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4,400 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id='step1'></a>
22 - Example Simulation
Step1: <a id='step2'></a>
Step2: 1. Create your module and evaluate irradiance without the mirror element
Step3: 2. Add Mirror
Approach 1
Step4:... | Python Code:
import os
from pathlib import Path
testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_22')
if not os.path.exists(testfolder):
os.makedirs(testfolder)
print ("Your simulation will be stored in %s" % testfolder)
import bifacial_radiance
import numpy as np
... |
4,401 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
word2vec
This notebook is equivalent to demo-word.sh, demo-analogy.sh, demo-phrases.sh and demo-classes.sh from Google.
Training
Download some data, for example
Step1: Run word2phrase to gr... | Python Code:
import word2vec
Explanation: word2vec
This notebook is equivalent to demo-word.sh, demo-analogy.sh, demo-phrases.sh and demo-classes.sh from Google.
Training
Download some data, for example: http://mattmahoney.net/dc/text8.zip
End of explanation
word2vec.word2phrase('/Users/drodriguez/Downloads/text8', '/U... |
4,402 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Image Classification
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. You'll preprocess the images... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if present
floyd_cifa... |
4,403 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Pairs Trading
By Delaney Mackenzie and Maxwell Margenot
Part of the Quantopian Lecture Series
Step1: Generating Two Fake Securities
We model X's daily returns by drawing fro... | Python Code:
import numpy as np
import pandas as pd
import statsmodels
import statsmodels.api as sm
from statsmodels.tsa.stattools import coint
# just set the seed for the random number generator
np.random.seed(107)
import matplotlib.pyplot as plt
Explanation: Introduction to Pairs Trading
By Delaney Mackenzie and Maxw... |
4,404 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploratory Analysis Round 2
Now that we have looked at the data on an unfiltered way, we now take into account information we know about the data. For example, the channels, channel types, ... | Python Code:
# Import Necessary Libraries
import numpy as np
import os, csv, json
from matplotlib import *
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import scipy
from scipy.cluster.hierarchy import dendrogram, linkage
from sklearn.neighbors import KernelDensity
# pretty charting
impor... |
4,405 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simplified Detection Efficiency Model
Update to
Step1: Station coordinates and thresholds from a set of log files
Specify
Step2: Station coordinates from csv file
Input network title and c... | Python Code:
%pylab inline
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import parsed_functions as pf
from mpl_toolkits.basemap import Basemap
from coordinateSystems import TangentPlaneCartesianSystem, GeographicSystem, MapProjection
c0 = 3.0e8 # m/s
dt_rms = 23.e-9 # seconds
sq = np.load('sou... |
4,406 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id="top"></a>
Db2 11 Time and Date Functions
There are plenty of new date and time functions found in Db2 11. These functions allow you to extract portions from a date
and format the date... | Python Code:
%run db2.ipynb
Explanation: <a id="top"></a>
Db2 11 Time and Date Functions
There are plenty of new date and time functions found in Db2 11. These functions allow you to extract portions from a date
and format the date in a variety of different ways. While Db2 already has a number of date and time function... |
4,407 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
String Methods
In this lecture we are going to be looking at string methods in more detail. To simplify, a method is a function that are bound to a particular type of object. String methods,... | Python Code:
print("hello".upper()) # This works
print(str.upper()) # This returns an error, upper needs an argument
Explanation: String Methods
In this lecture we are going to be looking at string methods in more detail. To simplify, a method is a function that are bound to a particular type of object. String meth... |
4,408 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BC Grid Extrapolation
Testing errors generated by grid extrapolation for extremely cool spot bolometric corrections. A first test of this will be to use a more extensive Phoenix color grid t... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import LinearNDInterpolator
Explanation: BC Grid Extrapolation
Testing errors generated by grid extrapolation for extremely cool spot bolometric corrections. A first test of this will be to use a more extensive Pho... |
4,409 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classwork 3
Michael Seaman, Chinmai Raman, Austin Ayers, Taylor Patti
Organized by Andrew Malfavon
Excercise A.2
Step1: Chinmai Raman
Classwork 3
5.49 Experience Overflow in a Function
Calc... | Python Code:
n = 30
plt.plot([x for x in range(n)],p3.pi_sequence(n, p3.fa),'g.')
plt.show()
plt.plot([x for x in range(n)],p3.pi_sequence(n, p3.fb) ** .5 ,'b.')
plt.show()
plt.plot([x for x in range(n)],p3.pi_sequence(n, p3.fc) ** .25 ,'y.')
plt.show()
plt.plot([x for x in range(n)],p3.pi_sequence(n, p3.fd),'r.')
plt.... |
4,410 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The four adjacent digits in the 1000-digit number that have the greatest product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016... | Python Code:
from six.moves import map, range, reduce
Explanation: The four adjacent digits in the 1000-digit number that have the greatest product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208... |
4,411 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Inspired by the work of
Step1: 2. Project 5 data set import
This cell
Step2: 3. Print a dataset summary
This cell
Step3: 4. Exploratory visualization of the dataset
This cell
Step4: 5. G... | Python Code:
# Visualisation parameters
display_output = 1
train_verbose_style = 2 # 1 every training image, 2 once very epoch
# Training parameters
use_generator = 0
epoch_num = 30
train_model = 1
Explanation: Inspired by the work of:
https://medium.com/@tuennermann/convolutional-neural-networks-to-find-cars-43cbc4fb... |
4,412 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 3
Imports
Step2: Using interact for animation with data
A soliton is a constant velocity wave that maintains its shape as it propagates. They arise from non-linear wave eq... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Explanation: Interact Exercise 3
Imports
End of explanation
def soliton(x, t, c, a):
Return phi(x, t) for a soliton wave with cons... |
4,413 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Andrea Manzini, Lorenzo Lazzara, Martin Josifoski, Mazen Fouad A-wali Mahdi
1. Introduction and General Information
In this project, we analyze the LastFM dataset released in the framework o... | Python Code:
%load_ext autoreload
%autoreload 1
import numpy as np
import pickle
import matplotlib.pyplot as plt
import scipy as sp
import pandas as pd
import os.path
import networkx as nx
from scipy.sparse import csr_matrix
from Dataset import Dataset
from plots import *
import os
from helpers import *
%matplotlib inl... |
4,414 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The famous Monty Hall brain teaser
Step2: setting up a game
There are many ways to do this, but to keep it simple and human comprehensible I'm going to do it one game at a time.
