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1,400 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
QGrid
Interactive pandas dataframes
Step1: Github
https | Python Code:
df = pd.read_csv("../data/coal_prod_cleaned.csv")
df.head()
df.shape
df.columns
qgrid_widget = qgrid.show_grid(
df[["Year", "Mine_State", "Labor_Hours", "Production_short_tons"]],
show_toolbar=True,
)
qgrid_widget
df2 = df.groupby('Mine_State').sum()
df3 = df.groupby('Mine_State').sum()
df2.loc['Wy... |
1,401 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1"><a href="#Task-1.-Compiling-Ebola-Data"><span class="toc-item-num">Task 1. </span>Compiling Ebola Data</a></div>
<div class="lev1"><a href=... | Python Code:
# Imports
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import glob
import csv
import calendar
import webbrowser
from datetime import datetime
# Constants
DATA_FOLDER = 'Data/'
Explanation: Table of Contents
<p><div class="lev1"><a href="#Task-1.-Compiling-Ebola-... |
1,402 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 4 - Tensorflow ANN for regression
In this lab we will use Tensorflow to build an Artificial Neuron Network (ANN) for a regression task.
As opposed to the low-level implementation from th... | Python Code:
%matplotlib inline
import math
import random
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
import numpy as np
import tensorflow as tf
sns.set(style="ticks", color_codes=True)
Explanation: Lab 4 - Tensorflow ANN for regression
In this lab ... |
1,403 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Customizing IPython - Magics
IPython extends Python by adding shell-like commands called magics.
Step2: Defining your own magic
As we have seen already, IPython has cell and line magics. Yo... | Python Code:
%lsmagic
import numpy
%timeit A=numpy.random.random((1000,1000))
%%timeit -n 1
A=numpy.random.random((1000,1000))
b = A.sum()
Explanation: Customizing IPython - Magics
IPython extends Python by adding shell-like commands called magics.
End of explanation
ip = get_ipython()
import time
def sleep_magic(line)... |
1,404 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy Exercise 1
Imports
Step2: Checkerboard
Write a Python function that creates a square (size,size) 2d Numpy array with the values 0.0 and 1.0
Step3: Use vizarray to visualize a checker... | 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 1
Imports
End of explanation
def checkerboard(size):
Return a 2d checkboard of 0.0 and 1.0 as a NumPy array
check = ... |
1,405 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Keras for Text Classification
Learning Objectives
1. Learn how to create a text classification datasets using BigQuery
1. Learn how to tokenize and integerize a corpus of text for training i... | Python Code:
import os
from google.cloud import bigquery
import pandas as pd
%load_ext google.cloud.bigquery
Explanation: Keras for Text Classification
Learning Objectives
1. Learn how to create a text classification datasets using BigQuery
1. Learn how to tokenize and integerize a corpus of text for training in Keras
... |
1,406 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Text mining
In this task we will use nltk package to recognize named entities and classify in a given text (in this case article about American Revolution from Wikipedia).
nltk.ne_chunk func... | Python Code:
import nltk
import numpy as np
import wikipedia
import re
Explanation: Text mining
In this task we will use nltk package to recognize named entities and classify in a given text (in this case article about American Revolution from Wikipedia).
nltk.ne_chunk function can be used for both recognition and clas... |
1,407 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Jupyter/IPython Notebook Quick Start Guide
The following is partially taken from the offical documentation
Step1: This is an equation formatted in LaTeX $y = \sin(x)$
double-click this cell... | Python Code:
# press Shit+Enter to execute this cell
print('This is a cell containing python code')
#we can also make figures
import matplotlib.pyplot as plt
import numpy as np
% matplotlib inline
x = np.linspace(-np.pi, np.pi, 100)
plt.plot(x, np.sin(x))
# Use `Tab` for completion and `Shift-Tab` for code info
Explana... |
1,408 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Parameters
Step3: Colab-only auth
Step4: tf.data.Dataset
Step5: Let's have a look at the data
Step6: Estimator model
If you are not sure what cross-entropy, dropou... | Python Code:
import os, re, math, json, shutil, pprint, datetime
import PIL.Image, PIL.ImageFont, PIL.ImageDraw
import numpy as np
import tensorflow as tf
from matplotlib import pyplot as plt
from tensorflow.python.platform import tf_logging
print("Tensorflow version " + tf.__version__)
Explanation: <a href="https://co... |
1,409 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How the Length of a Jeopardy Question Relates to its Value?
The American television game show Jeopardy is probably one of the most famous shows ever aired on TV. Few years ago IBM's Watson c... | Python Code:
# this line is required to see visualizations inline for Jupyter notebook
%matplotlib inline
# importing modules that we need for analysis
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import re
# read the data from file and print out first few rows
jeopardy = pd.read_csv("jeopardy... |
1,410 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Questions/Concerns
=======================================
Was/how was the main parachute bag held down for LV2?
How many lines were cut during LV2 recovery?
What if the drogue gets cut away... | Python Code:
# General
########################################
# Gravity (m/sec^2)
g = 9.81
# Air density (kg/m^3)
p = 1.225
# LV2 given information
#######################################
print ("LV2 Given Information\n")
# Mass of parachute (kg)
# From OpenRocket LV2.3.ork
m_p2 = 2.118
# Mass of system (rocket + chu... |
1,411 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overview
This is a generalized notebook for computing grade statistics from the Ted Grade Center.
Step1: Load data from exported CSV from Ted Full Grade Center. Some sanitization is perform... | Python Code:
#The usual imports
import math
from collections import OrderedDict
from pandas import read_csv
import numpy as np
from pymatgen.util.plotting_utils import get_publication_quality_plot
from monty.string import remove_non_ascii
import prettyplotlib as ppl
from prettyplotlib import brewer2mpl
import matplotli... |
1,412 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 14 – Recurrent Neural Networks
This notebook contains all the sample code and solutions to the exercises in chapter 14.
