Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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4,800 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kernel Density Estimation
by Parijat Mazumdar (GitHub ID
Step1: Now, we will apply KDE to estimate the actual pdf using the samples. Using KDE in Shogun is a 3 stage process
Step2: We hav... | Python Code:
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
%matplotlib inline
import os
import shogun as sg
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
# generates samples from the distribution
def generate_samples(n_samples,mu1,sigma1,mu2,sigma2):
samples1 = np.ra... |
4,801 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Examples Rankine Cycle 8.1,8.2
Michael J. Moran, Howard N. Shapiro, Daisie D. Boettner, Margaret B. Bailey. Fundamentals of Engineering Thermodynamics(7th Edition). John Wiley & Sons, I... | Python Code:
from seuif97 import *
# State 1
p1 = 8.0 # in MPa
t1 = px2t(p1, 1)
h1 = px2h(p1, 1) # h1 = 2758.0 From table A-3 kj/kg
s1 = px2s(p1, 1) # s1 = 5.7432 From table A-3 kj/kg.k
# State 2 ,p2=0.008
p2 = 0.008
s2 = s1
t2 = ps2t(p2, s2)
h2 = ps2h(p2, s2)
# State 3 is saturated liquid ... |
4,802 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting the outcome of a US presidential election using Bayesian optimal experimental design
In this tutorial, we explore the use of optimal experimental design techniques to create an op... | Python Code:
# Data path
BASE_URL = "https://d2hg8soec8ck9v.cloudfront.net/datasets/us_elections/"
import pandas as pd
import torch
from urllib.request import urlopen
electoral_college_votes = pd.read_pickle(urlopen(BASE_URL + "electoral_college_votes.pickle"))
print(electoral_college_votes.head())
ec_votes_tensor = t... |
4,803 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SpaCy
Step1: Let's start out with a short string from our reading and see what happens.
Step2: We've downloaded the English model, and now we just have to load it. This model will do every... | Python Code:
from datascience import *
import spacy
Explanation: SpaCy: Industrial-Strength NLP
The tradtional NLP library has always been NLTK. While NLTK is still very useful for linguistics analysis and exporation, spacy has become a nice option for easy and fast implementation of the NLP pipeline. What's the NLP pi... |
4,804 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmos
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'ncc', 'sandbox-3', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: NCC
Source ID: SANDBOX-3
Topic: Atmos
Sub-Topics: Dynamical Core, Radiation, T... |
4,805 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transect
Groupby and transform allow me to combine rows into a single 'transect' row.
Or, use a multiIndex, a hierarchical index, so I can target specific cells using id and type. The index ... | Python Code:
%matplotlib inline
import sys
import numpy as np
import pandas as pd
import json
import matplotlib.pyplot as plt
from io import StringIO
print(sys.version)
print("Pandas:", pd.__version__)
df = pd.read_csv('C:/Users/Peter/Documents/atlas/atlasdata/obs_types/transect.csv', parse_dates=['date'])
df = df.asty... |
4,806 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Here I test the idea of binary, or very discrete, coding in an adaption of Larry Abbott's FORCE learning [0].
I want to make sense of a world where the neural code is binary [6... | Python Code:
import pylab as plt
import numpy as np
%matplotlib inline
from __future__ import division
from scipy.integrate import odeint,ode
from numpy import zeros,ones,eye,tanh,dot,outer,sqrt,linspace,cos,pi,hstack,zeros_like,abs,repeat
from numpy.random import uniform,normal,choice
%config InlineBackend.figure_form... |
4,807 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An overview of feature engineering for regression and machine learning algorithms
Step1: A simple example to illustrate the intuition behind dummy variables
Step2: Now we have a matrix of ... | Python Code:
import pandas as pd
%matplotlib inline
Explanation: An overview of feature engineering for regression and machine learning algorithms
End of explanation
df = pd.DataFrame({'key':['b','b','a','c','a','b'],'data1':range(6)})
df
pd.get_dummies(df['key'],prefix='key')
Explanation: A simple example to illustrat... |
4,808 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Physicist's Crash Course on Artificial Neural Network
What is a Neuron
What a neuron does is to response when a stimulation is given. This response could be strong or weak or even null. If... | Python Code:
import numpy as np
print np.linspace(0,9,10), np.exp(-np.linspace(0,9,10))
Explanation: A Physicist's Crash Course on Artificial Neural Network
What is a Neuron
What a neuron does is to response when a stimulation is given. This response could be strong or weak or even null. If I would draw a figure, of th... |
4,809 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An interactive introduction to Noodles
Step1: Now we can create a workflow composing several calls to this function.
Step2: That looks easy enough; the funny thing is though, that nothing ... | Python Code:
from noodles import schedule
@schedule
def add(x, y):
return x + y
@schedule
def mul(x,y):
return x * y
Explanation: An interactive introduction to Noodles: translating Poetry
Noodles is there to make your life easier, in parallel! The reason why Noodles can be easy and do parallel Python at the sa... |
4,810 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Compare shapes of molecules
Step1: We'd like to compare the shape of heroin with other molecules.
ODDT supports three methods of molecular shape comparison
Step2: To compute the shape ... | Python Code:
from __future__ import print_function, division, unicode_literals
import oddt
from oddt.shape import usr, usr_similarity
print(oddt.__version__)
Explanation: <h1>Compare shapes of molecules
End of explanation
heroin = oddt.toolkit.readstring('smi',
'CC(=O)Oc1ccc2c3c1O[C@@H]4[C@]35CC[NH+]([C@H](C2)[C@@... |
4,811 | 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', 'bnu', 'sandbox-3', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: BNU
Source ID: SANDBOX-3
Topic: Ocean
Sub-Topics: Timestepping Framework, Adve... |
4,812 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building your Deep Neural Network
Step2: 2 - Outline of the Assignment
To build your neural network, you will be implementing several "helper functions". These helper functions will be used... | Python Code:
import numpy as np
import h5py
import matplotlib.pyplot as plt
from testCases import *
from dnn_utils import sigmoid, sigmoid_backward, relu, relu_backward
%matplotlib inline
plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams... |
4,813 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The Google Research Authors.
