Domain error in arguments

I was trying to sample random variables subject to a given probability density function (pdf) with scipy.stats.rv_continuous:

class Distribution(stats.rv_continuous):
    def _pdf(self,x, _a, _c):
        return first_hitting_time(x, _a, _c)

where the function first_hitting_time is

#pdf of first hitting time of W_t + c*t on a. 
def first_hitting_time(_t, _a, _c=0.0):
    return _a/_t*np.exp(-0.5/_t*(_a-_c*_t)**2)/np.sqrt(2.0*np.pi*_t)

then I continue with

myrv= Distribution(name='hittingtime', a=0.002,b=30.0)
data3= myrv.rvs(size=10000, _a=1.0, _c=0.0)

and interpreter starts to complain-

Traceback (most recent call last):

  File "<ipython-input-246-71f67047462b>", line 1, in <module>
    data3= myrv.rvs(size=10000, _a=1.0, _c=0.0)

  File "C:UsersMEAppDataLocalContinuumAnaconda2libsite-packagesscipystats_distn_infrastructure.py", line 856, in rvs
    raise ValueError("Domain error in arguments.")

ValueError: Domain error in arguments.

it seems if I set _c to be some number larger than 0.0, it works fine, but not for _c less than 0.

I am a bit confused about this. Any help would be appreciated.

How to Solve ValueError: math domain error in Python

You come across a special ValueError when working with Python’s math module. It is ValueError: math domain error. Python raises this error when you try to do something that is not mathematically possible or mathematically defined.

Python math domain error

To solve a domain error in Python, passing a valid input for which the function can calculate a numerical output. The math domain error occurs when you’ve passed an undefined input into the math function. For example, you are doing a log of a number less than or equal to zero. That’s mathematically undefined, so Python’s log function raises an exception.

Output

And we get the ValueError: math domain error.

Whenever you are getting the math domain error for either reason, you are trying to use a negative number inside the log function or a zero value.

Logarithms decide the base after being given a number and the power it was raised to.

The log(0) means that something raised to the power of 2 is 0. An exponent can never result in 0*, which means that log(0) has no answer, thus throwing the math domain error.

The domain of a function is the set of all possible input values. If Python throws the ValueError: math domain error, you’ve passed an undefined input into the math function.

In our case, don’t calculate the log of a negative number or zero, and it will resolve the error.

There are various scenarios in which this error can occur. Let’s see some of them one by one.

Python sqrt: Math domain error

To calculate the square root of a number in Python, use math.sqrt() method.

The math domain error appears if you pass a negative argument into the math.sqrt() function.

It’s mathematically impossible to calculate the square root of a negative number without using complex numbers.

Output

The square root of a negative number is not mathematically possible. That’s why it throws an error.

Источник

«Domain error in arguments» exception after lime update #352

I updated lime package from lime==0.1.1.34 to lime==0.1.1.35 version. After that LimeTabularExplainer raised ValueError: Domain error in arguments.

X_train object is a sparse matrix and feature_names is a list of strings.

The text was updated successfully, but these errors were encountered:

Fixed in 601b711, bumped version to 0.1.1.36
Please reopen if this doesn’t solve the issue.

same error I am facing the same issue above with @marcotcr ‘s mentioned version as well.

/anaconda3/lib/python3.7/site-packages/lime/lime_tabular.py in __init__(self, training_data, mode, training_labels, feature_names, categorical_features, categorical_names, kernel_width, kernel, verbose, class_names, feature_selection, discretize_continuous, discretizer, sample_around_instance, random_state, training_data_stats) 214 self.discretizer = QuartileDiscretizer( 215 training_data, self.categorical_features, —> 216 self.feature_names, labels=training_labels) 217 elif discretizer == ‘decile’: 218 self.discretizer = DecileDiscretizer(

/anaconda3/lib/python3.7/site-packages/lime/discretize.py in __init__(self, data, categorical_features, feature_names, labels, random_state) 190 BaseDiscretizer.__init__(self, data, categorical_features, 191 feature_names, labels=labels, —> 192 random_state=random_state) 193 194 def bins(self, data, labels):