<table align="left">
<td>
<a target="_blank" href="https... | Python Code:
# To support both python 2 and python 3
from __future__ import division, print_function, unicode_literals
# Common imports
import numpy as np
import os
try:
# %tensorflow_version only exists in Colab.
%tensorflow_version 1.x
except Exception:
pass
# to make this notebook's output stable across ... |
1,413 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating a Heatmap of Vector Results
In this notebook, you'll learn how to use Planet's Analytics API to display a heatmap of vector analytic results, specifically buildng change detections.... | Python Code:
!pip install cython
!pip install https://github.com/SciTools/cartopy/archive/v0.18.0.zip
Explanation: Creating a Heatmap of Vector Results
In this notebook, you'll learn how to use Planet's Analytics API to display a heatmap of vector analytic results, specifically buildng change detections. This can be us... |
1,414 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Feedforward Neural Network
Step1: <script type="text/javascript" src="https
Step2: It can be seen from the above figure that as we increase our input the our activation starts to sa... | Python Code:
# import feedforward neural net
from mlnn import neural_net
Explanation:
Feedforward Neural Network
End of explanation
# Visualize tanh and its derivative
x = np.linspace(-np.pi, np.pi, 120)
plt.figure(figsize=(8, 3))
plt.subplot(1, 2, 1)
plt.plot(x, np.tanh(x))
plt.title("tanh(x)")
plt.xlim(-3, 3)... |
1,415 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NEST implementation of the aeif models
Hans Ekkehard Plesser and Tanguy Fardet, 2016-09-09
This notebook provides a reference solution for the Adaptive Exponential Integrate and Fire
(AEIF) ... | Python Code:
# Install assimulo package in the current Jupyter kernel
import sys
!{sys.executable} -m pip install assimulo
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (15, 6)
Explanation: NEST implementation of the aeif models... |
1,416 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Words Associated to each Gender (through PMI)
In this notebook we compute PMI scores for the vocabulary obtained in the previous notebook.
By Eduardo Graells-Garrido.
Step1: First, we load ... | Python Code:
from __future__ import print_function, unicode_literals, division
from cytoolz.dicttoolz import valmap
from collections import Counter
import pandas as pd
import json
import gzip
import numpy as np
import pandas as pd
import dbpedia_config
target_folder = dbpedia_config.TARGET_FOLDER
Explanation: Words As... |
1,417 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Adaptive Filters Real-time Use with Padasip Module
This tutorial shows how to use Padasip module for filtering and prediction with adaptive filters in real-time.
Lets start with importing pa... | Python Code:
import numpy as np
import matplotlib.pylab as plt
import padasip as pa
%matplotlib inline
plt.style.use('ggplot') # nicer plots
np.random.seed(52102) # always use the same random seed to make results comparable
Explanation: Adaptive Filters Real-time Use with Padasip Module
This tutorial shows how to use P... |
1,418 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
EventVestor
Step1: Let's go over the columns
Step2: Finally, suppose we want a DataFrame of all earnings calendar releases in February 2012, but we only want the event_headline and the cal... | Python Code:
# import the dataset
from quantopian.interactive.data.eventvestor import earnings_calendar as dataset
# or if you want to import the free dataset, use:
# from quantopian.data.eventvestor import earnings_calendar_free
# import data operations
from odo import odo
# import other libraries we will use
import p... |
1,419 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: 3T_데이터베이스, 테이블 생성하고 데이터 추가하기
우리의 데이터베이스 서버에 "데이터베이스", "테이블", "데이터" 생성하고, 저장하기
데이터베이스 생성하기 ( 각자 이름으로 )
테이블 생성하기 ( "zigbang" )
데이터 추가하기
Step9: 실습)
데이터를 어떻게 저장할 것인가? - 확장성이 있는가, ... ( J... | Python Code:
zigbang_df = pd.read_csv("zigbang.csv")
zigbang_df.head()
import pymysql
db = pymysql.connect(
"db.fastcamp.us",
"root",
"dkstncks",
# "sakila",
charset="utf8",
)
# cursor 라는 객체를 가져와서 DB에 명령을 실행시킵니다.
cursor = db.cursor()
# 현재 있는 모든 데이터베이스 이름을 가져오는 명령어
SQL_QUERY =
SHOW DATABASES;
# ... |
1,420 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: The <span style="background-color
Step2: Creating placeholders
It's a best practice to create placeholders before variable assignments when using TensorFlow. Here we'... | Python Code:
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
Explanation: <a href="https://www.cognitiveclass.ai"><img src = "https://cognitiveclass.ai/wp-content/themes/bdu3.0/static/images/cc-logo.png" align = left></a>
<... |
1,421 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
I've implemented the integral of wt in pearce. This notebook verifies it works as I believe it should.
Step1: Load up the tptY3 buzzard mocks.