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 ... | Python Code:
# Installs additional packages
import pip
import IPython
def import_or_install(package):
try:
__import__(package)
except ImportError:
pip.main(['install', package])
app = IPython.Application.instance()
app.kernel.do_shutdown(True)
import_or_install('lightg... |
4,814 | 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', 'nims-kma', 'sandbox-2', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: NIMS-KMA
Source ID: SANDBOX-2
Topic: Land
Sub-Topics: Soil, Snow, Vegetatio... |
4,815 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Polyglot Unconference
This notebook holds a project conducting data analysis and visualization of the 2017 Polyglot Vancouver Un-Conference.
See the README in this repository for background ... | Python Code:
# Imports
import sys
import pandas as pd
import csv
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (20.0, 10.0)
# %load util.py
#!/usr/bin/python
# Util file to import in all of the notebooks to allow for easy code re-use
# Calculate Percent of Attendees that did not sp... |
4,816 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Greatest Common Divisor
Now, the greatest common divisor (GCD) is the largest natural number $d$ that divides $a$ and $b$ in a fraction $\frac{a}{b}$ without a remainder.
For example, the G... | Python Code:
def naive_gcd(a, b):
gcd = 0
if a < b:
n = a
else:
n = a
for d in range(1, n + 1):
if not a % d and not b % d:
gcd = d
return gcd
print('In: 1/1,', 'Out:', naive_gcd(1, 1))
print('In: 1/2,', 'Out:', naive_gcd(1, 2))
print('In: 3/9,', 'Out:', naive_gcd... |
4,817 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Combine an MLP with a GP
Modified from
https
Step1: Data
Step2: Deep kernel
We transform the (1d) input using an MLP and then pass it to a Matern kernel.
Step3: Shallow kernel | Python Code:
%%capture
import os
try:
from tinygp import kernels, transforms, GaussianProcess
except ModuleNotFoundError:
%pip install -qq tinygp
from tinygp import kernels, transforms, GaussianProcess
try:
import flax.linen as nn
except ModuleNotFoundError:
%pip install -qq flax
import flax.lin... |
4,818 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Load blast hits
Step1: 2. Process blastp results
2.1 Extract ORF stats from fasta file
Step2: 2.2 Annotate blast hits with orf stats
Step3: 2.3 Extract best hit for each ORF ( q_cov > ... | Python Code:
#Load blast hits
blastp_hits = pd.read_csv("2_blastp_hits.csv")
blastp_hits.head()
#Filter out Metahit 2010 hits, keep only Metahit 2014
blastp_hits = blastp_hits[blastp_hits.db != "metahit_pep"]
Explanation: 1. Load blast hits
End of explanation
#Assumes the Fasta file comes with the header format of EMBO... |
4,819 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Partial Differential Equations of Groundwater Flow
How to interpret the equations
If you are mathematically minded, then the groundwater flow equation by itself give you a really good feel f... | Python Code:
%matplotlib inline
'''
This is a function to calculate the gradient at a point in a long line
of points. You feed it coordinates (X), values (H) and - optional -
boundary conditions. It returns the gradient.
'''
def gradx(X, H, leftbc=None, rightbc=None):
size = len(H)
gradP = z... |
4,820 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python Visualization Landscape
Step1: Note
Using cleaned data from Data Cleaning Notebook. See Notebook for details.
Step2: BQPlot
Examples here are shamelessly stolen from the amazing
Ste... | Python Code:
from IPython.lib.display import YouTubeVideo
YouTubeVideo("FytuB8nFHPQ", width=400, height=300)
from __future__ import absolute_import, division, print_function
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_context('poster')
sns.set_style('whitegrid')
# sns.set_style('da... |
4,821 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Logistic Regression Using TF 2.0
Learning Objectives
Build a model,
Train this model on example data, and
Use the model to make predictions about unknown data.
Introduction
I... | Python Code:
import os
import matplotlib.pyplot as plt
import tensorflow as tf
print(f"TensorFlow version: {tf.__version__}")
print(f"Eager execution: {tf.executing_eagerly()}")
Explanation: Introduction to Logistic Regression Using TF 2.0
Learning Objectives
Build a model,
Train this model on example data, and
Use the... |
4,822 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Aggregation (via pymongo)
Step1: Do An Aggregation
Basic process to convert pipelines from a JavaScript array to a Python list
Convert all comments (from "//" to "#")
Title-case all true/fa... | Python Code:
# import pymongo
from pymongo import MongoClient
from pprint import pprint
# Create client
client = MongoClient('mongodb://localhost:32768')
# Connect to database
db = client['fifa']
# Get collection
my_collection = db['player']
Explanation: Aggregation (via pymongo)
End of explanation
def print_docs(pipel... |
4,823 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: In this notebook, we will use LSTM layers to develop time series forecasting models.
