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800 | <SYSTEM_TASK:>
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Description:
Tarea 1
Step1: Ejercicio1
Escribe los metodos repr y str para la clase Array de forma que se imprima legiblemente como en numpy arrays.
Step2: Ejerci... | <ASSISTANT_TASK:>
Python Code:
class Array:
"Una clase minima para algebra lineal"
def __init__(self, list_of_rows):
"Constructor y validador"
# obtener dimensiones
self.data = list_of_rows
nrow = len(list_of_rows)
# ___caso vector: redimensionar correctame... |
801 | <SYSTEM_TASK:>
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Description:
In this notebook a sensitivity analysis will be performed. The best Automatic Trader will be trained and tested many times, with the SPY symbol, to ass... | <ASSISTANT_TASK:>
Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
from multiprocessing import Pool
import pickle
%... |
802 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Multilabel Design Pattern
The Multilabel Design Pattern refers to models that can assign more than one label to a given input. This design requires cha... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import Model
from tensorflow.keras.layers import Dense, Embedding, Input, Flatten, Conv2D, MaxPooling2D
from sklearn.utils import shuffle
from sklearn.preprocessing import Mul... |
803 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Batch Normalization – Practice
Batch normalization is most useful when building deep neural networks. To demonstrate this, we'll create a convolutional... | <ASSISTANT_TASK:>
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, reshape=False)
Explanation: Batch Normalization – Practice
Batch normalization is most useful when building deep neural networks. To demonstrat... |
804 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Machine Learning Complications
Author
Step1: Now we plot a single example of both classes, to show what the data looks like. First the pulsar example.... | <ASSISTANT_TASK:>
Python Code:
# Import the libraries to be used throughout.
%pylab inline
import matplotlib.pyplot as plt
# The HTRU 2 profile data is split - one file containing the real pulsar
# profiles, one file containing noise/interference profiles. We load both
# these data sources here. First we construct rela... |
805 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Experiment
Step1: Load and check data
Step2: ## Analysis | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import glob
import tabulate
import pprint
import click
import numpy as np
import pandas as pd
from ray.tune.commands import *
from nupi... |
806 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Determining the worst winter ever in Minneapolis
The object of this exercise is to take weather observations from past winters in Minneapolis and deter... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
# Read data, sort by year & month
dateparse = lambda x: pd.datetime.strptime(x, '%Y%m%d')
noaa_monthly = pd.read_csv('mpls-noaa.csv', index_col=2,
parse_dates=True, date_parser=dateparse, na_values=-9999)
noaa_monthly = noaa_monthly.groupby([... |
807 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Define a kernel and function
Here we define a kernel. The function is drawn at random from the GP and is corrupted my Gaussian noise
Step1: Interactiv... | <ASSISTANT_TASK:>
Python Code:
# Measurement noise
noise_var = 0.05 ** 2
# Bounds on the inputs variable
bounds = [(-5., 5.), (-5., 5.)]
# Define Kernel
kernel = GPy.kern.RBF(input_dim=len(bounds), variance=2., lengthscale=1.0,
ARD=True)
# Initial safe point
x0 = np.zeros((1, len(bounds)))
# Gener... |
808 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Mapping with splot and PySAL
Imports
Step1: Data Preparation
Load example data into a geopandas.GeoDataFrame and inspect column names. In this example... | <ASSISTANT_TASK:>
Python Code:
import pysal.lib as lp
from pysal.lib import examples
import geopandas as gpd
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
%matplotlib inline
Explanation: Mapping with splot and PySAL
Imports
End of explanation
link_to_data = examples.get_path('... |
809 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Table of Contents
Step1: Distribution of Passengers
Gender - Analysis | Graph
<a id="Gender - Analysis | Graph"></a>
Distribution of Genders in Pass... | <ASSISTANT_TASK:>
Python Code:
# Imports for pandas, and numpy
import numpy as np
import pandas as pd
# imports for seaborn to and matplotlib to allow graphing
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="whitegrid")
%matplotlib inline
# import Titanic CSV - NOTE: adjust file path as neccessar... |
810 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
<center><h2>Scale your pandas workflows by changing one line of code</h2>
Exercise 2
Step1: Dataset
Step2: pandas.read_csv
Step3: Expect pandas to t... | <ASSISTANT_TASK:>
Python Code:
import modin.pandas as pd
import pandas
import time
import modin.config as cfg
cfg.StorageFormat.put("omnisci")
Explanation: <center><h2>Scale your pandas workflows by changing one line of code</h2>
Exercise 2: Speed improvements
GOAL: Learn about common functionality that Modin speeds up... |
811 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Importing Cells in NetPyNE
(1) Clone repository and compile mod files
Determine your location in the directory structure
Step1: Move to (or stay in) t... | <ASSISTANT_TASK:>
Python Code:
!pwd
Explanation: Importing Cells in NetPyNE
(1) Clone repository and compile mod files
Determine your location in the directory structure
End of explanation
%cd /content/
Explanation: Move to (or stay in) the '/content' directory
End of explanation
!pwd
Explanation: Ensure you are in the... |
812 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Here, we construct a simple neural network transform with the ability to add layers and change the optimizer while training. Note that this code is lar... | <ASSISTANT_TASK:>
Python Code:
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
class SimpleNN(ContinuousTransform):
def init_func(self,target_df,X_train_df,y_train_df,X_test_df,y_test_df):
model=Sequential()
model.add(Dens... |
813 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
DM_Halos and DM_IGM
Splitting $\langle DM_{cosmic}\rangle$ into its constituents.
