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Cleanup of imports in _features.pyx. Switched band IO to use _io.io_ubyte instead of duplicate in _featuers.pyx

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This commit is contained in:
Brendan Ward 2014-03-31 20:55:39 -07:00
parent 66643fd8ef
commit 0b4d353fe7
1 changed files with 6 additions and 24 deletions
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30
rasterio/_features.pyx
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@ -4,9 +4,7 @@ import logging
import json
import numpy as np
cimport numpy as np
from rasterio cimport _gdal, _ogr, _io
from rasterio.dtypes import dtype_rev
log = logging.getLogger('rasterio')
@ -16,9 +14,6 @@ class NullHandler(logging.Handler):
log.addHandler(NullHandler())
ctypedef np.uint8_t DTYPE_UBYTE_t
def _shapes(image, mask, connectivity, transform):
"""Return an iterator over Fiona-style features extracted from the
image.
@ -63,7 +58,7 @@ def _shapes(image, mask, connectivity, transform):
hband = _gdal.GDALGetRasterBand(hds, 1)
if hband == NULL:
raise ValueError("NULL band")
retval = io_ubyte(hband, 1, 0, 0, cols, rows, image)
retval = _io.io_ubyte(hband, 1, 0, 0, cols, rows, image)
elif isinstance(image, tuple):
rdr = image.ds
hband = rdr.band(image.bidx)
@ -85,7 +80,7 @@ def _shapes(image, mask, connectivity, transform):
a = np.ones(mask.shape, dtype=np.uint8)
a[mask == False] = 0
a[mask == True] = 1
retval = io_ubyte(hmaskband, 1, 0, 0, cols, rows, a)
retval = _io.io_ubyte(hmaskband, 1, 0, 0, cols, rows, a)
elif isinstance(mask, tuple):
if mask.shape != image.shape:
raise ValueError("Mask must have same shape as image")
@ -165,7 +160,7 @@ def _sieve(image, size, connectivity=4, output=None):
hbandin = _gdal.GDALGetRasterBand(hdsin, 1)
if hbandin == NULL:
raise ValueError("NULL input band")
retval = io_ubyte(hbandin, 1, 0, 0, cols, rows, image)
retval = _io.io_ubyte(hbandin, 1, 0, 0, cols, rows, image)
elif isinstance(image, tuple):
rdr = image.ds
hband = rdr.band(image.bidx)
@ -192,7 +187,7 @@ def _sieve(image, size, connectivity=4, output=None):
NULL, NULL, NULL)
out = output or np.zeros(image.shape, np.uint8)
retval = io_ubyte(hbandout, 0, 0, 0, cols, rows, out)
retval = _io.io_ubyte(hbandout, 0, 0, 0, cols, rows, out)
if hdsin != NULL:
_gdal.GDALClose(hdsin)
@ -264,7 +259,7 @@ def _rasterize(shapes, image, transform, all_touched):
pixel_values[i] = <double>value
# First, copy image data to the in-memory band.
retval = io_ubyte(out_band, 1, 0, 0, width, height, image)
retval = _io.io_ubyte(out_band, 1, 0, 0, width, height, image)
# Burn the shapes in.
retval = _gdal.GDALRasterizeGeometries(
@ -274,7 +269,7 @@ def _rasterize(shapes, image, transform, all_touched):
options, NULL, NULL)
# Write the in-memory band back to the image.
retval = io_ubyte(out_band, 0, 0, 0, width, height, image)
retval = _io.io_ubyte(out_band, 0, 0, 0, width, height, image)
finally:
for i in range(num_geometries):
@ -287,19 +282,6 @@ def _rasterize(shapes, image, transform, all_touched):
_gdal.CSLDestroy(options)
cdef int io_ubyte(
void *hband,
int mode,
int xoff,
int yoff,
int width,
int height,
np.ndarray[DTYPE_UBYTE_t, ndim=2, mode='c'] buffer):
return _gdal.GDALRasterIO(
hband, mode, xoff, yoff, width, height,
&buffer[0, 0], buffer.shape[1], buffer.shape[0], 1, 0, 0)
# Mapping of OGR integer geometry types to GeoJSON type names.
GEOMETRY_TYPES = {
0: 'Unknown',