bin_shift_test.py(file created)
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| 1 | + | import numpy as np | |
| 2 | + | ||
| 3 | + | # +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | |
| 4 | + | # First, using the method from Brian and Bob. | |
| 5 | + | # +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | |
| 6 | + | ||
| 7 | + | # Generate a dummy array with a constant binning on a logarithmic scale. | |
| 8 | + | start_exponent = 0 | |
| 9 | + | stop_exponent = 3 | |
| 10 | + | num_bins = 10 | |
| 11 | + | x = np.logspace(start_exponent, stop_exponent, num=num_bins, base=10.0) | |
| 12 | + | ||
| 13 | + | # Check the binning of the array on a logarithmic scale. | |
| 14 | + | logged_x = np.log(x) | |
| 15 | + | print("1 - Bin width on a logarithmic scale before shift, ", np.diff(logged_x)) | |
| 16 | + | ||
| 17 | + | # Shift the array by half of the 'bin'. | |
| 18 | + | xdiff = np.append(np.diff(x), x[-1] - x[-2]) | |
| 19 | + | x -= xdiff / 2 | |
| 20 | + | ||
| 21 | + | # Check the binning of the array on a logarithmic scale, after the shift. | |
| 22 | + | print("1 - Bin width on a logarithmic scale after shift, ", np.diff(x)) | |
| 23 | + | ||
| 24 | + | # +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | |
| 25 | + | # Second, using the method from Yuanpeng | |
| 26 | + | # +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | |
| 27 | + | ||
| 28 | + | # Generate a dummy array with a constant binning on a logarithmic scale. | |
| 29 | + | start_exponent = 0 | |
| 30 | + | stop_exponent = 3 | |
| 31 | + | num_bins = 10 | |
| 32 | + | x = np.logspace(start_exponent, stop_exponent, num=num_bins, base=10.0) | |
| 33 | + | ||
| 34 | + | # Check the binning of the array on a logarithmic scale. | |
| 35 | + | logged_x = np.log(x) | |
| 36 | + | print("2 - Bin width on a logarithmic scale before shift, ", np.diff(logged_x)) | |
| 37 | + | ||
| 38 | + | # Shift the array by half of the 'bin'. | |
| 39 | + | x = np.log(x) | |
| 40 | + | bin_size = x[-1] - x[-2] | |
| 41 | + | x = np.exp(x - bin_size / 2.) | |
| 42 | + | ||
| 43 | + | # Check the binning of the array on a logarithmic scale, after the shift. | |
| 44 | + | logged_x = np.log(x) | |
| 45 | + | print("2 - Bin width on a logarithmic scale after shift, ", np.diff(logged_x)) | |
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