First up, ... | Python Code:
import random
import numpy as np
# for plots, cause visuals
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
Explanation: The famous Monty Hall brain teaser:
Suppose you're on a game show, and you're given the choice of three doors: Behind one door is a car; behind the others, goat... |
4,415 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generate new columns with average block info
Take average values over two time horizons
6 blocks (~1 min) -> represents the current state (short frequency view)
60 blocks (~10 min) -> repres... | Python Code:
df['txcnt_second'] = df['tx_count'].values / df['blockTime'].values
df['avg_gasUsed_t_perblock'] = df.groupby('block_id')['gasUsed_t'].transform('mean')
df['avg_price_perblock'] = df.groupby('block_id')['price_gwei'].transform('mean')
def rolling_avg(window_size):
price = df[['block_id', 'avg_pric... |
4,416 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Self-Driving Car Engineer Nanodegree
Project
Step1: Read in an Image
Step9: Ideas for Lane Detection Pipeline
Some OpenCV functions (beyond those introduced in the lesson) that might be us... | Python Code:
#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
%matplotlib inline
Explanation: Self-Driving Car Engineer Nanodegree
Project: Finding Lane Lines on the Road
In this project, you will use the tools you learned about in the lesson... |
4,417 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Begin testing here
Step1: As given by newport (https
Step2: So we should expect about 0.25 maximum intensity through our 780 waveplate.
tinkering below here | Python Code:
qwp = np.matrix([[1, 0],[0, -1j]])
R(-np.pi/4)*qwp*R(np.pi/4)
qwp45 = wp(np.pi/2, np.pi/4)
qwp45
wp(np.pi/2, 0)
vpol = np.matrix([[0,0],[0,1]])
vpol
np.exp(1j*np.pi/4)
horiz = np.matrix([[1],[0]])
output = qwp*horiz
intensity(output)
before_cell = wp(np.pi/2,np.pi/4)*wp(np.pi,np.pi/10)*horiz
output = vpol*... |
4,418 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Batch Normalization – Practice
Batch normalization is most useful when building deep neural networks. To demonstrate this, we'll create a convolutional neural network with 20 convolutional l... | Python Code:
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True, reshape=False)
Explanation: Batch Normalization – Practice
Batch normalization is most useful when building deep neural networks. To demonstra... |
4,419 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Say I have these 2D arrays A and B. | Problem:
import numpy as np
A=np.asarray([[1,1,1], [1,1,2], [1,1,3], [1,1,4]])
B=np.asarray([[0,0,0], [1,0,2], [1,0,3], [1,0,4], [1,1,0], [1,1,1], [1,1,4]])
dims = np.maximum(B.max(0),A.max(0))+1
result = A[~np.in1d(np.ravel_multi_index(A.T,dims),np.ravel_multi_index(B.T,dims))]
output = np.append(result, B[~np.in1d(np... |
4,420 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.e - Correction de l'interrogation écrite du 26 septembre 2015
tests, boucles, fonctions
Step1: Enoncé 1
Q1
Le programme suivant provoque une erreur pourquoi ?
Step2: On découvre le prob... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.e - Correction de l'interrogation écrite du 26 septembre 2015
tests, boucles, fonctions
End of explanation
tab = [1, 3]
for i in range(0, len(tab)):
print(tab[i] + tab[i+1])
Explanation: Enoncé 1
Q1
Le programme suivant pro... |
4,421 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Manuscript3 - Analysis of Intrinsic Network FC Properties for Fig. 3
Master code for Ito et al., 2017¶
Takuya Ito (takuya.ito@rutgers.edu)
Step1: 1.0 Basic parameters
Step2: 2.0 Compute ou... | Python Code:
import sys
sys.path.append('utils/')
import numpy as np
import loadGlasser as lg
import scipy.stats as stats
from IPython.display import display, HTML
import matplotlib.pyplot as plt
import statsmodels.sandbox.stats.multicomp as mc
import sys
import multiprocessing as mp
import pandas as pd
import multregr... |
4,422 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple example of local processing
In this first tutorial we will show a complete example of usage of the library using some example datasets provided with it.
Importing the library
Importin... | Python Code:
import gmql as gl
Explanation: Simple example of local processing
In this first tutorial we will show a complete example of usage of the library using some example datasets provided with it.
Importing the library
Importing the library
End of explanation
dataset1 = gl.get_example_dataset("Example_Dataset_1"... |
4,423 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Hierarchical model for Rugby prediction
Step2: This is a Rugby prediction exercise. So we'll input some data
Step3: The model.
<p>The league is made up by a total of T= 6 teams, playing ... | Python Code:
!date
import numpy as np
import pandas as pd
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
%matplotlib inline
import pymc3 as pm3, theano.tensor as tt
Explanation: A Hierarchical model for Rugby prediction
End of explanation
data_csv = StringIO(home_team,away_team,h... |
4,424 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sun-Earth System
NOTE
Step1: As always, let's do imports and initialize a logger and a new bundle. See Building a System for more details.
