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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Grading
Step2: Word embedding
Step3: How to work with Google's word2vec embeddings?
Step5: From word to text embeddings
Step6: To check the ... | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append("..")
from common.download_utils import download_week3_resources
download_week3_resources()
from grader import Grader
grader = Grader()
import gensim
wv_embeddings = ######### YOUR CODE HERE #############
def check_embeddings(embeddings):
error_text = "So... |
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Description:
Step1: Now we move onto the ISPAQ-specific ones. Because of the directory structure and where this example lives, we need to add the main ispaq directo... | <ASSISTANT_TASK:>
Python Code:
import sys
import os
import logging
import pandas as pd
from obspy import UTCDateTime
path_parent = os.path.dirname(os.getcwd())
sys.path.insert(1, f'{path_parent}/ispaq/')
import concierge
from user_request import UserRequest
import PDF_aggregator
logger = logging.getLogger(__name__)
l... |
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Description:
Step1: Here we have to find the 'NaN' values and fill them with the mean. Probably it's not the best way to complete the info where we have empty value... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
#load the files
train = pd.read_csv('input/train.csv')
test = pd.read_csv('input/test.csv')
data = pd.concat([train, test])
#size of training dataset
train_samples = train.shape[0]
test_samples = test.shape[0]
# remove the Id feature
data.drop(['Id']... |
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Description:
Step 1.
Step 2.
Step 3.
Step 4.
Step1: 1.3. Descriptive Statistics
Step2: 1.4. Data Cleaning
Step3: 2. Implementation of machine learning pipeline.... | <ASSISTANT_TASK:>
Python Code:
# import dependencies for creating a data frame
from pyspark.sql import SparkSession
from pyspark.sql import Row
from pyspark.sql.types import *
import csv
# Create SparkSession
spark = SparkSession.builder.getOrCreate()
# create RDD from csv files
trainRDD = spark.read.csv("hdfs://salt... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 微分
Step2: 极限
Step3: 求和
Step4: 替换
Step5: expression.subs({x
Step6: 方程
Step7: sy.solve(方程,未知数) # 方程求解 ,返回值为list 方程求解
Step8: sy.roots(... | <ASSISTANT_TASK:>
Python Code:
sy.integrate(6*x**5, x)
sy.integrate(x**3, (x, 0, 10)) #定积分
sy.integrate(6*x**5+y, x,y) #双重不定积分
sy.integrate(x**3+y, (x, -1, 1),(y,1,3) ) #双重定积分
print f(x).diff(x)
sy.diff(sy.sin(x), x) # 解析微分
sy.diff(sy.sin(2*x), ... |
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Description:
Step1: Nomenclature
Step2: The type of an enumeration member is the enumeration it belongs to
Step3: Alternative way to create an Enum
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Python Code:
from enum import Enum
class MyEnum(Enum):
first = 1
second = 2
third = 3
print(MyEnum.first)
print(repr(MyEnum.first))
type(MyEnum.first)
SecondEnum = Enum('SecondEnum', 'first, second, third')
print(SecondEnum.first)
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Description:
Step1: The focus of this post is to expand on an extremely useful, vectorizable isomorphism between indices, that comes up all the time
Step2: This br... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
np.random.seed(1234)
x = np.random.choice(10, replace=False, size=10)
s = np.argsort(x)
inverse = np.empty_like(s)
inverse[s] = np.arange(len(s), dtype=int)
np.all(x == inverse)
# an edge index is determined by the isomorphism from
# ([n] choose 2) to [n choose 2]
# dr... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Define the vehicle class
Step2: Define the Moment Method class
Step3: Run simulation
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Python Code:
from opentire import OpenTire
from opentire.Core import TireState
import numpy as np
import matplotlib.pyplot as plt
class Vehicle():
def __init__(self):
self._mass = 1000
self._wb = 1
self._wd = 0.5
self._ft = None
self._rt = None
@pr... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Liblinear, a library for large- scale linear learning focusing on SVM, is used to do the classification. It supports different solver types.
Ste... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
import matplotlib.patches as patches
#To import all shogun classes
import modshogun as sg
import numpy as np
#Generate some random data
X = 2 * np.random.randn(10,2)
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Data Exploration
Step2: Question 1 - Feature Observation
Step4: Answer
Step5: Question 2 - Goodness of Fit
Step6: Answer
Step7: Question 3 ... | <ASSISTANT_TASK:>
Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
from sklearn.cross_validation import ShuffleSplit
# Import supplementary visualizations code visuals.py
import visuals as vs
# Pretty display for notebooks
%matplotlib inline
# Load the Boston housing dat... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: TFRecord and tf.train.Example
Step5: tf.train.Example
Step6: Note
Step7: All proto messages can be serialized to a binary-string using the .S... | <ASSISTANT_TASK:>
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 writin... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We follow the state-action pairs formulation approach.