Step2: Load up a snapshot at a redshift near ... | Python Code:
from pearce.mocks import cat_dict
import numpy as np
from os import path
from astropy.io import fits
import matplotlib
#matplotlib.use('Agg')
from matplotlib import pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set()
Explanation: I've implemented the integral of wt in pearce. This notebook ver... |
1,422 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<CENTER>
<a href="http
Step1: In order to activate the interactive visualisation of the histogram that is later created we can use the JSROOT magic
Step2: Next we have to open the data... | Python Code:
import ROOT
Explanation: <CENTER>
<a href="http://opendata.atlas.cern" class="icons"><img src="http://opendata.atlas.cern/DataAndTools/pictures/opendata-top-transblack.png" style="width:40%"></a>
</CENTER>
A more difficult notebook in python
In this notebook you can find a more difficult program that s... |
1,423 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The use of watermark (above) is optional, and we use it to keep track of the changes while developing the tutorial material. (You can install this IPython extension via "pip install watermar... | Python Code:
from sklearn.datasets import load_iris
iris = load_iris()
Explanation: The use of watermark (above) is optional, and we use it to keep track of the changes while developing the tutorial material. (You can install this IPython extension via "pip install watermark". For more information, please see: https://... |
1,424 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Recurrent Neural Networks (RNNs)
Recurrent Neural Networks (RNNs) are an interesting application of deep learning that allow models to predict the future. While regres... | 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... |
1,425 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Nipype Quickstart
Existing documentation
Visualizing the evolution of Nipype
This notebook is taken from reproducible-imaging repository
Import a few things from nipype and external librarie... | Python Code:
import os
from os.path import abspath
from nipype import Workflow, Node, MapNode, Function
from nipype.interfaces.fsl import BET, IsotropicSmooth, ApplyMask
from nilearn.plotting import plot_anat
%matplotlib inline
import matplotlib.pyplot as plt
Explanation: Nipype Quickstart
Existing documentation
Visual... |
1,426 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'miroc', 'nicam16-7s', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: MIROC
Source ID: NICAM16-7S
Topic: Aerosol
Sub-Topics: Transport, Emiss... |
1,427 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Suggestions for lab exercises.
Variables and assignment
Exercise 1
Remember that $n! = n \times (n - 1) \times \dots \times 2 \times 1$. Compute $15!$, assigning the result to a sensible var... | Python Code:
fifteen_factorial = 15*14*13*12*11*10*9*8*7*6*5*4*3*2*1
print(fifteen_factorial)
Explanation: Suggestions for lab exercises.
Variables and assignment
Exercise 1
Remember that $n! = n \times (n - 1) \times \dots \times 2 \times 1$. Compute $15!$, assigning the result to a sensible variable name.
Solution
En... |
1,428 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Unsupervised learning
Step1: First, we start with some exploratory clustering, visualizing the clustering dendrogram using SciPy's linkage and dendrogram functions
Step2: Next, let's use t... | Python Code:
from sklearn.datasets import load_iris
iris = load_iris()
X = iris.data[:, [2, 3]]
y = iris.target
n_samples, n_features = X.shape
plt.scatter(X[:, 0], X[:, 1], c=y);
Explanation: Unsupervised learning: Hierarchical and density-based clustering algorithms
In a previous notebook, "08 Unsupervised Learning -... |
1,429 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Inspecting the PubMed Paper Dataset
(Adapted from
Step1: To make it easier to access the data, we convert here paper entries into named tuples. This will allow us to refer to fields by keyw... | Python Code:
import pickle, bz2
Summaries_file = 'data/air__Summaries.pkl.bz2'
Summaries = pickle.load( bz2.BZ2File( Summaries_file, 'rb' ) )
Explanation: Inspecting the PubMed Paper Dataset
(Adapted from: Inspecting the dataset - Luís F. Simões. Assignments added by J.E. Hoeksema, 2014-10-16. Converted to Python 3 and... |
1,430 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Real World Tutorial 3
Step3: We define a function that computes the sum of all primes below a certain integer n, and don't try to be smart about it; the point is that it needs a lot of comp... | Python Code:
%load_ext cython
import multiprocessing
import threading
import queue
Explanation: Real World Tutorial 3: Parallel Number crunching using Cython
Python was not designed to be very good at parallel processing. There are two major problems at the core of the language that make it hard to implement parallel a... |
1,431 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparison of two means (T-test)
Step1: In this notebook we demo two equivalent ways of performing a two-sample Bayesian t-test to compare the mean value of two Gaussian populations using B... | Python Code:
import arviz as az
import bambi as bmb
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
az.style.use("arviz-darkgrid")
np.random.seed(1234)
Explanation: Comparison of two means (T-test)
End of explanation
a = np.random.normal(6, 2.5, 160)
b = np.random.normal(8, 2, 120)
df = pd.DataFr... |
1,432 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercises
Step1: Exercise 1
Step2: b. Checking for Normality
As an extra all-purpose check, and one that is often done on series, check whether the above series is normally distributed usi... | Python Code:
# Useful Functions
def check_for_stationarity(X, cutoff=0.01):
# H_0 in adfuller is unit root exists (non-stationary)
# We must observe significant p-value to convince ourselves that the series is stationary
pvalue = adfuller(X)[1]
if pvalue < cutoff:
print 'p-value = ' + str(pvalue... |
1,433 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Abstract
Titel
Step1: Einführung in<br/> Software Analytics
<b>Markus Harrer</b>, Software Development Analyst
@feststelltaste
<small>ML Summit 2019, 14. Oktober 2019</small>
<img src="../.... | Python Code:
%matplotlib inline
import pandas as pd
Explanation: Abstract
Titel: Einführung in Software Analytics
Beschreibung
In Unternehmen werden Datenanalysen intensiv genutzt, um aus Geschäftsdaten wertvolle Einsichten
zu gewinnen. Warum nutzen wir als Softwareentwickler Datenanalysen dann nicht auch für unsere ei... |
1,434 | 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', 'test-institute-3', 'sandbox-3', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: TEST-INSTITUTE-3
Source ID: SANDBOX-3
Topic: Atmos
Sub-Topics: Dy... |
1,435 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook is an effort to replicate the lessons found here
Step1: We're going to fetch the data file we need for this exercise from the following URL
Step2: Let's make a plot of the da... | Python Code:
import numpy as np
import pandas as pd
from geostatsmodels import utilities, kriging, variograms, model, geoplot
import matplotlib.pyplot as plt