Step2: Setting Parameters
Step3: Running Comput... | Python Code:
!pip install -I "phoebe>=2.1,<2.2"
Explanation: Sun-Earth System
NOTE: planets are currently under testing and not yet supported
Setup
Let's first make sure we have the latest version of PHOEBE 2.1 installed. (You can comment out this line if you don't use pip for your installation or don't want to update ... |
4,425 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
4,426 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
eDisGo basic example
This example shows you the first steps with eDisGo. Grid expansion costs for an example distribution grid are calculated assuming renewable and conventional power plant ... | Python Code:
import os
import sys
import pandas as pd
from edisgo import EDisGo
Explanation: eDisGo basic example
This example shows you the first steps with eDisGo. Grid expansion costs for an example distribution grid are calculated assuming renewable and conventional power plant capacities as stated in the scenario ... |
4,427 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Acceptance conditions
The acceptance condition of an automaton specifies which of its paths are accepting.
The way acceptance conditions are stored in Spot is derived from the way acceptance... | Python Code:
spot.mark_t()
spot.mark_t([0, 2, 3])
spot.mark_t((0, 2, 3))
Explanation: Acceptance conditions
The acceptance condition of an automaton specifies which of its paths are accepting.
The way acceptance conditions are stored in Spot is derived from the way acceptance conditions are specified in the HOA format.... |
4,428 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2A.ml - Classification binaire avec features textuelles
Ce notebook propose de voir comment incorporer des features pour voir l'amélioration des performances sur une classification binaire.
... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 2A.ml - Classification binaire avec features textuelles
Ce notebook propose de voir comment incorporer des features pour voir l'amélioration des performances sur une classification binaire.
End of explanation
from pyensae.datasour... |
4,429 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 Google LLC.
Step1: <a href="https
Step2: Explore checkpoints
This section contains shows how to use the index.csv table for model
selection.
See
vit_jax.checkpoint.get_augre... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# 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 r... |
4,430 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lecture 11. Going fast
Step1: Question
What is the typical size of particle system?
Millenium run
One of the most famous N-body computations is the Millenium run
More than 10 billions parti... | Python Code:
import numpy as np
import math
from numba import jit
N = 10000
x = np.random.randn(N, 2);
y = np.random.randn(N, 2);
charges = np.ones(N)
res = np.zeros(N)
@jit
def compute_nbody_direct(N, x, y, charges, res):
for i in xrange(N):
res[i] = 0.0
for j in xrange(N):
dist = (x[i,... |
4,431 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LAB 3b
Step1: Lab Task #1
Step2: Create two SQL statements to evaluate the model.
Step3: Lab Task #2
Step4: Create three SQL statements to EVALUATE the model.
Let's now retrieve the trai... | Python Code:
%%bigquery
-- LIMIT 0 is a free query; this allows us to check that the table exists.
SELECT * FROM babyweight.babyweight_data_train
LIMIT 0
%%bigquery
-- LIMIT 0 is a free query; this allows us to check that the table exists.
SELECT * FROM babyweight.babyweight_data_eval
LIMIT 0
Explanation: LAB 3b: BigQ... |
4,432 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Grove Light Sensor 1.1
This example shows how to use the Grove Light Sensor v1.1. You will also see how to plot a graph using matplotlib.
The Grove Light Sensor produces an analog signal whi... | Python Code:
from pynq.overlays.base import BaseOverlay
base = BaseOverlay("base.bit")
Explanation: Grove Light Sensor 1.1
This example shows how to use the Grove Light Sensor v1.1. You will also see how to plot a graph using matplotlib.
The Grove Light Sensor produces an analog signal which requires an ADC.
The Grove ... |
4,433 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Target selection bits and bitmasks
Author
Step1: The mask contains the name of the target bit (e.g. ELG) the bit value to which that name corresponds (e.g. 1, meaning 2-to-the-power-1), a d... | Python Code:
from desitarget.targets import desi_mask, bgs_mask, mws_mask
print(desi_mask)
Explanation: Target selection bits and bitmasks
Author: Adam D. Myers, University of Wyoming
This Notebook describes how to work with target selection bitmasks for DESI.
Setting up your environment
First, ensure that your environ... |
4,434 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1.x to 3.x Rule Migration Guide
This guide describes changes needed for rules to run under Insights Core 3.x.
It covers the following topics
Step1: @rule Example
Step2: <a id="filtering"><... | Python Code:
# Boilerplate used in later cells
# Not necessary for new rules.
from pprint import pprint
from insights.core import dr
from insights.core.filters import add_filter, get_filters
from insights.core.context import HostContext
from insights.core.plugins import make_response, rule
dr.load_components("insights.... |
4,435 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Automating image building
We saw in the last notebook how we can build images of our funwave-tvd code and use Agave to make the process a bit easier. We can take some lessons learned ... | Python Code:
writefile("funwave-tvd-docker-automation/Dockerfile",
FROM stevenrbrandt/science-base
MAINTAINER Steven R. Brandt <sbrandt@cct.lsu.edu>
ARG BUILD_DATE
ARG VERSION
LABEL org.agaveplatform.ax.architecture="x86_64" \
org.agaveplatform.ax.build-date="\$BUILD_DATE" ... |
4,436 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div style="width
Step1: Import Python libraries
Step2: Display options
Step3: Set directories
Step4: Chromedriver
If you want to download from sources which require scraping, download t... | Python Code:
version = '2020-10-06'
changes = '''Yearly update'''
Explanation: <div style="width:100%; background-color: #D9EDF7; border: 1px solid #CFCFCF; text-align: left; padding: 10px;">
<b>Time series: Processing Notebook</b>
<ul>
<li><a href="main.ipynb">Main Notebook</a></li>
<li>Pro... |
4,437 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting started
Step1: Creating the model
First, we need to decide on the model type. For the given example, we are working with a continuous model.