Step1: $\langle \rho_{diffuse, cosmic}\rangle$
Use f_diffuse to calc... | <ASSISTANT_TASK:>
Python Code:
# imports
from importlib import reload
import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline as IUS
from astropy import units as u
from frb.halos import ModifiedNFW
from frb import halos as frb_halos
from frb import igm as frb_igm
from frb.figures import utils as f... |
814 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
<a href="https
Step1: Below, the first computation shows that the type K thermocouple emf at 42 °C, with reference junction at 0 °C, is 1.694 mV (comp... | <ASSISTANT_TASK:>
Python Code:
# First let's install the module
!pip install thermocouples_reference
Explanation: <a href="https://colab.research.google.com/github/agmarrugo/sensors-actuators/blob/master/notebooks/thermocouples_reference_tables.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/... |
815 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
First step
In this tutorial we will use Brython, an implementation of Python written in javascript and Python, to access the Highcharts javascript libr... | <ASSISTANT_TASK:>
Python Code:
%load_ext brythonmagic
Explanation: First step
In this tutorial we will use Brython, an implementation of Python written in javascript and Python, to access the Highcharts javascript library and to manage the data to be used in the maps. To integrate Brython in the IPython notebook we are... |
816 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Übungsblatt 12
Präsenzaufgaben
Aufgabe 1 Evaluationsmetriken
Step1: Betrachten Sie folgende Daten. Es handelt sich um ein vereinfac... | <ASSISTANT_TASK:>
Python Code:
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
Explanation: Übungsblatt 12
Präsenzaufgaben
Aufgabe 1 Evaluationsmetriken
End of explanation
ground_truth = [1,0,1,0,0,1,1,1,1,0]
chunker1 = [1,1,1,0,1,0,1,1,1,1]
chunker2 = [1,0... |
817 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Fashion MNIST with Keras and TPUs
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step1: Defining our model... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
# add empty color dimension
x_train = np.expand_dims(x_train, -1)
x_test = np.expand_dims(x_test, -1)
Explanation: Fashion MNIST with Keras and TPUs
<table class="... |
818 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Heterojunction offsets
Heterojunctions are the basis of much of the semiconductor technology. From computer memory, to flat-panel display to photovolta... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import macrodensity as md
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
extrema = md.vasp_tools.get_band_extrema('OUTCAR_ZnO')
print extrema
extrema = md.vasp_tools.get_band_extrema('OUTCAR_ZnS')
print extrema
input_file = 'LOCP... |
819 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Copyright 2020 Google LLC.
Licensed under the Apache License, Version 2.0 (the "License");
Measuring Signal Properties of Various Initialization... | <ASSISTANT_TASK:>
Python Code:
#@title Imports and Definitions
import numpy as np
import os
import tensorflow.compat.v2 as tf
tf.enable_v2_behavior()
import gin
from rigl import sparse_utils
from rigl.rigl_tf2 import init_utils
from rigl.rigl_tf2 import utils
from rigl.rigl_tf2 import train
from rigl.rigl_tf2 import ne... |
820 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Viewing CNN Filters
Review
At this point, I've tested my CNN a little bit and learned that the hair really matters. If the CNN sees a lighter object re... | <ASSISTANT_TASK:>
Python Code:
import cv2
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
# TFlearn libraries
import tflearn
from tflearn.layers.conv import conv_2d, max_pool_2d
from tflearn.layers.core import input_data, dropout, fully_connected
from tflearn.layers.estimator import regressio... |
821 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
If the mean flux before transit is significantly different from the mean flux after transit, mask those results.
Step1: If the distribution of fluxs b... | <ASSISTANT_TASK:>
Python Code:
[n for n in table.colnames if n.startswith('ks')]
p = table['ttest:out_of_transit&before_midtransit-vs-out_of_transit&after_midtransit']
poorly_normalized_oot_threshold = -1
mask_poorly_normalized_oot = np.log(p) > poorly_normalized_oot_threshold
plt.hist(np.log(p[~np.isnan(p)]))
plt.axv... |
822 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
The MIT License (MIT)<br>
Copyright (c) 2016, 2017, 2018 Massachusetts Institute of Technology<br>
Authors
Step1: Get scale factor
Step2: Plot EWD $\... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams['figure.dpi']=150
# Gravity Recovery and Climate Experiment (GRACE) Data
# Source: http://grace.jpl.nasa.gov/
# Current surface mass change data, measuring equivalent water thickness in cm, versus time
# This data fetcher use... |
823 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
More on data structures
Iterable vs. Iterators
Lists are examples of iterable data structures, which means that you can iterate over the actual objects... | <ASSISTANT_TASK:>
Python Code:
# iterating over a list by object
x = ['bob', 'sue', 'mary']
for name in x:
print(name.upper() + ' WAS HERE')
# alternatively, you could iterate over position
for i in range(len(x)):
print(x[i].upper() + ' WAS HERE')
dir(x) # ignore the __ methods for now
Explanation: More on da... |
824 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
ABU量化系统使用文档
<center>
<img src="./image/abu_logo.png" alt="" style="vertical-align
Step1: 之前的章节无论讲解策略优化，还是针对回测进行滑点或是手续费都是针对一支股票进行择时操作。
本节将示例讲解多... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from __future__ import division
import warnings
warnings.filterwarnings('ignore')
warnings.simplefilter('ignore')
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import os
import sys
# 使用insert 0即只使用github，避免交... |
825 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
EIT lab notes
A notebook for relevant calculations regarding the observation conditions for EIT slow light
Goal
Step1: Notes from Klein et al 2011 (do... | <ASSISTANT_TASK:>
Python Code:
from numpy import pi
from scipy.constants import hbar
Explanation: EIT lab notes
A notebook for relevant calculations regarding the observation conditions for EIT slow light
Goal: observe slow light with 10% pulse delay by Nov 1, 2018
End of explanation
# Find the power for a 3 mm diamete... |
826 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Exercise 1
Step1: Exercise 2
Step2: Exercise 3 | <ASSISTANT_TASK:>
Python Code:
price = 0.9
# Print the header
print('Balls: Price: Balls: Price:')
# Print prices in two columns
for balls in range(1,11):
left = balls
right = balls + 10
skeletton = '{:^6} {:^6.2f} {:^6} {:^6.2f}'
print(skeletton.format(left, left*price, ri... |
827 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Jupyter notebook illustrating the use of PmagPy for analysis of paleomagnetic data
Before you begin
You may be viewing this notebook as a rendered html... | <ASSISTANT_TASK:>
Python Code:
import pmagpy.ipmag as ipmag
import pmagpy.pmag as pmag
Explanation: Jupyter notebook illustrating the use of PmagPy for analysis of paleomagnetic data
Before you begin
You may be viewing this notebook as a rendered html webpage (which can be seen at this link: http://pmagpy.github.io/Exa... |
828 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
model
<img style="float
Step1: The original data is 90 degree off. So in data loading function, I use transpose to fix it.
