626172a16b
Source files in libcamera start by a comment block header, which
includes the file name and a one-line description of the file contents.
While the latter is useful to get a quick overview of the file contents
at a glance, the former is mostly a source of inconvenience. The name in
the comments can easily get out of sync with the file name when files
are renamed, and copy & paste during development have often lead to
incorrect names being used to start with.
Readers of the source code are expected to know which file they're
looking it. Drop the file name from the header comment block.
The change was generated with the following script:
----------------------------------------
dirs="include/libcamera src test utils"
declare -rA patterns=(
['c']=' \* '
['cpp']=' \* '
['h']=' \* '
['py']='# '
['sh']='# '
)
for ext in ${!patterns[@]} ; do
files=$(for dir in $dirs ; do find $dir -name "*.${ext}" ; done)
pattern=${patterns[${ext}]}
for file in $files ; do
name=$(basename ${file})
sed -i "s/^\(${pattern}\)${name} - /\1/" "$file"
done
done
----------------------------------------
This misses several files that are out of sync with the comment block
header. Those will be addressed separately and manually.
Signed-off-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com>
Reviewed-by: Daniel Scally <dan.scally@ideasonboard.com>
75 lines
2.6 KiB
Python
75 lines
2.6 KiB
Python
# SPDX-License-Identifier: GPL-2.0-or-later
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#
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# Copyright (C) 2022, Paul Elder <paul.elder@ideasonboard.com>
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#
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# Gradients that can be used to distribute or map numbers
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import libtuning as lt
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import math
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from numbers import Number
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# @brief Gradient for how to allocate pixels to sectors
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# @description There are no parameters for the gradients as the domain is the
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# number of pixels and the range is the number of sectors, and
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# there is only one curve that has a startpoint and endpoint at
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# (0, 0) and at (#pixels, #sectors). The exception is for curves
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# that *do* have multiple solutions for only two points, such as
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# gaussian, and curves of higher polynomial orders if we had them.
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#
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# \todo There will probably be a helper in the Gradient class, as I have a
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# feeling that all the other curves (besides Linear and Gaussian) can be
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# implemented in the same way.
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class Gradient(object):
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def __init__(self):
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pass
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# @brief Distribute pixels into sectors (only in one dimension)
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# @param domain Number of pixels
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# @param sectors Number of sectors
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# @return A list of number of pixels in each sector
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def distribute(self, domain: list, sectors: list) -> list:
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raise NotImplementedError
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# @brief Map a number on a curve
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# @param domain Domain of the curve
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# @param rang Range of the curve
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# @param x Input on the domain of the curve
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# @return y from the range of the curve
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def map(self, domain: tuple, rang: tuple, x: Number) -> Number:
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raise NotImplementedError
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class Linear(Gradient):
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# @param remainder Mode of handling remainder
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def __init__(self, remainder: lt.Remainder = lt.Remainder.Float):
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self.remainder = remainder
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def distribute(self, domain: list, sectors: list) -> list:
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size = domain / sectors
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rem = domain % sectors
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if rem == 0:
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return [int(size)] * sectors
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size = math.ceil(size)
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rem = domain % size
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output_sectors = [int(size)] * (sectors - 1)
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if self.remainder == lt.Remainder.Float:
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size = domain / sectors
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output_sectors = [size] * sectors
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elif self.remainder == lt.Remainder.DistributeFront:
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output_sectors.append(int(rem))
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elif self.remainder == lt.Remainder.DistributeBack:
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output_sectors.insert(0, int(rem))
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else:
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raise ValueError
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return output_sectors
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def map(self, domain: tuple, rang: tuple, x: Number) -> Number:
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m = (rang[1] - rang[0]) / (domain[1] - domain[0])
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b = rang[0] - m * domain[0]
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return m * x + b
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