The dataset used for the examples of this notebook is on air pollution measured by concentration o... | Python Code:
from __future__ import print_function
import os
import sys
import pandas as pd
import numpy as np
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
import datetime
#set current working directory
os.chdir('D:/Practical Time Series')
#Read the dataset into a pandas.DataFrame
df = ... |
4,824 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
For the testing we will use a standard DSI acqusition scheme with 514 gradient directions and 1 S0. There's also the alternative of having a scheme with 4195 directions. In the case of the s... | Python Code:
btable = np.loadtxt(get_data('dsi515btable'))
#btable = np.loadtxt(get_data('dsi4169btable'))
gtab['test'] = gradient_table(btable[:, 0], btable[:, 1:],
big_delta=gtab['train'].big_delta, small_delta=gtab['train'].small_delta)
gtab['test'].info
Explanation: For the testing we ... |
4,825 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Duffing Oscillator Solution Using Frequency Domain Residuals
This notebook uses the newer solver. This solver minimizes frequency domain error. hb_freq can also ignore the constant term ($\o... | Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import scipy as sp
import numpy as np
import matplotlib.pyplot as plt
import mousai as ms
from scipy import pi, sin
# Test that all is working.
# f_tol adjusts accuracy. This is smaller than reasonable, but illustrative of usage.
t, x, e, amps, phases... |
4,826 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Looking at KIC 8462852 (Boyajian's star) with gPhoton
Using the time-tagged photon data from GALEX, available with gPhoton, lets make some light curves of "Tabby's Star"
Step1: Searching fo... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib
from gPhoton import gFind
from gPhoton import gAperture
from gPhoton import gMap
from gPhoton.gphoton_utils import read_lc
import datetime
from astropy.time import Time
fro... |
4,827 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Project
Step1: Step 1
Step2: Total number of columns is 14 + 1 target
Step3: Step 2
Step4: Step 3
Step5: Logistic Regression
Step6: KNN
Step7: Random Forest
Step8: Naive Bayes
Step9:... | Python Code:
# imports
import pandas as pd
import dateutil.parser
from sklearn import preprocessing
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import BernoulliNB
from sklearn.naive_bayes import GaussianNB
from sklearn.naive_bayes imp... |
4,828 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Calculate Coupling Coefficients
Two split rings are placed in a broadside coupled configuration. The scalar model of each resonator is augmented by additional coefficients representing the c... | Python Code:
# setup 2D and 3D plotting
%matplotlib inline
from openmodes.ipython import matplotlib_defaults
matplotlib_defaults()
import matplotlib.pyplot as plt
import numpy as np
import os.path as osp
import openmodes
from openmodes.constants import c, eta_0
from openmodes.model import EfieModelMutualWeight
from op... |
4,829 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Работа 2.4. Определение вязкости воздуха по скорости течения через тонкие трубки
Цель работы
Step1: Первые 7 точек укладываются на прямую, оставшиеся нет. Значит, примерно при $Q = 10^{-4}~... | Python Code:
import pandas
PQn = pandas.read_excel('lab-2-3.xlsx', 't-1')
PQn.head(len(PQn))
x = PQn.values[:, 6] / 3600
y = PQn.values[:, 8]
dx = PQn.values[:, 7] / 3600
dy = PQn.values[:, 9]
xl = x[:7]
yl = y[:7]
import numpy
k, b = numpy.polyfit(xl, yl, deg=1)
grid = numpy.linspace(0.04 / 3600, 0.0001)
import matplo... |
4,830 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 2
Step1: Visualize data
Step2: Interactive pandas Dataframe
Using qgrid it is possible to modify the tables in place as following
Step3: Grid and potential field
We can see the po... | Python Code:
# Importing
import theano.tensor as T
import sys, os
sys.path.append("../GeMpy")
# Importing GeMpy modules
import GeMpy
# Reloading (only for development purposes)
import importlib
importlib.reload(GeMpy)
# Usuful packages
import numpy as np
import pandas as pn
import matplotlib.pyplot as plt
# This was to... |
4,831 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Baseline is static, a straight line for each input - Test
Step1: Baseline is static, a straight line for each input - Train (small)
Step2: Baseline is static, a straight line for each inpu... | Python Code:
bltest = MyBaseline(npz_path=npz_test)
bltest.getMSE()
bltest.renderMSEs()
plt.show()
bltest.getHuberLoss()
bltest.renderHuberLosses()
plt.show()
%%time
bltest.get_dtw()
bltest.renderRandomTargetVsPrediction()
plt.show()
Explanation: Baseline is static, a straight line for each input - Test
End of explanat... |
4,832 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Challenge of processing large amounts of data
<ul>
<li>How to process is quickly?
<li>So how do we go about making the problem map so that it can be distributed computation?
<li> Distributed... | Python Code:
def cube(x): return x*x*x
map(cube,range(1,11))
Explanation: Challenge of processing large amounts of data
<ul>
<li>How to process is quickly?
<li>So how do we go about making the problem map so that it can be distributed computation?
<li> Distributed/Parrallel Programming is hard
</ul>
Mapreduce addresses... |
4,833 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
KeplerLightCurveCelerite.ipynb
‹ KeplerLightCurve.ipynb › Copyright (C) ‹ 2017 › ‹ Anna Scaife - anna.scaife@manchester.ac.uk ›
This program is free software
Step1: Import some libraries
St... | Python Code:
%matplotlib inline
Explanation: KeplerLightCurveCelerite.ipynb
‹ KeplerLightCurve.ipynb › Copyright (C) ‹ 2017 › ‹ Anna Scaife - anna.scaife@manchester.ac.uk ›
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free ... |
4,834 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I am having a problem with minimization procedure. Actually, I could not create a correct objective function for my problem. | Problem:
import scipy.optimize
import numpy as np
np.random.seed(42)
a = np.random.rand(3,5)
x_true = np.array([10, 13, 5, 8, 40])
y = a.dot(x_true ** 2)
x0 = np.array([2, 3, 1, 4, 20])
def residual_ans(x, a, y):
s = ((y - a.dot(x**2))**2).sum()
return s
out = scipy.optimize.minimize(residual_ans, x0=x0, args=(... |
4,835 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Inference
Step1: The uniform prior, $U\sim(a, b)$, here with $a=-10$ and $b=15$. When this function is called, its log density is returned.
Step2: To plot the density, we take the exponent... | Python Code:
import pints
import numpy as np
import matplotlib.pyplot as plt
Explanation: Inference: Log priors
This example notebook illustrates some of the functionality that is available for LogPrior objects that are currently available within PINTS.