However, the transposed dat... | <ASSISTANT_TASK:>
Python Code:
theta1, theta2 = nn.load_weight('ex3weights.mat')
theta1.shape, theta2.shape
Explanation: model
<img style="float: left;" src="../img/nn_model.png">
load weights and data
End of explanation
X, y = nn.load_data('ex3data1.mat',transpose=False)
X = np.insert(X, 0, values=np.ones(X.shape[0]),... |
829 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Example of DOV search methods for interpretations (informele hydrogeologische stratigrafie)
Use cases explained below
Get 'informele hydrogeologische s... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import inspect, sys
# check pydov path
import pydov
Explanation: Example of DOV search methods for interpretations (informele hydrogeologische stratigrafie)
Use cases explained below
Get 'informele hydrogeologische stratigrafie' in a bounding box
Get 'informele hydrogeo... |
830 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Examples of Incremental AI
Step1: Part 1
Step2: Sklearn function to generate random points
Step3: Function to compute kmeans and plot clusters.
Step... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns; sns.set() # for plot styling
import numpy as np
import threading
import time
from sklearn.datasets.samples_generator import make_blobs
from sklearn.cluster import KMeans
import sys
sys.path.append("../")
from IoTPy... |
831 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
<a href="https
Step1: The Fashion MNIST data is available directly in the tf.keras datasets API. You load it like this
Step2: Calling load_data on th... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
print(tf.__version__)
Explanation: <a href="https://colab.research.google.com/github/leopardbruce/FileFun/blob/master/%E2%80%9CCourse_1_Part_4_Lesson_2_Notebook_ipynb%E2%80%9D.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.sv... |
832 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
The computation graph
TensorFlow programs are usually structured into a construction phase, that assembles a graph, and an execution phase that uses a ... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
# Create a Constant op that produces a 1x2 matrix. The op is
# added as a node to the default graph.
#
# The value returned by the constructor represents the output
# of the Constant op.
matrix1 = tf.constant([[3., 3.]])
# Create another Constant that produces a 2... |
833 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
[3-1] 動画作成用のモジュールをインポートして、動画を表示可能なモードにセットします。
Step1: [3-2] x=0〜1の範囲で棒グラフを描いて面積を計算する関数integralを定義します。
Step2: [3-3] 二次関数 y=x*x を用意して、関数integralを呼び出します。... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
%matplotlib nbagg
Explanation: [3-1] 動画作成用のモジュールをインポートして、動画を表示可能なモードにセットします。
End of explanation
def integral(f, filename):
fig = plt.figure(figsize=(4,4))
images = []
step = 0.5
... |
834 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
DSGRN Query Functions
Step1: We show here the network being considered in this example
Step2: Query Overview
In order to perform queries on the datab... | <ASSISTANT_TASK:>
Python Code:
from DSGRN import *
database = Database("querytest.db")
database.parametergraph.dimension()
Explanation: DSGRN Query Functions
End of explanation
database
print(database.network.specification())
Explanation: We show here the network being considered in this example:
End of explanation
mon... |
835 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Binding Site Prediction
In this notebook we perform various machine learning methods and compare various aspects of machine learning paradigms
Step1: ... | <ASSISTANT_TASK:>
Python Code:
## matrix and vector tools
import pandas as pd
from pandas import DataFrame as df
from pandas import Series
import numpy as np
## sklearn
from sklearn.datasets import make_friedman1
from sklearn.feature_selection import RFE
from sklearn.svm import SVR
from sklearn.svm import SVC
from skle... |
836 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Blastocyst Development in Mice
Step1: Next we load in the data. We've provided a convenience function for loading in the data with GPy. It is loaded i... | <ASSISTANT_TASK:>
Python Code:
import pods, GPy, itertools
%matplotlib inline
from matplotlib import pyplot as plt
Explanation: Blastocyst Development in Mice: Single Cell TaqMan Arrays
presented at the EBI BioPreDyn Course 'The Systems Biology Modelling Cycle'
Max Zwiessele, Oliver Stegle, Neil Lawrence 12th May 2014 ... |
837 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Building an ML App
Now that we have a machine learning model to predict the defaults, let us try to build a web application to lend loans.
It'll have ... | <ASSISTANT_TASK:>
Python Code:
%%file sq.py
def square(n):
return n*n
Explanation: Building an ML App
Now that we have a machine learning model to predict the defaults, let us try to build a web application to lend loans.
It'll have two parts:
a form to submit the loans
admin panel to look at the submitted loans ... |
838 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Test isotherm fitting
Our strategy here is to generate data points that follow a given isotherm model, then fit an isotherm model to the data using pyI... | <ASSISTANT_TASK:>
Python Code:
import pyiast
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline
Explanation: Test isotherm fitting
Our strategy here is to generate data points that follow a given isotherm model, then fit an isotherm model to the data using pyIAST, and check that p... |
839 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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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 addition... | <ASSISTANT_TASK:>
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: AutoML training tabular forecasting model for batch predict... |
840 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Let's say we want to prepare data and try some scalers and classifiers for prediction in a classification problem. We will tune paramaters of classifie... | <ASSISTANT_TASK:>
Python Code:
from sklearn.datasets import make_classification
X, y = make_classification()
Explanation: Let's say we want to prepare data and try some scalers and classifiers for prediction in a classification problem. We will tune paramaters of classifiers by grid search technique.