/anaconda3/lib/python3.7/site-packages/lime/discretize.py in __init__(self, data, categorical_features, feature_names, labels, random_state, data_stats) 97 self.maxs[feature] = qts.tolist() + [boundaries[1]] 98 [self.get_undiscretize_value(feature, i) —> 99 for i in range(n_bins + 1)] 100 101 @abstractmethod

/anaconda3/lib/python3.7/site-packages/lime/discretize.py in
(.0) 97 self.maxs[feature] = qts.tolist() + [boundaries[1]] 98 [self.get_undiscretize_value(feature, i) —> 99 for i in range(n_bins + 1)] 100 101 @abstractmethod

/anaconda3/lib/python3.7/site-packages/lime/discretize.py in get_undiscretize_value(self, feature, val) 141 minz, maxz, loc=means[val], scale=stds[val], 142 random_state=self.random_state, —> 143 size=self.precompute_size)) 144 idx = self.undiscretize_idxs[feature][val] 145 ret = self.undiscretize_precomputed[feature][val][idx]

/anaconda3/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py in rvs(self, *args, **kwds) 936 cond = logical_and(self._argcheck(*args), (scale >= 0)) 937 if not np.all(cond): —> 938 raise ValueError(«Domain error in arguments.») 939 940 if np.all(scale == 0): ValueError: Domain error in arguments.»>

Here is my code.

version of lime ;
lime==0.1.1.36

I’m experiencing the same error ValueError: Domain error in arguments.
`—————————————————————————
ValueError Traceback (most recent call last)
in ()
1 lime_explainer = lime.lime_tabular.LimeTabularExplainer(x_a_trainp.values, feature_names=x_a_trainp.columns.tolist(),
—-> 2 verbose=True, mode=’classification’
3 )

/anaconda3/envs/python3/lib/python3.6/site-packages/lime/lime_tabular.py in init(self, training_data, mode, training_labels, feature_names, categorical_features, categorical_names, kernel_width, kernel, verbose, class_names, feature_selection, discretize_continuous, discretizer, sample_around_instance, random_state, training_data_stats)
214 self.discretizer = QuartileDiscretizer(
215 training_data, self.categorical_features,
—> 216 self.feature_names, labels=training_labels)
217 elif discretizer == ‘decile’:
218 self.discretizer = DecileDiscretizer(

/anaconda3/envs/python3/lib/python3.6/site-packages/lime/discretize.py in init(self, data, categorical_features, feature_names, labels, random_state)
190 BaseDiscretizer.init(self, data, categorical_features,
191 feature_names, labels=labels,
—> 192 random_state=random_state)
193
194 def bins(self, data, labels):

/anaconda3/envs/python3/lib/python3.6/site-packages/lime/discretize.py in init(self, data, categorical_features, feature_names, labels, random_state, data_stats)
97 self.maxs[feature] = qts.tolist() + [boundaries[1]]
98 [self.get_undiscretize_value(feature, i)
—> 99 for i in range(n_bins + 1)]
100
101 @AbstractMethod

/anaconda3/envs/python3/lib/python3.6/site-packages/lime/discretize.py in (.0)
97 self.maxs[feature] = qts.tolist() + [boundaries[1]]
98 [self.get_undiscretize_value(feature, i)
—> 99 for i in range(n_bins + 1)]
100
101 @AbstractMethod

/anaconda3/envs/python3/lib/python3.6/site-packages/lime/discretize.py in get_undiscretize_value(self, feature, val)
141 minz, maxz, loc=means[val], scale=stds[val],
142 random_state=self.random_state,
—> 143 size=self.precompute_size))
144 idx = self.undiscretize_idxs[feature][val]
145 ret = self.undiscretize_precomputed[feature][val][idx]

/anaconda3/envs/python3/lib/python3.6/site-packages/scipy/stats/_distn_infrastructure.py in rvs(self, *args, **kwds)
938 cond = logical_and(self._argcheck(*args), (scale >= 0))
939 if not np.all(cond):
—> 940 raise ValueError(«Domain error in arguments.»)
941
942 if np.all(scale == 0):

ValueError: Domain error in arguments.
`
Version:
lime ==0.1.1.36

Источник

Python Math Domain Error (How to Fix This Stupid Bug)

You may encounter a special ValueError when working with Python’s math module.

