numpy is the top package name, and doing import numpy doesn’t import submodule numpy.f2py. When you do import numpy it creats a link that points to numpy, but numpy is not further linked to f2py. The link is established when you do import numpy.f2py In your above code: Here is the difference between import numpy.f2py and import numpy.f2py as myf2py: import numpy.f2py put numpy into local symbol table(pointing to numpy), and … Read more
np.nan is not comparable to np.nan… directly. While Could also do examplesFilters nothing because nothing is equal to np.nan Filters out the null Use odd comparison behavior to get what we want anyway. If np.nan != np.nan is True then Just dropna
Use tolist(): Note that this converts the values from whatever numpy type they may have (e.g. np.int32 or np.float32) to the “nearest compatible Python type” (in a list). If you want to preserve the numpy data types, you could call list() on your array instead, and you’ll end up with a list of numpy scalars. … Read more
The exponential function is e^x where e is a mathematical constant called Euler’s number, approximately 2.718281. This value has a close mathematical relationship with pi and the slope of the curve e^x is equal to its value at every point. np.exp() calculates e^x for each value of x in your input array.
The variable mean_data is a nested list, in Python accessing a nested list cannot be done by multi-dimensional slicing, i.e.: mean_data[1,2], instead one would write mean_data[1][2]. This is becausemean_data[2] is a list. Further indexing is done recursively – since mean_data[2] is a list, mean_data[2][0] is the first index of that list. Additionally, mean_data[:][0] does not … Read more
The error “only length-1 arrays can be converted to Python scalars” is raised when the function expects a single value but you pass an array instead. If you look at the call signature of np.int, you’ll see that it accepts a single value, not an array. In general, if you want to apply a function that … Read more
np.max is just an alias for np.amax. This function only works on a single input array and finds the value of maximum element in that entire array (returning a scalar). Alternatively, it takes an axis argument and will find the maximum value along an axis of the input array (returning a new array). The default behaviour of np.maximum is to take two arrays and compute … Read more
EDIT: I put together this answer off and on over a couple of hours, so I missed your latest edits indicating that you only needed curvature. Hopefully, this answer will be helpful regardless. Other than doing some curve-fitting, our method of approximating derivatives is via finite differences. Thankfully, numpy has a gradient method that does these difference calculations for us, … Read more
r is a numpy (rec)array. So r[“dt”] >= startdate is also a (boolean) array. For numpy arrays the & operation returns the elementwise-and of the two boolean arrays. The NumPy developers felt there was no one commonly understood way to evaluate an array in boolean context: it could mean True if any element is True, … Read more
From the code you showed us, the only thing we can tell is that you are trying to create an array from a list that isn’t shaped like a multi-dimensional array. For example or will yield this error message, because the shape of the input list isn’t a (generalised) “box” that can be turned into … Read more