Data preparing:
En... |
841 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Tutorial for flexx.app - connecting to the browser
Step1: In normal operation, one uses flx.launch() to fire up a browser (or desktop app) to run the ... | <ASSISTANT_TASK:>
Python Code:
from flexx import flx
Explanation: Tutorial for flexx.app - connecting to the browser
End of explanation
%gui asyncio
flx.init_notebook()
class MyComponent(flx.JsComponent):
foo = flx.StringProp('', settable=True)
@flx.reaction('foo')
def on_foo(self, *events):
... |
842 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
The histogram above shows the dataset is unbalanced.
We will now go ahead and drop most of the zero steering angles, which correspond to mostly straigh... | <ASSISTANT_TASK:>
Python Code:
zero_steering = drive_log_df[drive_log_df.steering == 0].sample(frac=0.9)
drive_log_df = drive_log_df.drop(zero_steering.index)
plt.figure(figsize=(10,4))
drive_log_df.steering.hist(bins=100, color='r')
plt.xlabel('steering angle bins')
plt.ylabel('counts')
plt.show()
print("Current Datas... |
843 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Summarizing Images
Images are high dimensional objects
Step1: How Many Photons Came From the Cluster?
Let's estimate the total counts due to the clust... | <ASSISTANT_TASK:>
Python Code:
import astropy.io.fits as pyfits
import numpy as np
import astropy.visualization as viz
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 10.0)
targdir = 'a1835_xmm/'
imagefile = targdir+'P0098010101M2U009IMAGE_3000.FTZ'
expmapfile = targdir+'P009... |
844 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Tricks of the trade
Step1: Introducing randomized search
We have already built a random forest classifier, tuned using grid search, to predict spam em... | <ASSISTANT_TASK:>
Python Code:
import wget
import pandas as pd
import numpy as np
from sklearn.cross_validation import train_test_split
# Import the dataset
data_url = 'https://raw.githubusercontent.com/nslatysheva/data_science_blogging/master/datasets/spam/spam_dataset.csv'
dataset = wget.download(data_url)
dataset = ... |
845 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Jennifer 8. Lee et al have been using a Google spreadsheet to track the production of books in Project GITenberg
Step1: Getting access to the spreadsh... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import gspread
import json
# rtc50_settings.py holds URL related to the Google spreadsheet
from rtc50_settings import (g_name, g_url, g_key)
OFFICIAL_NAME_KEY = "Name in rtc/books.json, Official Name"
Explanation: Jennifer 8. Lee et al have been usin... |
846 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Matplotlib
<img src="images/matplotlib.svg" alt="matplotlib" style="width
Step1: File Reading
Line Plots
plt.plot Plot lines and/or markers
Step2: Sc... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
Explanation: Matplotlib
<img src="images/matplotlib.svg" alt="matplotlib" style="width: 600px;"/>
Using matplotlib in Jupyter notebook
End of explanation
x = np.arange(-np.pi,np.pi,0.01) # Create an array of x values fr... |
847 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Modules and Connection to MongoDb
Step1: Extraction of Data from MongoDB and Creating DataFrame
Step2: First five rows from the dataframe
Step3: Dat... | <ASSISTANT_TASK:>
Python Code:
from pymongo import MongoClient
import time
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.pyplot import *
import datetime as dt
import random as rnd
import warnings
import datetime as dt
import csv
%matplotlib inline
warnings.... |
848 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
확률 분포, 확률 변수, 확률 모형의 의미
분포
확률 분포
확률 변수
확률 모형
샘플링
모집단
확률 분포
자료의 분포(distribution)란 자료가 어떤 수치적인 값을 가지는지를 그 전반적인 특징을 서술한 것을 말한다.
어떤 경우에 자료의 분포가 필요할까? 다음의 ... | <ASSISTANT_TASK:>
Python Code:
sp.random.seed(0)
x = sp.random.normal(size=1000)
x
ns, bins, ps = plt.hist(x, bins=10)
ns
bins
ps
pd.DataFrame([bins, ns/1000])
Explanation: 확률 분포, 확률 변수, 확률 모형의 의미
분포
확률 분포
확률 변수
확률 모형
샘플링
모집단
확률 분포
자료의 분포(distribution)란 자료가 어떤 수치적인 값을 가지는지를 그 전반적인 특징을 서술한 것을 말한다.
어떤 경우에 자료의 분포가 필요할까? ... |
849 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
seaborn.heatmap
Heat maps display numeric tabular data where the cells are colored depending upon the contained value. Heat maps are great for making t... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
plt.rcParams['figure.figsize'] = (20.0, 10.0)
plt.rcParams['font.family'] = "serif"
df = pd.pivot_table(data=sns.load_dataset("flights"),
index='month',
... |
850 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Useful Scripts
Location of the scripts
Here are some scripts that you may find useful. They are in the folder "./eppy/useful_scripts"
And now for some ... | <ASSISTANT_TASK:>
Python Code:
import os
os.chdir("../eppy/useful_scripts")
# changes directory, so we are where the scripts are located
# you would normaly install eppy by doing
# python setup.py install
# or
# pip install eppy
# or
# easy_install eppy
# if you have not done so, the following three lines are needed
im... |
851 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Pandas and data wrangling
Pandas is a tool for accessing columnar data, like that in SQL tables or CSV files.
