/python/')
sys.path.insert(0, 'i:/dev/workspaces/python/att-workspace/att/src/python/')
Explanation: <h1>CAR Classic predictor - Regressor</h1>
<hr style="border: 1px solid #000;">
<span>
<h2>ATT hit predictor.</h2>
</span>
<br>
<span>
This notebook shows how t... |
7,171 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vision data
Helper functions to get data in a DataLoaders in the vision application and higher class ImageDataLoaders
The main classes defined in this module are ImageDataLoaders and Segment... | Python Code:
#|export
@delegates(subplots)
def get_grid(
n:int, # Number of axes in the returned grid
nrows:int=None, # Number of rows in the returned grid, defaulting to `int(math.sqrt(n))`
ncols:int=None, # Number of columns in the returned grid, defaulting to `ceil(n/rows)`
figsize:tuple=None, # Wid... |
7,172 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 8
Step1: Why was an a returned instead of b?
Computer scientists (and much of Europe) count starting with 0
These sequence are referred to as zero-based
The bracket notation only ac... | Python Code:
fruit = 'banana'
letter = fruit[1]
print( letter )
Explanation: Chapter 8: Strings
Contents
- A string is a sequence
- The len operator
- Traversal with a for loop
- String slices
- Strings are immutable
- Searching
- String methods
- The in operator
- String comparison
- Debugging
- Exercises
This noteboo... |
7,173 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using lambdify for plotting expressions
The syntethic isotope Technetium-99m is used in medical diagnostics (scintigraphy)
Step1: now we need to determine the integration constants from the... | Python Code:
import sympy as sym
sym.init_printing()
symbs = t, l1, l2, x0, y0, z0 = sym.symbols('t lambda_1 lambda_2 x0 y0 z0', real=True, nonnegative=True)
funcs = x, y, z = [sym.Function(s)(t) for s in 'xyz']
inits = [f.subs(t, 0) for f in funcs]
diffs = [f.diff(t) for f in funcs]
exprs = -l1*x, l1*x - l2*y, l2*y
eq... |
7,174 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Following the tutorial at
Step1: Accessing Data
You can access DataFrame data using familiar Python dict/list operations
Step2: Manipulating Data
You may apply Python's basic arithmetic op... | Python Code:
import pandas as pd
# There are two data structures in pandas, Series and DataFrames
city_names = pd.Series(['San Francisco', 'San Jose', 'Sacramento'])
population = pd.Series([852469, 1015785, 485199])
pd.DataFrame({"City Name": city_names, "Population": population})
# importing an existing csv file into ... |
7,175 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Google form analysis tests
Table of Contents
'Google form analysis' functions checks
Google form loading
Selection of a question
Selection of a user's answers
checking answers
comparison of ... | Python Code:
%run "../Functions/1. Google form analysis.ipynb"
# Localplayerguids of users who answered the questionnaire (see below).
# French
#localplayerguid = 'a4d4b030-9117-4331-ba48-90dc05a7e65a'
#localplayerguid = 'd6826fd9-a6fc-4046-b974-68e50576183f'
#localplayerguid = 'deb089c0-9be3-4b75-9b27-28963c77b10c'
#l... |
7,176 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting sentiment from product reviews
Fire up GraphLab Create
Step1: Read some product review data
Loading reviews for a set of baby products.
Step2: Let's explore this data together
D... | Python Code:
import graphlab
Explanation: Predicting sentiment from product reviews
Fire up GraphLab Create
End of explanation
products = graphlab.SFrame('amazon_baby.gl/')
Explanation: Read some product review data
Loading reviews for a set of baby products.
End of explanation
products.head()
Explanation: Let's explor... |
7,177 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Training Keras model on Cloud AI Platform</h1>
This notebook illustrates distributed training and hyperparameter tuning on Cloud AI Platform (formerly known as Cloud ML Engine). This use... | Python Code:
# change these to try this notebook out
BUCKET = 'cloud-training-demos-ml'
PROJECT = 'cloud-training-demos'
REGION = 'us-central1'
import os
os.environ['BUCKET'] = BUCKET
os.environ['PROJECT'] = PROJECT
os.environ['REGION'] = REGION
os.environ['TFVERSION'] = '2.0' # not used in this notebook
%%bash
gcloud... |
7,178 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
k-Nearest Neighbor (kNN) exercise
Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For ... | Python Code:
import sys
print(sys.version)
# Run some setup code for this notebook.
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
# This is a bit of magic to make matplotlib figures appear inline in the notebook
# rather than in a new window.
%matplotlib inl... |
7,179 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Particle Swarm Optimization Algorithm (in Python!)
[SPOILER] We will be using the Particle Swarm Optimization algorithm to obtain the minumum of a customed objective function
First of all, l... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
# import scipy as sp
# import time
%matplotlib inline
plt.style.use('bmh')
Explanation: Particle Swarm Optimization Algorithm (in Python!)