from scipy.stats import norm
Explanation: This notebook is an effort to replicate the lessons found here:
http://people.ku.edu/~gbohling/cpe940/Variograms.pdf
We'... |
1,436 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interpolation Exercise 2
Step1: Sparse 2d interpolation
In this example the values of a scalar field $f(x,y)$ are known at a very limited set of points in a square domain
Step2: The follow... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
sns.set_style('white')
from scipy.interpolate import griddata
from scipy.interpolate import interp2d
Explanation: Interpolation Exercise 2
End of explanation
x=np.array([5,5,5,5,5,5,4,3,2,1,0,-1,-2,-3,-4,-5,-5,-5,-5... |
1,437 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Linear Regression and Subset Selection
StatML
Step2: Recall LinearRegression.fit
Throughout let $p < n$
Fit in OLS solves the following, on training set
$$
\hat \beta = (X^\top X)^{-1} X^\t... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
import scipy as sc
Explanation: Linear Regression and Subset Selection
StatML: Lecture 3
Prof. James Sharpnack
Reading: "The Elements of Statistical Learning," Hastie, Tibshirani, Friedman, Ch. 3 (ESL)
End of explanation
de... |
1,438 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pyplot
pyplot is a context based functional API offering meaningful defaults. It's a concise API and very similar to matplotlib's pyplot. Users new to bqplot should use pyplot as a starting ... | Python Code:
import bqplot.pyplot as plt
# first, let's create two vectors x and y to plot using a Lines mark
import numpy as np
x = np.linspace(-10, 10, 100)
y = np.sin(x)
# 1. Create the figure object
fig = plt.figure(title="Simple Line Chart")
# 2. By default axes are created with basic defaults. If you want to cust... |
1,439 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Final Exam Review
CSCI 1360E
Step1: Another example is Part G, asking you to write a function that reverses the elements of an array. According to the instructions, you were not allowed to ... | Python Code:
def dot(arr1, arr2):
if arr1.shape[0] != arr2.shape[0]:
return None
p = arr1 * arr2 # Multiplies corresponding elements of the two arrays...no loops needed!
s = p.sum() # Computes the sum of all the elements...still no loops needed!
return s
Explanation: Final Exam Review
CSCI... |
1,440 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploring Optimizers
A Code Along of Kerem Turgutlu's Notebook
Step1: This notebook is inspired by Sebastian Ruder's awesome work from http
Step2: Training With Different Optimizers
Step3:... | Python Code:
# Classical
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
# PyTorch
import torch
from torch import nn
import torch.nn.functional as F
from torch.autograd import Variable
from torch.utils.data import Dataset, DataLoader
from torch import optim
# Misc
%matplotlib in... |
1,441 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LeNet Lab
Source
Step1: The MNIST data that TensorFlow pre-loads comes as 28x28x1 images.
However, the LeNet architecture only accepts 32x32xC images, where C is the number of color channel... | Python Code:
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", reshape=False)
X_train, y_train = mnist.train.images, mnist.train.labels
X_validation, y_validation = mnist.validation.images, mnist.validation.labels
X_test, y_test = mnist.tes... |
1,442 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
======================================================
Compute source power spectral density (PSD) in a label
======================================================
Returns an STC file conta... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD (3-clause)
import matplotlib.pyplot as plt
import mne
from mne import io
from mne.datasets import sample
from mne.minimum_norm import read_inverse_operator, compute_source_psd
print(__doc__)
Explanation: ==========================... |
1,443 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Resampling data
When performing experiments where timing is critical, a signal with a high
sampling rate is desired. However, having a signal with a much higher sampling
rate than is necessa... | Python Code:
# Authors: Marijn van Vliet <w.m.vanvliet@gmail.com>
#
# License: BSD (3-clause)
from matplotlib import pyplot as plt
import mne
from mne.datasets import sample
Explanation: Resampling data
When performing experiments where timing is critical, a signal with a high
sampling rate is desired. However, having ... |
1,444 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TFLearn [Participle Phrase] Fragment Detection
This notebook is based off the original fragment detection notebook, but specific to detection of participle phrase fragments. As our trainin
g... | Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
import spacy
nlp = spacy.load('en')
import re
from nltk.util import ngrams, trigrams
import csv
Explanation: TFLearn [Participle Phrase] Fragment Detection
This notebook is based off ... |
1,445 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 5
Step1: Example 1
Step2: Example 2
Step3: Example 3
Step4: Example 4
Step5: Example 5 | Python Code:
# Import relevant modules
%matplotlib inline
%load_ext autoreload
%autoreload 2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rcParams
from NPTFit import psf_correction as pc # Module for determining the PSF correction
from __future__ import print_function
Explanation: Example 5... |
1,446 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Integration Exercise 1
Imports
Step2: Trapezoidal rule
The trapezoidal rule generates a numerical approximation to the 1d integral
Step3: Now use scipy.integrate.quad to integrate the f an... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy import integrate
Explanation: Integration Exercise 1
Imports
End of explanation
def trapz(f, a, b, N):
Integrate the function f(x) over the range [a,b] with N points.
h=(b-a)/N
k=np.arange(1,N)
I=h*(0.5*f(a)+0.... |
1,447 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Randomly Generate A Stock Price & View The Data
Here, we create an application which is submitted to a remote host, yet we retrieve its data remotely via views. This way, we can graph remote... | Python Code:
from streamsx.topology.topology import Topology
from streamsx.topology import context
from some_module import jsonRandomWalk
#from streamsx import rest
import json
import logging
# Define topology & submit
rw = jsonRandomWalk()
top = Topology("myTop")
stock_data = top.source(rw)
# The view object can be us... |
1,448 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualización de sistemas mecánicos
Dado un sistema masa resorte amortiguador como el de la figura siguiente
Step1: Graficas
Una vez que tenemos los datos, nos disponemos a graficarlos, aho... | Python Code:
from control import step, tf
m = 1200
k = 15000
c = 1500
F = 1
G = tf([0, 0, 1/m], [1, c/m, k/m])
G
y, t = step(G)
Explanation: Visualización de sistemas mecánicos
Dado un sistema masa resorte amortiguador como el de la figura siguiente:
Graficar la trayectoria del sistema, y animar los componentes fisicos... |
1,449 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data preprocessing methods
