I would like to simply place a text object under an image object I created using jsxgraph.
Tried setting for the text object layer:2 and the image object layer:7.
Tried setting board.options.layer.text=2, then created the text object, then set board.options.layer.text=9 again.
The object does give the correct layer value when investigating, however it does not visually do this. This works well for non text objects. Would this a text related bug?
JSXGraph distinguishes two types of texts: display:'html' and display:'internal'. The former type of text element uses an HTML tag and is always strictly "above" any JSXGraph construction (and thus ignores the layer structur). The latter type of text element obeys the layer structure. The default is display:'html'.
Here is an example (https://jsfiddle.net/8xms49pu/2/):
var circ = board.create('circle', [[0, 0], 3],
{fillColor: 'yellow', fillOpacity: 0.8});
var txt1 = board.create('text', [1, 1, 'HTML'], {layer: 1});
var txt1 = board.create('text', [-3.2, -1, 'internal'],
{layer: 1, display: 'internal'});
Images can be put into layers. This means, one also has to use display:'internal'. Here is an example (https://jsfiddle.net/jdw7z1nq/1/):
var im = board.create('image', ['https://jsxgraph.org/wp/img/logo_tw.png', [-3, -3], [6, 6]],
{layer: 10});
var circ = board.create('circle', [[0,0], 3],
{fillColor: 'yellow', layer: 6});
var txt = board.create('text', [1, 1, 'Hello'],
{layer: 5, display: 'internal'});
The advantage of HTML texts is that they can contain any kind HTML content, for example MathJax or form tags or images, ... So, you might also consider putting the image into a text element.
Related
I was expecting to just say something like
ma.zeros(my_shape, mask=my_mask, hard_mask=True)
(where the mask is the correct shape) but ma.zeros (or ma.ones or ma.empty) rather surprisingly doesn't recognise the mask argument. The simplest I've come up with is
ma.array(np.zeros(my_shape), mask=my_mask, hard_mask=True)
which seems to involve unnecessary copying of lots of zeros. Is there a better way?
Make a masked array:
In [162]: x = np.arange(5); mask=np.array([1,0,0,1,0],bool)
In [163]: M = np.ma.MaskedArray(x,mask)
In [164]: M
Out[164]:
masked_array(data=[--, 1, 2, --, 4],
mask=[ True, False, False, True, False],
fill_value=999999)
Modify x, and see the result in M:
In [165]: x[-1] = 10
In [166]: M
Out[166]:
masked_array(data=[--, 1, 2, --, 10],
mask=[ True, False, False, True, False],
fill_value=999999)
In [167]: M.data
Out[167]: array([ 0, 1, 2, 3, 10])
In [169]: M.data.base
Out[169]: array([ 0, 1, 2, 3, 10])
The M.data is a view of the array used in creating it. No unnecessary copies.
I haven't used functions like np.ma.zeros, but
In [177]: np.ma.zeros
Out[177]: <numpy.ma.core._convert2ma at 0x1d84a052af0>
_convert2ma is a Python class, that takes a funcname and returns new callable. It does not add mask-specific parameters. Study that yourself if necessary.
np.ma.MaskedArray, the function that actually subclasses ndarray takes a copy parameter
copy : bool, optional
Whether to copy the input data (True), or to use a reference instead.
Default is False.
and the first line of its __new__ is
_data = np.array(data, dtype=dtype, copy=copy,
order=order, subok=True, ndmin=ndmin)
I haven't quite sorted out whether M._data is just a reference to the source data, or a view. In either case, it isn't a copy, unless you say so.
I haven't worked a lot with masked arrays, but my impression is that, while they can be convenient, they shouldn't be used where you are concerned about performance. There's a lot of extra work required to maintain both the mask and the data. The extra time involved in copying the data array, if any, will be minor.
I'm writing a custom Tensorflow op using the tutorial and I'm having trouble understanding how to read and write to/from Tensors.
let's say I have a Tensor in my OpKernel that I get from
const Tensor& values_tensor = context->input(0); (where context = OpKernelConstruction*)
if that Tensor has shape, say, [2, 10, 20], how can I index into it (e.g. auto x = values_tensor[1, 4, 12], etc.)?
equivalently, if I have
Tensor *output_tensor = NULL;
OP_REQUIRES_OK(context, context->allocate_output(
0,
{batch_size, value_len - window_size, window_size},
&output_tensor
));
how can I assign to output_tensor, like output_tensor[1, 2, 3] = 11, etc.?
sorry for the dumb question, but the docs are really tripping me up here and the examples in the Tensorflow kernel code for built-in ops somehow obfuscate this to the point that I get very confused :)
thank you!