Step2: The backward induction algorithm for finite horizon dynamic programs is offered
S... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
from scipy import sparse
import matplotlib.pyplot as plt
import quantecon as qe
from quantecon.markov import DiscreteDP, backward_induction, sa_indices
T = 0.5 # Time expiration (years)
vol = 0.2 # Annual volatility
r = 0.05 # Annual in... |
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Description:
Step1: DCP на примере CVXPy
Step2: CVXPy
Step3: Проверим решение
Step4: Проверим DCP правила
Step5: Autodiff на примере PyTorch'a
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Python Code:
import cvxpy as cvx
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
print(cvx.installed_solvers())
USE_COLAB = False
if USE_COLAB == False:
plt.rc("text", usetex=True)
n = 1000
m = 10
x_true = np.random.randn(n)
x_true[np.abs(x_true) > 0.05] = 0
print("Num of nn... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Contour plots of 2d wavefunctions
Step3: The contour, contourf, pcolor and pcolormesh functions of Matplotlib can be used for effective visuali... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
def well2d(x, y, nx, ny, L=1.0):
Compute the 2d quantum well wave function.
psi = 2*np.sin(nx*np.pi*x/L)*np.sin(ny*np.pi*y/L)/L
return psi
psi = well2d(np.linspace(0,1,10), np.linspace(0,1,10), 1, 1)
psi
ps... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Quick Look at the Data
Step2: Calibration Data
Step3: Perspective Transform
Step4: Color Thresholding
Step5: Coordinate Transformations
Step... | <ASSISTANT_TASK:>
Python Code:
%%HTML
<style> code {background-color : orange !important;} </style>
%matplotlib inline
#%matplotlib qt # Choose %matplotlib qt to plot to an interactive window (note it may show up behind your browser)
# Make some of the relevant imports
import cv2 # OpenCV for perspective transform
impo... |
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Description:
Step1: Examples
Step2: Example 1
Step3: Example 2
Step4: Example 3
Step5: Equation
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Python Code:
import numpy as np
def dftmatrix(N):
x = np.arange(N).reshape(N,1)
u = x
Wn = np.exp(-1j*2*np.pi/N)
A = (1./np.sqrt(N)) * (Wn ** u.dot(x.T))
return A
testing = (__name__ == "__main__")
if testing:
! jupyter nbconvert --to python dftmatrix.ipynb
import numpy as... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Filter logs for public items
Step2: Make the data set manageably smaller by filtering out users with short/long review histories
Step3: Load t... | <ASSISTANT_TASK:>
Python Code:
public_itemids = defaultdict(set)
fs = [x for x in os.listdir(os.path.join('data', 'shared_decks')) if '.xml' in x]
for f in fs:
try:
e = xml.etree.ElementTree.parse(os.path.join('data', 'shared_decks', f)).getroot()
for x in e.findall('log'):
public_itemid... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Bayesian optimization or sequential model-based optimization uses a surrogate model
Step2: This shows the value of the two-dimensional branin f... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
np.random.seed(123)
%matplotlib inline
import matplotlib.pyplot as plt
plt.set_cmap("viridis")
from skopt.benchmarks import branin as _branin
def branin(x, noise_level=0.):
return _branin(x) + noise_level * np.random.randn()
from matplotlib.colors import LogNorm
de... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set model run-time parameters
Step2: Investigate a couple of model variables
Step3: Run for a number of timesteps
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Python Code:
# First import the model. Here we use the HBV version
%pylab inline
from wflow.wflow_hbv import *
import IPython
from IPython.display import display, clear_output
#clear_output = IPython.core.display.clear_output
# define start and stop time of the run
startTime = 1
stopTime = 200
curre... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Steppermotor ST4118S0206-A settings
Step2: Max Frequency calulation
Step3: Max Speed calculations
Step4: Max Acceleration calculations
Step5:... | <ASSISTANT_TASK:>
Python Code:
# Function to calculate the Bits needed fo a given number
def unsigned_num_bits(num):
_nbits = 1
_n = num
while(_n > 1):
_nbits = _nbits + 1
_n = _n / 2
return _nbits
rev_distance = 0.5 # mm
step_angle = 1.8 # °
# Calculation one Step
step_distance = rev_distance/36... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Initialize Oorb
Step2: Read in some orbits.
Step3: Generate ephemerides
Step4: Transform orbital elements
Step5: There can be larger differe... | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import pyoorb as oo
# Initialize oorb
oo.pyoorb.oorb_init()
timeScales = {'UTC': 1, 'UT1': 2, 'TT': 3, 'TAI': 4}
elemType = {'CART': 1, 'COM': 2, 'KEP': 3, 'DEL': 4, 'EQX': 5}
# Set up some orbits
# orb is id, 6 elements, epoch_mjd, H, G, element type index
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2. Using Bio.Entrez to list available databases
Step2: The variable record contains a list of the available databases at NCBI, which you can se... | <ASSISTANT_TASK:>
Python Code:
# This line imports the Bio.Entrez module, and makes it available
# as 'Entrez'.
from Bio import Entrez
# The line below imports the Bio.SeqIO module, which allows reading
# and writing of common bioinformatics sequence formats.
from Bio import SeqIO
# This line sets the variable 'Entrez.... |
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Description:
Step1: <a id='svr_poly'></a>
Step2: <a id='svr_rbf'></a>
Step3: <a id='svr_sigmoid'></a>
Step4: SVR defaults<a id='svr_defaults'></a>
Step5: SVR ge... | <ASSISTANT_TASK:>
Python Code:
def svr_linear_config():
return {
'kernel': ('linear',),
'tol': (0.001,), # TODO add relevant range
'C': (1.0,), # ditto
'epsilon': (0.1,), # ditto
'shrinking': (True, False),
'max_iter': (-1,), # TODO add relevant range
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2. Simple Math in the Jupyter Notebook
Step2: uncomment this to download the data
Step3: Loading Data with Pandas
Step4: Now we can use the r... | <ASSISTANT_TASK:>
Python Code:
a = 1
a_list = [1, 'a', [1,2]]
a_list.append(2)
a_list
dir(a_list)
a_list.count(1)
a = 2
!ls
#!curl -o pronto.csv https://data.seattle.gov/api/views/tw7j-dfaw/rows.csv?accessType=DOWNLOAD
import pandas as pd
df = pd.read_csv('pronto.csv')
df.head()
df.columns
df.shape
df.dtypes
df_... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Lorenz system
Step4: Write a function solve_lorenz that solves the Lorenz system above for a particular initial condition $[x(0),y(0),z(0)]$. Y... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
def lorentz_derivs(yvec, t, sigma, rho, beta):
Compute the the derivatives for the Lorentz system at yvec(t).
