Indexerror index 0 is out of bounds for axis 0 with size 0
Indexerror index 0 is out of bounds for axis 0 with size 0
What does ‘index 0 is out of bounds for axis 0 with size 0’ mean?
I am new to both python and numpy. I ran a code that I wrote and I am getting this message: ‘index 0 is out of bounds for axis 0 with size 0’ Without the context, I just want to figure out what this means.. It might be silly to ask this but what do they mean by axis 0 and size 0? index 0 means the first value in the array.. but I can’t figure out what axis 0 and size 0 mean.
The ‘data’ is a text file with lots of numbers in two columns.
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So someplace in your code you are creating an array with a size 0 first axis.
When asking about errors, it is expected that you tell us where the error occurs.
Also when debugging problems like this, the first thing you should do is print the shape (and maybe the dtype ) of the suspected variables.
Applied to pandas
Resolving the error:
Essentially it means you don’t have the index you are trying to reference. For example:
will give me the error you are referring to, because I haven’t told Pandas how long my dataframe is. Whereas if I do the exact same code but I DO assign an index length, I don’t get an error:
Hope that answers your question!
This is an IndexError in python, which means that we’re trying to access an index which isn’t there in the tensor. Below is a very simple example to understand this error.
with this array arr in place, if we now try to assign any value to some index, for example to the index 0 as in the case below
The reason is that we are trying to access an index (here at 0 th position), which is not there (i.e. it doesn’t exist because we have an array of size 0 ).
So, in essence, such an array is useless and cannot be used for storing anything. Thus, in your code, you’ve to follow the traceback and look for the place where you’re creating an array/tensor of size 0 and fix that.
IndexError: index is out of bounds for axis 0 with size
The problem is, when I shuffle the training data and try to access to batches I get error saying:
Is there anybody who knows what am I doing wrong?
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you change the size of x_train with each iteration, yet you continue to use the train_idxs array that you created for the full size array.
It’s one thing to pull out random values from x_train in batches, but you have to keep the selection arrays consistent.
This question probably should have been closed for lack of a minimal, and verifiable example. It’s frustrating to have to guess and make a small testable example in hopes of recreating the problem.
If my current guess is wrong, just a few intermediate print statements would have made the problem clear.
Reducing your code to a simple case
I fed the (5,1) x_train back to the next_batch but tried to index it as though it were the original.
Changing the iteration to:
lets it run through producing 4 batches of 5 rows.
Not getting how to resolve «IndexError: index 0 is out of bounds for axis 0 with size 0»
I have a following table:
Trying the following Code:
but keep on getting the below error message:
Not getting what am I doing wrong?
After printing print(e_c_data) getting:
1 Answer 1
That error message is telling you that the object you’re indexing into has size 0— in other words, it’s empty. Why would it be empty? Well, you could put in print s to find out where it happens, or we can just look at your frame:
Assuming this is representative, note that your e_loc_id column starts with a 0. But if it’s an integer, it wouldn’t: those show up without leading zeros. Which means you must have strings:
But if your e_loc_ds are strings, this comparison will never succeed:
and so e_c_data is empty.
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What does ‘index 0 is out of bounds for axis 0 with size 0’ mean and how can I fix this error?
I am running a certain stoke prediction model code and getting the following error.
I have given below the code.
This is the error I am getting:
Is there anyway to resolve this error? I will share more dependencies information if required.
1 Answer 1
pred_price is an empty np.array so trying to index it like you have done on line 9 (» pred_price[0] «) will give an error. There has to be something in the array first.
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updated:IndexError: index 0 is out of bounds for axis 0 with size 0?
I have a questions about the following codes: I want to return 2 values in this function, one is orig_image which is fine, the other one is the cx,cx is the x-coordinate of the center of the biggest contour which’s area within certain range. The terminal saids «ValueError: too many values to unpack (expected 2)».(solved) Next problem pops out: «IndexError: index 0 is out of bounds for axis 0 with size 0?» May I know the reason and solution? Thankyou very much!