Step1: Let's start by reading in a datas... | <ASSISTANT_TASK:>
Python Code:
# convention recommended in documentation
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
#enable inline plotting in notebook
%matplotlib inline
Explanation: Pandas and data wrangling
Pandas is a tool for accessing columnar data, like that in SQL tables or CSV files... |
852 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Transit-Network
Making plots for my SETI idea, dreamed up on the airplane home from AAS 227
SHELVED
I put this idea on the backburner and removed it fr... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.cm as cm
import matplotlib
matplotlib.rcParams.update({'font.size':18})
matplotlib.rcParams.update({'font.family':'serif'})
Explanation: Transi... |
853 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
GWAS Tutorial
This notebook is designed to provide a broad overview of Hail's functionality, with emphasis on the functionality to manipulate and query... | <ASSISTANT_TASK:>
Python Code:
import hail as hl
hl.init()
Explanation: GWAS Tutorial
This notebook is designed to provide a broad overview of Hail's functionality, with emphasis on the functionality to manipulate and query a genetic dataset. We walk through a genome-wide SNP association test, and demonstrate the need ... |
854 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
This model buils a simple Hierarchial mixed effect model to look at dose response from 5 clinical trials.
In this example we are model the mean respons... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
from pymc3 import Model, Normal, Lognormal, Uniform, trace_to_dataframe, df_summary
Explanation: This model buils a simple Hierarchial mixed effect model to look at dose respon... |
855 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
DSGRN Python Interface Tutorial
This notebook shows the basics of manipulating DSGRN with the python interface.
Step1: Network
The starting point of t... | <ASSISTANT_TASK:>
Python Code:
import DSGRN
Explanation: DSGRN Python Interface Tutorial
This notebook shows the basics of manipulating DSGRN with the python interface.
End of explanation
network = DSGRN.Network("network.txt")
print(network)
print(network.graphviz())
Explanation: Network
The starting point of the DSGRN... |
856 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Regression
1. Information Generation
Simulation of values to train and test the linear regression model.
Step1: 2. ages_train vs ages_test relationshi... | <ASSISTANT_TASK:>
Python Code:
# importing packages
import numpy
import random
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
# setting ageNetWorthData
def ageNetWorthData():
random.seed(42)
numpy.random.seed(42)
ages = []
for ii in range(100):
ages.append( ran... |
857 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Fibonacci Stretch
Step1: You can also jump to Part 6 for more audio examples.
Part 1 - Representing rhythm as symbolic data
1.1 Rhythms as arrays
The ... | <ASSISTANT_TASK:>
Python Code:
import IPython.display as ipd
ipd.Audio("../data/out_humannature_90s_stretched.mp3", rate=44100)
Explanation: Fibonacci Stretch: An Exploration Through Code
by David Su
This notebook and its associated code are also available on GitHub.
Contents
Introduction
A sneak peek at the final resu... |
858 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
PDF is garbage
In this example, we are looking for a link to some source code
Step1: PDF is garbage, continued
If we remove line breaks to fix URLs t... | <ASSISTANT_TASK:>
Python Code:
urlre = re.compile( '(?P<url>https?://[^\s]+)' )
for page in doc :
print urlre.findall( page )
Explanation: PDF is garbage
In this example, we are looking for a link to some source code :
http://prodege.jgi-psf.org//downloads/src
However, in the PDF, the URL is line wrapped, so the sr... |
859 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Causal Effect
Import and settings
In this example, we need to import numpy, pandas, and graphviz in addition to lingam.
Step1: Utility function
We def... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import graphviz
import lingam
print([np.__version__, pd.__version__, graphviz.__version__, lingam.__version__])
np.set_printoptions(precision=3, suppress=True)
np.random.seed(0)
Explanation: Causal Effect
Import and settings
In this example, we need ... |
860 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
K-means Clustering in sci-kit learn
This example uses a dataset downloaded from https
Step1: Unarchive
Step2: Tokenizing and Filtering a Vocabulary
S... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import sys
sys.version
Explanation: K-means Clustering in sci-kit learn
This example uses a dataset downloaded from https://www.opensubtitles.org/en/search/vip and the raw data at opus.lingfil.uu.se/OpenSubtitles2016/raw/en. Metadata such as title actor and director ... |
861 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
ATM 623
Step1: Contents
Simulation versus parameterization of heat transport
The temperature diffusion parameterization
Solving the temperature diffus... | <ASSISTANT_TASK:>
Python Code:
# Ensure compatibility with Python 2 and 3
from __future__ import print_function, division
Explanation: ATM 623: Climate Modeling
Brian E. J. Rose, University at Albany
Lecture 18: The one-dimensional energy balance model
Warning: content out of date and not maintained
You really should ... |
862 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
<h1 id="tocheading">Table of Contents</h1>
<div id="toc"></div>
Step1: Getting and Knowing your Data
Task
Step2: Task
Step3: Task
Step4: Groupby
Ta... | <ASSISTANT_TASK:>
Python Code:
%%javascript
$.getScript('misc/kmahelona_ipython_notebook_toc.js')
Explanation: <h1 id="tocheading">Table of Contents</h1>
<div id="toc"></div>
End of explanation
fn = r"data/drinks.csv"
# Answer:
df = pd.read_csv(fn, sep=",")
Explanation: Getting and Knowing your Data
Task: load the fol... |
863 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Use the cleaner chaining method for transforming the data https
Step1: The sale price is in hte hundreds of thousands, so let's divide the price by 10... | <ASSISTANT_TASK:>
Python Code:
target = pd.read_csv('../data/train_target.csv')
target.describe()
Explanation: Use the cleaner chaining method for transforming the data https://tomaugspurger.github.io/method-chaining.html
Sale price distribution
First step is to look at the target sale price for the training data set, ... |
864 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
<div style="text-align
Step1: Two major version branches
Python 2.x
Latest
Step2: Mis-Conceptions
python does not have types?