Step2: The model is based on the assump... | Python Code:
import numpy as np
from casadi import *
# Add do_mpc to path. This is not necessary if it was installed via pip.
import sys
sys.path.append('../../')
# Import do_mpc package:
import do_mpc
Explanation: Getting started: MHE
Open an interactive online Jupyter Notebook with this content on Binder:
In this Jup... |
4,438 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Probability Authors.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: {TF Probability、R、Stan} における線形混合効果回帰
<table class="tfo-notebook-but... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License"); { display-mode: "form" }
# 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... |
4,439 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Préambule
Step2: Exercice Robozzle | Python Code:
if (cas simple):
(solution immédiate)
else:
(solution récursive,
impliquant un cas plus simple que le problème original)
Explanation: Préambule : nous avons commencé par faire un rappel sur la récursivité en ré-écrivant le comportement de factorielle au tableau et en déroulant l'algorithme à l... |
4,440 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Record, Save, and Play Moves on a Poppy Creature
This notebook is still work in progress! Feedbacks are welcomed!
In this tutorial we will show how to
Step1: Import the Move, Recorder and P... | Python Code:
from pypot.creatures import PoppyErgo
poppy = PoppyErgo()
for m in poppy.motors:
m.compliant = False
m.goal_position = 0.0
Explanation: Record, Save, and Play Moves on a Poppy Creature
This notebook is still work in progress! Feedbacks are welcomed!
In this tutorial we will show how to:
* record mo... |
4,441 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exact solution used in MES runs
We would like to MES the operation
$$
J\nabla \cdot \mathbf{f}_\perp
$$
Using cylindrical geometry.
Step1: Initialize
Step2: Define the variables
Step3: De... | Python Code:
%matplotlib notebook
from sympy import init_printing
from sympy import S
from sympy import sin, cos, tanh, exp, pi, sqrt
from boutdata.mms import x, y, z, t
from boutdata.mms import Delp2, DDX, DDY, DDZ
import os, sys
# If we add to sys.path, then it must be an absolute path
common_dir = os.path.abspath('.... |
4,442 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Optimisation
Step1: As before, we can define an error function and minimise it
Step2: We could also however define the inference problem statistically, by specifying a likelihood.
Step3: ... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pints
import pints.toy as toy
# Create a model
model = toy.LogisticModel()
# Set some parameters
real_parameters = [0.1, 50]
# Create fake data
times = model.suggested_times()
values = model.simulate(real_parameters, times)
sigma = 3
noisy_values = ... |
4,443 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Energy Meter Examples
BayLibre's ACME Cape and IIOCapture
More information can be found at https
Step1: Import required modules
Step2: Target Configuration
The target configuration is used... | Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
Explanation: Energy Meter Examples
BayLibre's ACME Cape and IIOCapture
More information can be found at https://github.com/ARM-software/lisa/wiki/Energy-Meters-Requirements#iiocapture---baylibre-acme-cape.
End of explanation
# Generate plots i... |
4,444 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook is a simulation of 5000 ms of 400 independent descending commands following a gamma distribution with mean of 12 ms and order 10 and the Soleus muscle (800 motoneurons). Each d... | Python Code:
import sys
sys.path.insert(0, '..')
import time
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import set_matplotlib_formats
set_matplotlib_formats('pdf', 'png')
plt.rcParams['savefig.dpi'] = 75
plt.rcParams['figure.autolayout'] = False
plt.rcParams['figure.figsize'] = 10, 6
plt.... |
4,445 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Superradiance in the open Dicke model
Step1: Wigner Function
Below we calculate the Wigner function of the photonic part of the steady state. It shows two displaced squeezed states in the r... | Python Code:
import matplotlib as mpl
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np
from qutip import *
from qutip.piqs import *
#TLS parameters
N = 6
ntls = N
nds = num_dicke_states(ntls)
[jx, jy, jz] = jspin(N)
jp = jspin(N,"+")
jm = jp.dag()
w0 = 1
gE = 0.1
gD = 0.01
h = w0 * jz
#photo... |
4,446 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Collaborative filtering example
collab models use data in a DataFrame of user, items, and ratings.
Step1: That's all we need to create and train a model
Step2: Movielens 100k
Let's try wit... | Python Code:
user,item,title = 'userId','movieId','title'
path = untar_data(URLs.ML_SAMPLE)
path
ratings = pd.read_csv(path/'ratings.csv')
ratings.head()
Explanation: Collaborative filtering example
collab models use data in a DataFrame of user, items, and ratings.
End of explanation
dls = CollabDataLoaders.from_df(rat... |
4,447 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
통계적 사고 (2판) 연습문제 (thinkstats2.com, think-stat.xwmooc.org)<br>
Allen Downey / 이광춘(xwMOOC)
Step3: 연습문제 12.1
이번 장에서 저자가 사용한 선형모형은 선형이라는 명백한 결점이 있고, 가격이 시간에 따라 선형으로 변할 것이라고 예측할 이유는 없다. 11.3 절에서... | Python Code:
from __future__ import print_function
import pandas
import numpy as np
import statsmodels.formula.api as smf
import thinkplot
import thinkstats2
import regression
import timeseries
%matplotlib inline
Explanation: 통계적 사고 (2판) 연습문제 (thinkstats2.com, think-stat.xwmooc.org)<br>
Allen Downey / 이광춘(xwMOOC)
End o... |
4,448 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Elemento Truss
El elemento Truss plano es un elemento finito con coordenadas locales y globales, tiene un modulo de elasticidad $E$, una sección transversal $A$ y una longitud $L$. Cada elem... | Python Code:
%matplotlib inline
from nusa import * # Importando nusa
E,A = 210e9, 3.1416*(10e-3)**2
n1 = Node((0,0))
n2 = Node((2,0))
n3 = Node((0,2))
e1 = Truss((n1,n2),E,A)
e2 = Truss((n1,n3),E,A)
e3 = Truss((n2,n3),E,A)
m = TrussModel()
for n in (n1,n2,n3): m.add_node(n)
for e in (e1,e2,e3): m.add_element(e)
m.add_c... |
4,449 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Análise Nodal com Fontes de Tensão
Jupyter Notebook desenvolvido por Gustavo S.S.