If I change the last part to:
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Your findContours function’s return value could be multiple form: None, targetCx, orig_image.
And at your function call side, you assume findContours function returns two return values exactly, tagetCx and original_image.
If None is returned, python cannot distribute it to your variables(targetCx, original_image) because None is not iterable. I don’t know what is in targetCx return value, maybe length of targetCx is greather than 2.
Suggestion
I think you want to get targetCx and original_image at the same time.
To achieve this, you should change your codes like this:
Getting Error: «IndexError: index 0 is out of bounds for axis 0 with size 0» #8085
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balandongiv commented Aug 4, 2020 •
Describe the bug
IndexError: index 0 is out of bounds for axis 0 with size 0
The full error trail:
Steps to reproduce
The text was updated successfully, but these errors were encountered:
larsoner commented Aug 4, 2020
I can’t replicate on Linux, it’s possible that this is a windows issue. Before I boot a VM to look into it, when you hit the error can you try:
and let us know the output? It can help with debugging
balandongiv commented Aug 4, 2020
larsoner commented Aug 4, 2020
Can you run Python from a standard terminal instead? Copy-pasting your code (with an import mne at the top) into some file then do:
It’s also likely that pycharm has some built-in debugging capability where you can have it drop to a prompt if it hits an error.
What does this error mean ‘IndexError: index 0 is out of bounds for axis 0 with size 0’?
I’m following a tutorial to train a chatbot. However, I keep getting this error and I don’t know what it means, line 16, in last_unix = df.tail(1)[‘unix’].values[0] IndexError: index 0 is out of bounds for axis 0 with size 0
Below is my code. line 16 is last_unix = df.tail(1)[‘unix’].values[0]
But that did nothing
I’m supposed to be getting the number of rows completed.
1 Answer 1
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How to solve «IndexError: index 0 is out of bounds for axis 0 with size 0` » error?
It is showing the following error. I have used 3 bands image and the resolution is 10000X10000 I don’t know how to solve it.
1 Answer 1
Your error occurred at instruction operating on image_dataset.
So probably just this array is empty (not mask_dataset as in a comment).
Of course, mask_dataset can also be empty, but this may come to light later, when this instruction gets executed.
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Error: IndexError: index 6319 is out of bounds for axis 0 with size 0
Th code below is taken from https://github.com/arunarn2/HierarchicalAttentionNetworks/blob/master/HierarchicalAttn.py with a few minor tweaks. Although I understand what the error means, I am not able to figure out how it is creeping in the following code and how to rectify it. I have been stuck on this for quite some time, would really appreciate some help. Thanks!
(This is the entire code)
1 Answer 1
Python is complaining because you are trying to access by index the labels array but it is empty, as displayed in the console output:
The problem is in this line:
A copy of arr with values appended to axis. Note that append does not occur in-place: a new array is allocated and filled.
If you want to achieve a similar behavior, you need to modify your code like this:
Please, be aware that this operation will be very inefficient for the reason explained, it is much better to append the sentiment result directly to the original labels list as in the original code:
IndexError: index 1 is out of bounds for axis 0 with size 1/ForwardEuler
I am numerically solving for x(t) for a system of first order differential equations. The system is:
I have implemented the Forward Euler method to solve this problem as follows: Here is my code:
I get following Traceback:
I don´t understand what is probably wrong.I already looked up after solved questions, but it doesn´t help me along.Can you find my error? I am using following code as an orientation: def euler( f, x0, t ):
My goal is to plot the function.
2 Answers 2
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The problem is with your line
Note: your imports are quite confused. You import numpy modules three times in the header, and then later import pylab (that already contains all numpy modules). If you want to go easy, with one single
line in the top you could use all the modules you need.
IndexError: index x is out of bounds for axis 0 with size x
The error takes place in this line (line 18):
I did see a few other similar errors on Stackoverflow, but I am too stupid to understand most of them, so please help, Thanks.
