-
Notifications
You must be signed in to change notification settings - Fork 0
/
oss_tools.py
260 lines (226 loc) · 9.14 KB
/
oss_tools.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
import numpy, gdal
from osgeo import gdal_array, ogr, osr
from gdalconst import *
import shapefile
import pygeoif
from pyproj import Proj, transform
import ogr2ogr
## RasterToNumPyArray: String NumPy(Datatype) --> NumPy Array
##
## Description:
##
## Takes in a raster and returns it as a 2D (if single band) or 3D (if >1 band) raster.
## Datatype of array is determined by input data, or can be passed in.
##
## Inputs:
##
## raster_path: Path to a valid Raster-type file.
##
## dtype: numpy datatype.
## ex. numpy.uint8
##
## Outputs:
## Returns a numpy array. Output is a 2D array if singular band input, and 3D if multiple bands.
def RasterToNumPyArray(raster_path, dtype=None):
if dtype == None:
return gdal.Open(raster_path).ReadAsArray()
else:
return gdal.Open(raster_path).ReadAsArray().astype(dtype)
## getNoDataValue: String --> Number
##
## Description:
##
## Returns the NoData value of an input raster
##
## Inputs:
##
## in_raster_path: Path to a valid raster file
##
## Outputs:
##
## Returns a numeric value representing the NoData pixel value of the input raster.
def getNoDataValue(in_raster_path):
t = gdal.Open(in_raster_path).GetRasterBand(1)
t = t.GetNoDataValue()
return t
## getProjection: String --> GDAL Projection Datatype
##
## Description:
##
## Gets the projection info from an existing raster file as a GDAL datatype.
##
## Inputs:
##
## in_raster_path: Path to a valid raster file
##
## Outputs:
##
## Returns the projection of the input raster
def getProjection(in_raster_path):
return gdal.Open(in_raster_path).GetProjection()
## getProjection: String --> GDAL Geotransformation Datatype
##
## Description:
##
## Gets the transformation info from an existing raster file as a GDAL datatype.
##
## Inputs:
##
## in_raster_path: Path to a valid raster file
##
## Outputs:
##
## Returns the transformation of the input raster
def getGeoTransform(in_raster_path):
return gdal.Open(in_raster_path).GetGeoTransform()
## NumPyArrayToRaster: Array[][], GDAL Projection, GDAL Geotransform, String, Datatype
##
## Description:
##
## Converts a Numpy array into a GeoTIFF using GDAL libraries.
## Designed to be a replacement to ESRI's equivalent function NumPyArrayToRaster.
##
## Inputs:
##
## nparr: A valid 2D or 3D Numpy array containing numerical data.
##
## proj: A valid GDAL projection datatype. Can be obtained by using getProjection()
##
## geot: A valid GDAL geotransform datatype. Can be obtained by using getGeoTransform()
##
## nodata_value: Sets the NoData value of the output raster. Should be a datatype that matches the
## input nparr (ex. if nparr is integers, use an integer value)
##
## out_raster_path: A path to where you would like to save the raster dataset.
##
## dtype: Optional, allows user to specify the datatype in the output TIFF. Is a GDAL datatype.
## If not specified, will use the closest match to what is contained in the Numpy array.
def NumPyArrayToRaster(nparr, proj, geot, nodata_value, out_raster_path, dtype=None):
gdal.AllRegister()
np_dt = nparr.dtype
if dtype == None:
dtype = gdal_array.NumericTypeCodeToGDALTypeCode(np_dt)
print( "saving")
# Check if working with multiband raster
if len(nparr.shape) == 3:
n_bands = nparr.shape[0]
for x in range(0, n_bands):
driver = gdal.GetDriverByName('GTIFF')
outDs = driver.Create(out_raster_path, nparr.shape[2], nparr.shape[1], n_bands, dtype,
['COMPRESS=LZW', 'TILED=YES', 'BLOCKXSIZE=128', 'BLOCKYSIZE=128'])
outDs.GetRasterBand(x + 1).WriteArray(nparr[x])
outDs.GetRasterBand(x + 1).SetNoDataValue(nodata_value)
outDs.GetRasterBand(x + 1).FlushCache()
outDs.SetProjection(proj)
outDs.SetGeoTransform(geot)
outDs = None
else:
driver = gdal.GetDriverByName('GTIFF')
outDs = driver.Create(out_raster_path, nparr.shape[1], nparr.shape[0], 1, dtype,
['COMPRESS=LZW', 'TILED=YES', 'BLOCKXSIZE=128', 'BLOCKYSIZE=128'])
outDs.GetRasterBand(1).WriteArray(nparr)
outDs.GetRasterBand(1).SetNoDataValue(nodata_value)
outDs.GetRasterBand(1).FlushCache()
outDs.SetProjection(proj)
outDs.SetGeoTransform(geot)
