matplotlib graph legend is in reverse order (barh)

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• Smart::Comments for Python?

  Are there any Python packages that provide similar functionality to perl's Smart::Comments?

  It has a number of features, but its core functionality is to make specially prefixed comments that contain variable names print those comments with the variables interpolated when the program is run.

  To take a simple example from the docs:

  ### Expected: 2 * $prediction
  ###      Got: $result
  

  prints:

  ### Expected: 42
  ###      Got: 13
  

  I've tried a number of debug priting packages for Python, and found that they all resulted in code that was too noisy, as the debug print statements were interspersed with the code.

  Smart::Comments lets me keep debug print statements in comments, where I can easily ignore them when I don't need to focus on them and focus on just the code instead.

  Is there anything like this for Python?

  I realise that Python's lack of sigils for variable names makes it impossible to distinguish variable names from any other word when they're in comments, but I'd be willing to prefix them with sigils in the comments, if it got the result I wanted.
• running mpi on OS X

  I'm parallelizing some python code on my laptop. It's a OS X macbook pro. while running the simple hello world code I notice I'm getting the same number for all processes is this correct? or I have configured something wrong?

  from mpi4py import MPI
  
  if (__name__ == '__main__'):
      comm = MPI.COMM_WORLD
      myrank = comm.Get_rank() 
      nproc = comm.Get_size()
      print("Hello, World ! from process {0} of {1} \n"
          .format(myrank , nproc))
  
  Hello, World ! from process 0 of 1
  
  Hello, World ! from process 0 of 1
  
  Hello, World ! from process 0 of 1
  
  Hello, World ! from process 0 of 1
  

  Here's how my /etc/hosts

  127.0.0.1       localhost
  255.255.255.255 broadcasthost
  ::1             localhost
  127.0.0.1       bobs.local
  
• How to fix TypeError: unsupported operand question

  I'm writing a function in Python product_z which computes the product of (N^z)/z * ∏ k/z+k from k=1 to N.

  The code looks like this;

  import numpy as np
  
  def z_product(z,N):
      terms = [k/(z+k) for k in range(1,N+1)]
      total = (N^z/z)*np.prod(terms)
      return total
  

  However, I'm running the code with this input for example but I get a TypeError in return.

  "Check that z_product returns the correct datatype."
  assert type(z_product(2,7)) == np.float64 , "Return value should be a NumPy float."
  print("Problem 2 Test 1: Success!")
  ---------------------------------------------------------------------------
  TypeError                                 Traceback (most recent call last)
  <ipython-input-9-d2e9161f328a> in <module>()
        1 "Check that z_product returns the correct datatype."
  ----> 2 assert type(z_product(2,7)) == np.float64 , "Return value should be 
  a NumPy float."
        3 print("Problem 2 Test 1: Success!")
  
  <ipython-input-8-1cd27b06388f> in z_product(z, N)
        1 def z_product(z,N):
        2     terms = [k/(z+k) for k in range(1,N+1)]
  ----> 3     total = (N^z/z)*np.prod(terms)
        4     return total
  
  TypeError: unsupported operand type(s) for ^: 'int' and 'float'
  

  What am I doing wrong and how do I fix this to make the code run?
• My current Ptyhon code at matplotlib is not running but if I change the data it does, what should I do?

  I have been struggling recently with my code:

  import numpy as np
  import matplotlib.pyplot as plt
  
  x1 = [5,10,15,17,20,21,23,24,25,26,30,35,40,45,50,55]
  dy = [0, 0, 0, 0, 0, 0.11547,0.34641, 0.46188, 0.57735, 0.46188, 0, 0, 0.57735, 1, 2.309401, 0]
  ya = [0,0,1,1.4,2,2.667,2.8,3.0667,3.8667,3.333,6,11,17.333,26,33.667,60]
  
  x2 = [5,10,15,17,20,21,23,24,25,26]
  dy2 = [0,0,0.57735,0.57735,0.57735,1.154701,1.732051,1.527525,0.57735]
  ya2 = [1,2,5.667,9.667,10.667,13.333,19,20.667,24.667,60]
  
  
  x = np.array(x1)
  y = np.array(ya)
  err = np.array(dy)
  a = np.array(x2)
  b= np.array(ya2)
  err2 = np.array(dy2)
  
  plt.xlabel("Time(min)")
  plt.ylabel("CO2 produced (mL)")
  plt.scatter(x2,ya2, label="5 g yeast", color="blue")
  plt.scatter(x1,ya, label="3 g yeast", color="green")
  plt.errorbar(a,b,yerr=err2,fmt='.', color="blue", ecolor="blue", capsize=5, capthick=1.5)
  plt.errorbar(x,y,yerr=err,fmt='.', color="green", ecolor="green", capsize=5, capthick=1.5)
  
  
  plt.title("Second conditional, changes in grams of yeast")
  plt.legend()
  plt.show()
  

  When I run it it appears ValueError: err must be [ scalar | N, Nx1 or 2xN array-like ]

  This is weird for me because I have used this code before and it run perfectly Thanks!
• SSH shuts down with broken pipe before python program finishes matplotlib part

  I am running a python 3 program via SSH which takes a few hours to finish. After all computations the program should save a matplotlib figure and then stop. What happens is that after all computations a Write failed: broken pipe error is shown and when I log back in the figure is not updated.