x = yvec[0]
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Correlation analysis
Step2: P-value非常小，而ks statistic数值较大，认为FRI/FRII有一定的可分性。即原假设FRI/FRII的射电光学和光度服从统一分布是错误的。
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Python Code:
lumo_fr1_typical = lumo[idx2_same] * 10**-22
lumo_fr2_typical = lumo[idx3_same] * 10**-22
mag_fr1_typical = mag_abs[idx2_same]
mag_fr2_typical = mag_abs[idx3_same]
lumo_fr1_like = lumo[idx_fr1] * 10**-22
lumo_fr2_like = lumo[idx_fr2] * 10**-22
mag_fr1_like = mag_abs[idx_fr1]
mag_fr2_like ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: train_test split
Step2: QDA
Step3: LDA
Step4: solver
Step5: NB
Step6: BernoulliNB 쓸수 없음 => 타겟변수뿐만아니라 독립변수도 0또는 1값을 가져야 하기때문
Step7: Decisi... | <ASSISTANT_TASK:>
Python Code:
df1 = df.ix[:,0:8]
df1.tail() # 박사님께서 설명을 위해 뒷부분에 컬럼을 채워놓은 것같아서 who 부터 끝까지 잘랐습니다
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
df1['sex']= le.fit_transform(df1['sex'])
df1['embarked'] = le.fit_transform(df1['embarked'])
from sklearn.preprocessing import Imputer
imp =... |
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Description:
Step1: All we need to do is
| <ASSISTANT_TASK:>
Python Code:
# Update data
# autoupdate.autoupdate() # Comment in if needed, and loop if needed
# manip.get_5v5_player_log(2017, force_create) # Comment in if needed, and loop if needed
log = pd.concat([manip.get_5v5_player_log(season).assign(Season=season) for season in range(2012, 2018)])
sch = pd... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Model
Step2: check rates
Step3: It slightly underestimates heterogeneity, but is close for max rate
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Python Code:
%matplotlib inline
import ABCPRC as prc
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
def ibm(*ps):
m0,k = ps[0],ps[1]
T0 = 0.5
#measurements in regular increments throughout the year
ms,ts = np.zeros(100),np.linspace(0,1,100)
ms = (m0... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The sgrid object
Step2: The object knows about sgrid conventions
Step3: Being generic is nice! This is an improvement up on my first design ;... | <ASSISTANT_TASK:>
Python Code:
from netCDF4 import Dataset
url = ('http://geoport.whoi.edu/thredds/dodsC/clay/usgs/users/'
'jcwarner/Projects/Sandy/triple_nest/00_dir_NYB05.ncml')
nc = Dataset(url)
import pysgrid
# The object creation is a little bit slow. Can we defer some of the loading/computations?... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
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Python Code:
def findnum(s1 ) :
v =[]
a = 0
b = 0
sa = 0
sb = 0
i = 0
if(s1[0 ] == ' - ' ) :
sa = 1
i = 1
while(s1[i ] . isdigit() ) :
a = a * 10 +(int(s1[i ] ) )
i += 1
if(s1[i ] == ' + ' ) :
sb = 0
i += 1
if(s1[i ] == ' - ' ) :
sb = 1
i += 1
while(i... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Creating the parameter file
Step4: Let's describe the bands we will use. This must be a superset (ideally the union) of all the bands involved ... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats
import sys
sys.path.append('../')
from delight.io import *
from delight.utils import *
from delight.photoz_gp import PhotozGP
%cd ..
paramfile_txt =
# DELIGHT parameter file
# Syntactic rules:
# - Y... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Improving Reading Ability
Step3: Exercise
Step9: Paintball
Step10: Exercise
Step11: Exercise
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Python Code:
from __future__ import print_function, division
% matplotlib inline
import warnings
warnings.filterwarnings('ignore')
import math
import numpy as np
from thinkbayes2 import Pmf, Cdf, Suite, Joint
import thinkplot
import pandas as pd
df = pd.read_csv('drp_scores.csv', skiprows=21, delimit... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Modo correcto de definir una función
Step2: Ejemplo de uso de funciónes
Step3: y se desa calcular el promedio para cada uno, una forma de hace... | <ASSISTANT_TASK:>
Python Code:
printfunc(3)
def func(num):
return(num**num+num)
def func(num):
return(num**num+num)
func(3)
alex=[90,70,80,60,90]
kate=[60,70,90,70,90]
david=[90,60,80,90,80]
#Promedio para Alex
i=0
sumatoria = 0
while i < len(alex):
sumatoria += alex[i]
i += 1
promedio=sumatoria... |
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Description:
Step1: Saving and loading fields
Step2: Running the simulation
Step3: (Optional) Plotting
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Python Code:
from crpropa import *
randomSeed = 42
turbSpectrum = SimpleTurbulenceSpectrum(Brms=8*nG, lMin = 60*kpc, lMax=800*kpc, sIndex=5./3.)
gridprops = GridProperties(Vector3d(0), 256, 30*kpc)
BField = SimpleGridTurbulence(turbSpectrum, gridprops, randomSeed)
# print some properties of our field
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Import required modules
Step2: Target Configuration
Step3: Workload Execution and Functions Profiling Data Collection
Step4: Parse Trace and ... | <ASSISTANT_TASK:>
Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
# Generate plots inline
%matplotlib inline
import json
import os
# Support to access the remote target
import devlib
from env import TestEnv
from executor import Executor
# RTApp configurator for generation of PERIODIC tasks... |
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Description:
Step1: <table align="left">
Step2: Selection Bias
Step3: The treated group has a lower outcome mean than that of the control group, but the differenc... | <ASSISTANT_TASK:>
Python Code:
#@title Copyright 2019 The Empirical Calibration Authors.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# ... |
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Description:
Step1: Model Creation
Step2: The model is set up by default with a meridional diffusion term.