End of explanation
uniform_log_prior = pints.UniformLogPrior(-10, ... |
4,836 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python data types
Python can be a little strange in providing lots of data types, dynamic type allocation, and some interconversion.
Numbers
Integers, Floating point numbers, and complex nu... | Python Code:
f = 1.0
i = 1
print f, i
print
print "Value of f is {}, value of i is {}".format(f,i)
print
print "Value of f is {:f}, value of i is {:f}".format(f,i)
## BUT !!
print "Value of f is {:d}, value of i is {:f}".format(f,i)
c = 0.0 + 1.0j
print c
print "Value of c is {:f}".format(c)
print "Value of c**2 is ... |
4,837 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Save this file as studentid1_studentid2_lab#.ipynb
(Your student-id is the number shown on your student card.)
E.g. if you work with 3 people, the notebook should be named
Step1: Lab 1
Step... | Python Code:
NAME = "Laura Ruis"
NAME2 = "Fredie Haver"
NAME3 = "Lukás Jelínek"
EMAIL = "lauraruis@live.nl"
EMAIL2 = "frediehaver@hotmail.com"
EMAIL3 = "lukas.jelinek1@gmail.com"
Explanation: Save this file as studentid1_studentid2_lab#.ipynb
(Your student-id is the number shown on your student card.)
E.g. if you work ... |
4,838 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Demonstration of accessing lepton information
Import what we need from Matplotlib and ROOT
Step1: Create a "chain" of files (but just one file for now)
Step2: This is how we plotted the pT... | Python Code:
import pylab
import matplotlib.pyplot as plt
%matplotlib inline
pylab.rcParams['figure.figsize'] = 12,8
from ROOT import TChain
Explanation: Demonstration of accessing lepton information
Import what we need from Matplotlib and ROOT:
End of explanation
data = TChain("mini"); # "mini" is the name of the TTr... |
4,839 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I am trying to find col duplicates rows in a pandas dataframe. | Problem:
import pandas as pd
df=pd.DataFrame(data=[[1,1,2,5],[1,3,4,1],[4,1,2,5],[5,1,4,9],[1,1,2,5]],columns=['val', 'col1','col2','3col'])
def g(df):
cols = list(df.filter(like='col'))
df['index_original'] = df.groupby(cols)[cols[0]].transform('idxmin')
return df[df.duplicated(subset=cols, keep='first')]
... |
4,840 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation
Trois exercices pour manipuler les donner, manipulation de texte, données vélib.
Step1: Données
Les don... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation
Trois exercices pour manipuler les donner, manipulation de texte, données vélib.
End of explanation
from pyensae.datasource import download_data... |
4,841 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preprocessing
Step2: Training LeNet
First, we will train a simple CNN with a single hidden fully connected layer as a classifier.
Step3: Training Random Forests
Preprocessing to a fixed si... | Python Code:
import os
from skimage import io
from skimage.color import rgb2gray
from skimage import transform
from math import ceil
IMGSIZE = (100, 100)
def load_images(folder, scalefactor=(2, 2), labeldict=None):
images = []
labels = []
files = os.listdir(folder)
for file in (fname for fname in ... |
4,842 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Look at the hourly data
Now on to the real challenge, the hourly data. So, as usual, make some plots, do a bit of anaalysis and try to get a feel for the data.
Remaining TO DO
Step1: It's q... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
hourly = pd.read_csv('Bike-Sharing-Dataset/hour.csv',header = 0)
hourly.head(20)
type(hourly)
for row_index, row in hourly.iterrows():
print row_index , row['registered']
if (row_index > 5):
brea... |
4,843 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Principal Components Analysis on the UCI Image Segmentation Data Set.
Kevin Maher
<span style="color
Step1: Read in the data. Extra header rows in the UCI data file were manually deleted u... | Python Code:
%matplotlib inline
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn import decomposition
from sklearn import metrics
Explanation: Princip... |
4,844 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Install dependencies
Step2: Clone, compile and set up Tesseract
Step3: Grab some things to scrape the RIA corpus
Step4: Scrape the RIA corpus
Step5: Get the raw co... | Python Code:
!wget https://github.com/jimregan/tesseract-gle-uncial/releases/download/v0.1beta2/gle_uncial.traineddata
Explanation: <a href="https://colab.research.google.com/github/jimregan/tesseract-gle-uncial/blob/master/Update_gle_uncial_traineddata_for_Tesseract_4.ipynb" target="_parent"><img src="https://colab.re... |
4,845 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
← Back to Index
Spectral Features
For classification, we're going to be using new features in our arsenal
Step1: librosa.feature.spectral_bandwidth
librosa.feature.spectral_bandwidth
S... | Python Code:
x, fs = librosa.load('simple_loop.wav')
IPython.display.Audio(x, rate=fs)
spectral_centroids = librosa.feature.spectral_centroid(x, sr=fs)
plt.plot(spectral_centroids[0])
Explanation: ← Back to Index
Spectral Features
For classification, we're going to be using new features in our arsenal: spectral mo... |
4,846 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Make decision tree from iris data
Taken from Google's Visualizing a Decision Tree - Machine Learning Recipes #2
Step1: Tensorflow
Examples from http
Step3: Custom model with TensorFlowEsti... | Python Code:
import tensorflow.contrib.learn as skflow
from sklearn.datasets import load_iris
from sklearn import metrics
iris = load_iris()
iris.keys()
iris.feature_names
iris.target_names
# Withhold 3 for testing
test_idx = [0, 50, 100]
train_data = np.delete(iris.data, test_idx, axis=0)
train_target = np.delete(iris... |
4,847 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize Evoked data
In this tutorial we focus on the plotting functions of
Step1: First we read the evoked object from a file. Check out
tut_epoching_and_averaging to get to this stage f... | Python Code:
import os.path as op
import numpy as np
import matplotlib.pyplot as plt
import mne
# sphinx_gallery_thumbnail_number = 9
Explanation: Visualize Evoked data
In this tutorial we focus on the plotting functions of :class:mne.Evoked.
