270 lines
8.5 KiB
Python
270 lines
8.5 KiB
Python
from emis_funky_funktions import *
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from world import Point, Terrain, World
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from PIL import Image
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from itertools import chain
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from typing import List, NamedTuple, Tuple
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def meters_to_millimeters(meters: float) -> int:
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"""
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Convert meters (floating point) to millimeters (int)
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>>> meters_to_millimeters(1.9333473e+02)
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193334
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>>> meters_to_millimeters(1.0)
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1000
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"""
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return int(1000 * meters)
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def read_single_elevation(dat: str) -> Result[int, str]:
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"""
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Read in a single elevation
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Expects a single, stringified floating point value, in meters, without a unit, e.g.
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"2.057e+02". If there is a parsing error, returns an error containing the input
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string. Otherwise, returns the elevation in millimeters.
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>>> read_single_elevation("1.9333473e+02")
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Ok(193334)
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>>> read_single_elevation("1.0")
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Ok(1000)
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>>> read_single_elevation("10.0m")
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Err('10.0m')
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"""
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try:
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# fuck floating points
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return Ok(meters_to_millimeters(float(dat)))
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except ValueError:
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return Err(dat)
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def read_elevation_line(line: str) -> Result[Sequence[int], Tuple[int, str]]:
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"""
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Reads a line of elevations
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Each elevation should be in the format specified by `read_single_elevation`. Every
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element of the line is parsed and combined into an iterator, which is returned. If
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any parsing errors are encountered, the first error is returned. It takes the form of
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a tuple containing the column of the error (in terms of whitespace-deliniated words,
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not characters) and the string which could not be parsed.
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Recall from the definition of `read_single_elevation()` that the return value is an
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integer number of millimeters.
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As per the problem specification, the last five columns of the line are not read or
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parsed. Parsing errors in these columns therefor cannot be encountered, and any data
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in these columns will not be returned.
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>>> map_res(list, read_elevation_line("1.9e2 18e1 181 179.1 ignored 170.1 1.8e2 18i+2 20e1"))
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Ok([190000, 180000, 181000, 179100])
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>>> map_res(list, read_elevation_line("1.9e2 18e 181 179.1 ignored 170.1 1.8e2 18i+2 20e1"))
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Err((2, '18e'))
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"""
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return sequence([
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map_err(
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lambda err_text: (col_no + 1, err_text),
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read_single_elevation(elem)
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)
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# As per spec, we drop the last five entries of the file.
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for (col_no, elem) in enumerate(line.split()[:-5])
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])
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class UnparsableElevation(NamedTuple):
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"An elevation entry failed to be parsed as a floating point"
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line_no: int
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"The line on which the error occurred"
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col_no: int
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"The column (1-indexed number of whitespace deliniated words) on which the error occurred"
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invalid_entry: str
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"The text which failed to parse as a floating point value"
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def read_elevations(lines: Iterable[str]) -> Result[Iterator[int], UnparsableElevation]:
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"""
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Read an entire elevation file into a list
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This parses each line in of the file using `read_elevation_line()`. Errors
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encountered are reported using an `UnparsableElevation`. The resulting list is
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single-dimensional, but can be indexed arbitrarily, meaning for an input file with a
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constant number of columns per line, this data can be accessed as if it were a 2d
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square array.
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However, keep in mind that, as with `read_elevation_line()`, the last five columns of
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each line are dropped/ignored, and are therefor not present in the returned data.
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>>> map_res(list, read_elevations('''
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... 1 2 3 4 5 6 7 8 9e 10
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... 11 2.0 3e1 4 5 6 7 bwa 9 10
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... 11 2.0 3e0 4 5 ign err 8 9 10
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... '''.strip().split('\\n')))
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Ok([1000, 2000, 3000, 4000, 5000, 11000, 2000, 30000, 4000, 5000, 11000, 2000, 3000, 4000, 5000])
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>>> map_res(list, read_elevations('''
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... 1 2 3 4 5 6 7 8 9e 10
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... 11 ERR 3e1 4 5 6 7 bwa 9 10
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... 11 2.0 3e0 4 5 ign err 8 9 10
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... '''.strip().split('\\n')))
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Err(UnparsableElevation(line_no=2, col_no=2, invalid_entry='ERR'))
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"""
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return map_res(
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chain.from_iterable,
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sequence([
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map_err(
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lambda err: UnparsableElevation(line_no + 1, *err),
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read_elevation_line(line)
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)
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for (line_no, line) in enumerate(lines)
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])
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)
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gb_to_terrain_type = {
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(148, 18): Terrain.OPEN_LAND,
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(192, 0): Terrain.ROUGH_MEADOW,
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(255, 255): Terrain.EASY_FOREST,
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(208, 60): Terrain.MEDIUM_FOREST,
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(136, 40): Terrain.WALK_FOREST,
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(73, 24): Terrain.BRUSH,
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(0, 255): Terrain.WET,
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(51, 3): Terrain.ROAD,
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(0, 0): Terrain.FOOTPATH,
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(0, 101): Terrain.OOB
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}
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"""
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Maps the green and blue components of a color to a terrain type.