  Another question mentioned the process spawns child processes for the figure which might be killed when the main program finishes computation, so I ran it with nohup to no avail. What other options can I try out?
• matplotlib basemap etopo colorbar

  How can I generate a colorbar for basemap's etopo? I can't find any documentation on it but the NOAA poster for etopo has a colorbar (here).
• Pairwise distance of different elements in pandas

  I have a dataframe with some different elements, identified by an ID. For each of them LAT, LON are provided. A sample is provided below:

  ID       LAT        LON
  
  2426  0.351649  36.921941
  2451  0.351666  36.921939
  2457  0.351687  36.921966
  

  I would like to have a dictionary identified by the tuple (ID1,ID2) and the distance as value:

  {(2426,2451):d1, (2426,2457):d2, (2451,2457):d3}
  

  Now I am computing the distance between each pair with the following code:

  distances = {}
  ids = to_network['ID'].values
  for id_1 in ids:
      ids = np.delete(ids, np.where(ids == id_1), axis=0)
      for id_2 in ids:
          distances[(id_1,id_2)] = compute_distance_m(to_network.loc[(to_network['ID'] == id_1),'LAT'].values[0],to_network.loc[(to_network['ID'] == id_1),'LON'].values[0],to_network.loc[(to_network['ID'] == id_2),'LAT'].values[0],to_network.loc[(to_network['ID'] == id_2),'LON'].values[0])
  
  # Result in m
  def compute_distance_m(lat1,lon1,lat2,lon2):
      coords_1 = (lat1, lon1)
      coords_2 = (lat2, lon2)
      return geopy.distance.vincenty(coords_1, coords_2).km*1000
  
  #returns
  {(2426, 2451): 1.9917619328904765,
   (2426, 2457): 5.083739036769186,
   (2451, 2457): 3.7473346626876483}
  

  The problem is that this code is really slow, and I have billion of instances in the dataset, so I was looking for a better version that could work on the initial dataframe directly.
• Graphs Traversal. It's ok to store visited as property?

  I'm having a simple question that I have not found the answer yet.

  When I learned the BFS and DFS of a Graph, I used a visited[] array with the length of the vertices where each position is false if is not visited and true if it is.

  I have seen in another places that some people don't use an array of visited an instead of that, they store the visited in each node as a property.

  My question is: is it okay to do it in any of the ways?

  Thanks in advance
• Graph that connect between two groups

  I created a program that accepts two groups of sentences as input and makes some comparison between them. Each sentence from group 'A' has one or more matching sentences in group 'B', and sentence from group 'B' can match more than one sentence in 'A'. Each relationship has a numeric value. I'm trying to create a graph describing these connections for the purpose of easy visualization of the connections. I thought to create a bipartite graph so that each arc has value, Somthing like the example image below (group A on the left and group B on the right) (from here).

  I am looking for other ideas or maybe an library that I can use for it. Thank you.
• ggplot legend with geom_rect

  I am trying to create a legend item for a geom_rect legend. But the legends also shows a shape as well instead of a simple grey rectangle (see example below).

  Is there a way to create a legend item that only shows the grey rectangle for the geom_rect and a filled shape for the data points?

  library(ggplot2)
  
  ggplot(iris, aes(Sepal.Length, Sepal.Width))+ 
    geom_rect(mapping=aes(xmin=5.5,
                           xmax=6.5,
                            ymin=2.5,
                           ymax=3.5,fill="historic range"))+
    geom_point(aes(Sepal.Length, Sepal.Width,fill="Data points",shape="Data points")) +
    scale_fill_manual(values=c("darkgreen","grey"),labels=c("Data points","historic range")) +
    scale_shape_manual(values=c(22),labels=c("Data points"))
  

  Result with code above:
• Why is there an error regarding handles with labels in Python?