Step1: 1. Data preprocessing
1.1. The dataset.
A key component of any data processing method or any machine learning algorithm is the dataset, i.e., the set of da... | Python Code:
# Some libraries that will be used along the notebook.
import numpy as np
import matplotlib.pyplot as plt
Explanation: Data preprocessing methods: Normalization
Notebook version:
* 1.0 (Sep 15, 2020) - First version
* 1.1 (Sep 15, 2021) - Exercises
Authors: Jesús Cid Sueiro (jcid@ing.uc3m.es)
End of explan... |
1,450 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Artifact Correction with ICA
ICA finds directions in the feature space
corresponding to projections with high non-Gaussianity. We thus obtain
a decomposition into independent components, and... | Python Code:
import numpy as np
import mne
from mne.datasets import sample
from mne.preprocessing import ICA
from mne.preprocessing import create_eog_epochs, create_ecg_epochs
# getting some data ready
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif'
raw = mne.io.read... |
1,451 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualizing time series metabolome profile
by Kozo Nishida (Riken, Japan)
Software Requirments
Please install the following software packages to run this workflow
Step1: Load a KGML pathway... | Python Code:
import json
import requests
import pandas as pd
PORT_NUMBER = 1234
BASE_URL = "http://localhost:" + str(PORT_NUMBER) + "/v1/"
HEADERS = {'Content-Type': 'application/json'}
Explanation: Visualizing time series metabolome profile
by Kozo Nishida (Riken, Japan)
Software Requirments
Please install the followi... |
1,452 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 4
Work on this before the next lecture on 1 May. We will talk about questions, comments, and solutions during the exercise after the third lecture.
Please do form study groups! When... | Python Code:
%config InlineBackend.figure_format='retina'
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = (8, 8)
plt.rcParams["font.size"] = 14
from sklearn.utils import check_random_state
Explanation: Exercise 4
Work on this before the next lecture on 1 May. We wi... |
1,453 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stay Alert! The Ford Challenge
by Scott Josephson
Driving while distracted, fatigued or drowsy may lead to accidents. Activities that divert the driver's attention from the road ahead, such ... | Python Code:
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, classification_report
Explanation: Stay Alert! The Ford Challenge
by Scott Josephson
Driving while distracted, fatigued... |
1,454 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Show noise levels from empty room data
This shows how to use
Step1: We can plot the absolute noise levels | Python Code:
# Author: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import mne
data_path = mne.datasets.sample.data_path()
raw_erm = mne.io.read_raw_fif(op.join(data_path, 'MEG', 'sample',
'ernoise_raw.fif'), preload=True)
Explanation: Show... |
1,455 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BeautifulSoup 4
Step1: findNext() - Finding e-mail trough its label
There are unlimited number of options for matching an e-mail from a page. This time, we will try to find my e-mail by fir... | Python Code:
import requests
from BeautifulSoup import *
url = "https://hrantdavtyan.github.io/"
response = requests.get(url)
page = response.text
soup = BeautifulSoup(page)
Explanation: BeautifulSoup 4: Navigation
BeautifulSoup is a powerful package mostly due to the abundance of Navigation methods in the package. Bel... |
1,456 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Hill-Tononi Neuron and Synapse Models
Hans Ekkehard Plesser, NMBU/FZ Jülich/U Oslo, 2016-12-01
Background
This notebook describes the neuron and synapse model proposed by Hill and Tononi... | Python Code:
import sys
import math
import numpy as np
import pandas as pd
import scipy.optimize as so
import scipy.integrate as si
import matplotlib.pyplot as plt
import nest
%matplotlib inline
plt.rcParams['figure.figsize'] = (12, 3)
Explanation: The Hill-Tononi Neuron and Synapse Models
Hans Ekkehard Plesser, NMBU/F... |
1,457 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
syncID
Step1: Next, set display preferences so that plots are inline (meaning any images you output from your code will show up below the cell in the notebook) and turn off plot warnings
St... | Python Code:
import numpy as np
import h5py
import gdal, osr, os
import matplotlib.pyplot as plt
Explanation: syncID: 61ad1fc43ddd45b49cad1bca48656bbe
title: "NEON AOP Hyperspectral Data in HDF5 format with Python - Tiled Data"
description: "Learn how to read NEON AOP hyperspectral flightline data using Python and dev... |
1,458 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You are currently looking at version 1.0 of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the Jupyter Notebook ... | Python Code:
import pandas as pd
import numpy as np
def blight_model():
# Your code here
return # Your answer here
df_train = pd.read_csv('train.csv', encoding = "ISO-8859-1")
df_test = pd.read_csv('test.csv', encoding = "ISO-8859-1")
df_train.columns
list_to_remove = ['balance_due',
'collection_stat... |
1,459 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dynamic Programming and Graph Algorithm Problems
Here are what we went over in the class. In addition here are the links to the MIT Course I mentioned and to my repo that has a lot more impl... | Python Code:
def fib(n):
if n < 0:
raise Exception("Index was negative. Cannot have a negative index in a series")
if n < 2:
return n
return fib(n-1) + fib(n-2)
fib(25)
def fib(n):
if n < 0:
raise Exception("Index was negative. Cannot have a negative inde... |
1,460 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 15
Modeling and Simulation in Python
Copyright 2021 Allen Downey
License
Step1: So far the systems we have studied have been physical in the sense that they exist in the world, but ... | Python Code:
# install Pint if necessary
try:
import pint
except ImportError:
!pip install pint
# download modsim.py if necessary
from os.path import exists
filename = 'modsim.py'
if not exists(filename):
from urllib.request import urlretrieve
url = 'https://raw.githubusercontent.com/AllenDowney/ModSim/... |
1,461 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Date