Step3: Create new subprocess
Step4: Note that the mode... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import climlab
from climlab import constants as const
# model creation
ebm_budyko = climlab.EBM()
# print model states and suprocesses
print(ebm_budyko)
# create Budyko subprocess
budyko_transp = climlab.dynamics.Bud... |
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Description:
Step1: Let's evaluate how much the membrane potential depends on Input resistance and
| <ASSISTANT_TASK:>
Python Code:
%pylab inline
import pandas as pd
#mypath = '/fs3/group/jonasgrp/MachineLearning/Cell_types.xlsx'
mypath = './Cell_types.xlsx'
df = pd.read_excel(io=mypath, sheetname='PFC', skiprows=1)
df.head()
df.columns
df['CellID']
for key in df.columns:
if df[key].dtype != object:
print"... |
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Description:
Step1: Damped, driven nonlinear pendulum
Step4: Write a function derivs for usage with scipy.integrate.odeint that computes the derivatives for the da... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
g = 9.81 # m/s^2
l = 0.5 # length of pendulum, in meters
tmax = 50. # seconds
t = np.linspace(0, tmax, int(... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Genome version
Step2: Products
| <ASSISTANT_TASK:>
Python Code:
bsmaploc="/Applications/bioinfo/BSMAP/bsmap-2.74/"
!curl \
ftp://ftp.ensemblgenomes.org/pub/release-32/metazoa/fasta/crassostrea_gigas/dna/Crassostrea_gigas.GCA_000297895.1.dna_sm.toplevel.fa.gz \
> /Volumes/caviar/wd/data/Crassostrea_gigas.GCAz_000297895.1.dna_sm.toplevel.fa.gz
!cur... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Where in your code does this error come from?
Step2: Stack trace
Step3: Printing during execution
Step4: Printing attributes of a variable
St... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import theano
import theano.tensor as T
x = T.vector()
y = T.vector()
z = x + x
z = z * y
f = theano.function([x, y], z)
f(np.ones((2,)), np.ones((3,)))
# TODO: finish to define the mode below
mode=...
import numpy as np
import theano
import theano.tensor as T
x = T.ve... |
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Description:
Step1: 1. Run a pre-trained Transformer
Step2: 2. Features and resources
Step3: Gradients can be calculated using trax.fastmath.grad.
Step4: Layers
... | <ASSISTANT_TASK:>
Python Code:
#@title
# Copyright 2020 Google LLC.
# 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... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1) create a vector of $d$ parameters
Step2: 2) Create an array of covariates
Step3: 3) Construct the conditional intensity $\lambda(t)$
Step4:... | <ASSISTANT_TASK:>
Python Code:
N = 10000# number of observations
d = 5 # number of covariates
theta = np.random.normal(size = (d,))
X = 0.1*np.random.normal(size = (d,N))
# X = linalg.orth(X.T).T
# X = np.eye((d))
l = np.exp(np.dot(X.T,theta))
dt = 0.001 # discretization step
u = np.random.uniform(size = len(l))
y... |
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Description:
Step1: ScrollZoomToggler
Step2: MarkerCluster
Step3: Terminator
Step4: Leaflet.boatmarker
Step5: Leaflet.TextPath
| <ASSISTANT_TASK:>
Python Code:
# This is to import the repository's version of folium ; not the installed one.
import sys, os
sys.path.insert(0,'..')
import folium
from folium import plugins
import numpy as np
import json
%load_ext autoreload
%autoreload 2
m = folium.Map([45.,3.], zoom_start=4)
plugins.ScrollZoomToggl... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Считаем данные по росту и весу (weights_heights.csv, приложенный в задании) в объект Pandas DataFrame
Step2: Чаще всего первое, что надо надо с... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
data = pd.read_csv('weights_heights.csv', index_col='Index')
data.plot(y='Height', kind='hist',
color='red', title='Height (inch.) distribution')
data.head(n=5)
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: So far the systems we have studied have been physical in the sense that they exist in the world, but they have not been physics, in the sense of... | <ASSISTANT_TASK:>
Python Code:
# install Pint if necessary
try:
import pint
except ImportError:
!pip install pint
# download modsim.py if necessary
from os.path import exists
filename = 'modsim.py'
if not exists(filename):
from urllib.request import urlretrieve
url = 'https://raw.githubusercontent.com/A... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Note
Step2: Lesson
Step3: Project 1
Step4: We'll create three Counter objects, one for words from postive reviews, one for words from negativ... | <ASSISTANT_TASK:>
Python Code:
def pretty_print_review_and_label(i):
print(labels[i] + "\t:\t" + reviews[i][:80] + "...")
g = open('reviews.txt','r') # What we know!
reviews = list(map(lambda x:x[:-1],g.readlines()))
g.close()
g = open('labels.txt','r') # What we WANT to know!
labels = list(map(lambda x:x[:-1].uppe... |
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Description:
Step1: Are we dealing with form or metric information here?