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Try changing your code to this:
The first thing is that you use derivatives, so your acceleration data has one fewer point than your velocity data. You could add a 0 value at the start (0-index) of the acceleration array like so aks.insert(0, 0) before iterating over it.
Now, there are many things in the code you do manually that can be essentially one-liners in numpy. Here are my suggestions:
IndexError: index 10000 is out of bounds for axis 0 with size 10000
IndexError: index 10000 is out of bounds for axis 0 with size 10000
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Mason Wheeler’s answer told you what Python was telling you. The problem occurs in this loop:
The simple fix is to change the loop to something like (I don’t know Python syntax, so bear with me):
That will stop the sim when you run out of array, but it will (potentially) also stop the sim with the projectile hanging in mid-air.
What you have here is a very simple ballistic projectile simulation, modeling atmospheric friction as a linear function of altitude. QUALITATIVELY, what is happening is that your projectile is not hitting the ground in the time you allowed, and you are attempting to overrun your tracking arrays. This is caused by failure to allow sufficient time-of-flight. Observe that the greatest possible time-of-flight occurs when atmospheric friction is zero, and it is then trivial to compute a closed-form upper bound for time-of-flight. You then use that upper bound as your time, and you will allocate sufficient array space to simulate the projectile all the way to impact.
IndexError: index 1000 is out of bounds for axis 0 with size 1000
I am very new to python and indexing is still difficult for me. I am trying to plot few values using iterative operation but it seems it is not working and giving me above error. Please help me. Thanks.
2 Answers 2
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This line is giving you the error i += 1
If you plan on using the while loop, don’t forget to add your break statement, otherwise you’ll be stuck in an infinite loop. Without any additional details, I don’t see why it is necessary in this case.
In addition to that, I would define H_2 as an empty list, and append any values in your calculation to it. According to the documentation, H_2 needs to be an array-like value.
So it should look like:
Hopefully the graph appears as expected.
So just as a general primer to indexes you need to remember that indexes are zero based. So if you have an array of 5 elements the index 0 will get you the first element, etc and index 4 will get you the 5th and last element. That being said index 5 is therefore trying to access the 6th element and so is invalid.
Now to Python, you should know that the ‘for x in list’ statement will iterate through all the elements in the lost, placing the actually value and not the index into the variable x.
IndexError: index 13 is out of bounds for axis 0 with size 13 issue
IndexError: index 13 is out of bounds for axis 0 with size 13
but I can’t seem to fix it. Can you please help me?
Here is a sample of the printed statements
sorted_prob [12, 13, 4, 2, 3, 0, 6, 1, 14, 5, 7, 8, 9, 11, 10]
sorted_prob len 15
word [3.9363772e-06 6.2428586e-07 1.2910984e-05 4.0524797e-06 4.3209013e-05 2.4976660e-07 1.3571737e-06 1.0090356e-09 1.5341955e-11 4.4677283e-12 1.8482331e-15 1.6146554e-14 9.9985778e-01 7.5455580e-05 4.0608529e-07]
number of classes 1
cur and end of inner 4 loop [[‘P-I’]]
classesind [‘A0-B’ ‘A0-I’ ‘A1-B’ ‘A1-I’ ‘A2-B’ ‘A2-I’ ‘A3-B’ ‘A3-I’ ‘A4-B’ ‘A4-I’ ‘O’ ‘P-B’ ‘P-I’]
sorted_prob [13, 12, 14, 1, 3, 0, 5, 4, 9, 2, 6, 7, 8, 11, 10]
sorted_prob len 15
word [1.40233034e-10 1.62562830e-09 1.44035496e-14 7.12817139e-10 2.15579486e-12 1.05151512e-11 2.58049413e-15 1.43085274e-15 1.61804985e-16 1.13536066e-13 4.95883708e-23 6.91257209e-19 1.88131162e-06 9.99998093e-01 7.41057393e-09]
IndexError: index 1 is out of bounds for axis 0 with size 1. and doesn’t run
Well my code goes like this:
And when I execute it Python says:
File «C:/Users/2014/Desktop/ddsdsa.py», line 45, in valorcdnuevo=eulerd(cb[i],cd[i],h,k3,k5)
IndexError: index 1 is out of bounds for axis 0 with size 1
1 Answer 1
Cb has length 1 on shape[0], therefore that causes an index out of bound exception when i reached value 1
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IndexError: index is out of bounds for axis 0 with size
The problem is, when I shuffle the training data and try to access to batches I get error saying:
Is there anybody who knows what am I doing wrong?