End of explanation
data_path = mne.datasets.sample.data_path()
fname = op.joi... |
4,848 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You can use LPVisu to visualize Integer Linear Programming problems in Jupyter notebooks. First import the LPVisu class
Step1: You can then define a problem
Step2: To draw the polygon, cre... | Python Code:
from lp_visu import LPVisu
Explanation: You can use LPVisu to visualize Integer Linear Programming problems in Jupyter notebooks. First import the LPVisu class:
End of explanation
# problem definition
A = [[1.0, 0.0], [1.0, 2.0], [2.0, 1.0]]
b = [8.0, 15.0, 18.0]
c = [-4.0, -3.0]
x1_bounds = (0, None)
x2_b... |
4,849 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This may be more readable on NBViewer.
Step1: As we saw earlier the Dirichlet process describes the distribution of a random probability distribution. The Dirichlet process takes two parame... | Python Code:
%matplotlib inline
Explanation: This may be more readable on NBViewer.
End of explanation
from numpy.random import choice
from scipy.stats import beta
class DirichletProcessSample():
def __init__(self, base_measure, alpha):
self.base_measure = base_measure
self.alpha = alpha
... |
4,850 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
House Prices Estimator
Note
Step1: Here we have to find the 'NaN' values and fill them with the mean. Probably it's not the best way to complete the info where we have empty values but at l... | Python Code:
import numpy as np
import pandas as pd
#load the files
train = pd.read_csv('input/train.csv')
test = pd.read_csv('input/test.csv')
data = pd.concat([train, test])
#size of training dataset
train_samples = train.shape[0]
test_samples = test.shape[0]
# remove the Id feature
data.drop(['Id'],1, inplace=True);... |
4,851 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Raw data structure
Step1: Loading continuous data
.. sidebar
Step2: As you can see above,
Step3: By default, the
Step4: Querying the Raw object
.. sidebar
Step5: <div class="alert... | Python Code:
import os
import numpy as np
import matplotlib.pyplot as plt
import mne
Explanation: The Raw data structure: continuous data
This tutorial covers the basics of working with raw EEG/MEG data in Python. It
introduces the :class:~mne.io.Raw data structure in detail, including how to
load, query, subselect, ex... |
4,852 | 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 の再帰型ニューラルネットワーク（RNN）
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: ビルトイン RNN レイヤー
Step3:... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
4,853 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting distributions
First, import relevant libraries
Step1: Then, load the data (takes a few moments)
Step2: The code below creates a calls-per-person frequency distribution, which is t... | Python Code:
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt
Explanation: Plotting distributions
First, import relevant libraries:
End of explanation
# Load data
uda = pd.read_csv("./aws-data/user_dist.txt", sep="\t") # User dis... |
4,854 | 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('./reviews.txt', 'r') as f:
reviews = f.read()
with open('./labels.txt', 'r') as f:
labels = f.read()
reviews[:2000]
Explanation: Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent neural network that performs sentiment... |
4,855 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Parser for Regular Expression
This notebook implements a parser for regular expressions. The parser that is implemented in the function parseExpr parses a regular expression
according to ... | Python Code:
import re
Explanation: A Parser for Regular Expression
This notebook implements a parser for regular expressions. The parser that is implemented in the function parseExpr parses a regular expression
according to the following <em style="color:blue">EBNF grammar</em>.
regExp -> product ('+' product)*
... |
4,856 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
IMDB Predictive Analytics
This notebook explores using data science techniques on a data set of 5000+ movies, and predicting whether a movie will be highly rated on IMDb.
The objective of th... | Python Code:
# data analysis and wrangling
import pandas as pd
import numpy as np
import random as rnd
from scipy.stats import truncnorm
# visualization
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
# machine learning
from sklearn.linear_model import LogisticRegression
from sklearn.svm import... |
4,857 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Receptive Field Estimation and Prediction
This example reproduces figures from Lalor et al's mTRF toolbox in
matlab
Step1: Load the data from the publication
First we will load the data co... | Python Code:
# Authors: Chris Holdgraf <choldgraf@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
# Nicolas Barascud <nicolas.barascud@ens.fr>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
from os.path import join
import mne
from mne.dec... |
4,858 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: TensorFlow 애드온 콜백
Step2: 데이터 가져오기 및 정규화
Step3: 간단한 MNIST CNN 모델 빌드하기
Step4: 간단한 TimeStopping 사용법 | 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... |
4,859 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Excercises Electric Machinery Fundamentals
Chapter 5
Problem 5-10
Step1: Description
A synchronous machine has a synchronous reactance of $1.0\,\Omega$ per phase and an armature resistance ... | Python Code:
%pylab notebook
Explanation: Excercises Electric Machinery Fundamentals
Chapter 5
Problem 5-10
End of explanation
Ea = 460 # [V]
EA_angle = -10/180*pi # [rad]
EA = Ea * (cos(EA_angle) + 1j*sin(EA_angle))
Vphi = 480 # [V]
VPhi_angle = 0/180*pi # [rad]
VPhi =... |
4,860 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Map
<script type="text/javascript">
localStorage.setItem('language', 'language-py')
</script>
<table align="left" style="margin-right
Step2: Examples
In the following... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License")
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this fi... |
4,861 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
North Atlantic Winter Weather Regimes from a Self-Organizing Map Perspective
The four weather regimes typically found over the North Atlantic in winter are identified as
* NAO+ (positive NAO... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import xarray as xr
import cartopy.crs as ccrs
from sompy.sompy import SOMFactory
Explanation: North Atlantic Winter Weather Regimes from a Self-Organizing Map Perspective
The four weather regimes typically found over the North Atlantic ... |
4,862 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify ... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nerc', 'sandbox-1', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: NERC
Source ID: SANDBOX-1
Topic: Seaice
Sub-Topics: Dynamics, Thermodynamic... |
4,863 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FloPy
MT3D-USGS Example
Demonstrates functionality of the flopy MT3D-USGS module using the 'Crank-Nicolson' example distributed with MT3D-USGS.
