I want to run modules of Geopandas in Spyder. Apparently Geopandas is compatible with Sypder 4.2.5, (not with any higher version) and I could run code with this combination. However, in one of my code I had to use "input" command and the problem starts there. Sypder 4.2.5 crashes if I try to run input command. From the internet, I came to know that there was a bug in spyder and it was fixed in Spyder 5.3. Now I have no idea how to fix this problem. If I upgrade Spyder, Geopandas will not work. If I don't upgrade spyder, 'input' will not work.
I was trying to run something like the following code
def Coditions_R3():
print("This is R3")
def Coditions_R4():
print("This is R4")
System = input('Please Enter drone system: \n' )
print(System)
if (System == 'R3'):
Coditions_R3()
elif (System == 'R4'):
Coditions_R4()
Can anyone help? is there any way around to run geopandas with higher Spyder versions? or use something else in place of input?
I'm quite new to Python so please have me excused if this question contain some newbie misunderstandings, but I've failed to google the answer for this:
On my personal laptop running Python 3.9.7 on Windows 11 this code is working without errors.
from dataclasses import dataclass, field
#dataclass
class SomeDataClass:
somelist: list[str] = field(default_factory=lambda:['foo', 'bar'])
if __name__ == '__main__':
instance = SomeDataClass()
print(instance)
But when at work running Python 3.8.5 on Windows 10 I get the following error:
File "c:\...\test_dataclass.py", line 13, in SomeDataClass
somelist: list[str] = field(default_factory=lambda:['foo', 'bar'])
TypeError: 'type' object is not subscriptable
I'd like to understand why this behaves differently and what I could do to make it work.
I would expect dataclasses to behave similarly on both computers.
You have already intuited the reason: this is a new feature in version 3.9. You can see it in the What's New article for 3.9 here.
This feature is available in version 3.8 as well, but it is not enabled by default. You can enable it in your code by including this import:
from __future__ import annotations
Good day to all,
2 weeks ago my pyplots graph were working good. Hoever this week using the same code they are not plotting corectly on the y_axis. I thank you in advance all the help. Please find below a link to an example notebook as well as the example code I took from here [2], using seabrone library.
On the following picture you can see that the first and last row are incomplete.
https://drive.google.com/open?id=1My18DBfbTLsmeN2TxKYeFMkezXMGeb5W
Or you can copy the following code:
import seaborn as sn
import pandas as pd
import matplotlib.pyplot as plt
array = [[33,2,0,0,0,0,0,0,0,1,3],
[3,31,0,0,0,0,0,0,0,0,0],
[0,4,41,0,0,0,0,0,0,0,1],
[0,1,0,30,0,6,0,0,0,0,1],
[0,0,0,0,38,10,0,0,0,0,0],
[0,0,0,3,1,39,0,0,0,0,4],
[0,2,2,0,4,1,31,0,0,0,2],
[0,1,0,0,0,0,0,36,0,2,0],
[0,0,0,0,0,0,1,5,37,5,1],
[3,0,0,0,0,0,0,0,0,39,0],
[0,0,0,0,0,0,0,0,0,0,38]]
df_cm = pd.DataFrame(array, index = [i for i in "ABCDEFGHIJK"],
columns = [i for i in "ABCDEFGHIJK"])
plt.figure(figsize = (10,7))
sn.heatmap(df_cm, annot=True)
## Retrieved from https://stackoverflow.com/questions/35572000/how-can-i-plot-a-confusion-matrix
I already solved it or at least I found the reason of the problem. There was an update of matplotlib. The lastest version is 3.1.1 and I was using 3.1.0. So I used the following command to install the 3.1.0 version on colab. After that everything went back to normal
#This was the code for changing the matplotlib version in Google Colab:
! pip install matplotlib==3.1.0
I am using tensorflow version 1.3. But the tutorial that I following is written on the version 1.0 and I am quite new on tensorflow. The problem that I get is:
module' object has no attribute 'prepare_attention
And the code is ;
tf.contrib.seq2seq.prepare_attention(attention_states, attention_option = "bahdanau", num_units = decoder_cell.output_size)
I couldn't figure out what the use instead of tf.contrib.seq2seq.prepare_attention() function. Is there anyone who can help?
Degrade your tensorflow and it'll work. The problem is that prepare_attention is deprecated and hence we use an older version of tf to work with it
Okay, all you need to do is create a new environment with python 3.5.4 and then install tensorflow 1.0.0. That's it. Everything will work fine.
tf.contrib.seq2seq.prepare_attention works only when the TensorFlow version is 1.0, I have version 2.3.1
My solution:
tf.contrib.seq2seq.prepare_attention = tf.compat.v1.nn.rnn_cell.prepare_attention
System information
custom code: no, it is the one in https://www.tensorflow.org/get_started/estimator
system: Apple
OS: Mac OsX 10.13
TensorFlow version: 1.3.0
Python version: 3.6.3
GPU model: AMD FirePro D700 (actually, two such GPUs)
Describe the problem
Dear all,
I am running the simple iris program:
https://www.tensorflow.org/get_started/estimator
under python 3.6.3 and tensorflow 1.3.0.
The program executes correctly, apart from the very last part, i.e. the one related to the confusion matrix.
In fact, the result I get for the confusion matrix is:
New Samples, Class Predictions: [array([b'1'], dtype=object), array([b'2'], dtype=object)]
rather than the expected output:
New Samples, Class Predictions: [1 2]
Has anything about confusion matrix changed in the latest release?
If so, how should I modify that part of the code?
Thank you very much for your help!
Best regards
Ivan
Source code / logs
https://www.tensorflow.org/get_started/estimator
This looks like a numpy issue. array([b'1'], dtype=object) is one way numpy represents the string '1'.