python-2.7

问题 Suppose I have a string such as 'I hate *some* kinds of duplicate. This string has a duplicate phrase, duplicate phrase.' I want to remove the second occurrence of duplicate phrase without removing other occurrences of its constituent parts, such as the other use of duplicate . Moreover, I need to remove all potential duplicate phrases, not just the duplicates of some specific phrase that I know in advance. I have found several posts on similar problems, but none that have helped me solve my

问题 Suppose I have a string such as 'I hate *some* kinds of duplicate. This string has a duplicate phrase, duplicate phrase.' I want to remove the second occurrence of duplicate phrase without removing other occurrences of its constituent parts, such as the other use of duplicate . Moreover, I need to remove all potential duplicate phrases, not just the duplicates of some specific phrase that I know in advance. I have found several posts on similar problems, but none that have helped me solve my

问题 Given the following dictionary and set: d = {1 : a, 2 : b, 3 : c, 4 : d, 5 : e } s = set([1, 4]) I was wondering if it is possible to remove all dictionary entries that are not contained in the set (i.e. 2,3,5). I am aware that i can achieve this by iterating over the dictionary and check each key but since i'm new to Python and came across many "shortcuts" so far I was wondering if there exists one for this particular problem. 回答1: d = {1 : 'a', 2 : 'b', 3 : 'c', 4 : 'd', 5 : 'e' } s = set(

问题 I would like to remove any single letter from a string in python. For example: input: 'z 23rwqw a 34qf34 h 343fsdfd' output: '23rwqw 34qf34 343fsdfd' Been trying to figure out for a while with regex without success. I know how to cut things from certain char/symbol in two pieces, but not what I am trying to do. I have been tinkering with re.sub(r'^[^ ]*', '', text) 回答1: >>> ' '.join( [w for w in input.split() if len(w)>1] ) '23rwqw 34qf34 343fsdfd' 回答2: import re text = "z 23rwqw a 34qf34 h

问题 Intro I am using a modified version of the Tensorflow tutorial "Deep MNIST for experts" with the Python API for a medical images classification project using convolutionnal networks. I want to artificially increase the size of my training set by applying random modifications on the images of my training set. Problem When I run the line : flipped_images = tf.image.random_flip_left_right(images) I get de following error : AttributeError: 'numpy.ndarray' object has no attribute 'get_shape' My

问题 Intro I am using a modified version of the Tensorflow tutorial "Deep MNIST for experts" with the Python API for a medical images classification project using convolutionnal networks. I want to artificially increase the size of my training set by applying random modifications on the images of my training set. Problem When I run the line : flipped_images = tf.image.random_flip_left_right(images) I get de following error : AttributeError: 'numpy.ndarray' object has no attribute 'get_shape' My

问题 I am trying to use the newer version of Python but when I type: import sys print sys.version_info I get back: sys.version_info(major=2, minor=7, micro=1, releaselevel='final', serial=0) In the terminal when I type python I get: Python 2.7.1 (r271:86832, Jun 16 2011, 16:59:05) [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2335.15.00)] on darwin When I type python3 I get: Python 3.3.2 (v3.3.2:d047928ae3f6, May 13 2013, 13:52:24) [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin As

问题 I am trying to use the newer version of Python but when I type: import sys print sys.version_info I get back: sys.version_info(major=2, minor=7, micro=1, releaselevel='final', serial=0) In the terminal when I type python I get: Python 2.7.1 (r271:86832, Jun 16 2011, 16:59:05) [GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2335.15.00)] on darwin When I type python3 I get: Python 3.3.2 (v3.3.2:d047928ae3f6, May 13 2013, 13:52:24) [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin As

问题 I was wondering how is it possible to detect new peaks within an FFT plot in Python. let's say i have this simple Plot: And i want to automatically measure the 'Similarity' or the Peaks location within a noisy Signal, i have tried to use the cosine Similarity but my real Signal is way too noisy, and with even if i add a new peak to the signal, i keep getting a Cosine of 0.9 since it's only one peak. This is an example of my real signal, and i also have the problem that my signal can be

问题 I was wondering how is it possible to detect new peaks within an FFT plot in Python. let's say i have this simple Plot: And i want to automatically measure the 'Similarity' or the Peaks location within a noisy Signal, i have tried to use the cosine Similarity but my real Signal is way too noisy, and with even if i add a new peak to the signal, i keep getting a Cosine of 0.9 since it's only one peak. This is an example of my real signal, and i also have the problem that my signal can be