[SPOILER] We will be using the Particle Swarm Optimization algorithm to obtain the minumum of a customed objective fu... |
7,180 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Quantum Approximate Optimization Algorithm for MAX-CUT
The following is a step-by-step guide to running QAOA on the MaxCut problem. In the debue paper on QAOA (arXiv
Step1: The cost Ha... | Python Code:
import pyquil.forest as qvm_module
import numpy as np
from grove.pyqaoa.maxcut_qaoa import maxcut_qaoa
barbell = [(0, 1)] # graph is a defined by a list of edges. Edge weights are assumed to be 1.0
steps = 1 # evolution path length between the ref hamiltonian and cost hamiltonian
inst = maxcut_qaoa(barb... |
7,181 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Distributed Deep Learning with Apache Spark and Keras
Joeri Hermans (Technical Student, IT-DB-SAS, CERN)
Departement of Knowledge Engineering
Maastricht University, The Net... | Python Code:
!(date +%d\ %B\ %G)
Explanation: Distributed Deep Learning with Apache Spark and Keras
Joeri Hermans (Technical Student, IT-DB-SAS, CERN)
Departement of Knowledge Engineering
Maastricht University, The Netherlands
End of explanation
import numpy as np
import time
import requests
from kera... |
7,182 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Question 1
Step1: Motivations
The problem we try to solve in the question 1 is evaluating the average causal effect of the "treatment" represented by the job training program.
A naive anal... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from scipy import optimize
from scipy import spatial
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
sns.set(rc={"figure.figsize": (15, 6)})
sns.set_palette(sns.color_palette("Set2", 10))
lalon... |
7,183 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook is intended to show how to use pandas, and sql alchemy to upload data into DB2-switch and create geospatial coordinate and indexes.
Install using pip or any other package manag... | Python Code:
import pandas as pd
from sqlalchemy import create_engine
Explanation: This notebook is intended to show how to use pandas, and sql alchemy to upload data into DB2-switch and create geospatial coordinate and indexes.
Install using pip or any other package manager pandas, sqlalchemy and pg8000. The later one... |
7,184 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Funciones y expresiones booleanas
El paquete sympy tiene un módulo de lógica. Con él podemos hacer algunas simplificaciones
Step1: Definimos los símbolos que vamos a utilizar. Supremo e ínf... | Python Code:
from sympy import *
Explanation: Funciones y expresiones booleanas
El paquete sympy tiene un módulo de lógica. Con él podemos hacer algunas simplificaciones
End of explanation
x, y, z = symbols("x,y,z")
p = (x | y) & ~ z
pprint(p)
Explanation: Definimos los símbolos que vamos a utilizar. Supremo e ínfimo s... |
7,185 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Lea
Step1: Summary
Random variables are abstract objects. Transparent method for drawing random samples variable.random(times). Standard statistical metrics of the probabil... | Python Code:
from lea import *
# mandatory die example - initilize a die object
die = Lea.fromVals(1, 2, 3, 4, 5, 6)
# throw the die a few times
die.random(20)
# mandatory coin toss example - states can be strings!
coin = Lea.fromVals('Head', 'Tail')
# toss the coin a few times
coin.random(10)
# how about a Boolean var... |
7,186 | 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', 'mpi-m', 'mpi-esm-1-2-lr', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: MPI-M
Source ID: MPI-ESM-1-2-LR
Topic: Ocnbgchem
Sub-Topics: Tr... |
7,187 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I am trying to find duplicates rows in a pandas dataframe. | Problem:
import pandas as pd
df=pd.DataFrame(data=[[1,2],[3,4],[1,2],[1,4],[1,2]],columns=['col1','col2'])
def g(df):
df['index_original'] = df.groupby(['col1', 'col2']).col1.transform('idxmin')
return df[df.duplicated(subset=['col1', 'col2'], keep='first')]
result = g(df.copy()) |
7,188 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Wilson-Devinney Style Meshing
NOTE
Step1: As always, let's do imports and initialize a logger and a new bundle. See Building a System for more details.
Step2: Changing Meshing Options
Nex... | Python Code:
!pip install -I "phoebe>=2.1,<2.2"
%matplotlib inline
Explanation: Wilson-Devinney Style Meshing
NOTE: Wilson-Devinney Style meshing requires developer mode in PHOEBE and is meant to be used for testing, not used for science.