Python raises this error when you try to do something that is not mathematically possible or mathematically defined.

To understand this error, have a look at the definition of the domain:

“The domain of a function is the complete set of possible values of the independent variable. Roughly speaking, the domain is the set of all possible (input) x-values which result in a valid (output) y-value.” (source)

The domain of a function is the set of all possible input values. If Python throws the ValueError: math domain error , you’ve passed an undefined input into the math function. Fix the error by passing a valid input for which the function is able to calculate a numerical output.

Here are a few examples:

Python Math Domain Error Sqrt

The math domain error appears if you pass a negative argument into the math.sqrt() function. It’s mathematically impossible to calculate the square root of a negative number without using complex numbers. Python doesn’t get that and throws a ValueError: math domain error .

Here’s a minimal example:

You can fix the math domain error by using the cmath package that allows the creation of complex numbers:

Python Math Domain Error Log

The math domain error for the math.log() function appears if you pass a zero value into it—the logarithm is not defined for value 0.

Here’s the code on an input value outside the domain of the logarithm function:

The output is the math domain error:

You can fix this error by passing a valid input value into the math.log() function:

This error can sometimes appear if you pass a very small number into it—Python’s float type cannot express all numbers. To pass a value “close to 0”, use the Decimal module with higher precision, or pass a very small input argument such as:

Python Math Domain Error Acos

The math domain error for the math.acos() function appears if you pass a value into it for which it is not defined—arccos is only defined for values between -1 and 1.

Here’s the wrong code:

The output is the math domain error:

You can fix this error by passing a valid input value between [-1,1] into the math.acos() function:

Python Math Domain Error Asin

The math domain error for the math.asin() function appears if you pass a value into it for which it is not defined—arcsin is only defined for values between -1 and 1.

Here’s the erroneous code:

The output is the math domain error:

You can fix this error by passing a valid input value between [-1,1] into the math.asin() function:

Python Math Domain Error Pow

The math domain error for the math.pow(a,b) function to calculate a**b appears if you pass a negative base value into it and try to calculate a negative power of it. The reason it is not defined is that any negative number to the power of 0.5 would be the square number—and thus, a complex number. But complex numbers are not defined by default in Python!

The output is the math domain error:

If you need a complex number, a b must be rewritten into e b ln a . For example:

You see, it’s a complex number!

NumPy Math Domain Error — np.log(x)

This is the graph of log(x) . Don’t worry if you don’t understand the code, what’s more important is the following point. You can see that log(x) tends to negative infinity as x tends to 0. Thus, it is mathematically meaningless to calculate the log of a negative number. If you try to do so, Python raises a math domain error.

Where to Go From Here?

Enough theory. Let’s get some practice!

Coders get paid six figures and more because they can solve problems more effectively using machine intelligence and automation.

To become more successful in coding, solve more real problems for real people. That’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?

You build high-value coding skills by working on practical coding projects!

Do you want to stop learning with toy projects and focus on practical code projects that earn you money and solve real problems for people?

🚀 If your answer is YES!, consider becoming a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.

If you just want to learn about the freelancing opportunity, feel free to watch my free webinar “How to Build Your High-Income Skill Python” and learn how I grew my coding business online and how you can, too—from the comfort of your own home.

While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.

To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.

His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.

Источник

ValueError: Math Domain Error in Python

In this tutorial, we aim to explore different methods to resolve the ValueError: math domain error in Python.

This article tackles the following topics.

