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I'm trying to iterate an array of values generated with numpy.linspace:
slX = numpy.linspace(obsvX, flightX, numSPts) slY = np.linspace(obsvY, flightY, numSPts) for index,point in slX: yPoint = slY[index] arcpy.AddMessage(yPoint) This code worked fine on my office computer, but I sat down this morning to work from home on a different machine and this error came up:
File "C:\temp\gssm_arcpy.1.0.3.py", line 147, in AnalyzeSightLine for index,point in slX: TypeError: 'numpy.float64' object is not iterable slX is just an array of floats, and the script has no problem printing the contents -- just, apparently iterating through them. Any suggestions for what is causing it to break, and possible fixes?
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To check for NaN values in a Numpy array you can use the np. isnan() method. This outputs a boolean mask of the size that of the original array. The output array has true for the indices which are NaNs in the original array and false for the rest.
float is an alias for python float type. np. float32 and np. float64 are numpy specific 32 and 64-bit float types.
Conclusion # The Python "TypeError: 'float' object is not iterable" occurs when we try to iterate over a float or pass a float to a built-in function like, list() or tuple() . To solve the error, use the range() built-in function to iterate over a range, e.g. for i in range(int(3.0)): .
Python's floating-point numbers are usually 64-bit floating-point numbers, nearly equivalent to np. float64 . In some unusual situations it may be useful to use floating-point numbers with more precision.
numpy.linspace() gives you a one-dimensional NumPy array. For example:
>>> my_array = numpy.linspace(1, 10, 10) >>> my_array array([ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.]) Therefore:
for index,point in my_array cannot work. You would need some kind of two-dimensional array with two elements in the second dimension:
>>> two_d = numpy.array([[1, 2], [4, 5]]) >>> two_d array([[1, 2], [4, 5]]) Now you can do this:
>>> for x, y in two_d: print(x, y) 1 2 4 5 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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