Step1: Only train on data when the rat is moving
Step2: Encoding Model
Train model
Step3: Get predicted conditional intensities
Step4: Plot model fits for each neuron to check fit q... | Python Code:
%matplotlib inline
%reload_ext autoreload
%autoreload 2
%qtconsole
import sys
import collections
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
from tqdm import tqdm_notebook as tqdm
import patsy
import statsmodels.api as sm
import statsmodels.formula.api as sm... |
1,462 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Nonlinear Astro Features
This notebook examines whether $w_1 - w_2$ and $w_2 - w_3$ are good features. There are indications that these may be correlated with whether galaxies contain AGNs. ... | Python Code:
import h5py, numpy, sklearn.linear_model, sklearn.cross_validation, sklearn.metrics
with h5py.File('../data/training.h5') as f:
raw_astro_features = f['features'][:, :4]
dist_features = f['features'][:, 4]
image_features = f['features'][:, 5:]
w1_w2 = raw_astro_features[:, 0] - raw_ast... |
1,463 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Competition assay analysis and thoughts
Here we will analyze two competition assay conducted as a rough beginning to understand how to best design competition assays to the fluorescent kinas... | Python Code:
#import needed libraries
import re
import os
from lxml import etree
import pandas as pd
import pymc
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
Explanation: Competition assay analysis and thoughts
Here we will analyze two competition ... |
1,464 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dane treningowe
Ponieważ będziemy potrzebowali na czymś wytrenować naszą sieć neuronową skorzystamy z popularnego zbioru w Machine Learningu czyli MNIST. Zbiór ten zawiera ręcznie pisane cyf... | Python Code:
# skorzystamy z gotowej funkcji do pobrania tego zbioru
from sklearn.datasets import fetch_mldata
mnist = fetch_mldata('MNIST original')
Explanation: Dane treningowe
Ponieważ będziemy potrzebowali na czymś wytrenować naszą sieć neuronową skorzystamy z popularnego zbioru w Machine Learningu czyli MNIST. Zbi... |
1,465 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Structure Prediction
In this notebook, we aim to do a test of the structure substitution algorithm implemented in SMACT
Before we can do predictions, we need to create our cation mutator, da... | Python Code:
comps=pd.read_csv("Li-Garnet_Comps_sus.csv")
comps.head()
Explanation: Structure Prediction
In this notebook, we aim to do a test of the structure substitution algorithm implemented in SMACT
Before we can do predictions, we need to create our cation mutator, database and a table, and a list of hypothetical... |
1,466 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Association Mining
The goal in this problem set is to design and code an algorithm for generating association rules based on the apriori algorithm. The dataset that you will use to mine for ... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
with open('itemsets.dat') as f:
transactions = []
for row in f:
transactions.append(row.strip().split(','))
transactions[0:5]
Explanation: Association Mining
The goal in this problem set is to design a... |
1,467 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Python for Everyone!<br/>Oregon Curriculum Network
Descriptors and Properties in Python
<img src="https
Step2: y's value is an ordinary int, equivalently the value of MyClass.__dict_... | Python Code:
class RevealAccess(object):
A data descriptor that sets and returns values
normally and prints a message logging their access.
Descriptor Example:
https://docs.python.org/3/howto/descriptor.html
def __init__(self, initval=None, name='var'):
self.val = initva... |
1,468 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced Matplotlib Concepts Lecture
In this lecture we cover some more advanced topics which you won't usually use as often. You can always reference the documentation for more resources!
... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
x = np.linspace(0, 5, 11)
y = x**2
fig, axes = plt.subplots(1, 2, figsize=(10,4))
axes[0].plot(x, x**2, x, np.exp(x))
axes[0].set_title("Normal scale")
axes[1].plot(x, x**2, x, np.exp(x))
axes[1].set_yscale("log")
axes[1].set_titl... |
1,469 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: TF Lattice 사전 제작 모델
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 필수 패키지 가져오기
Step3: UCI Stat... | 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... |
1,470 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
xlrd demo
This notebook demonstrates the xlrd package which is designed to read MS Excel files. This is not a built-in package, but rather 3rd party package that is installed with ArcGIS Des... | Python Code:
#Import the os and the xlrd modules
import xlrd
#Set a variable to the path of the xlsx file
xlFilename = './Data/USGSCircular1405-tables1-14.xlsx'
Explanation: xlrd demo
This notebook demonstrates the xlrd package which is designed to read MS Excel files. This is not a built-in package, but rather 3rd par... |
1,471 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Part 7
Step1: The totient is a multiplicative function, meaning that if $GCD(a,b) = 1$, then $\phi(ab) = \phi(a) \phi(b)$. Therefore, the totient of number can be found quickly from the to... | Python Code:
def GCD(a,b):
while b: # Recall that != means "not equal to".
a, b = b, a % b
return abs(a)
def totient(m):
tot = 0 # The running total.
j = 0
while j < m: # We go up to m, because the totient of 1 is 1 by convention.
j = j + 1 # Last step of while loop: j = m-1, an... |
1,472 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
File IO
These notebooks are used to check certain examples in the course notes, hence they are mainly for the benefit of the course developers, rather than a teaching resource.
Step1: Pytho... | Python Code:
import numpy as np
import pandas as pd
#Go up one directory as this is where the 'current' directory assumed in the course notes
cd ..
!head -3 "data/titanic.csv"
!tail -3 "data/titanic.csv"
Explanation: File IO
These notebooks are used to check certain examples in the course notes, hence they are mainly ... |
1,473 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BUILDING A RECOMMENDER SYSTEM ON USER-USER COLLABORATIVE FILTERING (MOVIELENS DATASET)
We will load the data sets firsts.
