mpmath

Install the mpmath library using pip or conda:
`pip install mpmath`
or
`conda install mpmath`

Pin the mpmath version to a compatible older release, such as 1.3.0, or update the dependent library if a version compatible with newer mpmath releases is available.
`pip install mpmath==1.3.0`

Explicitly convert the input to a standard Python float or a string before passing it to `mpmath.mpf` or an `mpmath` function. For NumPy types, cast to `float` first.
```python
from mpmath import mpf
import numpy as np

# Original problematic code (example with numpy.int64)
# x_np_int = np.int64(1)
# m_val = mpf(x_np_int) # This would raise the TypeError

# Corrected code
x_np_int = np.int64(1)
m_val = mpf(float(x_np_int)) # Convert to Python float first
print(m_val)

# Example with a numpy array (common when plotting)
# import mpmath
# arr = np.array([1.0, 2.0, 3.0])
# mpmath.cos(arr) # This would raise the TypeError

# Corrected code for array element-wise operations
import mpmath
arr = np.array([1.0, 2.0, 3.0])
m_arr = [mpmath.cos(mpmath.mpf(x)) for x in arr]
print(m_arr)
```

Convert the `mpmath.mpf` object (or the float) to a standard Python integer using `int()` before passing it to functions or operations that expect an integer.
```python
from mpmath import mp

# Original problematic code
# mp.dps = 15
# num_iterations_float = mp.sqrt(25.0)
# for i in range(num_iterations_float): # This would raise the TypeError
#     print(i)

# Corrected code
mp.dps = 15
num_iterations_mpf = mp.sqrt(25.0) # This is an mpf object equivalent to 5.0
num_iterations_int = int(num_iterations_mpf) # Convert mpf to Python int
for i in range(num_iterations_int):
    print(i)

# Example with numpy.linspace num argument
import numpy as np
# interval_len = mp.pi / 2
# x_values = np.linspace(0, float(mp.pi), num=interval_len) # This would raise TypeError if interval_len is mpf

# Corrected code
interval_len_mpf = mp.pi / 2 # This is an mpf object
interval_len_int = int(interval_len_mpf.real) # Convert mpf to Python int (using .real for complex mpf)
x_values = np.linspace(0, float(mp.pi), num=interval_len_int)
print(x_values)
```