Speed up nested if loops under a for loop

On a 2d plane, there is a large circle centered at (0,0) with a radius of 𝑅𝑜. It encloses ∼100 or so smaller circles distributed randomly across the parent circle otherwise with known radii and positions with respect to the origin. (It is possible that some smaller sub-circles are partially or entirely inside some larger sub-circles.)

The entire plane is gridded uniformly into pixels with sides being horizontal and vertical (along coordinate axes). The size of the pixels is fixed and known a priori but otherwise much smaller than the size of parent circle; there are on the order of ~1000 special pixels all over the parent circle. We are given the 2D Cartesian coordinates for (the centers of) all these special grids. Those sub-circles which enclose at least one of these special grids are named *special" sub-circles for later use.

Now, imagine all this 3d space is filled with ~100,000,000 particles. My code tries to add up these particles within each one of the special sub-circles.

I managed to debug my code but it seems that when I am dealing with such a great number of particles, it is very slow as written below. I would like to see if I can use any trick to speed it up at least by an order of magnitude.

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for x, y in zip(vals1, vals2):  # vals1, vals2 are the 2d position array of the *special* grids each with a 1d array of size ~1000
    enclosing_circles, sub_circle_catalog, some_parameter_catalog, totals = {}, [], [], {}


    for id, mass in zip(ids_data, masss_data): # These two arrays are equal in size equal to an array of size ~100,000,000
        rule1 = some_condition
        rule2 = some_other_condition

        if (rule1 and rule2):
            calculated_property = some_function

            if condition_3:
                calculated_some_other_property = some_other_function

                if condition_4:
                    some_quantity = something
                    enclosing_circles[id] = float('{:.4f}'.format(log10(mass)))
                    some_parameter[id] = float('{:.3e}'.format(some_quantity))


    # choose all sub-circles' IDs enclosing the special pixel
    enclosing_circles_list = list(enclosing_circles.keys())
    some_parameter_list = list(some_parameter.keys())
    sub_circle_catalog += [(enclosing_circles[i], 1) for i in enclosing_circles_list]
    some_parameter_catalog += [(enclosing_circles[i], some_parameter[j]) for i, j in zip(enclosing_circles_list, some_parameter_list)]

# add up all special grids in each sub-circle when looping over all grids
for key, value in sub_circle_catalog:
    totals[key] = totals.get(key, 0) + value
totals_dict = collections.OrderedDict(sorted(totals.items()))
totals_list = list(totals.items())


with open(some_file_path, "a") as some_file:
    print('{}'.format(totals_list), file=some_file)
    some_file.close()
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