1. Understanding the root cause of the problem.
2. Replicating the issue.
3. Resolving the issue.

Understand the Root Cause of the ValueError: math domain error in Python

A ValueError: math domain error is generally raised in Python whenever there is an inherent flaw in the usage of Mathematics (Basic or Advanced) in the coding aspect.

Dividing any integer or floating point value by zero, taking the logarithm of any non-positive number or multiplying any integer by infinity are some examples that generally lead to the ValueError: math domain error .

Replicate the ValueError: math domain error in Python

Now that we understand the reason behind the issue let us try replicating it. This can be done in Python with the help of the following block of code.

Here, we are trying to calculate a simple expression that subtracts the result of log(-3) and 7 . The code above gives us the error below.

This error is because we are trying to calculate the log of a negative number, which is impossible.

Similarly, we get the ValueError: math domain error if we use the sqrt function with a negative number in Python.

This error can be replicated with the help of the following block of code.

The output of the above code can be illustrated as follows.

The primary reason is that a negative integer’s square root is a complex number.

Similarly, while using the pow function in Python, we can get the ValueError: math domain error with the following code block.

The output of the above code block can be illustrated as:

The primary reason is that a negative number cannot be raised to a fractional power in Python.

Solve the ValueError: math domain error in Python

We can use the absolute operator abs in Python to resolve the above issues. The following block of code can help us eliminate the error mentioned.

The output of the above code can be illustrated as follows.

Similarly, if we ever want to take the square root of a negative number, we can also use abs . This can be understood better with the help of the following block of code.

The output of the above code can be illustrated as follows.

The same logic can be used to calculate a negative number’s power.

The output of the above code can be illustrated as follows.

Thus, with the help of this tutorial, we have managed to get rid of the ValueError: math domain error in Python.

Preet writes his thoughts about programming in a simplified manner to help others learn better. With thorough research, his articles offer descriptive and easy to understand solutions.

Источник

I am trying to tune the hyperparameters of an SVM using skopt. Following the example on the docs I implemented the below. However, I am getting a ValueError: Domain error in arguments. error. Is it something about the way I have set it up?

import numpy as np
from sklearn.model_selection import cross_val_score
from sklearn import datasets, svm
from skopt import gp_minimize

iris = datasets.load_iris()
X, y = iris.data, iris.target
X = X[y != 0, :2]
y = y[y != 0]

clf = svm.SVC(kernel='rbf', gamma=10, C=100)


def objective(params):
    kernel_gamma, penalty_C = params

    clf.set_params(gamma=kernel_gamma,
                   C=penalty_C)

    return -np.mean(cross_val_score(clf, X, y, cv=5, n_jobs=-1))


space = [(0.01, 0.001),  # gamma
         (10, 20, 200)]  # C

res_gp = gp_minimize(objective, space, n_calls=100, random_state=0)

print("Best score=%.4f" % res_gp.fun)

Full stack trace below:

Traceback (most recent call last):
  File "C:Program FilesAnaconda3libsite-packagesIPythoncoreinteractiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-11-ce3d26def919>", line 30, in <module>
    res_gp = gp_minimize(objective, space, n_calls=100, random_state=0)
  File "C:Program FilesAnaconda3libsite-packagesskoptoptimizergp.py", line 247, in gp_minimize
    callback=callback, n_jobs=n_jobs)
  File "C:Program FilesAnaconda3libsite-packagesskoptoptimizerbase.py", line 234, in base_minimize
    next_x = optimizer.ask()
  File "C:Program FilesAnaconda3libsite-packagesskoptoptimizeroptimizer.py", line 181, in ask
    return self.space.rvs(random_state=self.rng)[0]
  File "C:Program FilesAnaconda3libsite-packagesskoptspacespace.py", line 456, in rvs
    columns.append(dim.rvs(n_samples=n_samples, random_state=rng))
  File "C:Program FilesAnaconda3libsite-packagesskoptspacespace.py", line 102, in rvs
    samples = self._rvs.rvs(size=n_samples, random_state=rng)
  File "C:Program FilesAnaconda3libsite-packagesscipystats_distn_infrastructure.py", line 466, in rvs
    return self.dist.rvs(*self.args, **kwds)
  File "C:Program FilesAnaconda3libsite-packagesscipystats_distn_infrastructure.py", line 936, in rvs
    raise ValueError("Domain error in arguments.")
ValueError: Domain error in arguments.