Step2: Revise and edit to best convey the scientific result.
| <ASSISTANT_TASK:>
Python Code:
import pickle
data = pickle.load(open('data/correlation_map.pkl', 'rb'))
data.keys()
type(data['excitation energy'])
data['excitation energy'].shape
data['correlation'].shape
import matplotlib
%matplotlib inline
matplotlib.style.use('ggplot')
import matplotlib.pyplot as plt
plt.imshow(dat... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Training a multi-layer perceptron
Step2: Neural networks tend to perform better when the inputs are scaled to have zero mean and unit variance.... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import expit
from sklearn import datasets, mixture
xs = np.linspace(-5, 5)
fig = plt.figure(figsize=(20, 5))
## Plot relu
ax1 = fig.add_subplot(1, 3, 1)
ax1.plot(xs, np.maximum(0, xs))
## Plot sigmoid
ax2 = fig.add_sub... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Wykresy punktowe
Step2: Histogramy
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(15,10))
ax = fig.add_subplot(111)
## the data
N = 5
menMeans = [18, 35, 30, 35, 27]
menStd = [2, 3, 4, 1, 2]
womenMeans = [25, 32, 34, 20, 25]
womenStd = [3, 5, 2, 3, 3]
## necessary variab... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The Elves in accounting are thankful for your help; one of them even offers you a starfish coin they had left over from a past vacation. They of... | <ASSISTANT_TASK:>
Python Code:
for a,b in itertools.permutations(list(map(int, data)), 2):
if a+b == 2020:
print(a*b)
break
for a,b,c in itertools.permutations(list(map(int, data)), 3):
if a+b+c == 2020:
print(a*b*c)
break
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Import section specific modules
Step2: 3.3 Horizontal Coordinates (ALT,AZ)
Step3: Figure 3.3.3
Step4: Figure 3.3.4
| <ASSISTANT_TASK:>
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
from IPython.display import HTML
HTML('../style/code_toggle.html')
import ephem
import matplotlib
%pylab inline
pylab.rcParams['figure.fi... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Bonus Material - Softmax Regression
Step2: First, we want to encode the class labels into a format that we can more easily work with; we apply ... | <ASSISTANT_TASK:>
Python Code:
%load_ext watermark
%watermark -a '' -u -d -v -p matplotlib,numpy,scipy
# to install watermark just uncomment the following line:
#%install_ext https://raw.githubusercontent.com/rasbt/watermark/master/watermark.py
%matplotlib inline
import numpy as np
y = np.array([0, 1, 2, 2])
y_enc = ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create a Raster Model Grid
Step2: Visualize Basin topography
Step3: Create a Network Model Grid
Step4: Let's plot our network
Step5: As are... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
# landlab modules
from landlab.plot.graph import plot_nodes, plot_links
from landlab.io import read_esri_ascii
# Package for plotting raster data
from landlab.plot.imshow import imshow_grid
from landlab.grid.create_network import network_... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Download weather data
Step2: Cleaning the weather dataset
Step3: Merge weather and NYPD MVC datasets
Step4: Make some nice data analysis
Step... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import datetime
from datetime import date
from dateutil.rrule import rrule, DAILY
from __future__ import division
import geoplotlib as glp
from geoplotlib.utils import BoundingBox, DataAccessObject
pd.set_option('display.max_columns', None)
%matplotl... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Setup and imports
Step2: Define your indico API key
Step4: Convenience function for making batches of examples
Step5: Check that the requeste... | <ASSISTANT_TASK:>
Python Code:
seed = 3 # for reproducibility across experiments, just pick something
train_num = 100 # number of training examples to use
test_num = 100 # number of examples to use for testing
base_model_name = "sentiment_train%s_test%s" % (train_num, test_num)
lab2bin = {'pos': 1, 'neg':... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: retrieving the available fields as a reference
Step2: build a field specific stop word list
Step3: plotting the wordcloud for abstracts and ti... | <ASSISTANT_TASK:>
Python Code:
client = MongoClient('localhost:27017')
db = client.arXivDB
db.arXivfeeds.count()
print(db.arXivfeeds.find_one().keys())
for item in db.arXivfeeds.find({'published_parsed': 2016}).sort('_id', pymongo.DESCENDING).limit(5):
print(item['title'])
#db.arXivfeeds.delete_many({})
def clean... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Example with more savings, but slower to optimize
Step2: Look at the recommendations
| <ASSISTANT_TASK:>
Python Code:
def func(a, b, c):
res = tf.einsum('ijk,ja,kb->iab', a, b, c) + 1
res = tf.einsum('iab,kb->iak', res, c)
return res
a = tf.random_normal((10, 11, 12))
b = tf.random_normal((11, 13))
c = tf.random_normal((12, 14))
# res = func(a, b, c)
orders, optimized_func = tf_einsum_opt.opt... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Let's start by creating some data that we can store. 2000 images with shape (254, 254, 3) along with 2000 targets are generated.
Step2: The ten... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import time
import numpy as np
import pyxis as px
np.random.seed(1234)
nb_samples = 2000
X = np.zeros((nb_samples, 254, 254, 3), dtype=np.uint8)
y = np.arange(nb_samples, dtype=np.uint8)
X[10, :, :, 0] = 255
db = px.Writer(dirpath='data', map_size_... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: For information on how to configure and tune the solver, please see the documentation for optlang project and note that model.solver is simply a... | <ASSISTANT_TASK:>
Python Code:
import cobra.test
model = cobra.test.create_test_model('textbook')
model.solver = 'glpk'
# or if you have cplex installed
model.solver = 'cplex'
type(model.solver)
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: First we'll load the text file and convert it into integers for our network to use.