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you change the size of x_train with each iteration, yet you continue to use the train_idxs array that you created for the full size array.
It’s one thing to pull out random values from x_train in batches, but you have to keep the selection arrays consistent.
This question probably should have been closed for lack of a minimal, and verifiable example. It’s frustrating to have to guess and make a small testable example in hopes of recreating the problem.
If my current guess is wrong, just a few intermediate print statements would have made the problem clear.
Reducing your code to a simple case
I fed the (5,1) x_train back to the next_batch but tried to index it as though it were the original.
Changing the iteration to:
lets it run through producing 4 batches of 5 rows.
index 1 is out of bounds for axis 0 with size 1
IndexError: index 1 is out of bounds for axis 0 with size 1
1 Answer 1
means that activ has 1 row and N columns. activ[0] refers to the first row. activ[1] would raise an IndexError because there is no second row.
One way to fix the error while changing the least amount of your current code would be to use
However, assigning values to a NumPy array element-by-element is usually not the ideal way to take advantage of NumPy. You’ll get much better performance if you can express the computation as one done on larger arrays and without the Python for-loops.
For example, If I understand the shapes of the undefined arrays correctly, you could replace
How to eliminate those loops is a problem sufficiently difficult and interesting to justify a separate question. If you do post a new question about it, please include a minimal example with runnable code so it is absolutely clear what the desired output is for the given input.
IndexError: index 1491188345 is out of bounds for axis 0 with size 1491089723
I have a dataframe,df with 646585 rows and 3 columns which looks like :
I tried to pivot the dataframe using the code:
1 Answer 1
There is open Pandas issue describing this error.
AFAIK currently there is no solution/workaround provided, except reducing the data set
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IndexError: index 1 is out of bounds for axis 0 with size 1 #45
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roaur commented Jan 11, 2018 •
Thank you for all the work you’ve done to port SSD to Keras!
I’m trying to train a subset of annotated data from MS COCO using ssd7_training.ipynb with two classes (background and the one feature I’m interested in) and I’ve largely left your parameters the way they are in the repo except for file and directory paths. I’ve made it to 4. Run the training without a hitch ( n_train_samples and n_val_samples are giving the correct number of images I have in my directories).
Here is a sample of my training label data I’ve tried to mimic the labels.csv example in your Udacity training dataset:
| frame | xmin | xmax | ymin | ymax | class_id |
|---|---|---|---|---|---|
| 000000246963.jpg | 437 | 480 | 81 | 125 | 1 |
| 000000222094.jpg | 107 | 157 | 81 | 156 | 1 |
| 000000441586.jpg | 525 | 549 | 74 | 96 | 1 |
| 000000261888.jpg | 236 | 245 | 221 | 230 | 1 |
| 000000480944.jpg | 71 | 116 | 216 | 286 | 1 |
Thinking my data is set up correctly, I try to train it by executing what is included in ssd7_training.ipynb:
But I’m experiencing the following error when I start training:
/.conda/envs/deep-learning/lib/python3.6/site-packages/keras/engine/training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch) 2009 batch_index = 0 2010 while steps_done 2011 generator_output = next(output_generator) 2012 2013 if not hasattr(generator_output, ‘__len__’): StopIteration: «>
Is this error indicative of something that I haven’t correctly set up? I’m using Keras 2.0.8. I’m on commit 65c5ca572ec
The text was updated successfully, but these errors were encountered:
IndexError: index 0 is out of bounds for axis 0 with size 0 #626
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j3mdamas commented Jan 18, 2017
I installed yank using conda, and followed the tutorial, and it errored with:
I also attach the experiments.log file. Everything I tried was out of the box.
