Implementation of ImageStack #5751
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philippjfr
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Nice to have:
|
import holoviews as hv
import xarray as xr
import numpy as np
import panel as pn
hv.extension("bokeh")
da = xr.DataArray(coords={"x": [1, 2, 3], "y": [6, 7, 8]}, dims=["x", "y"])
da_1 = da.copy()
da_1.name = "a"
da_1.values = [[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3]
da_2 = da.copy()
da_2.name = "b"
da_2.values = [[np.nan] * 3, [1, 1, np.nan], [np.nan] * 3]
da_3 = da.copy()
da_3.name = "c"
da_3.values = [[np.nan] * 3, [np.nan] * 3, [1, 1, 1]]
ds = xr.merge([da_1, da_2, da_3])
colors = ["red", "blue", "green"]
a = hv.ImageStack(ds).opts(
# colorbar=True,
cmap=colors,
num_colors=100,
title="original",
)
b = a.clone().opts(invert_axes=True, title="invert axes")
c = a.clone().opts(invert_yaxis=True, title="invert yaxis")
d = a.clone().opts(invert_xaxis=True, title="invert xaxis")
pn.GridBox(
pn.panel(a, linked_axes=False),
pn.panel(b, linked_axes=False),
pn.panel(c, linked_axes=False),
pn.panel(d, linked_axes=False),
ncols=2,
)
|
|
Does hover need support? |
Hover support is out of scope for this PR as it also needs work in Bokeh (or a new release). See bokeh/bokeh#13193, bokeh/bokeh#13200, and bokeh/bokeh#13354. |
|
|
mpl & plotly 
|
|
Weirdly using numpy array transposes the plot import holoviews as hv
import xarray as xr
import numpy as np
import panel as pn
hv.extension("bokeh")
x = np.arange(0, 3)
y = np.arange(5, 8)
a = np.array([[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3])
b = np.array([[np.nan] * 3, [1, 1, np.nan], [np.nan] * 3])
c = np.array([[np.nan] * 3, [np.nan] * 3, [1, 1, 1]])
ds = xr.Dataset(
{"a": (["x", "y"], a), "b": (["x", "y"], b), "c": (["x", "y"], c)},
coords={"x": x, "y": y},
)
colors = ["green", "red", "blue"]
(
hv.ImageStack(ds, kdims=["x", "y"], vdims=["a", "b", "c"]).opts(cmap=colors) +
hv.ImageStack((x, y, a, b, c), kdims=["x", "y"], vdims=["a", "b", "c"]).opts(cmap=colors)
)
|
|
Okay, I guess Image does the same, so maybe it's not an issue / separate issue import holoviews as hv
import xarray as xr
import numpy as np
import panel as pn
hv.extension("bokeh")
x = np.arange(0, 3)
y = np.arange(5, 8)
a = np.array([[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3])
b = np.array([[np.nan] * 3, [1, 1, np.nan], [np.nan] * 3])
c = np.array([[np.nan] * 3, [np.nan] * 3, [1, 1, 1]])
ds = xr.Dataset(
{"a": (["x", "y"], a), "b": (["x", "y"], b), "c": (["x", "y"], c)},
coords={"x": x, "y": y},
)
colors = ["green", "red", "blue"]
(
hv.ImageStack(ds, kdims=["x", "y"], vdims=["a", "b", "c"]).opts(cmap=colors) +
hv.ImageStack((x, y, a, b, c), kdims=["x", "y"], vdims=["a", "b", "c"]).opts(cmap=colors) +
hv.Image(ds["a"], kdims=["x", "y"], vdims=["a"]) +
hv.Image((x, y, a))
).cols(2) |
|
Yeah definitely an issue but a separate issue. |
ahuang11
reviewed
Aug 29, 2023
ahuang11
reviewed
Aug 29, 2023
|
I believe this is ready for initial review, but I don't understand the invert_x/yaxis tests because although the tests pass, the inverted data matches the original data and it renders as expected. |
ahuang11
changed the title
ahuang11
reviewed
Aug 29, 2023
philippjfr
reviewed
Aug 30, 2023
philippjfr
reviewed
Aug 30, 2023
|
Hmm this error seems a bit tricky: Traceback```python |
Hoxbro
commented
Sep 12, 2023
There was a problem hiding this comment.
I just had a quick look at the code and left some comments.
For the hover problem, try to filter the _hover_opts method. For now, I think we should remove these extra dimensions, as we can only get one layer of information for now. When Bokeh 3.3 is released, we can extract more information because of bokeh/bokeh#13193 (maybe we can already get this with a dev release). Further down the line, we should be able to get even better support with bokeh/bokeh#13200.
(Merged in main to be able only to be able to see the changes made in this PR)
|
I don't quite understand the behavior of the ImageStack hover Alone, it's understandable import holoviews as hv
import xarray as xr
import numpy as np
import panel as pn
from holoviews.operation.datashader import rasterize
hv.extension("bokeh")
da = xr.DataArray(coords={"x": [1, 2, 3], "y": [6, 7, 8]}, dims=["x", "y"])
da_1 = da.copy()
da_1.name = "a"
da_1.values = [[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3]
ds = xr.merge([da_1]).fillna(0)
colors = ["red", "blue", "green"]
a = hv.ImageStack(ds).opts(
cmap=colors,
title="original",
).opts(tools=["hover"])
a
However, stacked on another image, it doesn't match expectations. import holoviews as hv
import xarray as xr
import numpy as np
import panel as pn
from holoviews.operation.datashader import rasterize
hv.extension("bokeh")
da = xr.DataArray(coords={"x": [1, 2, 3], "y": [6, 7, 8]}, dims=["x", "y"])
da_1 = da.copy()
da_1.name = "a"
da_1.values = [[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3]
da_2 = da.copy()
da_2.name = "b"
da_2.values = [[np.nan, np.nan, 1], [np.nan] * 3, [np.nan] * 3]
ds = xr.merge([da_1, da_2]).fillna(0)
colors = ["red", "blue", "green"]
a = hv.ImageStack(ds).opts(
cmap=colors,
title="original",
).opts(tools=["hover"])
aWhy does this show 0? |
|
It is a limitation in Bokeh. Try to read the issues I mentioned in my last post. |
Okay. To build upon that though, I don't think we can even get one layer though: e.g. I expect 1 instead of 0 here: So do we just keep x and y? |
yes |
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Should I be worried about the core tests? Eh I just wrapped try/except. |
I would rather see something like this: holoviews/holoviews/tests/core/data/test_binneddatasets.py Lines 225 to 228 in d3f3458 |
Hoxbro
commented
Sep 13, 2023
philippjfr
reviewed
Sep 13, 2023
philippjfr
approved these changes
Sep 13, 2023
There was a problem hiding this comment.
Apart from the minor comments left by @Hoxbro and I this looks great.
Hoxbro
commented
Sep 14, 2023
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WIP
Reference for me:
#4806
bokeh/bokeh#12356