rasterio.enums module

Enumerations.

class rasterio.enums.ColorInterp(value)

Bases: enum.IntEnum

Raster band color interpretation.

Cb = 15
Cr = 16
Y = 14
alpha = 6
black = 13
blue = 5
cyan = 10
gray = 1
green = 4
grey = 1
hue = 7
lightness = 9
magenta = 11
palette = 2
red = 3
saturation = 8
undefined = 0
yellow = 12
class rasterio.enums.Compression(value)

Bases: enum.Enum

Available compression algorithms.

ccittfax3 = 'CCITTFAX3'
ccittfax4 = 'CCITTFAX4'
ccittrle = 'CCITTRLE'
deflate = 'DEFLATE'
jpeg = 'JPEG'
jpeg2000 = 'JPEG2000'
lerc = 'LERC'
lerc_deflate = 'LERC_DEFLATE'
lerc_zstd = 'LERC_ZSTD'
lzma = 'LZMA'
lzw = 'LZW'
none = 'NONE'
packbits = 'PACKBITS'
webp = 'WEBP'
zstd = 'ZSTD'
class rasterio.enums.Interleaving(value)

Bases: enum.Enum

An enumeration.

band = 'BAND'
line = 'LINE'
pixel = 'PIXEL'
class rasterio.enums.MaskFlags(value)

Bases: enum.IntEnum

An enumeration.

all_valid = 1
alpha = 4
nodata = 8
per_dataset = 2
class rasterio.enums.MergeAlg(value)

Bases: enum.Enum

Available rasterization algorithms

add = 'ADD'
replace = 'REPLACE'
class rasterio.enums.PhotometricInterp(value)

Bases: enum.Enum

An enumeration.

black = 'MINISBLACK'
cielab = 'CIELAB'
cmyk = 'CMYK'
icclab = 'ICCLAB'
itulab = 'ITULAB'
rgb = 'RGB'
white = 'MINISWHITE'
ycbcr = 'YCbCr'
class rasterio.enums.Resampling(value)

Bases: enum.IntEnum

Available warp resampling algorithms.

nearest

Nearest neighbor resampling (default, fastest algorithm, worst interpolation quality).

bilinear

Bilinear resampling.

cubic

Cubic resampling.

cubic_spline

Cubic spline resampling.

lanczos

Lanczos windowed sinc resampling.

average

Average resampling, computes the weighted average of all non-NODATA contributing pixels.

mode

Mode resampling, selects the value which appears most often of all the sampled points.

gauss

Gaussian resampling, Note: not available to the functions in rio.warp.

max

Maximum resampling, selects the maximum value from all non-NODATA contributing pixels. (GDAL >= 2.0)

min

Minimum resampling, selects the minimum value from all non-NODATA contributing pixels. (GDAL >= 2.0)

med

Median resampling, selects the median value of all non-NODATA contributing pixels. (GDAL >= 2.0)

q1

Q1, first quartile resampling, selects the first quartile value of all non-NODATA contributing pixels. (GDAL >= 2.0)

q3

Q3, third quartile resampling, selects the third quartile value of all non-NODATA contributing pixels. (GDAL >= 2.0)

sum

Sum, compute the weighted sum of all non-NODATA contributing pixels. (GDAL >= 3.1)

rms

RMS, root mean square / quadratic mean of all non-NODATA contributing pixels. (GDAL >= 3.3)

Notes

The first 8, ‘nearest’, ‘bilinear’, ‘cubic’, ‘cubic_spline’, ‘lanczos’, ‘average’, ‘mode’, and ‘gauss’, are available for making dataset overviews.

‘max’, ‘min’, ‘med’, ‘q1’, ‘q3’ are only supported in GDAL >= 2.0.0.

‘nearest’, ‘bilinear’, ‘cubic’, ‘cubic_spline’, ‘lanczos’, ‘average’, ‘mode’ are always available (GDAL >= 1.10).

‘sum’ is only supported in GDAL >= 3.1.

‘rms’ is only supported in GDAL >= 3.3.

Note: ‘gauss’ is not available to the functions in rio.warp.

average = 5
bilinear = 1
cubic = 2
cubic_spline = 3
gauss = 7
lanczos = 4
max = 8
med = 10
min = 9
mode = 6
nearest = 0
q1 = 11
q3 = 12
rms = 14
sum = 13
class rasterio.enums.TransformDirection(value)

Bases: enum.IntEnum

Coordinate transform direction

Forward transform direction defined as image pixel (row, col) to geographic/projected (x, y) coordinates. Reverse transform direction defined as geographic/projected (x, y) to image pixel (row, col) coordinates.

Notes

The convention for transform direction for RPC based coordinate transform is typically the opposite of what is previously described. For consistency all coordinate transforms methods use the same convention.

forward = 1
reverse = 0
class rasterio.enums.TransformMethod(value)

Bases: enum.Enum

An enumeration.

affine = 'transform'
gcps = 'gcps'
rpcs = 'rpcs'
class rasterio.enums.WktVersion(value)

Bases: enum.Enum

New in version 1.3.0.

Supported CRS WKT string versions

WKT1 = 'WKT1'

Alias for WKT Version 1 GDAL Style

WKT1_ESRI = 'WKT1_ESRI'

WKT Version 1 ESRI Style

WKT1_GDAL = 'WKT1_GDAL'

WKT Version 1 GDAL Style

WKT2 = 'WKT2'

Alias for latest WKT Version 2

WKT2_2015 = 'WKT2_2015'

WKT Version 2 from 2015

WKT2_2019 = 'WKT2_2018'

WKT Version 2 from 2019