Step1: We will use the file u.data first as it contains User ID, Mo... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math
#column headers for the dataset
data_cols = ['user id','movie id','rating','timestamp']
item_cols = ['movie id','movie title','release date','video release date','IMDb URL','unknown','Action',
'Adventure','Animation','Childr... |
1,474 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Checking standard usage
Step1: NOTE
easyplot crashes if nicknames are not given
Step2: Loading journal
Step3: NOTE
should rename index to cell_name instead of filename
Step4: Note
need t... | Python Code:
files = [f1, f2]
names = [f1.name, f2.name]
ezplt = easyplot.EasyPlot(files, names, figtitle="Test1")
ezplt.plot()
Explanation: Checking standard usage
End of explanation
easyplot.EasyPlot(
files,
names,
figtitle="Test2",
galvanostatic_normalize_capacity=True,
all_in_one=True,
dqdv_... |
1,475 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numerical Modeling
Reference
Step1: We need to give an initial wave which is a function of $x$ (remember, $u(x,0)=u_0(x)$). We can easily choose a step-function for the velocity
Step2: Bre... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# spatial grid
nx = 41 # try changing from 41 to 81
dx = 2./(nx-1) #dx = delta x
nt = 20
dt = nt/1000. #dt = delta t
c = 1. # wavespeed
Explanation: Numerical Modeling
Reference: 12 steps to Navier-Stokes.
Given the broad topics of "Mode... |
1,476 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Core data model
Xarray-Beam tries to make it straightforward to write distributed pipelines with Xarray objects, but unlike libraries like Xarray with Dask or Dask/Spark DataFrames, it doesn... | Python Code:
import apache_beam as beam
import numpy as np
import xarray_beam as xbeam
import xarray
Explanation: Core data model
Xarray-Beam tries to make it straightforward to write distributed pipelines with Xarray objects, but unlike libraries like Xarray with Dask or Dask/Spark DataFrames, it doesn't hide the dist... |
1,477 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 7
CHE 116
Step1: 2. Chemical Reaction (6 Points)
A set of frist-order chemical reactions can be described by the following system of differential equations
Step2: 2.4 Answer
That ... | Python Code:
import numpy as np
from numpy import linalg
#note z^2 doesn't affect our answer
a_matrix = [[6, 4,-1],\
[1, -1, 0],\
[2, -2, -1]]
b_matrix = [0, 6, -4]
#convert them to numpy arrays/matrices
np_a_matrix = np.array(a_matrix)
np_b_matrix = np.array(b_matrix).transpose()
#Solve the pro... |
1,478 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
请在环境变量中设置DB_URI指向数据库
Step1: 1. Single Day Analysis
Step2: Portfolio Construction
using EPS factor as alpha factor;
short selling is forbiden;
target of volatility for the activate weight i... | Python Code:
%matplotlib inline
import os
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from PyFin.api import *
from alphamind.api import *
from alphamind.strategy.strategy import Strategy, RunningSetting
from alphamind.portfolio.meanvariancebuilder import target_vol_builder
plt.style.use(... |
1,479 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
design a simple deep learning architecture for next word predection
| Python Code::
model = Sequential()
model.add(Embedding(vocab_size, 10, input_length=1))
model.add(LSTM(1000, return_sequences=True))
model.add(LSTM(1000))
model.add(Dense(1000, activation="relu"))
model.add(Dense(vocab_size, activation="softmax"))
|
1,480 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Learning to Use XGBoost
XGBoost is the leading model for working with standard tabular data (the type of data you store in pandas DataFrames, as opposed to more exotic types of data like ima... | Python Code:
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import Imputer
data = pd.read_csv('input/train.csv')
data.dropna(axis=0, subset=['SalePrice'], inplace=True)
y = data.SalePrice
X = data.drop(['SalePrice'], axis=1).select_dtypes(exclude=['object'])
train_X,... |
1,481 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parameter identification example
Here is a simple toy model that we use to demonstrate the working of the inference package
$\emptyset \xrightarrow[]{k_1(I)} X \; \; \; \; X \xrightarrow[]{d... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = "retina"
from matplotlib import rcParams
rcParams["savefig.dpi"] = 100
rcParams["figure.dpi"] = 100
rcParams["font.size"] = 20
%matplotlib inline
import bioscrape as bs
from bioscrape.types import Model
from bioscrape.simulator import py_simulate_mod... |
1,482 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overfitting
Create a dataset based on a true sinusoidal relationship
Let's look at a synthetic dataset consisting of 30 points drawn from the sinusoid $y = \sin(4x)$
Step1: Create random va... | Python Code:
import graphlab
import math
import random
import numpy
from matplotlib import pyplot as plt
%matplotlib inline
Explanation: Overfitting
Create a dataset based on a true sinusoidal relationship
Let's look at a synthetic dataset consisting of 30 points drawn from the sinusoid $y = \sin(4x)$:
End of explanati... |
1,483 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simulating Galaxy Observations
Step1: Galaxy Model
The model for the spatial intensity of the galaxy we observe (i.e. the distribution of brightness on the sky) has two basic components
Ste... | Python Code:
# only necessary if you're running Python 2.7 or lower
from __future__ import print_function
from __builtin__ import range
import numpy as np
# import plotting utility and define our naming alias
from matplotlib import pyplot as plt
# plot figures within the notebook rather than externally
%matplotlib inli... |
1,484 | 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', 'hammoz-consortium', 'sandbox-3', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: HAMMOZ-CONSORTIUM
Source ID: SANDBOX-3
Topic: Ocnbgchem
... |
1,485 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
We won't work through this notebook
We won't have time. But I thought I'd include it, in case you want to see exactly how I implement my population-level quality metric.
