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doc update
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vincentsarago committed May 6, 2020
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6 changes: 4 additions & 2 deletions CHANGES.txt
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NEXT (TBD)
2.0a5 (2020-05-06)
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- make `rio_tiler.io.landsat8.tile` return Uint16 data and not float32
- make `rio_tiler.io.landsat8.tile` return Uint16 data and not float32 (#173)
- `rio_tiler.profiles.img_profiles` item access return `copy` of the items (#177)
- better colormap docs (#176, author @kylebarron)

2.0a4 (2020-04-08)
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -146,7 +146,7 @@ landsat8.metadata('LC08_L1TP_016037_20170813_20170814_01_RT', pmin=5, pmax=95)
The primary purpose for calculating minimum and maximum values of an image is to rescale pixel values from their original range (e.g. 0 to 65,535) to the range used by computer screens (i.e. 0 and 255) through a linear transformation.
This will make images look good on display.

#### Working SpatioTemporal Asset Catalog (STAC)
#### Working with SpatioTemporal Asset Catalog (STAC)

In rio-tiler v2, we added a `rio_tiler.io.stac` submodule to allow tile/metadata fetching of assets withing a STAC item.

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2 changes: 1 addition & 1 deletion docs/v2_migration.md
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Expand Up @@ -68,7 +68,7 @@ In *rio_tiler==1* most of the magic was happening in [`rio_tiler.utils._tile_rea

To ease the transition we added a `rio_tiler.reader.tile` function.

Note: The new `rio_tiler.reader.part` function enables to perform non-squared data cropping of different.
Note: The new `rio_tiler.reader.part` function enables to perform non-squared data cropping by passing output width and height (instead of just tilesize).

```python
# v1
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2 changes: 1 addition & 1 deletion setup.py
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setup(
name="rio-tiler",
version="2.0a4",
version="2.0a5",
python_requires=">=3",
description=u"""Get mercator tile from CloudOptimized GeoTIFF and other cloud hosted raster such as CBERS-4, Sentinel-2, Sentinel-1 and Landsat-8 AWS PDS""",
long_description=readme,
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