Um supernó é formado envolvendo-se uma fonte de tensão (dependente
ou independente) conectada entre dois nós... | Python Code:
print("Exemplo 3.3")
import numpy as np
from sympy import *
Vsource = 2
Csource1 = 2
Csource2 = 7
R1 = 2
R2 = 4
R3 = 10
#i1 = v1/R1 = v1/2
#i2 = v2/R2 = v2/4
#i1 + i2 + 7 = 2 => i1 + i2 = -5
#v2 - v1 = 2
#v1/2 + v2/4 = -5 => (v2 - 2)/2 + v2/4 = - 5
#3v2/4 = -4
v2 = -16/3
v1 = v2 - 2
print("V1:", v1, "V")
p... |
4,450 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Simple Image Classification Problem using Keras (dog_vs_cat)
Step1: Data Preprocessing
Step2: Define an architecture - > Feed Forward Network of dimension "3072-768-384-2" | Python Code:
# import the necessary packages
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from keras.models import Sequential
from keras.layers import Activation
from keras.optimizers import SGD
from keras.layers import Dense
from keras.utils import np_utils
from i... |
4,451 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mahalanobis Distance
This notebook shows how I think we should do Mahalanobis distance for the SECIM project. From JMP Website
Step1: Generation of a simulated data set
As an example I will... | Python Code:
import pandas as pd
import numpy as np
import scipy as sp
import scipy.stats as stats
import matplotlib.pyplot as plt
import cPickle as pickle
import os
%matplotlib inline
Explanation: Mahalanobis Distance
This notebook shows how I think we should do Mahalanobis distance for the SECIM project. From JMP Web... |
4,452 | 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: W... | Python Code:
# Author: Annalisa Pascarella <a.pascarella@iac.cnr.it>
#
# License: BSD (3-clause)
import os.path as op
import matplotlib.pyplot as plt
from nilearn import plotting
import mne
from mne.minimum_norm import make_inverse_operator, apply_inverse
# Set dir
data_path = mne.datasets.sample.data_path()
subject = ... |
4,453 | 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: How to use the GFSA layer for new tasks
This notebook describes the high-level process for ... | 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... |
4,454 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Model understanding and interpretability
In this colab, we will
- Will learn how to interpret model results and reason about the features
- Visualize the model results
Please complete the e... | Python Code:
import time
# We will use some np and pandas for dealing with input data.
import numpy as np
import pandas as pd
# And of course, we need tensorflow.
import tensorflow as tf
from matplotlib import pyplot as plt
from IPython.display import clear_output
tf.__version__
Explanation: Model understanding and int... |
4,455 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Statistics
There are many specialized packages for dealing with data analysis and statistical programming. One very important code that you will see in MATH1024, Introduction to Probability ... | Python Code:
!head southampton_precip.txt
Explanation: Statistics
There are many specialized packages for dealing with data analysis and statistical programming. One very important code that you will see in MATH1024, Introduction to Probability and Statistics, is R. A Python package for performing similar analysis of l... |
4,456 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Statistics Fundamentals
Statistics is primarily about analyzing data samples, and that starts with udnerstanding the distribution of data in a sample.
Analyzing Data Distribution
A great dea... | Python Code:
import pandas as pd
df = pd.DataFrame({'Name': ['Dan', 'Joann', 'Pedro', 'Rosie', 'Ethan', 'Vicky', 'Frederic'],
'Salary':[50000,54000,50000,189000,55000,40000,59000]})
print (df['Salary'].mean())
Explanation: Statistics Fundamentals
Statistics is primarily about analyzing data samples, ... |
4,457 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TensorFlow Tutorial
Welcome to this week's programming assignment. Until now, you've always used numpy to build neural networks. Now we will step you through a deep learning framework that w... | Python Code:
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.python.framework import ops
from tf_utils import load_dataset, random_mini_batches, convert_to_one_hot, predict
%matplotlib inline
np.random.seed(1)
Explanation: TensorFlow Tutorial
Welcome to... |
4,458 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: ¿Por qué PyCUDA?
Hasta ahora hemos visto que si bien CUDA no es un lenguaje imposible de aprender, puede llegar a ser un dolor de cabeza el tener muchos apuntadores y manejar la memor... | Python Code:
import pycuda.autoinit
import pycuda.driver as drv
import numpy
from pycuda.compiler import SourceModule
mod = SourceModule(
__global__ void multiplicar(float *dest, float *a, float *b)
{
const int i = threadIdx.x;
dest[i] = a[i] * b[i];
}
)
multiplicar = mod.get_function("multiplicar")
a = numpy.rando... |
4,459 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clase 4
Step1: 2. Uso de Pandas para descargar datos de precios de cierre
Ahora, en forma de función
Step2: Una vez cargados los paquetes, es necesario definir los tickers de las acciones ... | Python Code:
#importar los paquetes que se van a usar
import pandas as pd
import pandas_datareader.data as web
import numpy as np
import datetime
from datetime import datetime
import scipy.stats as stats
import scipy as sp
import scipy.optimize as scopt
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib ... |
4,460 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute
Now that we have datasets added to our Bundle, our next step is to run the forward model and compute a synthetic model for each of these datasets.
Setup
Let's first make sure we have... | Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
Explanation: Compute
Now that we have datasets added to our Bundle, our next step is to run the forward model and compute a synthetic model for each of these datasets.