The text was updated successfully, but these errors were encountered:
Lnaden commented Jan 18, 2017
There are a few things that strike me as odd here. The first is that according to the error you posted here, MBAR detected 0 decorated samples across the entire simulation. Effectively its trying to run statistics on N=0, which it never expects and thus the error.
That leads me to the the 2nd problem in that the logfile you provided appears to show the simulation throwing NaN’s a couple times before giving up. We have been trying to work with OpenMM’s lead dev to trace down why we see NaN’s occurring and we think we may have finally gotten them all worked out in recent development versions.
What version of OpenMM are you running right now? conda list openmm
What command did you issue to start the analysis? The N=0 is worrying me since I think the minimum the de-correlation algorithm can return is 1.
I think we can fix part of the problem with a new version of OpenMM, its the 2nd part that may take more debugging.
j3mdamas commented Jan 18, 2017
Thanks for the prompt response. I am using openmm 7.0.1 (as a matter of clarity, it’s not the one in the omnia channel, but one we have on acellera channel, which is a sync of 7.0.1 https://anaconda.org/acellera/openmm).
Yeah, I saw the NaNs on the log, and I have seen that there has been some NaN issue reporting earlier, but I didn’t think it was related.
This is out-of-the-box tutorial/example. I didn’t do any modification.
Lnaden commented Jan 18, 2017
The NaN’s are very much related sadly, OpenMM 7.0.1 has some issues with the neighbor lists which cause NaN’s in YANK. It also looks like your sync has 7.1.0 which I think still had the outstanding NaN issues, there is a beta for 7.2.0 available for linux only through the omnia conda channel. What OS are you running this on?
In the meantime, I will try to replicate the analyze bug as best I can here. Can you provide what GPU you are using (and CUDA version if its an nvidia card). The OS would be helpful for this as well.
j3mdamas commented Jan 18, 2017
True, I was using an un-updated version. Sorry. I will try with 7.1.0 first, and then try with the 7.2.0 beta. I will report back.
jchodera commented Jan 18, 2017
For now, please try the 7.2.0 version, which you can get via:
since this contains the NaN bugfixes.
j3mdamas commented Jan 18, 2017
Ok John. I am going to try now
Lnaden commented Jan 19, 2017
@j3mdamas I figured out what happened. Your solvent phase crashed with a NaN resulting in the simulations stopping, however, YANK actually initializes both NetCDF files (where data is saved) before starting either phase of the simulation.
I think the update to the 7.2.0 beta of OpenMM should resolve the nans, allowing simulations to run, and avoiding this issue. Any luck with the new version?
j3mdamas commented Jan 19, 2017
New experiments.log file, still with NaN’s (but no retrying?)
j3mdamas commented Jan 19, 2017
@Lnaden thanks for your time. It would be great if we could put the example to work.
Lnaden commented Jan 19, 2017
The log file you provided does not show an actual crash, it shows a few NaN’s, but it just seems to stop at the end, so I don’t know what caused the termination, but I am guessing a series of NaN’s. The error you posted is the same problem as before in that the 2nd phase of the simulation part did not run since the first phase crashed, so the analysis step is still looking at a blank file.
@jchodera could it be that the version labeled 7.2.0 is actually using old code still? The Anaconda site says that the files for linux 7.2 were only uploaded about 23hrs ago (from this post). My personal current install of «7.2.0» has a version.py file which points to a github hash from late December, before all the neighbor list bugs went in. Since I don’t know quite how the openmm-dev builds are uploaded, is it possible that @j3mdamas has a version that does not have the bug fixes? Is the version.py file a decent way to check that?
j3mdamas commented Jan 19, 2017
Well, I don’t have other outputs. Am I doing anything wrong?