No! Python does have ty... | <ASSISTANT_TASK:>
Python Code:
print("Hello World")
Explanation: <div style="text-align: center;">
<h1> Python - Why should you learn? </h1>
<h3> Thamme Gowda </h3> <h4> Feb 9th, 2018. SJCIT </h4>
<br/>
<a href="https://twitter.com/thammegowda">@thammegowda</a>
<br/>
<a href="https://isi.edu/~tg">https://isi.edu/~tg <... |
865 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Executed
Step1: Multi-spot vs usALEX FRET histogram comparison
Load FRETBursts software
Step2: 8-spot paper plot style
Step3: Data files
Data folder... | <ASSISTANT_TASK:>
Python Code:
data_id = '17d'
ph_sel_name = "None"
data_id = "17d"
Explanation: Executed: Mon Mar 27 22:24:30 2017
Duration: 12 seconds.
End of explanation
from fretbursts import *
sns = init_notebook()
import os
import pandas as pd
from IPython.display import display, Math
import lmfit
print('lmfit ve... |
866 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Load data
Step1: Baselines
Step2: Dense example
Step3: Sparse example
Step4: Regression example
Step5: n_features/time complexity
Step6: Logging ... | <ASSISTANT_TASK:>
Python Code:
from tensorflow.examples.tutorials.mnist import input_data
from sklearn.datasets import fetch_mldata
from sklearn.preprocessing import scale
from sklearn.model_selection import train_test_split
from sklearn.metrics import roc_auc_score, accuracy_score
mnist = input_data.read_data_sets("MN... |
867 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Profiling BatchFlow code
A profile is a set of statistics that describes how often and for how long various parts of the program executed.
This noteboo... | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append("../../..")
from batchflow import B, V, W
from batchflow.opensets import MNIST
from batchflow.models.torch import ResNet18
dataset = MNIST()
Explanation: Profiling BatchFlow code
A profile is a set of statistics that describes how often and for how long various ... |
868 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Тест. Практика проверки гипотез
По данным опроса, 75% работников ресторанов утверждают, что испытывают на работе существенный стресс, оказывающий негат... | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import numpy as np
import pandas as pd
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
n = 100
prob =... |
869 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Charge Noise Mask Design
General Notes
Step1: CPW
We want to use the same cpw dimensions for resonator and feedline/purcell filter cpw's so the kineti... | <ASSISTANT_TASK:>
Python Code:
ri = (40, 50, 60, 70, 80, 90, 100, 108)
ro = (40.7, 52.9, 69, 90.5, 123, 182, 305, 500)
Cq = (46.3, 47.0, 46.9, 47.0, 47.0, 47.0, 46.9, 46.9)
#Cq = (46.3, 49.5, 46.9, 49.5, 47.0, 51.7, 46.9, 54)
Cg = (1.5, 1.44, 1.47, 1.45, 1.46, 1.49, 1.42, 1.48)
Cgnd = (39.0... |
870 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Heapsort
Graphical Representation
Step1: The function toDot takes four arguments
Step2: HeapSort
The function call swap(A, i, j) takes an array A and... | <ASSISTANT_TASK:>
Python Code:
import graphviz as gv
Explanation: Heapsort
Graphical Representation
End of explanation
def toDot(A, f, g, u=None):
n = len(A)
dot = gv.Digraph(node_attr={'shape': 'record'})
for k, p in enumerate(A):
if k == u:
dot.node(str(k), label='{' + str(p) + '|' +... |
871 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
9 - Advanced topics - 1 axis torque tube Shading for 1 day (Research Documentation)
Recreating JPV 2019 / PVSC 2018 Fig. 13
Calculating and plotting sh... | <ASSISTANT_TASK:>
Python Code:
import os
from pathlib import Path
testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_09')
if not os.path.exists(testfolder):
os.makedirs(testfolder)
print ("Your simulation will be stored in %s" % testfolder)
# VARIABLES of the simulation:
lat... |
872 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
HoloCube is a Python library that makes it easy to explore and visualize geographical, meterological, oceanographic, and other multidimensional gridded... | <ASSISTANT_TASK:>
Python Code:
import holoviews as hv
import holocube as hc
from cartopy import crs
from cartopy import feature as cf
hv.notebook_extension()
%%opts GeoFeature [projection=crs.Geostationary()]
coasts = hc.GeoFeature(cf.COASTLINE)
borders = hc.GeoFeature(cf.BORDERS)
ocean = hc.GeoFeature(cf.OCEAN)
oce... |
873 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Introduction to the Lomb-Scargle Periodogram
Version 0.2
By AA Miller (Northwester/CIERA)
15 Sep 2021
Today we examine the detection of periodic signal... | <ASSISTANT_TASK:>
Python Code:
def gen_periodic_data(x, period=1, amplitude=1, phase=0, noise=0):
'''Generate periodic data given the function inputs
y = A*sin(2*pi*x/p - phase) + noise
Parameters
----------
x : array-like
input values to evaluate the array
period : float ... |
874 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Short-Sentence Similarity using Gensim Word Mover Distance
1. Gensim Word-Movers model
Reference
Step1: Load the Google's pre-trained model
Step2: Al... | <ASSISTANT_TASK:>
Python Code:
# Importing the dependecies
import gensim
Explanation: Short-Sentence Similarity using Gensim Word Mover Distance
1. Gensim Word-Movers model
Reference:
Note: Refer to other similarity functions
https://radimrehurek.com/gensim/models/word2vec.html
End of explanation
#load word2vec model, ... |
875 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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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}$F for more th... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df = pd.read_csv('data/human_body_temperature.csv')
df.info()
df.head()
Explanation: What is the true normal human body temperature?