Step3: Now I need to split up the data into batches, and in... | <ASSISTANT_TASK:>
Python Code:
import time
from collections import namedtuple
import numpy as np
import tensorflow as tf
with open('anna.txt', 'r') as f:
text=f.read()
vocab = set(text)
vocab_to_int = {c: i for i, c in enumerate(vocab)}
int_to_vocab = dict(enumerate(vocab))
chars = np.array([vocab_to_int[c] for c ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1. 입력DataLoader 설정
Step2: 2. 사전 설정
Step3: 3. Trainning loop
Step4: 4. Predict & Evaluate
Step5: 5. save model parameter
Step6: 6. plot imag... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
from torchvision import datasets, transforms
from torch.autograd import Variable
import matplotlib.pyplot as plt
import numpy as np
is_cuda = torch.cuda.is_available() # cuda사 사용가능시, ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We can now import the deepchem package to play with.
Step2: Anatomy of a Dataset
Step3: We now have three Dataset objects
Step4: There's a lo... | <ASSISTANT_TASK:>
Python Code:
!pip install --pre deepchem
import deepchem as dc
dc.__version__
tasks, datasets, transformers = dc.molnet.load_delaney(featurizer='GraphConv')
train_dataset, valid_dataset, test_dataset = datasets
print(test_dataset)
test_dataset.y
for X, y, w, id in test_dataset.itersamples():
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'bcc', 'sandbox-2', 'ocnbgchem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "e... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load the weight matrices from the training
Step2: Visualize the digit from one hot representation through the activity weight matrix to the ima... | <ASSISTANT_TASK:>
Python Code:
import nengo
import numpy as np
import cPickle
import matplotlib.pyplot as plt
from matplotlib import pylab
import matplotlib.animation as animation
#Weight matrices generated by the neural network after training
#Maps the label vectors to the neuron activity of the ensemble
label_weight... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Notice that we have a lot of speeches that are relatively short. They probably aren't the best for clustering because of their brevity
| <ASSISTANT_TASK:>
Python Code:
!curl -O http://www.cs.cornell.edu/home/llee/data/convote/convote_v1.1.tar.gz
!tar -zxvf convote_v1.1.tar.gz
paths = glob.glob("convote_v1.1/data_stage_one/development_set/*")
speeches = []
for path in paths:
speech = {}
filename = path[-26:]
speech['filename'] = filename
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Let's load the actual data. We're going to use astropy to do that
Step2: Since this is Chandra data, we know where all the relevant information... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
try:
import seaborn as sns
except ImportError:
print("No seaborn installed. Oh well.")
import numpy as np
from scipy.special import gammaln as scipy_gammaln
import scipy.stats
import astropy.io.fits as fits
import astropy.mo... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Exploring the dataset
Step2: Based on the above exploratory commands, I believe that the following questions can be answered using the dataset
... | <ASSISTANT_TASK:>
Python Code:
# The first step is to import the dataset into a pandas dataframe.
import pandas as pd
#path = 'C:/Users/hrao/Documents/Personal/HK/Python/ml-20m/ml-20m/'
path = '/Users/Harish/Documents/HK_Work/Python/ml-20m/'
movies = pd.read_csv(path+'movies.csv')
movies.shape
tags = pd.read_csv(path+... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Webdriver
Step2: 下载和设置Webdriver
Step3: 访问页面
Step4: 查找元素
Step5: 这里我们通过三种不同的方式去获取响应的元素，第一种是通过id的方式，第二个中是CSS选择器，第三种是xpath选择器，结果都是相同的。
Step6: 多... | <ASSISTANT_TASK:>
Python Code:
!pip install selenium
from selenium import webdriver
help(webdriver)
#browser = webdriver.Firefox() # 打开Firefox浏览器
browser = webdriver.Chrome() # 打开Chrome浏览器
from selenium import webdriver
browser = webdriver.Chrome()
browser.get("http://music.163.com")
print(browser.page_source)
#... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Flower power
Step2: ConvNet Codes
Step3: Below I'm running images through the VGG network in batches.
Step4: Building the Classifier
Step5: ... | <ASSISTANT_TASK:>
Python Code:
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
vgg_dir = 'tensorflow_vgg/'
# Make sure vgg exists
if not isdir(vgg_dir):
raise Exception("VGG directory doesn't exist!")
class DLProgress(tqdm):
last_block = 0
def hook(self, block_... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create sample data set
Step2: Winsorize
| <ASSISTANT_TASK:>
Python Code:
import pandas as pd # pandas for handling mixed data sets
import numpy as np # numpy for basic math and matrix operations
from scipy.stats.mstats import winsorize # scipy for stats and more advanced calculations
scratch_df = pd.DataFrame({'x... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Load raw data
Step2: Train and Evaluate input Functions
Step3: Feature columns for Wide and Deep model
Step4: We also add our engineered feat... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
import shutil
print(tf.__version__)
!gsutil cp gs://cloud-training-demos/taxifare/small/*.csv .
!ls -l *.csv
CSV_COLUMN_NAMES = ["fare_amount","dayofweek","hourofday","pickuplon","pickuplat","dropofflon","dropofflat"]
CSV_DEFAULTS = [[0.0],[1],... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Cf. jp-quadratic.html
Step2: Simplify
Step3: Then quadratic becomes
Step4: Define a "native" pm function.
Step5: The resulting trace is shor... | <ASSISTANT_TASK:>
Python Code:
from notebook_preamble import J, V, define
define('quadratic == over [[[neg] dupdip sqr 4] dipd * * - sqrt [+] [-] cleave] dip 2 * [truediv] cons app2 roll< pop')
J('3 1 1 quadratic')
define('pm == [+] [-] cleave popdd')
define('quadratic == over [[[neg] dupdip sqr 4] dipd * * - sqrt p... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set some colors and linestyles.
Step2: Hardcode the loop length. In this paper, we only use a single loop half-length of $L=40$ Mm.
