Math¶
Functions:
arctan2 (y, x) 
Elementwise arc tangent of y/x choosing the quadrant correctly. 
cos (obj) 
Elementwise cosine of an Image or ImageCollection . 
arccos (obj) 
Elementwise inverse cosine of an Image or ImageCollection . 
log (obj) 
Elementwise natural log of an Image or ImageCollection . 
log2 (obj) 
Elementwise base 2 log of an Image or ImageCollection . 
log10 (obj) 
Elementwise base 10 log of an Image or ImageCollection . 
log1p (obj) 
Elementwise log of 1 + an Image or ImageCollection . 
normalized_difference (x, y) 
Normalized difference helper function for computing an index such as NDVI. 
sin (obj) 
Elementwise sine of an Image or ImageCollection . 
arcsin (obj) 
Elementwise inverse sine of an Image or ImageCollection . 
sqrt (obj) 
Elementwise square root of an Image or ImageCollection . 
tan (obj) 
Elementwise tangent of an Image or ImageCollection . 
arctan (obj) 
Elementwise inverse tangent of an Image or ImageCollection . 
exp (obj) 
Elementwise exponential of an Image or ImageCollection . 
square (obj) 
Elementwise square of an Image or ImageCollection . 

arctan2
(y, x)[source]¶ Elementwise arc tangent of
y/x
choosing the quadrant correctly.The quadrant (i.e., branch) is chosen so that
arctan2(y, x)
is the signed angle in radians between the ray ending at the origin and passing through the point (1,0), and the ray ending at the origin and passing through the point (x, y). (Note the role reversal: the “ycoordinate” is the first function parameter, the “xcoordinate” is the second.) By IEEE convention, this function is defined for x = +/0 and for either or both of y and x = +/inf (see Notes for specific values).Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(1) >>> wf.arctan2(my_int, my_int).compute() 0.7853981633974483
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(1) >>> img = wf.Image.from_id("landsat:LC08:PRE:TOAR:meta_LC80270312016188_v1").pick_bands("red") >>> wf.arctan2(img, my_int).compute(geoctx) # geoctx is an arbitrary geocontext for 'img' ImageResult: * ndarray: MaskedArray<shape=(1, 512, 512), dtype=float64> * properties: 'acquired', 'area', 'bits_per_pixel', 'bright_fraction', ... * bandinfo: 'red' * geocontext: 'geometry', 'key', 'resolution', 'tilesize', ...
Parameters: Returns: x – Angle(s) in radians, in the range
[pi, pi]
, of the type that results from broadcastingy
tox
, (exceptInt
is promoted toFloat
)Return type: Float, Image, ImageCollection
Notes
arctan2 is identical to the
atan2
function of the underlying C library. The following special values are defined in the C standard: [1]y
x
arctan2(y,x)
+/ 0 +0 +/ 0 +/ 0 0 +/ pi > 0 +/inf +0 / +pi < 0 +/inf 0 / pi +/inf +inf +/ (pi/4) +/inf inf +/ (3*pi/4) Note that +0 and 0 are distinct floating point numbers, as are +inf and inf.
References
[1] ISO/IEC standard 9899:1999, “Programming language C.”

cos
(obj)[source]¶ Elementwise cosine of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(0) >>> wf.cos(my_int).compute() 1.0

arccos
(obj)[source]¶ Elementwise inverse cosine of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(0) >>> wf.arccos(my_int).compute() 1.0

log
(obj)[source]¶ Elementwise natural log of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(1) >>> wf.log(my_int).compute() 0.0

log2
(obj)[source]¶ Elementwise base 2 log of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(1) >>> wf.log2(my_int).compute() 0.0

log10
(obj)[source]¶ Elementwise base 10 log of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(1) >>> wf.log10(my_int).compute() 0.0

log1p
(obj)[source]¶ Elementwise log of 1 + an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(1) >>> wf.log1p(my_int).compute() 0.6931471805599453

normalized_difference
(x, y)[source]¶ Normalized difference helper function for computing an index such as NDVI.
Example
>>> import descarteslabs.workflows as wf >>> col = wf.ImageCollection.from_id("landsat:LC08:01:RT:TOAR", ... start_datetime="20170101", ... end_datetime="20170530") >>> nir, red = col.unpack_bands("nir red") >>> # geoctx is an arbitrary geocontext for 'col' >>> wf.normalized_difference(nir, red).compute(geoctx) ImageCollectionResult of length 2: * ndarray: MaskedArray<shape=(2, 1, 512, 512), dtype=float64> * properties: 2 items * bandinfo: 'nir_sub_red_div_nir_add_red' * geocontext: 'geometry', 'key', 'resolution', 'tilesize', ...

sin
(obj)[source]¶ Elementwise sine of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(0) >>> wf.sin(my_int).compute() 0.0

arcsin
(obj)[source]¶ Elementwise inverse sine of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(0) >>> wf.arcsin(my_int).compute() 0.0

sqrt
(obj)[source]¶ Elementwise square root of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(4) >>> wf.sqrt(my_int).compute() 2.0

tan
(obj)[source]¶ Elementwise tangent of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(0) >>> wf.tan(my_int).compute() 0.0

arctan
(obj)[source]¶ Elementwise inverse tangent of an
Image
orImageCollection
.Can also be used with
Int
andFloat
types.Examples
>>> import descarteslabs.workflows as wf >>> my_int = wf.Int(0) >>> wf.arctan(my_int).compute() 0.0