You may encounter a special ValueError when working with Python’s math module.

ValueError: math domain error

Python raises this error when you try to do something that is not mathematically possible or mathematically defined.

To understand this error, have a look at the definition of the domain:

“The domain of a function is the complete set of possible values of the independent variable. Roughly speaking, the domain is the set of all possible (input) x-values which result in a valid (output) y-value.” (source)

The domain of a function is the set of all possible input values. If Python throws the ValueError: math domain error, you’ve passed an undefined input into the math function. Fix the error by passing a valid input for which the function is able to calculate a numerical output.

Here are a few examples:

The math domain error appears if you pass a negative argument into the math.sqrt() function. It’s mathematically impossible to calculate the square root of a negative number without using complex numbers. Python doesn’t get that and throws a ValueError: math domain error.

Here’s a minimal example:

from math import sqrt
print(sqrt(-1))
'''
Traceback (most recent call last):
  File "C:UsersxcentDesktopFinxterBlogcode.py", line 2, in <module>
    print(sqrt(-1))
ValueError: math domain error
'''

You can fix the math domain error by using the cmath package that allows the creation of complex numbers:

from cmath import sqrt
print(sqrt(-1))
# 1j

Python Math Domain Error Log

The math domain error for the math.log() function appears if you pass a zero value into it—the logarithm is not defined for value 0.

Here’s the code on an input value outside the domain of the logarithm function:

from math import log
print(log(0))

The output is the math domain error:

Traceback (most recent call last):
  File "C:UsersxcentDesktopFinxterBlogcode.py", line 3, in <module>
    print(log(0))
ValueError: math domain error

You can fix this error by passing a valid input value into the math.log() function:

from math import log
print(log(0.000001))
# -13.815510557964274

This error can sometimes appear if you pass a very small number into it—Python’s float type cannot express all numbers. To pass a value “close to 0”, use the Decimal module with higher precision, or pass a very small input argument such as:

math.log(sys.float_info.min)

Python Math Domain Error Acos

The math domain error for the math.acos() function appears if you pass a value into it for which it is not defined—arccos is only defined for values between -1 and 1.

Here’s the wrong code:

import math
print(math.acos(2))

The output is the math domain error:

Traceback (most recent call last):
  File "C:UsersxcentDesktopFinxterBlogcode.py", line 3, in <module>
    print(math.acos(2))
ValueError: math domain error

You can fix this error by passing a valid input value between [-1,1] into the math.acos() function:

import math
print(math.acos(0.5))
# 1.0471975511965979

Python Math Domain Error Asin

The math domain error for the math.asin() function appears if you pass a value into it for which it is not defined—arcsin is only defined for values between -1 and 1.

Here’s the erroneous code:

import math
print(math.asin(2))

The output is the math domain error:

Traceback (most recent call last):
  File "C:UsersxcentDesktopFinxterBlogcode.py", line 3, in <module>
    print(math.asin(2))
ValueError: math domain error

You can fix this error by passing a valid input value between [-1,1] into the math.asin() function:

import math
print(math.asin(0.5))
# 0.5235987755982989

Python Math Domain Error Pow

The math domain error for the math.pow(a,b) function to calculate a**b appears if you pass a negative base value into it and try to calculate a negative power of it. The reason it is not defined is that any negative number to the power of 0.5 would be the square number—and thus, a complex number. But complex numbers are not defined by default in Python!

import math
print(math.pow(-2, 0.5))

The output is the math domain error:

Traceback (most recent call last):
  File "C:UsersxcentDesktopFinxterBlogcode.py", line 3, in <module>
    print(math.pow(-2, 0.5))
ValueError: math domain error

If you need a complex number, a^b must be rewritten into e^{b ln a}. For example:

import cmath
print(cmath.exp(0.5 * cmath.log(-2)))
# (8.659560562354932e-17+1.414213562373095j)

You see, it’s a complex number!