Step2: Let's put t... | Python Code:
import numpy as np, pandas as pd
Explanation: We won't work through this notebook
We won't have time. But I thought I'd include it, in case you want to see exactly how I implement my population-level quality metric.
End of explanation
def measure_prediction_quality(csmf_pred, y_test):
Calculate popula... |
1,486 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AdaptiveMD
Example 4 - Custom Task objects
0. Imports
Step1: Let's open our test project by its name. If you completed the first examples this should all work out of the box.
Step2: Open a... | Python Code:
from adaptivemd import Project, File#, PythonTask, Task
Explanation: AdaptiveMD
Example 4 - Custom Task objects
0. Imports
End of explanation
project = Project('tutorial')
Explanation: Let's open our test project by its name. If you completed the first examples this should all work out of the box.
End of e... |
1,487 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2017 Google LLC.
Step1: # 사전 작업 | 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... |
1,488 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mixtures of Gaussian processes with GPclust
This notebook accompanies the paper
Nonparameteric Clustering of Structured Time Series
James Hensman, Magnus Rattray and Neil D. Lawrence
IEEE TP... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'png'#'svg' would be better, but eats memory for these big plots.
from matplotlib import pyplot as plt
import numpy as np
import GPy
import sys
sys.path.append('/home/james/work/gpclust/')
import GPclust
Explanation: Mixtures of Gaussian processes wi... |
1,489 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have a file with arrays or different shapes. I want to zeropad all the array to match the largest shape. The largest shape is (93,13). | Problem:
import numpy as np
a = np.ones((41, 12))
shape = (93, 13)
result = np.pad(a, ((0, shape[0]-a.shape[0]), (0, shape[1]-a.shape[1])), 'constant') |
1,490 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Model Explanation for Classification Models
This document describes the usage of a classification model to provide an explanation for a given prediction.
Model explanation provides the abili... | Python Code:
from sklearn import datasets
import pandas as pd
%matplotlib inline
ds = datasets.load_breast_cancer();
NC = 4
lFeatures = ds.feature_names[0:NC]
df_orig = pd.DataFrame(ds.data[:,0:NC] , columns=lFeatures)
df_orig['TGT'] = ds.target
df_orig.sample(6, random_state=1960)
Explanation: Model Explanation for Cl... |
1,491 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook illustrates the use of tables in conveying the combination of inferential and computational thinking through studying concepts of probability theory. It the Birthday Surprise ... | Python Code:
# HIDDEN
from datascience import *
%matplotlib inline
import matplotlib.pyplot as plots
plots.style.use('fivethirtyeight')
import numpy as np
# datascience version number of last run of this notebook
version.__version__
Explanation: This notebook illustrates the use of tables in conveying the combination o... |
1,492 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex SDK
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Once you've installed the additional packages, you need to restart the no... | Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
Explanation: Vertex SDK: Custom training image classification model for online prediction with explain... |
1,493 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Centrality
This evaluates the Eigenvector Centrality and PageRank implemented in Python against C++-native EVZ and PageRank. The Python implementation uses SciPy (and thus ARPACK) to compute... | Python Code:
cd ../../
import networkit
G = networkit.graphio.readGraph("input/celegans_metabolic.graph", networkit.Format.METIS)
Explanation: Centrality
This evaluates the Eigenvector Centrality and PageRank implemented in Python against C++-native EVZ and PageRank. The Python implementation uses SciPy (and thus ARPAC... |
1,494 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Exploratory Data Analysis (EDA) for Propensity Modeling
This notebook helps to
Step1: Notebook custom settings
Step2: Configuration
Edit config.yaml to update GCP configuration that is ... | Python Code:
# Uncomment to install required python modules
# !sh ../utils/setup.sh
# Add custom utils module to Python environment
import os
import sys
sys.path.append(os.path.abspath(os.pardir))
import pandas as pd
from gps_building_blocks.cloud.utils import bigquery as bigquery_utils
from utils import eda_ga
from ut... |
1,495 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MSM of the alanine dipeptide
Here we run through most of the things that can be done with this package using a simple two-state model. There are more sophisticated examples that enable for f... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
import math
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="ticks", color_codes=True, font_scale=1.5)
sns.set_style({"xtick.direction": "in", "ytick.direction": "in"})
Explanation: MSM of the alanine dipeptide
Her... |
1,496 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ODEs
We will use this notebook to define the differential equations that will be solved.
Each function representing a differential equation or set of differential equations should take a sta... | Python Code:
def Exponential(y, t, args=None):
dydt=y
return(dydt)
Explanation: ODEs
We will use this notebook to define the differential equations that will be solved.
Each function representing a differential equation or set of differential equations should take a state vector and time array as its first two ... |
1,497 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Introduction to Regular Expressions
Regular Expressions are a powerful feature of the Python programming language. You can access Python's regular expression support t... | 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... |
1,498 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Make figures more publication ready
In this example, we show several use cases to take MNE plots and
customize them for a more publication-ready look.
Step1: Imports
We are importing everyt... | Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
# Daniel McCloy <dan.mccloy@gmail.com>
# Stefan Appelhoff <stefan.appelhoff@mailbox.org>
#
# License: BSD-3-Clause
Explanation: Make figures more publication ready
In this example, we show several use cases to take MNE plots and
customize t... |
1,499 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<small><i>This notebook was prepared by Donne Martin. Source and license info is on GitHub.</i></small>
Solution Notebook
Problem
Step1: Pythonic-Code
This question has an artificial constr... | Python Code:
from __future__ import division
def list_of_chars(chars):
if chars is None:
return None
size = len(chars)
for i in range(size//2):
chars[i], chars[size-1-i] = \
chars[size-1-i], chars[i]
return chars
Explanation: <small><i>This notebook was prepared by Donne Mart... |
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