Background
The mean normal body temperature was held to be 37$^{\circ}$C or 98.6$^{\circ}$F for more than 120 years since it was first c... |
876 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
def sghmc(Y, X, stogradU, M, eps, m, theta, C, V)
Step1: Correct coefficients
Step2: Our code - SGHMC
Step3: Our code - Gradient descent
Step5: Cli... | <ASSISTANT_TASK:>
Python Code:
# Load data
X = np.concatenate((np.ones((pima.shape[0],1)),pima[:,0:8]), axis=1)
Y = pima[:,8]
Xs = (X - np.mean(X, axis=0))/np.concatenate((np.ones(1),np.std(X[:,1:], axis=0)))
n, p = X.shape
M = np.identity(p)
### HMC version
def logistic(x):
return 1/(1+np.exp(-x))
def U(theta, Y, ... |
877 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Telecom subscriber churn prediction on Vertex AI
<table align="left">
<td>
<a href="https
Step1: Restart the kernel
Once you've installed the ad... | <ASSISTANT_TASK:>
Python Code:
import os
# The Google Cloud Notebook product has specific requirements
IS_GOOGLE_CLOUD_NOTEBOOK = os.path.exists("/opt/deeplearning/metadata/env_version")
USER_FLAG = ""
# Google Cloud Notebook requires dependencies to be installed with '--user'
if IS_GOOGLE_CLOUD_NOTEBOOK:
USER_FLAG... |
878 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
FASTA
This notebook briefly explores the FASTA format, a very common format for storing DNA sequences. FASTA is the preferred format for storing refer... | <ASSISTANT_TASK:>
Python Code:
import gzip
import urllib.request
url = 'ftp://ftp.ncbi.nlm.nih.gov/genomes/archive/old_genbank/Eukaryotes/vertebrates_mammals/Homo_sapiens/GRCh38/non-nuclear/assembled_chromosomes/FASTA/chrMT.fa.gz'
response = urllib.request.urlopen(url)
print(gzip.decompress(response.read()).decode('UTF... |
879 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Scientific programming with the SciPy stack
Pandas
Import libraries and check versions.
Step1: Read the data and get a row count. Data source
Step2: ... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import sys
print('Python version ' + sys.version)
print('Pandas version ' + pd.__version__)
print('Numpy version ' + np.__version__)
Explanation: Scientific programming with the SciPy stack
Pandas
Import libraries and check versions.
End of explanati... |
880 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
The charts below have dollar signs in their titles, which get formatted into mathematical notation by Mathjax, which messes up the intended title
Step... | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('../')
import mustaching as ms
%load_ext autoreload
%autoreload 2
Explanation: The charts below have dollar signs in their titles, which get formatted into mathematical notation by Mathjax, which messes up the intended title :(
The only way i know to avoid this ... |
881 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
The data
The gas data
$\mathbf{H_2}$
McKee et al. (2015) take their spatial distribution from Dame et al. (1987). Dame et al. estimate the FWHM of the ... | <ASSISTANT_TASK:>
Python Code:
cloud_name= 'apjaa4dfdt1_mrt.txt'
if not os.path.exists(cloud_name):
!wget http://iopscience.iop.org/0004-637X/834/1/57/suppdata/apjaa4dfdt1_mrt.txt
cloud_data= ascii.read(cloud_name,format='cds')
# Compute distsance and height z based on whether near of far kinematic distance is more... |
882 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
<a href="https
Step1: Getting a dataset
The first step is going to be to load our data. As our example, we will be using the dataset CalTech-101, whic... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
%matplotlib inline
import os
#if using Theano with GPU
#os.environ["KERAS_BACKEND"] = "tensorflow"
import random
import numpy as np
import keras
import matplotlib.pyplot as plt
from matplotlib.pyplot import imshow
from keras.preprocessing import image
from keras.applica... |
883 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This is the ipython notebook you should use as a template for your agent. Your task for this assignment is to implement a winning AI for the gam... | <ASSISTANT_TASK:>
Python Code:
from random import randint
class RandomPlayer():
Player that chooses a move randomly.
def move(self, game, legal_moves, time_left):
if not legal_moves: return (-1,-1)
return legal_moves[randint(0,len(legal_moves)-1)]
Explanation: This is the ipython notebook you sh... |
884 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
<a href="https
Step1: Introduction to Regular Expressions
Regular Expressions are a powerful feature of the Python programming language. You can acces... | <ASSISTANT_TASK:>
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, sof... |
885 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Translation of Numeric Phrases with Seq2Seq
In the following we will try to build a translation model from french phrases describing numbers to the cor... | <ASSISTANT_TASK:>
Python Code:
from french_numbers import to_french_phrase
for x in [21, 80, 81, 300, 213, 1100, 1201, 301000, 80080]:
print(str(x).rjust(6), to_french_phrase(x))
Explanation: Translation of Numeric Phrases with Seq2Seq
In the following we will try to build a translation model from french phrases de... |
886 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
pyISC Example
Step1: Data Creation
Create two arrays with normal and anomalous frequency data respectively.</b>
Step2: Create an 2D array with two co... | <ASSISTANT_TASK:>
Python Code:
import pyisc;
import numpy as np
from scipy.stats import poisson
%matplotlib inline
from pylab import hist, plot, figure
Explanation: pyISC Example: Simple Anomaly Detection with Frequency Data
This is a simple example on how to use the pyISC anomaly detector for computing the anomaly sco... |
887 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Learning to Resize in Computer Vision
Author
Step1: Define hyperparameters
In order to facilitate mini-batch learning, we need to have a fixed shape f... | <ASSISTANT_TASK:>
Python Code:
from tensorflow.keras import layers
from tensorflow import keras
import tensorflow as tf
import tensorflow_datasets as tfds
tfds.disable_progress_bar()
import matplotlib.pyplot as plt
import numpy as np
Explanation: Learning to Resize in Computer Vision
Author: Sayak Paul<br>
Date created... |
888 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step5: Basic Idea of Count Min sketch
We map the input value to multiple points in a relatively small output space. Therefore, the count associated wit... | <ASSISTANT_TASK:>
Python Code:
import sys
import random
import numpy as np
import heapq
import json
import time
BIG_PRIME = 9223372036854775783
def random_parameter():
return random.randrange(0, BIG_PRIME - 1)
class Sketch:
def __init__(self, delta, epsilon, k):
Setup a new count-min sketch wit... |
889 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Routing electrical
For routing low speed DC electrical ports you can use sharp corners instead of smooth bends.