The easiest way to read from and write to tensorflow::Tensor objects is to convert them to an Eigen tensor, using the tensorflow::Tensor::tensor<T, NDIMS>() method. Note that you have to specify the (C++) type of elements in tensor as template parameter T.
For example, to read a particular value from a DT_FLOAT32 tensor:
const Tensor& values_tensor = context->input(0);
auto x = value_tensor.tensor<float, 3>()(1, 4, 12);
To write a particular value to a DT_FLOAT32 tensor:
Tensor* output_tensor = ...;
output_tensor->tensor<float, 3>()(1, 2, 3) = 11.0;
There are also convenience methods for accessing a scalar, vector, or matrix.
The following output code outputs an array from the manipulate statement. I would like to output the fitting and plot as two separate output cells that update dynamically. I think it should be pretty simple, but I am having trouble with it. I've tried using the CellPrint[] function, but did not get it to work.
Thanks,
Tal
temperatures(*mK*)= {300, 200, 150, 100, 75, 50, 25, 11, 10};
F[t_, \[Nu]_] := t^\[Nu];
rd (*uOhms*)= {27173.91304, 31250., 42372.88136, 200601.80542,
1.05263*10^6, 1.33333*10^7, 1.33333*10^8, 2.*10^8, 2.1*10^8};
logRd = Log10[rd];
f[\[Nu]0_] := Module[{\[Nu]},
\[Nu] = \[Nu]0;
data = Transpose[{F[temperatures, \[Nu]]*10^3, logRd}];
fitToHexatic = LinearModelFit[data[[4 ;; 6]], x, x];
plota =
Plot[fitToHexatic["BestFit"], {x, 0, data[[-1]][[1]]},
Axes -> False];
plotb = ListPlot[data, Axes -> False];
{fitToHexatic, Show[{plota, plotb}, Axes -> True]}
]
Manipulate[
f[nu],
{nu, -0.2, -1}
]
Screenshot of the output:
You don't need to use a Manipulate. You can get more control with lower level functions. E.g.
Slider[Dynamic[nu, (f[#]; nu = #) &], {-0.2, -1}]
Dynamic[Normal[fitToHexatic]]
Dynamic[Show[{plota, plotb}, Axes -> True]]
See also Prototypical Manipulate in lower level functions.
I defined the following slice layer, where I want to split Nx7 into Nx3 and Nx4 two blobs
layers {
name: "slice_label"
type: SLICE
bottom: "label"
top: "label_pos"
top: "label_rotation"
slice_param {
slice_dim: 1
slice_point: 3
}
How can I do the same thing in Tensorflow?
I believe that you can do this with a hand-crafted layer, using the split method. You can also do it with separate calls to slice. Something like
slice3, slice4 = tf.split(input_tensor, [3, 4], 1)
Correction per OP comment:
slice3, slice4 = tf.split_v(labels, [3, 4], 1)
BTW, the spacing follows PEP8 standards. It's not required, of course, but there is checking software that prefers the spacing this way.
dalist = {901, 503, 522, 1305}
cogColors = {RGBColor[0, 0, 1], RGBColor[1, 0, 0], RGBColor[0, 1, 0], RGBColor[1, 1, 0]}
BarChart[dalist, ChartStyle -> cogColors]
Is it possible to decrease the Bars Width ?
I may be missing the point, but cannot you merely change the aspect ratio?
BarChart[dalist, ChartStyle -> cogColors, AspectRatio -> 3, ImageSize -> 120]
BarChart is not intended to do that. You can only change the spacings.
Use RectangleChart instead if you need finer control:
RectangleChart[{{{1, 1}, {1, 1}, {1, 1}}, {{2, 2}, {2, 2}, {2, 2}}}]
Rather than changing the bar chart width, you can increase the bar spacing.
BarChart[dalist, ChartStyle -> cogColors, BarSpacing -> 1]
See Heike's answer to my earlier question. You need to use RectangleChart. If you want to keep a constant distance between bar centres, so that the bar-plus-spacing takes up a constant space, you can use the ChartElementFunction option together with an auxiliary function, as shown in Heike's answer. (This might also do what you want using BarChart, but I'd still recommend RectangleChart.)