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"""
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class UnrecognizedColor(NamedTuple):
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"A color in a provided map was not in the list of recognized colors"
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x: int
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"The x coordinate of the unidentifided color"
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y: int
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"The y coordinate of the unidentifided color"
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def load_gb_pixels_as_map(pixels: Iterable[Tuple[int, int]]) -> Result[Sequence[Terrain], UnrecognizedColor]:
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"""
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Interpret the green and blue bands of an image as pixels on a map
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This assumes that the map follows the specification laid out at
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https://cs.rit.edu/~jro/courses/intelSys/labs/orienteering/
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Namely, the map should be exactly 395 pixels wide, and should follow the color
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conventions laid out in the Terrain Type table.
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This function is only interested in the green and blue channels of the image. Rather
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than pass a full pixel, it is only necessary to pass the green and blue color values.
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If an error is encountered, the returned `Err` type will contain the x and y
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coordinates of the pixel which could not be identified.
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"""
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return sequence([
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try_(lambda _: UnrecognizedColor(pix_no % 395, pix_no // 395), gb_to_terrain_type.get, gb)
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for (pix_no, gb) in enumerate(pixels)
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])
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def load_image(path: str) -> Result[Sequence[Terrain], UnrecognizedColor]:
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"Run `load_gb_pixels_as_map` on an image read from a path"
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with Image.open(path) as im:
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return load_gb_pixels_as_map(zip(im.getdata(1), im.getdata(2)))
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def load_elevations(path: str) -> Result[Iterator[int], UnparsableElevation]:
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"Run `read_elevations` on a text file read from a path"
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with open(path) as file:
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return read_elevations(file)
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def load_world_from_paths(map_path: str, elevation_path: str) -> Result[World, UnparsableElevation | UnrecognizedColor]:
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"""
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Read world information (terrain and elevation) from file paths.
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See `read_elevations` and `load_gb_pixels_as_map` for more information on the format
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that this data should be in. Note that for this method, you do not need to worry
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about the channels present in the terrain map, just that it align with the colors and
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size of the specified format.
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"""
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return bind_res(
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lambda terrain_data:
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map_res(
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lambda elevation_data: World((*zip(terrain_data, elevation_data),)),
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load_elevations(elevation_path)
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),
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load_image(map_path)
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)
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def parse_point(s: str) -> Result[Point, str]:
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"""
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Parses a point from a string
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The point is expected to be a string containing two integer values seperated by
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whitespace.
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Any errors in parsing the string will result in an `Err` being returned, containing
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the original string.
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>>> parse_point('230 327')
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Ok((230, 327))
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>>> parse_point('230327')
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Err('230327')
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>>> parse_point('23O 327')
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Err('23O 327')
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"""
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match s.strip().split():
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case [p1, p2]:
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try:
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return Ok(Point(int(p1), int(p2)))
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except ValueError:
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return Err(s)
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case _:
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return Err(s)
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def parse_points(lines: Iterable[str]) -> Result[Sequence[Point], str]:
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"""
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Parse a series of points
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Each point should be in the format specified by `parse_point()`, and each should be on
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it's own "line" (aka, item in an iterable). Blank lines are ignored and dropped. If
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any one of the lines in the input string fail to parse, the text of the first failed
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line will be returned in an `Err`.
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>>> parse_points('''
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... 230 327
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... 276 279
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...
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... 303 240
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... '''.split('\\n'))
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Ok([(230, 327), (276, 279), (303, 240)])
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>>> parse_points('''
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... 230 327
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... 276 2BAD
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... 3BAD 240
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... '''.split('\\n'))
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Err('276 2BAD')
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"""
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return sequence([
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parse_point(line)
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for line in lines
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if len(line) and not line.isspace()
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])
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def load_points(path: str) -> Result[Sequence[Point], str]:
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"""
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Load a file full of points by passing the lines to `parse_points()`
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See `parse_points()` for format specifications
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"""
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with open(path) as f:
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return parse_points(f)
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if __name__ == '__main__':
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import doctest
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doctest.testmod() |