I’ve done the installation John suggested. If there’s a different version to install, please tell me, and I’ll install and test it. We want to calculate the free energy of solvation of many compounds and it would be really helpful to have this protocol working.
Lnaden commented Jan 19, 2017
No, you’re not doing anything wrong. The conda install process makes installing easy, but slightly harder to debug when there are subtle version differences and file updates. We just need to make sure we get you the right version to test with.
j3mdamas commented Jan 19, 2017
Lnaden commented Jan 19, 2017
If the version.py is to believed, then you have the most recent commit which should have had all the NaN bugfixes in. The fact that you are still seeing NaN’s indicate that there is still a bug we have not fully diagnosed yet. We (YANK devs) will need to coordinate with the OpenMM devs to figure out the bug, unless there is something I am missing.
j3mdamas commented Jan 19, 2017
So, do you guys solve this within you, or should I go to the openmm issues page?
Also, can everybody (you, for example) run this example? When you said:
I am also testing locally to try and replicate the issue here to further debug
I got the impression it is working for you. If it is so, what is your settings? Do you manually check-out the openmm repo or something? We are looking for a fast solution, even if not officially released.
jchodera commented Jan 19, 2017
If the version.py is to believed, then you have the most recent commit which should have had all the NaN bugfixes in. The fact that you are still seeing NaN’s indicate that there is still a bug we have not fully diagnosed yet. We (YANK devs) will need to coordinate with the OpenMM devs to figure out the bug, unless there is something I am missing.
Can you guys try to reproduce this locally? It is important to see if we can sort out those NaN issues ASAP since OpenMM is about to go into 7.1 release candidate.
Lnaden commented Jan 19, 2017
Keep the issue here, I am going to have to try and make a test case to replicate the issue and try before I can pass on the information.
I got the impression it is working for you. If it is so, what is your settings?
Its not really a fair comparison, I was also seeing NaN’s, but I had a slightly older version of the code that did not have the supposed fixes in.
Do you manually check-out the openmm repo or something?
I use conda to get my versions, I forgot that there is a nightly push to the omnia/label/dev channel and did not update. You can install OpenMM from source if you need to, but with the nightly conda build its not really required.
We are looking for a fast solution, even if not officially released.
I’m not sure how fast the solution will be since I first have to trap the error in a repeatable way. Sorry for the inconvenience on that part. What are you looking to do that you need a fast solution for if I may ask?
Can you guys try to reproduce this locally? It is important to see if we can sort out those NaN issues ASAP
@jchodera yes, that is now my highest priority since I knew that was coming down the works. I had not had issues on the example runs I was doing, but I also did not check every log file as I figured the NaN’s would halt the process eventually.
IndexError: index 2 is out of bounds for axis 0 with size 2
In Python you may come across IndexError: index 2 is out of bounds for axis 0 with size 2 from time to time.
The error relates to the use of indexes and the no of columns you are referencing.
We discussed single positional indexer is out-of-bounds and in that blog post, it was related to referencing indexes for rows that do not exist.
In this blog post, the error relates to referencing the index for columns that do not exist.
Lets walk through the code below and where the problem arises
So let us refresh ourselves with the data that is in the excel CSV file below:
As you can see the column index value can be either 0 or 1, this is because they represent the index values of the columns starting at 0 and ending at 1.
As a result by replacing it with a column index value within the proper range ( in this case 0 or 1), the error will disappear and the code will work as expected.
Finally, in a = df.iloc[4][1] you can also change the value 4, which is the index for that row to either 0,1,2,3 and the code will work with no errors as it brings back the values that you expect.
So in summary:
(A) This error happens when you try to use a column index value does not exist as it is outside the index values for the columns that are in the data set.
(B) If this error does occur always check the expected index values for each column and compare against what you are trying to return.