You can also define port.orientation = ... | <ASSISTANT_TASK:>
Python Code:
import gdsfactory as gf
c = gf.Component("pads")
pt = c << gf.components.pad_array(orientation=270, columns=3)
pb = c << gf.components.pad_array(orientation=90, columns=3)
pt.move((70, 200))
c
c = gf.Component("pads_with_routes_with_bends")
pt = c << gf.components.pad_array(orientation=27... |
890 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
<a href="https
Step1: Fitting a model using sklearn
Models in the sklearn library support the fit method for parameter estimation. Under the hood, thi... | <ASSISTANT_TASK:>
Python Code:
import sklearn
import scipy
import scipy.optimize
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings("ignore")
import itertools
import time
from functools import partial
import os
import numpy as np
# np.set_printoptions(precision=3)
np.set_printoptions(formatter={"fl... |
891 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Advanced
Step1: As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
Step2: And we'll attac... | <ASSISTANT_TASK:>
Python Code:
!pip install -I "phoebe>=2.1,<2.2"
Explanation: Advanced: Alternate Backends
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 to the latest release).
End of exp... |
892 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Processing Steps
Determine noise parameters of noise model
This will be based on <a href="http
Step1: First we will take a look at the fluorescence "b... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from load_environment import * # python file with imports and basics to set up this computing environment
Explanation: Processing Steps
Determine noise parameters of noise model
This will be based on <a href="http://www.cs.tut.fi/~foi/papers/Foi-PoissonianGaussianClippe... |
893 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
<h1><center>[Notebooks](../) - [Numerical Cartography](../numerical cartography)</center></h1>
The Geodesic Problem
Distances and angles
The distances ... | <ASSISTANT_TASK:>
Python Code:
from pyproj import Geod
g = Geod(ellps='WGS84')
Explanation: <h1><center>[Notebooks](../) - [Numerical Cartography](../numerical cartography)</center></h1>
The Geodesic Problem
Distances and angles
The distances between two points can be axpressesd as the shortest path between the points ... |
894 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Adding Multiple Wells
This notebook shows how a WellModel can be used to fit multiple wells with one response function. The influence of the individual... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import pastas as ps
import matplotlib.pyplot as plt
ps.show_versions()
Explanation: Adding Multiple Wells
This notebook shows how a WellModel can be used to fit multiple wells with one response function. The influence of the individual wells is scale... |
895 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Gaussian Process (GP) smoothing
This example deals with the case when we want to smooth the observed data points $(x_i, y_i)$ of some 1-dimensional fun... | <ASSISTANT_TASK:>
Python Code:
%pylab inline
figsize(12, 6);
import numpy as np
import scipy.stats as stats
x = np.linspace(0, 50, 100)
y = (np.exp(1.0 + np.power(x, 0.5) - np.exp(x/15.0)) +
np.random.normal(scale=1.0, size=x.shape))
plot(x, y);
xlabel("x");
ylabel("y");
title("Observed Data");
Explanation: Gauss... |
896 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Using the Illumina InterOp Library in Python
Step1: Getting SAV Imaging Tab-like Metrics
The run_metrics class encapsulates the model for all the indi... | <ASSISTANT_TASK:>
Python Code:
run_folder = r""
Explanation: Using the Illumina InterOp Library in Python: Part 5
Install
If you do not have the Python InterOp library installed, then you can do the following:
$ pip install interop
You can verify that InterOp is properly installed:
$ python -m interop --test
Before you... |
897 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Quiz - Week 5B
Q1.
We wish to cluster the following set of points
Step1: Q2.
When performing a k-means clustering, success depends very much on the in... | <ASSISTANT_TASK:>
Python Code:
# Solution
import numpy as np
import math
def dist(pt1, pt2):
return math.sqrt( (pt1[0] - pt2[0])**2 + (pt1[1] - pt2[1])**2 )
pts1 = [ (25,125), (44,105), (29,97), (35, 63), (55, 63), (42, 57), (23, 40), (64,37), (33,22), (55,20) ]
pts2 = [ (28,145), (38,115), (50,130),(65,140), (55,... |
898 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
*This notebook was created by Svitozar Serkez. Source and license info is on GitHub. August 2016. *
Tutorial N5
Step1: Setting input parameters
electr... | <ASSISTANT_TASK:>
Python Code:
# the output of plotting commands is displayed inline within frontends,
# directly below the code cell that produced it
%matplotlib inline
from __future__ import print_function
# this python library provides generic shallow (copy) and deep copy (deepcopy) operations
from copy import dee... |
899 | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
10 For-Loop-Rückblick-Übungen
In den Teilen der folgenden Übungen habe ich den Code mit "XXX" ausgewechselt. Es gilt in allen Übungen, den korrekten Co... | <ASSISTANT_TASK:>
Python Code:
primzweibissieben = [2, 3, 5, 7]
for prime in primzweibissieben:
print(prime)
Explanation: 10 For-Loop-Rückblick-Übungen
In den Teilen der folgenden Übungen habe ich den Code mit "XXX" ausgewechselt. Es gilt in allen Übungen, den korrekten Code auszuführen und die Zelle dann auszuführ... |
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