outDs = None
## convertToNetlogo: String String --> None
##
## Purpose
## Converts an input GeoTIFF raster into a plaintext file that can be read in by the NetLogo
## modelling language and use it as a surface for the turtles to interact with.
##
## Inputs
## tif_file A path to a valid GeoTIFF file. Spatial information does not necessarily matter.
## output_nlogo_textfile A path to where you'd like the output netlogo surface file to go
## percentage_increase How often you'd like progress indicators to print to the screen. Default value: 20. Optional.
def convertToNetLogo(tif_file, output_nlogo_textfile, percentage_increase=20):
# Specifies which band the input data is in for the raster.
data_band = 1
# Read the TIF file as a GDAL object
tif_connection = gdal.Open(tif_file)
# Convert the TIF connection to a Numpy 2D array (First band only)
tif_array = numpy.array(tif_connection.GetRasterBand(data_band).ReadAsArray())
#tif_array = numpy.full((200, 10000), 0)
# Setup connection to output dataset
output_connection = open(output_nlogo_textfile, 'w')
# An indicator dict to print percentage
progress = {}
for x in range(0, 101, percentage_increase):
progress[x] = True
# Begin looping through numpy array
for y in range(tif_array.shape[0] - 1, -1, -1):
for x in range(0, tif_array.shape[1]):
# Get percentage (Current PercenTage)
cpt = round((((x + 1) * ( y + 1)) / float(tif_array.shape[0] * tif_array.shape[1])) * 100, 0 )
cpt = int(cpt)
# Print the progress if it hasn't been printed before - good simple UI
if cpt in progress.keys():
if progress[cpt]:
print ("{}% done".format(cpt))
progress[cpt] = False
# Write current indice to output file
output_connection.write("{}\t{}\t{}\n".format(y, tif_array.shape[1] - x, tif_array[y][x]))
# Close the IO stream
output_connection.close()
## reclass: String List String --> None
## Purpose
## Reclassifies a raster based on a raster reclassification table
##
## Inputs
## in_raster Path to a singleband input raster
## reclass_table A list of three element lists.
## [start_range, end_range, reclass_value]
## Mathematically, this looks like
## start_range <= x < end_range
##
## There is a final element where it is a single value where you reclass all other
## values not in the specified ranges.
##
## out_raster Path to an output raster
def reclass(in_raster, reclass_table, out_raster):
nparr = RasterToNumPyArray(in_raster)
min_start_range = reclass_table[0][0]
max_end_range = reclass_table[0][1]
for i in reclass_table[:-1]:
start_range = i[0]
end_range = i[1]
if start_range < min_start_range:
min_start_range = start_range
if end_range > max_end_range:
max_end_range = end_range
rc_val = i[2]
nparr[numpy.where((start_range <= nparr) & (nparr < end_range))] = rc_val
final_rc_val = reclass_table[-1:][0]
#nparr[numpy.where(nparr < min_start_range)] = final_rc_val
#nparr[numpy.where(nparr >= max_end_range)] = final_rc_val
NumPyArrayToRaster(nparr, getProjection(in_raster), getGeoTransform(in_raster), out_raster)
## reprojectShp: String, String -> String
## Purpose: Takes in the path to an ESRI shapefile and reprojects it to a specified EPSG.
## By default, will reproject the shapefile to EPSG:4326 prior to converting to WKT, but can be disabled by passing in False as
## the second parameter.
##
## Inputs:
## in_shp Valid path to an existing ESRI shapefile on disk
## epsg EPSG code (ie. "EPSG:4326")
##
## out_shp Path to where you want to save reprojected shapefile to.
##
def reprojectShp(in_shp, epsg, out_shp):
ogr2ogr.main(["", "-f", "ESRI Shapefile", "-t_srs", epsg, out_shp, in_shp])
## shpToWKT: String, boolean -> String
## Purpose: Takes in the path to an ESRI shapefile and converts it to a WKT string.
## By default, will reproject the shapefile to EPSG:4326 prior to converting to WKT, but can be disabled by passing in False as
## the second parameter.
##
## Inputs:
## in_shp Valid path to an existing ESRI shapefile on disk
## reproj (Optional, default is True) Disables reprojecting to EPSG:4326 and keeps the source CRS when set to False
##
def shpToWKT(in_shp, reproj=True):
r = shapefile.Reader(in_shp)
g = []
for s in r.shapes():
g.append(pygeoif.geometry.as_shape(s))
m = pygeoif.MultiPoint(g)
return m.wkt