Step3: Fir... | <ASSISTANT_TASK:>
Python Code:
import os
import sys
import pickle
import numpy as np
import seaborn.apionly as sns
import matplotlib.pyplot as plt
from matplotlib import ticker
sys.path.append(os.path.join(os.environ['EXP_DIR'],'EBTEL_analysis/src'))
import em_binner as emb
%matplotlib inline
plt.rcParams.update({'figu... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2. Training
Step2: Model 2
Step3: Model 3
Step4: 3. Evaluate
Step5: 4. Final Result(Ensemble)
| <ASSISTANT_TASK:>
Python Code:
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
# test data
test_images = mnist.test.images.reshape(10000, 28, 28, 1)
test_labels = mnist.test.labels[:]
augmentation_size = 440000
images = np.concatenate((mnist.train.images.reshape(55000, 28, 28, 1), mnist.validation.images... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Audio Data Preparation and Augmentation
Step2: Usage
Step3: In the above example, the Flac file brooklyn.flac is from a publicly accessible au... | <ASSISTANT_TASK:>
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 writin... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: 1. kNN
Step3: 1. kNN
Step4: 2. Aplicación al Iris Dataset
Step5: 2. Aplicación al Iris Dataset
Step6: 2. Aplicación al Iris Dataset
Step7:... | <ASSISTANT_TASK:>
Python Code:
def hamming(s1, s2):
# Caso no comparable
if len(s1)!=len(s2):
print("No comparable")
return None
h = 0
# Caso comparable
for ch1, ch2 in zip(s1,s2):
if ch1!=ch2:
h+= 1
# FIX ME
return h
print hamming("cara", "c")
print hamm... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Implement a basic sub-string counter
Step2: Check if a string is ascii encoded
Step3: Solution
| <ASSISTANT_TASK:>
Python Code:
s = 'ABCD'
for i in range(0, len(s)):
print (s[i])
string = 'ABCABDEABCF'
sub_string = 'ABC'
string[5:7]
def output_substring(string, sub_string):
for i in range(0, len(string)-len(sub_string)+1):
n = i
print (string[n:(n+len(sub_string))])
output_substring(string,... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Write a Jython function for IDV and export as IDV Formula in GUI
Step2: Above function was created for use in this session, it will not be avai... | <ASSISTANT_TASK:>
Python Code:
def moistStaticEnergy(T,Q,GZ):
Calculates Moist Static Energy with Temperature, Specific Humidity and Geopotential Height.
from ucar.visad.quantities import SpecificHeatCapacityOfDryAirAtConstantPressure,LatentHeatOfEvaporation
cp=SpecificHeatCapacityOfDryAirAtConstantPressu... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Convert the monthly average flow rates to volumes using
Step2: Convert monthly runoff to annual runoff
| <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import calendar
from charistools.hypsometry import Hypsometry
from charistools.timeSeries import TimeSeries
import datetime as dt
import pandas as pd
import numpy as np
import os
import re
from time import strptime
%cd /Users/brodzik/projects/CHARIS/s... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'sandbox-3', 'atmoschem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: given the RFAM id of a family we retrieve it from the RFAM online database
Step2: prepare a function that composes all desired pre-processing s... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from eden.util import configure_logging
import logging
configure_logging(logging.getLogger(),verbosity=2)
def rfam_uri(family_id):
return '%s.fa'%(family_id)
def rfam_uri(family_id):
return 'http://rfam.xfam.org/family/%s/alignment?acc=%s&format=fastau&download... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Types Matter
Step2: Switching Types
Step3: Inputs type str
Step4: We can use a built in Python function to convert the type from str to our d... | <ASSISTANT_TASK:>
Python Code:
a = "4"
type(a) # should be str
a = 4
type(a) # should be int
a = 4
b = 5
a + b # this plus in this case means add so 9
a = "4"
b = "5"
a + b # the plus + in this case means concatenation, so '45'
x = "45" # x is a str
y = int(x) # y is now an int
z = float(x) # z is a float
print(x,y,... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Ejecutar códigos con otros kernels
Step2: Cargar datos
Step3: Gráficos
Step4: Widgets
Step5: Para más informaciones sobre ipywidgets, consul... | <ASSISTANT_TASK:>
Python Code:
a = 1
b = 2.2
c = 3
d = 'a'
%who
def f1(n):
for x in range(n):
pass
%%time
f1(100)
%%timeit
f1(100)
%%bash
ls -lah
import pandas as pd
df = pd.read_csv('data/kaggle-titanic.csv')
df.head()
df.info()
df.describe()
from matplotlib import pyplot as plt
df.Survived.value_count... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Exploring Your Data
Step3: Two Dimensions
Step5: Many Dimensions
Step9: Cleaning And Munging
Step10: Manipulating Data
Step11: Rescaling
St... | <ASSISTANT_TASK:>
Python Code:
def bucketize(point, bucket_size):
floor the point to the next lower multiple of bucket size
return bucket_size * math.floor(point / bucket_size)
def make_histogram(points, bucket_size):
return Counter(bucketize(point, bucket_size) for point in points)
def plot_histogram(point... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Make population dynamic model
Step2: Population of haplotypes maps to counts and fitnesses
Step3: Map haplotype string to fitness float.