Setup
Let's first make sure we have the latest version of PHOEBE 2.1 installed. (... |
7,189 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
We're going to simulate data discretely sampled in time. We need to set a sample rate in Hz. The highest resolvable frequency, the Nyquist frequency, is half the sample rate. We also need to... | Python Code:
sample_rate = 4096
nyquist = sample_rate/2
time_length_seconds = 512
Explanation: We're going to simulate data discretely sampled in time. We need to set a sample rate in Hz. The highest resolvable frequency, the Nyquist frequency, is half the sample rate. We also need to decide how long the simulated data... |
7,190 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Statistics of Stable
Step2: Property Occurence
Step3: Success Ratio of Properties (Normalized)
Step4: Success Ratio by unit
Step5: Failure Ratio does not depend on #props
Step6: ... | Python Code:
import json, re, pprint, os, datetime
import pandas as pd
import numpy as np
import matplotlib
pltsettings = {
"figure.figsize" : (5.0, 4.0),
"pgf.texsystem" : "pdflatex",
"font.family": "sans",
"font.serif": [], # use latex default serif font
#"font.sans-serif": ["Dej... |
7,191 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Earth Engine and TensorFlow in Cloud Datalab
This notebook walks you through a simple example of using Earth Engine and TensorFlow together in Cloud Datalab.
Specifically, we... | Python Code:
import ee
from IPython import display
import math
from matplotlib import pyplot
import numpy
from osgeo import gdal
import tempfile
import tensorflow as tf
import urllib
import zipfile
Explanation: Introduction to Earth Engine and TensorFlow in Cloud Datalab
This notebook walks you through a simple example... |
7,192 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Benchmarking Python Clustering Algorithms on 2D Data
Other notebooks perform a more genenral analysis of clustering algorithms; this notebook is looking at the special case of two dimensiona... | Python Code:
import hdbscan
import debacl
import fastcluster
import sklearn.cluster
import scipy.cluster
import sklearn.datasets
import numpy as np
import pandas as pd
import time
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
sns.set_context('poster')
sns.set_palette('Paired', 10)
sns.set_col... |
7,193 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyBroom Example - Multiple Datasets - Minimize
This notebook is part of pybroom.
This notebook demonstrate using pybroom when performing Maximum-Likelihood fitting
(scalar minimization as op... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format='retina' # for hi-dpi displays
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.pylab import normpdf
import seaborn as sns
from lmfit import Model
import lmfit
print('lmfit: %s' % lmfit.__version__)
sns.set_style(... |
7,194 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exogenous Variables with PyAF
PyAF allows using some external sources to improve its forecasts.
In addition to the training dataset, the user can provide an external table with exogenous va... | Python Code:
import numpy as np
import pandas as pd
import datetime
csvfile_link = "https://raw.githubusercontent.com/antoinecarme/pyaf/master/data/ozone-la-exogenous-2.csv"
exog_dataframe = pd.read_csv(csvfile_link);
exog_dataframe['Date'] = exog_dataframe['Date'].astype(np.datetime64);
print(exog_dataframe.info())
ex... |
7,195 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Continuing from the previous blog post, this notebook will explain how to deploy a Bokeh server on Heroku, allowing the world to access the brilliant data visualizations that you've develope... | Python Code:
python-3.6.1
Explanation: Continuing from the previous blog post, this notebook will explain how to deploy a Bokeh server on Heroku, allowing the world to access the brilliant data visualizations that you've developed using Bokeh. Note- this tutorial was written in May 2017. If you're reading at a much lat... |
7,196 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examining racial discrimination in the US job market
Background
Racial discrimination continues to be pervasive in cultures throughout the world. Researchers examined the level of racial dis... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
from IPython.core.display import HTML
css = open('style-table.css').read() + open('style-notebook.css').read()
HTML('<style>{}</style>'.forma... |
7,197 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load up some example data. This is a little 28 residue peptide
Step1: md.baker_hubbard idenfies hydrogen bonds baced on cutoffs
for the Donor-H...Acceptor distance and angle. The criterion ... | Python Code:
t = md.load_pdb('http://www.rcsb.org/pdb/files/2EQQ.pdb')
print(t)
Explanation: Load up some example data. This is a little 28 residue peptide
End of explanation
hbonds = md.baker_hubbard(t, periodic=False)
label = lambda hbond : '%s -- %s' % (t.topology.atom(hbond[0]), t.topology.atom(hbond[2]))
for hbond... |
7,198 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Summarizing Images
Images are high dimensional objects
Step1: How Many Photons Came From the Cluster?
Let's estimate the total counts due to the cluster.
That means we need to somehow ignor... | Python Code:
import astropy.io.fits as pyfits
import numpy as np
import astropy.visualization as viz
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 10.0)
targdir = 'a1835_xmm/'
imagefile = targdir+'P0098010101M2U009IMAGE_3000.FTZ'
expmapfile = targdir+'P0098010101M2U009EXPMA... |
7,199 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Detecting Twitter Bots
Step1: Exploratory Data Analysis
Identifying Missingness in the data
Step2: Identifying Imbalance in the data
Step3: Feature Independence using Spearman correlation... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rcParams['patch.force_edgecolor'] = True
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")
%matplotlib inline
filepath = 'https://raw.githubusercontent.com/jubins/ML-TwitterBotDetection... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.