  I am trying to plot from a .txt file and I am getting an error when executing regarding the legend. I'm not sure what the error here is. Here is the code:

  # -*- coding: utf-8 -*-
  import numpy as np
  import matplotlib.pyplot as plt
  from scipy.optimize import curve_fit
  plt.close('all')
  
  #-----------------------------------------------------------------------
  # read data
  #-----------------------------------------------------------------------
  DATA_PATH = '/home/public/WS1819_Ex3/experiments/exercise_02/Absorption.txt'
  data = np.genfromtxt(DATA_PATH, skip_header=1)
  x, y1, y2, y3 = data[:,0], data[:,1], data[:,2], data[:,3]
  
  #-----------------------------------------------------------------------
  # prepare canvas
  #-----------------------------------------------------------------------
  
  fig, ax = plt.subplots(1, 1)
  ax.grid(True)
  ax.set_xlabel('Abstand [cm]')
  ax.set_ylabel(u'Intensität [V]')
  ax.set_title(u'Absorption von Licht in Wasser')
  # set logarithmic y-scale
  ax.set_yscale('log')
  #-----------------------------------------------------------------------
  # plot data
  plt.plot(x,y1)
  plt.show()
  
  ax.legend()
  fig.savefig('Absorption.pdf')
  

  And here is the output:

  OUTPUT:
  
  No handles with labels found to put in legend.
  
• MATLAB plot: automatically using a column variable (Name) as Display Name in the legend

  So I have a series of temperature loggers which all have a specific name and I want to plot them as follows:

  

  Now, as you can see in the example plot I added, the legend automatically labels the lines as data1, data2, data3,.... However, I need the legend to show the names of the loggers. Because there are many loggers, I need MATLAB to do it automatically because it would take hours to use DisplayName and type in every logger name manually. Does anyone know how I can chose a column in my data table as the name for my lines? My table is built as follows:

  Name of logger 1| Date | Temperature | Name of logger 2 | Date | Temperature % and so on
  

  This is part of the code I use for the plots:

  hold on
  for i=2:2:35
     plot(data{:,1}, data{:,i})
  end
  hold off
  

  structure of the data:

  
• Append reversed dataframe to original dataframe

  does anyone know how to append a reverse dataframe to a given dataframe? I am representing paths. Each unique id stands for one path in the dataframe. Given the columns x,y,t,id,frequency I want to reverse mainly the x,yvalues and append them to the input dataframe. The id should go on increasing and the frequency can stay the same as in the original. I mean it is not really a clean reverse but more like in the example here:

  df1 = pd.DataFrame({'x':[1,1,2,9,9], 'y':[1,2,2,100,101],'t':[1,2,3,1,2],'id':[1,1,1,2,2]},'frequency':[5,5,5,1,1]})
  x   y   t   id   frequency
  1   1   1   1     5
  1   2   2   1     5
  2   2   3   1     5
  9  100  1   2     1
  9  101  2   2     1
  

  should become:

  x   y   t   id   frequency
  1   1   1   1     5
  1   2   2   1     5
  2   2   3   1     5
  9  100  1   2     1
  9  101  2   2     1
  -------------------   ---> here begins the reverse
  2   2   1   3     5
  1   2   2   3     5
  1   1   3   3     5
  9  101  1   4     1
  9  100  2   4     1
  

  I tried some approaches but could not find a solution. Does anyone know how to do it?
• Parse date in pyspark without udf

  I am trying to parse a date column in pyspark by replacing dd/mm/yyyy with yyyy-mm-dd.

  import pyspark.sql.functions as F
  spark = SparkSession.builders.appName('test').getOrCreate()
  sc = spark.sparkContext
  sqlc = pyspark.sql.SQLContext(sc)
  
  df = sqlc.createDataFrame([('01/01/2018','user1'),('28/02/2017','user2')], ['Date','user'])
  df.show()
  +----------+-----+
  |      Date| user|
  +----------+-----+
  |01/01/2018|user1|
  |28/02/2017|user2|
  +----------+-----+
  

  What I've done so far is:

  df.select( F.concat_ws('-',F.split(F.col('Date'),'/')).alias('Date_parsed')).show()
  +-----------+
  |Date_parsed|
  +-----------+
  | 01-01-2018|
  | 28-02-2017|
  +-----------+
  

  What I would like to obtain is:

  +-----------+
  |Date_parsed|
  +-----------+
  | 2018-01-01|
  | 2017-02-28|
  +-----------+
  

  Any idea how to do this without using a udf?
• Compare two reversal user input

  I'm really a beginner in programming and this question is my homework. the question is:

  compare 2 numbers reversal.

  for example:

  123>321
  201>800
  

  input

  In the first line the first number and the next line enter the second number. The input numbers are integers and 3digits

  sample input1:

  123
  421
  

  sample output1:

  421<123
  

  sample input2:

  121
  121
  

  sample output2:

  121=121
  

  I try to get 2 input but I don't know how to continue with revers and compare

  Scanner scn = new Scanner(System.in);
  int x = scn.nextInt();
  int y = scn.nextInt();