Problem description
Step1: Set up model dis... | Python Code:
%matplotlib inline
import sys
import os
import platform
import string
from io import StringIO, BytesIO
import math
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import flopy
print(sys.version)
print('numpy version: {}'.format(np.__version__))
print('matplotlib version: {}'.for... |
4,864 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
xarray with MetPy Tutorial
xarray <http
Step1: ...and opening some sample data to work with.
Step2: While xarray can handle a wide variety of n-dimensional data (essentially anything th... | Python Code:
import numpy as np
import xarray as xr
# Any import of metpy will activate the accessors
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.units import units
Explanation: xarray with MetPy Tutorial
xarray <http://xarray.pydata.org/>_ is a powerful Python package that provid... |
4,865 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing PHOEBE 2 vs PHOEBE Legacy
NOTE
Step1: As always, let's do imports and initialize a logger and a new bundle. See Building a System for more details.
Step2: Adding Datasets and Co... | Python Code:
!pip install -I "phoebe>=2.0,<2.1"
Explanation: Comparing PHOEBE 2 vs PHOEBE Legacy
NOTE: PHOEBE 1.0 legacy is an alternate backend and is not installed with PHOEBE 2.0. In order to run this backend, you'll need to have PHOEBE 1.0 installed.
Setup
Let's first make sure we have the latest version of PHOEBE... |
4,866 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clustered Multitask GP (w/ Pyro/GPyTorch High-Level Interface)
Introduction
In this example, we use the Pyro integration for a GP model with additional latent variables.
We are modelling a m... | Python Code:
import math
import torch
import pyro
import gpytorch
from matplotlib import pyplot as plt
%matplotlib inline
%load_ext autoreload
%autoreload 2
# this is for running the notebook in our testing framework
import os
smoke_test = ('CI' in os.environ)
Explanation: Clustered Multitask GP (w/ Pyro/GPyTorch High-... |
4,867 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Static tumbling neural network
Imports
Step1: Load and prepare the data
Import data from static tumbling csv file
Step2: Separate the data into features and targets
Step3: Generate global... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
import matplotlib.pyplot as plt
from itertools import product
Explanation: Static tumbling neural network
Imports
End... |
4,868 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using python's cartopy package to georeference EASE-Grid 2.0 cube data
This notebook demonstrates the following typical tasks you might want to do with CETB EASE-Grid 2.0 cube data
Step1: R... | Python Code:
%matplotlib notebook
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from netCDF4 import Dataset
import numpy as np
geod = ccrs.Geodetic()
e2n = ccrs.LambertAzimuthalEqualArea(central_latitude=90.0)
Explanation: Using python's cartopy package to georeference EASE-Grid 2.0 cube data
This notebook... |
4,869 | 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', 'nims-kma', 'sandbox-3', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: NIMS-KMA
Source ID: SANDBOX-3
Topic: Ocean
Sub-Topics: Timestepping Frame... |
4,870 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify ... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cmcc', 'sandbox-1', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: CMCC
Source ID: SANDBOX-1
Topic: Seaice
Sub-Topics: Dynamics, Thermodynamic... |
4,871 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Scraping Webpages with BeautifulSoup
Lets try to get a list of all the years of all of Amitabh Bachchan movies! If you don't know, he's kind of the Sean Connery of India.
BeautifulSoup lets... | Python Code:
import requests
r = requests.get('http://www.imdb.com/name/nm0000821') # lets look at Amitabh Bachchan's list of movies
Explanation: Scraping Webpages with BeautifulSoup
Lets try to get a list of all the years of all of Amitabh Bachchan movies! If you don't know, he's kind of the Sean Connery of India.
Be... |
4,872 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
use erosion operation first then dilation on the image
| Python Code::
import cv2
import numpy as np
%matplotlib notebook
%matplotlib inline
from matplotlib import pyplot as plt
img = cv2.imread("hsv_ball.jpg",cv2.IMREAD_GRAYSCALE)
_,mask = cv2.threshold(img, 220,255,cv2.THRESH_BINARY_INV)
kernal = np.ones((5,5),np.uint8)
dilation = cv2.dilate(mask,kernal,iterations = 3)
ero... |
4,873 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Repeated measures ANOVA on source data with spatio-temporal clustering
This example illustrates how to make use of the clustering functions
for arbitrary, self-defined contrasts beyond stand... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Eric Larson <larson.eric.d@gmail.com>
# Denis Engemannn <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
from numpy.random import randn
import matplotlib.pyplot as plt
i... |
4,874 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
20160110-etl-census-with-python
Related post
Step1: Globals
File sources
Step2: Extract, transform, and load
Data dictionary
Step4: PUMS data
Step5: PUMS estimates for user verification
... | Python Code:
cd ~
# Import standard packages.
import collections
import functools
import os
import pdb # Debug with pdb.
import subprocess
import sys
import time
# Import installed packages.
import numpy as np
import pandas as pd
# Import local packages.
# Insert current directory into module search path.
# Autoreload ... |
4,875 | 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: M-layer experiments
This notebook trains M-layers on the problems discussed in "Intelligent... | Python Code:
# Copyright 2020 The Google Research Authors.
#
# 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 la... |
4,876 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Structured data prediction using Vertex AI Platform
Learning Objectives
Create a BigQuery Dataset and Google Cloud Storage Bucket
Export from BigQuery to CSVs in GCS
Training on Cloud AI Pl... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
!pip install --user google-cloud-bigquery==2.26.0
Explanation: Structured data prediction using Vertex AI Platform
Learning Objectives
Create a BigQuery Dataset and Google Cloud Storage Bucket
Export from BigQuery to CSVs in GCS
Training o... |
4,877 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
One interesting question for open source communities is whether they are growing. Often the founding members of a community would like to see new participants join and become active in the c... | Python Code:
url = "6lo"
arx = Archive(url,archive_dir="../archives")
arx.data[:1]
Explanation: One interesting question for open source communities is whether they are growing. Often the founding members of a community would like to see new participants join and become active in the community. This is important for co... |
4,878 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
QuTiP example
Step1: Energy spectrum of three coupled qubits
Step2: Versions | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from numpy import pi
from qutip import *
Explanation: QuTiP example: Energy-levels of a quantum systems as a function of a single parameter
J.R. Johansson and P.D. Nation
For more information about QuTiP see http://qutip.org
End of expla... |
4,879 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to TensorFlow, now leveraging tensors!