Step4... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import itertools
pop_size = 100
seq_length = 10
alphabet = ['A', 'T']
base_haplotype = "AAAAAAAAAA"
fitness_effect = 1.1 # fitness effect if a functional mutation occurs
fitness_chance = 0.1 # chance that a mutation has a fitness effect
pop = {}
pop["AAAAAAAAAA"] = 40... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Simulation
Step2: Spielverläufe
Step3: Ergebnisse
| <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from random import random, choice
# Kugeln (Werte erstmal unwichtig)
black, red, green, white = 0, 1, 2, 7
# Urnen
kugeln_urne1 = [white, white, white, black, black]
kugeln_urne2 = [white, green, green, red, red]
# Wkeiten
p_urne1 = 0... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: matplotlib figure
Step2: matplotlib axes
Step3: matplotlib artists
| <ASSISTANT_TASK:>
Python Code:
import autofig
import numpy as np
import matplotlib.pyplot as plt
#autofig.inline()
x = np.linspace(0,0.1,11)
y = x**2
mplfig = autofig.plot(x=x, y=y, show=True)
print dir(mplfig)
mplfig.set_facecolor('blue')
mplfig
mplfig.axes
mplax = mplfig.axes[0]
print dir(mplax)
mplax.set_xticks([0... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 이 히스토그램에서 -0.143394 부터 0.437156 사이의 값이 전체의 약 24%를 차지하고 있음을 알 수 있다. 그럼 만약 -0.01 부터 0.01 사이의 구간에 대한 정보를 얻고 싶다면? 더 세부적인 구간에 대해 정보를 구하고 싶다면 히스토그램의 ... | <ASSISTANT_TASK:>
Python Code:
sp.random.seed(0)
x = sp.random.normal(size=1000)
ns, bins, ps = plt.hist(x, bins=10)
pd.DataFrame([bins, ns/1000])
ns, bins, ps = plt.hist(x, bins=100)
pd.DataFrame([bins, ns/1000])
x = np.linspace(-3, 3, 100)
y = sp.stats.norm.pdf(x)
plt.plot(x, y)
<END_TASK> |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: In this example notebook, we will walk through the creation of logsums from
Step2: We'll also load the saved model from the mode choice estimat... | <ASSISTANT_TASK:>
Python Code:
# TEST
import larch.numba as lx
from pytest import approx
import os
import numpy as np
import xarray as xr
from addicty import Dict
from larch import P, X
import larch.numba as lx
hh, pp, tour, skims = lx.example(200, ['hh', 'pp', 'tour', 'skims'])
exampville_mode_choice_file = lx.examp... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step3: Data
Step6: We make a vocabulary, replacing any word that occurs less than 10 times with unk.
Step8: Mikolov suggested keeping word $w$ with p... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import math
import os
import random
random.seed(0)
import jax
import jax.numpy as jnp
try:
from flax import linen as nn
except ModuleNotFoundError:
%pip install -qq flax
from flax import linen as nn
from flax.training import t... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: First here's a very compact set of statements to get and plot the data for a station. No exploratory side trips.
Step2: Now the same thing, but... | <ASSISTANT_TASK:>
Python Code:
from datetime import datetime, timedelta
import pandas as pd
from pyoos.collectors.nerrs.nerrs_soap import NerrsSoap
# FROM pyoos SOS handling
# Convenience function to build record style time series representation
def flatten_element(p):
rd = {'time':p.time}
for m in p.members:
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step2: 1 - The problem of very deep neural networks
Step4: Expected Output
Step6: Expected Output
Step7: Run the following code to build the model's... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from keras import layers
from keras.layers import Input, Add, Dense, Activation, ZeroPadding2D, BatchNormalization, Flatten, Conv2D, AveragePooling2D, MaxPooling2D, GlobalMaxPooling2D
from keras.models import Model, load_model
from keras.preprocessing import image
from ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Now that you have imported the library, we will walk you through its different applications. You will start with an example, where we compute fo... | <ASSISTANT_TASK:>
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)
y_hat = tf.constant(36, ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Read history file from Virtual Explorer
Step2: Visualise calculated geophysical fields
Step3: We now get two files for the caluclated fields
S... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import sys, os
import matplotlib.pyplot as plt
# adjust some settings for matplotlib
from matplotlib import rcParams
# print rcParams
rcParams['font.size'] = 15
# determine path of repository to set paths corretly below
repo_path = os.path.realpath('../..')
import pynod... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Example - Tunnel Traffic
Step2: Let's take a look at seasonal plots over a week and over a year.
Step3: Now let's look at the periodogram
Step... | <ASSISTANT_TASK:>
Python Code:
#$HIDE_INPUT$
import numpy as np
def fourier_features(index, freq, order):
time = np.arange(len(index), dtype=np.float32)
k = 2 * np.pi * (1 / freq) * time
features = {}
for i in range(1, order + 1):
features.update({
f"sin_{freq}_{i}": np.sin(i * k),
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step2: 1. Utility functions
Step3: 2. Open the data file
Step4: We can open the file, as a normal HDF5 file
Step5: The object h5file is a pytables f... | <ASSISTANT_TASK:>
Python Code:
from __future__ import division, print_function # only needed on py2
%matplotlib inline
import numpy as np
import h5py
import matplotlib.pyplot as plt
def print_children(group):
Print all the sub-groups in `group` and leaf-nodes children of `group`.
Parameters:
data_file... |
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step2: Examine a single patient
Step4: Here we can see that these drugs were documented 2153 minutes (1.5 days) after ICU admission, but administered ... | <ASSISTANT_TASK:>
Python Code:
# Import libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import psycopg2
import getpass
import pdvega
# for configuring connection
from configobj import ConfigObj
import os
%matplotlib inline
# Create a database connection using settings from config file
... |
<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: 2. Read in the hanford.csv file in the data/ folder
Step2: <img src="../../images/hanford_variables.png"></img>
Step3: 4. Find a reasonable th... | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
%matplotlib inline
import numpy as np
from sklearn.linear_model import LogisticRegression
df = pd.read_csv("hanford.csv")
df.head()
df.describe()
df.median()
rang= df['Mortality'].max() - df['Mortality'].min()
rang
iqr_m = df['Mortality'].quantile(q=0.75)- df['Mortal... |
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