NumPy Math Domain Error — np.log(x)

import numpy as np
import matplotlib.pyplot as plt

# Plotting y = log(x)
fig, ax = plt.subplots()
ax.set(xlim=(-5, 20), ylim=(-4, 4), title='log(x)', ylabel='y', xlabel='x')
x = np.linspace(-10, 20, num=1000)
y = np.log(x)

plt.plot(x, y)

This is the graph of log(x). Don’t worry if you don’t understand the code, what’s more important is the following point. You can see that log(x) tends to negative infinity as x tends to 0. Thus, it is mathematically meaningless to calculate the log of a negative number. If you try to do so, Python raises a math domain error.

>>> math.log(-10)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: math domain error

Where to Go From Here?

Enough theory. Let’s get some practice!

Coders get paid six figures and more because they can solve problems more effectively using machine intelligence and automation.

To become more successful in coding, solve more real problems for real people. That’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?

You build high-value coding skills by working on practical coding projects!

Do you want to stop learning with toy projects and focus on practical code projects that earn you money and solve real problems for people?

🚀 If your answer is YES!, consider becoming a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.

If you just want to learn about the freelancing opportunity, feel free to watch my free webinar “How to Build Your High-Income Skill Python” and learn how I grew my coding business online and how you can, too—from the comfort of your own home.

Join the free webinar now!

The domain of a mathematical function is the set of all possible input values. If you pass an undefined input to a function from the math library, you will raise the ValueError: math domain error.

To solve this error, ensure that you use a valid input for the mathematical function you wish to use. You can put a conditional statement in your code to check if the number is valid for the function before performing the calculation.

You cannot use functions from the math library with complex numbers, such as calculating a negative number’s square root. To do such calculations, use the cmath library.

This tutorial will go through the error in detail and solve it with the help of some code examples.

ValueError: math domain error

What is a ValueError?

In Python, a value is the information stored within a particular object. You will encounter a ValueError in Python when you use a built-in operation or function that receives an argument with the right type but an inappropriate value.

The ValueError: math domain error occurs when you attempt to use a mathematical function with an invalid value. You will commonly see this error using the math.sqrt() and math.log() methods.

Example #1: Square Root of a Negative Number

Let’s look at an example of a program that calculates the square root of a number.

import math

number = int(input("Enter a number: "))

sqrt_number = math.sqrt(number)

print(f' The square root of {number} is {sqrt_number}')

We import the math library to use the square root function in the above code. We collect the number from the user using the input() function. Next, we find the square root of the number and print the result to the console using an f-string. Let’s run the code to see the result:

Enter a number: -4

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
      3 number = int(input("Enter a number: "))
      4 
----> 5 sqrt_number = math.sqrt(number)
      6 
      7 print(f' The square root of {number} is {sqrt_number}')

ValueError: math domain error

We raise the ValueError because a negative number does not have a real square root.

Solution #1: Use an if statement

To solve this error, we can check the value of the number before attempting to calculate the square root by using an if statement. Let’s look at the revised code:

import math

number = int(input("Enter a number: "))

if number > 0:

    sqrt_number = math.sqrt(number)

    print(f' The square root of {number} is {sqrt_number}')

else:

    print('The number you input is less than zero. You cannot find the real square root of a negative number.')

In the above code, we check if the user’s number is greater than zero. If it is, we calculate the number’s square root and print it to the console. Otherwise, we print a statement telling the user the number is invalid for the square root function. Let’s run the code to see the result:

Enter a number: -4
The number you input is less than zero. You cannot find the real square root of a negative number.

Go to the article: Python Square Root Function for further reading on calculating the square root of a number in Python.