Setup
Let's first make sure we have the latest version of PHOEBE 2.4 installed (uncomment this line if ... |
4,461 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id='beginning'></a> <!--\label{beginning}-->
* Outline
* Glossary
* 4. The Visibility Space
* Previous
Step1: Import section specific modules
Step2: 4.5.1 UV coverage
Step3: Let's... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
Explanation: <a id='beginning'></a> <!--\label{beginning}-->
* Outline
* Glossary
* 4. The Visibility Space
* Previous: 4.4 The Visibility Function
... |
4,462 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting topographic maps of evoked data
Load evoked data and plot topomaps for selected time points using multiple
additional options.
Step1: Basic
Step2: If times is set to None at most... | Python Code:
# Authors: Christian Brodbeck <christianbrodbeck@nyu.edu>
# Tal Linzen <linzen@nyu.edu>
# Denis A. Engeman <denis.engemann@gmail.com>
# Mikołaj Magnuski <mmagnuski@swps.edu.pl>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import ... |
4,463 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Acoustic system calibration
Since the calibration measurements may be dealing with very small values, there's potential for running into the limitations of <a href="https
Step1: Calculating... | Python Code:
%matplotlib inline
from scipy import signal
from scipy import integrate
import pylab as pl
import numpy as np
Explanation: Acoustic system calibration
Since the calibration measurements may be dealing with very small values, there's potential for running into the limitations of <a href="https://docs.oracle... |
4,464 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning
Step1: Writing the objective function
We can decompose the objective function as the sum of a least squares loss function and an $\ell_1$ regularizer.
Step2: Generating da... | Python Code:
import cvxpy as cp
import numpy as np
import matplotlib.pyplot as plt
Explanation: Machine Learning: Lasso Regression
Lasso regression is, like ridge regression, a shrinkage method. It differs from ridge regression in its choice of penalty: lasso imposes an $\ell_1$ penalty on the paramters $\beta$. That i... |
4,465 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Heap
La structure heap ou tas en français est utilisée pour trier. Elle peut également servir à obtenir les k premiers éléments d'une liste.
Step1: Un tas est peut être considéré comme un t... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: Heap
La structure heap ou tas en français est utilisée pour trier. Elle peut également servir à obtenir les k premiers éléments d'une liste.
End of explanation
%matplotlib inline
Explanation: Un tas est peut être considéré comme u... |
4,466 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dans ce notebook je récupère une liste de chocs Tore Supra obtenue avec Ged.
Pour chacun de ces chocs, je récupère les signaux de puissance FCI, et j'en déduis la puissance couplée max et l... | Python Code:
from pywed import * # Tore Supra database library
%pylab inline
pulse_list = np.loadtxt('data/liste_choc_fci.txt', dtype=int)
pulse_list = np.arange(44092, 48311, dtype='int')
ts_max_power = []
ts_max_duration = []
for pulse in pulse_list:
#print('Retrieve date for pulse {}'.format(pulse))
# retrie... |
4,467 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What is the true normal human body temperature?
Background
The mean normal body temperature was held to be 37$^{\circ}$C or 98.6$^{\circ}$F for more than 120 years since it was first concept... | Python Code:
import pandas as pd
%matplotlib inline
df = pd.read_csv('data/human_body_temperature.csv')
Explanation: What is the true normal human body temperature?
Background
The mean normal body temperature was held to be 37$^{\circ}$C or 98.6$^{\circ}$F for more than 120 years since it was first conceptualized and r... |
4,468 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Week 4
Step1: Load in house sales data
Dataset is from house sales in King County, the region where the city of Seattle, WA is located.
Step2: If we want to do any "feature engi... | Python Code:
import graphlab
Explanation: Regression Week 4: Ridge Regression (gradient descent)
In this notebook, you will implement ridge regression via gradient descent. You will:
* Convert an SFrame into a Numpy array
* Write a Numpy function to compute the derivative of the regression weights with respect to a sin... |
4,469 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Random forest parameter-tuning
Table of contents
Data preprocessing
Validation curves
KS-test tuning
Step1: Data preprocessing
Load simulation dataframe and apply specified quality cuts
Ext... | Python Code:
import sys
sys.path.append('/home/jbourbeau/cr-composition')
print('Added to PYTHONPATH')
from __future__ import division, print_function
from collections import defaultdict
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import seaborn.ap... |
4,470 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multi-label data stratification
With the development of more complex multi-label transformation methods the community realizes how much the quality of classification depends on how the data ... | Python Code:
from skmultilearn.dataset import load_dataset
X,y, _, _ = load_dataset('scene', 'undivided')
Explanation: Multi-label data stratification
With the development of more complex multi-label transformation methods the community realizes how much the quality of classification depends on how the data is split in... |
4,471 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First Step
Step1: Now, we have the data stored as a DataFrame titled "imdb". As a simple first step, we'd like to see the structure of this DataFrame. We'll use different ways to do this ("... | Python Code:
imdb = pd.DataFrame.from_csv('imdb.csv', index_col=None)
Explanation: First Step: Get the data from storage into the dataframe.
Simple and easy method: pd.DataFrame.from_csv
* CSV: Comma Separated Values, used in spreadsheets. Popular for import & export of smaller datasets.
* Arguments: path-locat... |
4,472 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: TPU 사용하기
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: TPU 초기화
TPU는 일반적으로 사용자 파이썬 프로그램을 실행하는 로... | 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... |
4,473 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 2
Imports
Step1: Plotting with parameters
Write a plot_sin1(a, b) function that plots $sin(ax+b)$ over the interval $[0,4\pi]$.
