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Dumb replacement of functions. The functions work only to the extent
required, no more.
Creating chip databases (this includes fuzzing etc), packaging and
unpacking work.
Special moments:
* you will still need numpy to create the PNG, but the import only
happens when that function is called.
* compression packaging needs to be tested.
* perhaps somewhere in places that I rarely use there are numpy
calls.
Signed-off-by: YRabbit <[email protected]>- Loading branch information
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,113 @@ | ||
|
|
||
| def fliplr(bmp): | ||
| """ | ||
| Flips the entries in each row in the left/right direction. | ||
| Returns a new matrix. | ||
| """ | ||
| return [row[::-1] for row in bmp] | ||
|
|
||
| def flipud(bmp): | ||
| """ | ||
| Reverse the order of elements in each column (up/down). | ||
| Returns a refence. | ||
| """ | ||
| return bmp[::-1] | ||
|
|
||
| def vstack(bmp_0, bmp_1): | ||
| """ | ||
| Stack matrices in sequence vertically (row wise). | ||
| Returns a reference. | ||
| """ | ||
| return [*bmp_0, *bmp_1] | ||
|
|
||
| def hstack(bmp_0, bmp_1): | ||
| """ | ||
| Stack matrices in sequence horizontally (column wise). | ||
| Returns a new matrix. | ||
| """ | ||
| return [bmp[0] + bmp[1] for bmp in zip(bmp_0, bmp_1)] | ||
|
|
||
| def shape(bmp): | ||
| """ | ||
| Return the shape of a matrix. | ||
| """ | ||
| return [len(bmp), len(bmp[0])] | ||
|
|
||
| def ones(rows, cols): | ||
| """ | ||
| Returns a new matrix of given shape, filled with ones. | ||
| """ | ||
| return [[1] * cols for i in range(rows)] | ||
|
|
||
| def zeros(rows, cols): | ||
| """ | ||
| Returns a new matrix of given shape, filled with zeros. | ||
| """ | ||
| return [[0] * cols for i in range(rows)] | ||
|
|
||
| def packbits(bmp, axis = None): | ||
| """ | ||
| Packs the elements of a bitmap into bytes. | ||
| [1, 1, 0, 0, 0] -> [24] # [5'b11000] | ||
| Returns a list of bytes. | ||
| """ | ||
| byte_list = [] | ||
| if not axis: | ||
| for bmp_r in bmp: | ||
| for col in range(shape(bmp)[1] // 8): | ||
| bcol = col << 3 | ||
| byte_list.append((bmp_r[bcol] << 7) + (bmp_r[bcol + 1] << 6) + (bmp_r[bcol + 2] << 5) + | ||
| (bmp_r[bcol + 3] << 4) + (bmp_r[bcol + 4] << 3) + (bmp_r[bcol + 5] << 2) + | ||
| (bmp_r[bcol + 6] << 1) + bmp_r[bcol + 7]) | ||
| else: | ||
| for bmp_r in bmp: | ||
| byte_list.append([]) | ||
| byte_list_r = byte_list[-1] | ||
| for col in range(shape(bmp)[1] // 8): | ||
| bcol = col << 3 | ||
| byte_list_r.append((bmp_r[bcol] << 7) + (bmp_r[bcol + 1] << 6) + (bmp_r[bcol + 2] << 5) + | ||
| (bmp_r[bcol + 3] << 4) + (bmp_r[bcol + 4] << 3) + (bmp_r[bcol + 5] << 2) + | ||
| (bmp_r[bcol + 6] << 1) + bmp_r[bcol + 7]) | ||
| return byte_list | ||
|
|
||
| def xor(bmp_0, bmp_1): | ||
| """ | ||
| Bitwise XOR | ||
| Returns a new matrix | ||
| """ | ||
| return [[ vals[0] ^ vals[1]for vals in zip(row[0], row[1])] for row in zip(bmp_0, bmp_1)] | ||
|
|
||
| def histogram(lst, bins): | ||
| """ | ||
| Compute the histogram of a list. | ||
| Returns a list of counters. | ||
| """ | ||
| l_bins = len(bins) - 1 | ||
| r_lst = [0] * l_bins | ||
| for val in lst: | ||
| for i in range(l_bins): | ||
| if val in range(bins[i], bins[i + 1]) or (i == l_bins - 1 and val == bins[-1]): | ||
| r_lst[i] += 1 | ||
| return r_lst | ||
|
|
||
| def any(bmp): | ||
| """ | ||
| Test whether any matrix element evaluates to True. | ||
| """ | ||
| for row in bmp: | ||
| for val in row: | ||
| if val: | ||
| return True | ||
| return False | ||
|
|
||
| def nonzero(bmp): | ||
| """ | ||
| Return the indices of the elements that are non-zero. | ||
| """ | ||
| res = ([], []) | ||
| for ri, row in enumerate(bmp): | ||
| for ci, val in enumerate(row): | ||
| if val: | ||
| res[0].append(ri) | ||
| res[1].append(ci) | ||
| return res |
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