Solution #2: Use cmath

We can also solve the square root math domain error using the cmath library. This library provides access to mathematical functions for complex numbers. The square root of a negative number is a complex number with a real and an imaginary component. We will not raise a math domain error using the square root function from cmath on a negative number. Let’s look at the revised code:

import cmath

number = int(input("Enter a number: "))

sqrt_number = cmath.sqrt(number)

print(f' The square root of {number} is {sqrt_number}')

Let’s run the code to get the result:

Enter a number: -4

The square root of -4 is 2j

Example #2: Logarithm of Zero

Let’s look at an example of a program that calculates the natural logarithm of a number. The log() method returns the natural logarithm of a number or to a specified base. The syntax of the math.log() method is:

math.log(x, base)

Parameters:

• x: Required. The value to calculate the number logarithm for.
• base: Optional. The logarithmic base to use. The default is e.

import math

number = int(input("Enter a number: "))

print(f'The log of {number} is {math.log(number)}.')

We import the math library to use the natural logarithm function in the above code. We collect the number from the user using the input() function. Next, we find the natural logarithm of the number and print the result to the console using an f-string. Let’s run the code to see the result:

Enter a number: 0

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
      3 number = int(input("Enter a number: "))
      4 
----> 5 print(f'The log of {number} is {math.log(number)}.')

ValueError: math domain error

We raise the ValueError because you cannot calculate the natural logarithm of 0 or a negative number. The log(0) means that the exponent e raised to the power of a number is 0. An exponent can never result in 0, which means log(0) has no answer, resulting in the math domain error.

Solution

We can put an if statement in the code to check if the number we want to use is positive to solve this error. Let’s look at the revised code:

import math

number = int(input("Enter a number: "))

if number > 0:

    print(f'The log of {number} is {math.log(number)}.')

else:

    print(f'The number you provided is less than or equal to zero. You can only get the logarithm of positive real numbers')

Now we will only calculate the natural logarithm of the number if it is greater than zero. Let’s run the code to get the result:

Enter a number: 0

The number you provided is less than or equal to zero. You can only get the logarithm of positive real numbers

Summary

Congratulations on reading to the end of this tutorial! ValueError: math domain error occurs when you attempt to perform a mathematical function with an invalid number. Every mathematical function has a valid domain of input values you can choose. For example, the logarithmic function accepts all positive, real numbers. To solve this error, ensure you use input from the domain of a function. You can look up the function in the math library documentation to find what values are valid and which values will raise a ValueError.

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The ValueError: math domain error occurs in Python when you try to do something that is not mathematically possible or mathematically defined.

import math

var = -1

result = math.sqrt(var)

print(result)

Output

ValueError: math domain error

You can see that it throws an error because of the math.sqrt() function is not defined for negative numbers, and trying to find the square root of a negative number results in a ValueError: math domain error.

How to fix ValueError: math domain error in Python

To fix the ValueError: math domain error in Python, pass a valid input for which the function can calculate a numerical output.

import math

var = -1

if var >= 0:
  result = math.sqrt(var)
else:
  print("Error: Cannot find square root of negative number")

Output

Error: Cannot find square root of negative number

You can see that we used an if-else statement to check if the number is negative and if it is then we print the statement; otherwise, it will find the square root of that number.

Another example

If you are doing a log of a number less than or equal to zero. Unfortunately, that’s mathematically undefined, so Python’s log() function raises an exception.

from math import log

print(log(-1))

Output

Traceback (most recent call last):
  File "/Users/krunal/Desktop/code/pyt/database/app.py", line 3, in <module>
    print(log(-1))
ValueError: math domain error

And we get the ValueError: math domain error.

Whenever you are getting the math domain error for either reason, you are trying to use a negative number inside the log function or a zero value.

Logarithms decide the base after being given a number and the power it was raised to.

The log(0) means that something raised to the power of 2 is 0.

An exponent can never result in 0*, which means that log(0) has no answer, thus throwing the math domain error.

The domain of a function is the set of all possible input values.

If Python throws the ValueError: math domain error, you’ve passed an undefined input into the math function.

In our case, don’t calculate the log of a negative number or zero; it will resolve the error.