Customize your visualization to make it eff... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Explanation: Interact Exercise 2
Imports
End of explanation
t=np.linspace(0,4*np.pi,250)
def plot_sine1(a, b):
plt.figure(figsize=... |
4,474 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Calculating Ground Motion Intensity Measures
The SMTK contains two modules for the characterisation of ground motion
Step1: Get Response Spectrum - Nigam & Jennings
Step2: Plot Time Series... | Python Code:
# Import modules
%matplotlib inline
import numpy as np # Numerical Python package
import matplotlib.pyplot as plt # Python plotting package
# Import
import smtk.response_spectrum as rsp # Response Spectra tools
import smtk.intensity_measures as ims # Intensity Measure Tools
periods = np.array([0.01, 0.02,... |
4,475 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Alternative More Detailed Solution for Lab01 - Task C
Step1: First try - Computing the probability using for loops
The following was not clear in the instructions
Step2: And it works prett... | Python Code:
%matplotlib inline
import numpy as np
from numpy.random import rand, randn
import matplotlib.pyplot as plt
%load_ext autoreload
%autoreload 2
# Data generation
n, d, k = 100, 2, 2
np.random.seed(20)
X = rand(n, d)
means = [rand(d) * 0.5 + 0.5 , - rand(d) * 0.5 + 0.5] # for better plotting when k = 2
S = ... |
4,476 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="http
Step1: From Landlab, we'll need a grid on which to plot data, and a plotting function. We'll start with just imshow_grid, but be aware that similar but more specifically named... | Python Code:
import numpy as np
Explanation: <a href="http://landlab.github.io"><img style="float: left" src="../../landlab_header.png"></a>
Plotting grid data with Landlab
<hr>
<small>For more Landlab tutorials, click here: <a href="https://landlab.readthedocs.io/en/latest/user_guide/tutorials.html">https://landlab.re... |
4,477 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MachineLearningWorkShop at UCSC
Aug 18th - Learning with TESS Simulated data
Last month we explored all type of learning algorithms with simulated light curves including
Step1: Let's first ... | Python Code:
import sklearn
from sklearn.linear_model import LogisticRegression
from sklearn.cross_validation import train_test_split
from sklearn.utils import shuffle
from sklearn import metrics
from sklearn.metrics import roc_curve
from sklearn.metrics import classification_report
from sklearn.decomposition import PC... |
4,478 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Process Discovery
by
Step1: Observe that the process model that we discovered, describes the same behavior as the model that we have shown above.
As indicated, the algorithm used in this ex... | Python Code:
import pandas as pd
import pm4py
df = pm4py.format_dataframe(pd.read_csv('data/running_example.csv', sep=';'), case_id='case_id',activity_key='activity',
timestamp_key='timestamp')
bpmn_model = pm4py.discover_bpmn_inductive(df)
pm4py.view_bpmn(bpmn_model)
Explanation: Process D... |
4,479 | 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', 'awi', 'sandbox-3', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: AWI
Source ID: SANDBOX-3
Topic: Seaice
Sub-Topics: Dynamics, Thermodynamics,... |
4,480 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data and Data Visualization
Machine learning, and therefore a large part of AI, is based on statistical analysis of data. In this notebook, you'll examine some fundamental concepts related t... | Python Code:
import statsmodels.api as sm
df = sm.datasets.get_rdataset('GaltonFamilies', package='HistData').data
df
Explanation: Data and Data Visualization
Machine learning, and therefore a large part of AI, is based on statistical analysis of data. In this notebook, you'll examine some fundamental concepts related ... |
4,481 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">Registration Settings
Step1: Read the RIRE data and generate a larger point set as a reference
Step2: Initial Alignment
We use the CenteredTransformInitializer. Should w... | Python Code:
import SimpleITK as sitk
# Utility method that either downloads data from the network or
# if already downloaded returns the file name for reading from disk (cached data).
from downloaddata import fetch_data as fdata
# Always write output to a separate directory, we don't want to pollute the source directo... |
4,482 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Widgets in a Jupyter Notebook
An example of using version 4.x widgets in a Jupyter Notebook.
Reference
Step1: Define a sine wave
Step2: Plot the sine wave
Step3: Define a function that al... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from ipywidgets import interact
Explanation: Widgets in a Jupyter Notebook
An example of using version 4.x widgets in a Jupyter Notebook.
Reference: https://ipywidgets.readthedocs.io/en/latest/.
Depending on the current state of your Pyt... |
4,483 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The purpose of this notebook is twofold. First, it demonstrates the basic functionality of PyLogit for estimating nested logit models. Secondly, it compares the nested logit capabilities of ... | Python Code:
from collections import OrderedDict # For recording the model specification
import pandas as pd # For file input/output
import numpy as np # For vectorized math operations
import statsmodels.tools.numdiff as numdiff # For numeric hessian
import scipy.linalg ... |
4,484 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Language Translation
In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset o... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
Explanation: Language Translation
In this project, you’re going ... |
4,485 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Radiation Forces on Circumplanetary Dust
This example shows how to integrate circumplanetary dust particles under the action of radiation forces. We use Saturn's Phoebe ring as an example, ... | Python Code:
import rebound
import reboundx
import numpy as np
sim = rebound.Simulation()
sim.G = 6.674e-11 # SI units
sim.dt = 1.e4 # Initial timestep in sec.
sim.N_active = 2 # Make it so dust particles don't interact with one another gravitationally
sim.add(m=1.99e30, hash="Sun") # add Sun with mass in kg
sim.add(m=... |
4,486 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stacks Getting Started
Welcome to the Subinitial Stacks Getting Started Guide!
This document will guide you through setup of the Stacks and your first script.
Useful Links
Official Hardware ... | Python Code:
!pip3 install --user git+https://bitbucket.org/subinitial/subinitial.git
Explanation: Stacks Getting Started
Welcome to the Subinitial Stacks Getting Started Guide!
This document will guide you through setup of the Stacks and your first script.