In this notebook, we modify our intro to TensorFlow notebook to use tensors in place of our for loop. This is a derivation of Jared Ostmey... | Python Code:
import numpy as np
np.random.seed(42)
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import tensorflow as tf
tf.set_random_seed(42)
xs = [0., 1., 2., 3., 4., 5., 6., 7.]
ys = [-.82, -.94, -.12, .26, .39, .64, 1.02, 1.]
fig, ax = plt.subplots()
_ = ax.scatter(xs, ys)
m = tf.Variabl... |
4,880 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An Interactive Monty Hall Simulation
nbinteract was designed to make interactive explanations easy to create. In this tutorial, we will show the process of writing a simulation from scratch ... | Python Code:
from ipywidgets import interact
import numpy as np
import random
PRIZES = ['Car', 'Goat 1', 'Goat 2']
def monty_hall(example_num=0):
'''
Simulates one round of the Monty Hall Problem. Outputs a tuple of
(result if stay, result if switch, result behind opened door) where
each results is one ... |
4,881 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step5: Tutorial
Step6: 2. Harmonic Oscillator Example
In this first example we apply the GPFA to spike train data derived from dynamics of a harmonic oscillator defined in a 2-dimensional l... | Python Code:
import numpy as np
from scipy.integrate import odeint
import quantities as pq
import neo
from elephant.spike_train_generation import inhomogeneous_poisson_process
def integrated_oscillator(dt, num_steps, x0=0, y0=1, angular_frequency=2*np.pi*1e-3):
Parameters
----------
dt : float
... |
4,882 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute MNE inverse solution on evoked data in a mixed source space
Create a mixed source space and compute MNE inverse solution on evoked dataset.
Step1: Set up our source space.
Step2: E... | Python Code:
# Author: Annalisa Pascarella <a.pascarella@iac.cnr.it>
#
# License: BSD (3-clause)
import os.path as op
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample
from mne import setup_volume_source_space
from mne import make_forward_solution
from mne.minimum_norm import make_inverse_opera... |
4,883 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Jupyter Notebook -- это удобно!
Код организван отдельными болками. Блоки кода можно выполнять в произвольном порядке. Сочетает в себе достоинства полноценных скриптов и интерактивной оболочк... | Python Code:
print(math.sqrt(4))
import math
Explanation: Jupyter Notebook -- это удобно!
Код организван отдельными болками. Блоки кода можно выполнять в произвольном порядке. Сочетает в себе достоинства полноценных скриптов и интерактивной оболочки. Порядок выполнения блоков указан слева от ячейки.
End of explanation
... |
4,884 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analysis of Dataset Variance
Data which is collected differently, look differently. This principle extends to all data (that I can think of), and of course MRI is no exception. In the case o... | Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import nibabel as nb
import os
from histogram_window import histogram_windowing
Explanation: Analysis of Dataset Variance
Data which is collected differently, look differently. This principle extends to all data (that I can think of), an... |
4,885 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building operators
Step1: Looks like exactly what we wanted! We can even check that the anticommutation relation holds
Step2: It was instructive to build it ourselves, but dynamite actuall... | Python Code:
from dynamite.operators import sigmax, sigmay, sigmaz, index_product
# product of sigmaz along the spin chain up to index k
k = 4
index_product(sigmaz(), size=k)
# with that, we can easily build our operator
def majorana(i):
k = i//2
edge_op = sigmay(k) if (i%2) else sigmax(k)
bulk = index_prod... |
4,886 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Labels
We want to use the Radio Galaxy Zoo click data as training data. To do this, we first need to convert the raw click data to a useful label — most likely the $(x, y)$ coordinate ... | Python Code:
import collections
import operator
from pprint import pprint
import sqlite3
import sys
import warnings
import matplotlib.pyplot
import numpy
import scipy.stats
import sklearn.mixture
%matplotlib inline
sys.path.insert(1, '..')
import crowdastro.data
import crowdastro.show
warnings.simplefilter('ignore', Us... |
4,887 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Grouping all encounter nbrs under respective person nbr
Step1: Now grouping other measurements and properties under encounter_nbrs
Step2: Aggregating encounter entities under respective pe... | Python Code:
encounter_key = 'Enc_Nbr'
person_key = 'Person_Nbr'
encounters_by_person = {}
for df in dfs:
if df is not None:
df_columns =set(df.columns.values)
if encounter_key in df_columns and person_key in df_columns:
for row_index, dfrow in df.iterrows():
rowdict = di... |
4,888 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A count of the total number of mitochondria within the bounds (694×1794, 1750×2460, 1004×1379).
Step1: We can count annotated mitochondria by referencing the mitochondria channel
Step2: We... | Python Code:
import ndio.remote.OCP as OCP
oo = OCP()
token = "kasthuri2015_ramon_v1"
Explanation: A count of the total number of mitochondria within the bounds (694×1794, 1750×2460, 1004×1379).