There are various scenarios in which this error can occur. Let’s see some of them one by one.

Python sqrt: Math domain error

To calculate the square root of a number in Python, use math.sqrt() method.

The math domain error appears if you pass a negative argument into the math.sqrt() function.

It’s mathematically impossible to calculate the square root of a negative number without using complex numbers.

from math import sqrt

print(sqrt(-1))

Output

Traceback (most recent call last):
  File "/Users/krunal/Desktop/code/pyt/database/app.py", line 3, in <module>
    print(sqrt(-1))
ValueError: math domain error

The square root of a negative number is not mathematically possible. That’s why it throws an error.

Python pow: Math domain error

The math domain error for the math.pow(a,b) function to calculate a**b arises if you pass the negative base value into it and try to calculate a negative power.

from math import pow

print(pow(-1, 0.5))

Output

Traceback (most recent call last):
  File "/Users/krunal/Desktop/code/pyt/database/app.py", line 3, in <module>
    print(pow(-1, 0.5))
ValueError: math domain error

And we get the ValueError.

That is it for the article.

1. Understand the Root Cause of the ValueError: math domain error in Python
2. Replicate the ValueError: math domain error in Python
3. Solve the ValueError: math domain error in Python

In this tutorial, we aim to explore different methods to resolve the ValueError: math domain error in Python.

This article tackles the following topics.

1. Understanding the root cause of the problem.
2. Replicating the issue.
3. Resolving the issue.

Understand the Root Cause of the ValueError: math domain error in Python

A ValueError: math domain error is generally raised in Python whenever there is an inherent flaw in the usage of Mathematics (Basic or Advanced) in the coding aspect.

Dividing any integer or floating point value by zero, taking the logarithm of any non-positive number or multiplying any integer by infinity are some examples that generally lead to the ValueError: math domain error.

Replicate the ValueError: math domain error in Python

Now that we understand the reason behind the issue let us try replicating it. This can be done in Python with the help of the following block of code.

from numpy import zeros, array
from math import sin, log

def f(x):
    f= log(-3) - 7.0
    return "Executed successfully"

x = array([1.0, 1.0, 1.0])
a = f(x)
print(a)

Here, we are trying to calculate a simple expression that subtracts the result of log(-3) and 7. The code above gives us the error below.

line 5, in f
    f = log(-3) - 7.0
ValueError: math domain error

This error is because we are trying to calculate the log of a negative number, which is impossible.

Similarly, we get the ValueError: math domain error if we use the sqrt function with a negative number in Python.

This error can be replicated with the help of the following block of code.

from math import sqrt
print(sqrt(-4))

The output of the above code can be illustrated as follows.

line 2, in print(srqt(-4))
ValueError: math domain error

The primary reason is that a negative integer’s square root is a complex number.

Similarly, while using the pow function in Python, we can get the ValueError: math domain error with the following code block.

import math
print(math.pow(-2, 0.5))

The output of the above code block can be illustrated as:

line 2, in print(math.pow(-2, 0.5))
ValueError: math domain error

The primary reason is that a negative number cannot be raised to a fractional power in Python.

Solve the ValueError: math domain error in Python

We can use the absolute operator abs in Python to resolve the above issues. The following block of code can help us eliminate the error mentioned.

from numpy import zeros, array
from math import sin, log

def f(x):
    f= log(abs(-3)) - 7.0
    return "Executed successfully"

x = array([1.0, 1.0, 1.0])
a = f(x)
print(a)

The output of the above code can be illustrated as follows.

Similarly, if we ever want to take the square root of a negative number, we can also use abs. This can be understood better with the help of the following block of code.

from math import sqrt
print(sqrt(abs(-4)))

The output of the above code can be illustrated as follows.

The same logic can be used to calculate a negative number’s power.

import math
print(math.pow(abs(-2), 0.5))

The output of the above code can be illustrated as follows.

Thus, with the help of this tutorial, we have managed to get rid of the ValueError: math domain error in Python.