Useful Links
Official Hardware Getting Started Guide
Official ... |
4,487 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction GPU
Chainer とはニューラルネットの実装を簡単にしたフレームワークです。
今回は言語の分野でニューラルネットを適用してみました。
今回は言語モデルを作成していただきます。
言語モデルとはある単語が来たときに次の単語に何が来やすいかを予測するものです。
言語モデルにはいくつか種類があるのでここでも紹介しておきます。
n-グラム言語モデル
単語の... | Python Code:
import time
import math
import sys
import pickle
import copy
import os
import re
import numpy as np
from chainer import cuda, Variable, FunctionSet, optimizers
import chainer.functions as F
Explanation: Introduction GPU
Chainer とはニューラルネットの実装を簡単にしたフレームワークです。
今回は言語の分野でニューラルネットを適用してみました。
今回は言語モデルを作成していただきます。
... |
4,488 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GPFlow first approximation
Step1: Simulating Data
Simulate random uniform 4-d vector. Give N of this.
Step2: Calculate distance
X can be interpreted as covariate matrix in which the first ... | Python Code:
## Import modules
import numpy as np
import scipy.spatial.distance as sp
from matplotlib import pyplot as plt
plt.style.use('ggplot')
## Parameter definitions
N = 1000
phi = 0.05
sigma2 = 1.0
beta_0 = 10.0
beta_1 = 1.5
beta_2 = -1.0
# AL NAGAT
nugget = 0.03
Explanation: GPFlow first approximation
End of ex... |
4,489 | 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', 'cas', 'sandbox-1', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: CAS
Source ID: SANDBOX-1
Topic: Ocnbgchem
Sub-Topics: Tracers.
Proper... |
4,490 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Running a Tapas fine-tuned checkpoint
This notebook shows how to load and make predictions with TAPAS model, which was introduced in the paper
Step2: Fetch models fom... | Python Code:
# Copyright 2019 The Google AI Language Team 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... |
4,491 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
From here is seems clear that the criteria necessary to satisfy the "suspect" condition are relatively narrow, and the real issue is whether or not poor photometry significantly affects the ... | Python Code:
print("Of the {} mean det sources, {} have suspect, and {} have poor photometry".format(sum(mean_det), sum(mean_det & suspect_phot), sum(mean_det & poor_phot)))
Explanation: From here is seems clear that the criteria necessary to satisfy the "suspect" condition are relatively narrow, and the real issue is ... |
4,492 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Molecular Dynamics
Step1: Basics of Molecular Dynamics | Python Code:
from IPython.core.display import HTML
css_file = 'https://raw.githubusercontent.com/ngcm/training-public/master/ipython_notebook_styles/ngcmstyle.css'
HTML(url=css_file)
Explanation: Molecular Dynamics: Lab 1
In part based on Fortran code from Furio Ercolessi.
End of explanation
%matplotlib inline
import n... |
4,493 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
7 - Advanced topics - Multiple SceneObjects Example
This journal shows how to
Step1: <a id='step1a'></a>
A. Generating the first scene object
This is a standard fixed-tilt setup for one hou... | Python Code:
import os
import numpy as np
import pandas as pd
from pathlib import Path
testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_07')
if not os.path.exists(testfolder):
os.makedirs(testfolder)
print ("Your simulation will be stored in %s" % testfolder)
from... |
4,494 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Optimisation in a transformed parameter space
This example shows you how to run an optimisation in a transformed parameter space, using a pints.Transformation object.
Parameter transformatio... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pints
import pints.toy as toy
# Set some random seed so this notebook can be reproduced
np.random.seed(10)
# Load a logistic forward model
model = toy.LogisticModel()
Explanation: Optimisation in a transformed parameter space
This example shows you ... |
4,495 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Teorema da Convolução
Convolução periódica
Antes de falarmos sobre o Teorema da Convolução, precisamos entender a convolução periódica (pconv). Até agora, vimos a convolução linear (conv ou ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
from numpy.fft import *
import sys,os
ia898path = os.path.abspath('../../')
if ia898path not in sys.path:
sys.path.append(ia898path)
import ia898.src as ia
f = np.array([[1,0,0,0,0,0,0,0,0],
... |
4,496 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Contact Binary with Spots
Setup
Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't w... | Python Code:
!pip install -I "phoebe>=2.2,<2.3"
%matplotlib inline
Explanation: Contact Binary with Spots
Setup
Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
End of expla... |
4,497 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Updating Plots
bqplot is an interactive plotting library. Attributes of plots can be updated in place without recreating the whole figure and marks. Let's look at idiomatic ways of updating ... | Python Code:
import numpy as np
import bqplot.pyplot as plt
x = np.linspace(-10, 10, 100)
y = np.sin(x)
fig = plt.figure()
line = plt.plot(x=x, y=y)
fig
Explanation: Updating Plots
bqplot is an interactive plotting library. Attributes of plots can be updated in place without recreating the whole figure and marks. Let's... |
4,498 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Java vs Python
Who am I?
Cesare Placanica
Cisco Photonics NMTG group.
Java developer since 2010 (Java 1.5/1.7, Spring, Hibernate and Tomcat).
Previously C/C++ embedded RTOSes.
Python Wannabe... | Python Code:
"Elapsed decorator."
import datetime
def elapsed(func):
"Elapsed decorator"
def _wrapper(*args, **kwargs):
"Decoration function"
start = datetime.datetime.now()
ret = func(*args, **kwargs)
print("Elapsed time", datetime.datetime.now() - start)
return ret
... |
4,499 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What's New in Marvin 2.2!
Lots of things are new in Marvin 2.2.0. See the list with links to individual sections here http
Step1: Smarter handling of inputs
You can still specify plateifu,... | Python Code:
%matplotlib inline
from marvin import config
config.switchSasUrl('local')
config.forceDbOff()
from marvin.tools.cube import Cube
plateifu='8485-1901'
cube = Cube(plateifu=plateifu)
print(cube)
maps = cube.getMaps(bintype='HYB10')
print(maps)
Explanation: What's New in Marvin 2.2!
Lots of things are new in ... |
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