End of explanation
mito_cutout = oo.get_cutout(token, 'mitochondria', 694, 1794, 1750, 2460, 1004, 1379, resolution=3)
Explan... |
4,889 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Retrieve HiC dataset from NCBI
We will use data from <a name="ref-1"/>(Stadhouders R, Vidal E, Serra F, Di Stefano B et al. 2018), which comes from mouse cells where Hi-C experiment where co... | Python Code:
%%bash
mkdir -p FASTQs
fastq-dump SRR5344921 --defline-seq '@$ac.$si' -X 100000000 --split-files --outdir FASTQs/
mv FASTQs/SRR5344921_1.fastq FASTQs/mouse_B_rep1_1.fastq
mv FASTQs/SRR5344921_2.fastq FASTQs/mouse_B_rep1_2.fastq
fastq-dump SRR5344925 --defline-seq '@$ac.$si' -X 100000000 --split-files --out... |
4,890 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about emb... | Python Code:
import time
import numpy as np
import tensorflow as tf
import utils
Explanation: Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about embedding words for use in natural lang... |
4,891 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Algebra Lineal con Python
Esta notebook fue creada originalmente como un blog post por Raúl E. López Briega en Mi blog sobre Python. El contenido esta bajo la licencia BSD.
<img alt="Algebra... | Python Code:
# Vector como lista de Python
v1 = [2, 4, 6]
v1
# Vectores con numpy
import numpy as np
v2 = np.ones(3) # vector de solo unos.
v2
v3 = np.array([1, 3, 5]) # pasando una lista a las arrays de numpy
v3
v4 = np.arange(1, 8) # utilizando la funcion arange de numpy
v4
Explanation: Algebra Lineal con Python
Esta... |
4,892 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Anna KaRNNa
In this notebook, I'll build a character-wise RNN trained on Anna Karenina, one of my all-time favorite books. It'll be able to generate new text based on the text from the book.... | Python Code:
import time
from collections import namedtuple
import numpy as np
import tensorflow as tf
Explanation: Anna KaRNNa
In this notebook, I'll build a character-wise RNN trained on Anna Karenina, one of my all-time favorite books. It'll be able to generate new text based on the text from the book.
This network ... |
4,893 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Plotting with Matplotlib
Matplotlib is a standard plotting package for python.
Autor
Step1: Import several modules which will be useful for doing plots.
Step2: Scatter Plot... | Python Code:
%matplotlib inline
Explanation: Introduction to Plotting with Matplotlib
Matplotlib is a standard plotting package for python.
Autor: George Privon
Preliminaries
Show plots in the notebook.
End of explanation
import matplotlib.pyplot as plt
import numpy as np
Explanation: Import several modules which will ... |
4,894 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h2>Analisi comparativa dei metodi di dosaggio degli anticorpi anti recettore del TSH</h2>
<h3>Metodo Routine
Step1: <h4>Importazione del file con i dati </h4>
Step2: Varibili d'ambiete in... | Python Code:
%matplotlib inline
#importo le librerie
import pandas as pd
import os
from __future__ import print_function,division
import numpy as np
import seaborn as sns
os.environ["NLS_LANG"] = "ITALIAN_ITALY.UTF8"
Explanation: <h2>Analisi comparativa dei metodi di dosaggio degli anticorpi anti recettore del TSH</h2>... |
4,895 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Logistic Regression (scikit-learn) Experiment Versioning & Registry
<a href="https
Step1: This example features
Step2: Phase 1
Step3: Prepare data
Step4: Prepare hyperparameters
Step5: ... | Python Code:
# restart your notebook if prompted on Colab
try:
import verta
except ImportError:
!pip install verta
Explanation: Logistic Regression (scikit-learn) Experiment Versioning & Registry
<a href="https://colab.research.google.com/github/VertaAI/modeldb/blob/master/client/workflows/demos/census-experime... |
4,896 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 2, part 1 (40 points)
This warm-up problem set is provided to help you get used to PyTorch.
Please, only fill parts marked with "Your code here".
Step1: To learn best practices $-$... | Python Code:
import numpy as np
import math
import matplotlib.pyplot as plt
%matplotlib inline
import torch
assert torch.__version__ >= '1.0.0'
import tqdm
Explanation: Homework 2, part 1 (40 points)
This warm-up problem set is provided to help you get used to PyTorch.
Please, only fill parts marked with "Your code her... |
4,897 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
VarData Speed Calculation Comparison
Notebook for calculation a VarData Test Case and have a Unit Number for Comparison
For more speed calculations see VarData Speed Calculations
Step1: Tes... | Python Code:
import math
import datetime
def varData_speedCalc_comparison(test_case, test_title, test_description, test_time=None, cups_speed=250.0, substrate_size_mm=None, substrate_size_px=None, dpi_image=[360.0,360.0]):
inch2mm = 25.4 # mm/inch
bpp = 4.0 # bit/px
if test_time == Non... |
4,898 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notes
Permuation matrices and graphs
$P$ obtained by permuting rows of an identity matrix. $N!$ possile permutations possible of an identity matrix. $PA$ permutes the $i^{th}$ row of A to $\... | Python Code:
from IPython.display import IFrame
IFrame("./projection_onto_bistochastic_matrices.pdf", width=800, height=500)
Explanation: Notes
Permuation matrices and graphs
$P$ obtained by permuting rows of an identity matrix. $N!$ possile permutations possible of an identity matrix. $PA$ permutes the $i^{th}$ row of... |
4,899 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sparse Linear Inverse Demo with AMP
In this demo, we illustrate how to use the vampyre package for a simple sparse linear inverse problem. The problem is to estimate a sparse vector z0 fro... | Python Code:
import os
import sys
vp_path = os.path.abspath('../../')
if not vp_path in sys.path:
sys.path.append(vp_path)
import vampyre as vp
Explanation: Sparse Linear Inverse Demo with AMP
In this demo, we illustrate how to use the vampyre package for a simple sparse linear inverse problem. The problem is to ... |
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