I am using the embed .html example given on the bokeh site: http://docs.bokeh.org/en/latest/docs/user_guide/embed.html. Note I am using bokeh 12.3. The plots are displaying fine but the text is rendering as the exact output from the script function - including '{' and '\n' characters.
scatter function:
from bokeh.plotting import figure
from bokeh.models import Range1d
from bokeh.embed import components
def scatter():
# create some data
x1 = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
y1 = [0, 8, 2, 4, 6, 9, 5, 6, 25, 28, 4, 7]
x2 = [2, 5, 7, 15, 18, 19, 25, 28, 9, 10, 4]
y2 = [2, 4, 6, 9, 15, 18, 0, 8, 2, 25, 28]
x3 = [0, 1, 0, 8, 2, 4, 6, 9, 7, 8, 9]
y3 = [0, 8, 4, 6, 9, 15, 18, 19, 19, 25, 28]
# select the tools we want
TOOLS="pan,wheel_zoom,box_zoom,reset,save"
# the red and blue graphs will share this data range
xr1 = Range1d(start=0, end=30)
yr1 = Range1d(start=0, end=30)
# only the green will use this data range
xr2 = Range1d(start=0, end=30)
yr2 = Range1d(start=0, end=30)
# build our figures
p1 = figure(x_range=xr1, y_range=yr1, tools=TOOLS, plot_width=300, plot_height=300)
p1.scatter(x1, y1, size=12, color="red", alpha=0.5)
p2 = figure(x_range=xr1, y_range=yr1, tools=TOOLS, plot_width=300, plot_height=300)
p2.scatter(x2, y2, size=12, color="blue", alpha=0.5)
p3 = figure(x_range=xr2, y_range=yr2, tools=TOOLS, plot_width=300, plot_height=300)
p3.scatter(x3, y3, size=12, color="green", alpha=0.5)
# plots can be a single Bokeh Model, a list/tuple, or even a dictionary
plots = {'Red': p1, 'Blue': p2, 'Green': p3}
script, div = components(plots)
return script, div
My flask code is:
script, div = scatter()
return self.render_template('bokeh_example.html', script=script, div=div)
bokeh_example.html:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<link rel="stylesheet" href="http://cdn.bokeh.org/bokeh/release/bokeh-0.12.3.min.css" type="text/css" />
<script type="text/javascript" src="http://cdn.bokeh*emphasized text*.org/bokeh/release/bokeh-0.12.3.min.js"></script>
{{ script | safe }}
</head>
<body>
<div class='bokeh'>
<h1>Scatter Example</h1>
{{ div | safe }}
</div>
</body>
</html>
The plots display fine but the div text renders as literals:
{'Red': '\n #this text displays instead of just the string 'Red'
\n #this displays on next line in smaller font
#plot displays fine here
\n #this text displays after the plot instead of creating a blank line.
Any clues?
You are passing a dictionary of plots to components:
plots = {'Red': p1, 'Blue': p2, 'Green': p3}
script, div = components(plots)
return script, div
This means (per the documentation) that the result is not a single script and a single div. Rather, it's a single script and a dictionary mapping your original names to multiple divs:
components({"Red": p1, "Blue": p2, "Green": p3})
#=> (script, {"Red": p1_div, "Blue": p2_div, "Green": p3_div})
Right now you are trying to template the dict itself into your HTML. Presumably Jinja just calls str on the dict to turn it into a string, and the browser doesn't know what to do with that. You need to template each one of the divs in the dict returned by components, individually.
For a suitably updated template, that might look like:
script, divs = scatter() # notice plural: divS
return self.render_template(
'bokeh_example.html',
script=script,
div_red=divs['Red'],
div_blue=divs['Blue'],
div_green=divs['Green'],
)
Or alternatively you might update the template to iterate over divs directly using some of Jinja2's capabilities for iterating over template arguments that are collections.
Related
Can I sample an array a = [1, 2, 3, 4] based on the specified probabilities p = [0.1, 0.1, 0.3, 0.5]?
For example, in python I can use np.random.choice(a=[1, 2, 3, 4], size=100, p=[0.1, 0.1, 0.3, 0.5])
For me I will form a new random choice data list by percentages/probabilities, for example do random choice on [1, 2, 3, 3, 3, 4, 4, 4, 4, 4] will be equivalent with your data and probabilities.
You can use take (https://www.dolphindb.com/help/FunctionsandCommands/FunctionReferences/t/take.html) function for helping the data forming:
v = take(1, 1) <- take(2, 1) <- take(3, 3) <- take(4, 5)
rand(v, 100)
I am trying to implement something like this for 2 nodes (each node with 2 GPUs):
#### Parallel process initiated with torch.distributed.init_process_group()
### All GPUs work in parallel, and generate lists like :
[20, 0, 1, 17] for GPU0 of node A
[1, 2, 3, 4] for GPU1 of node A
[5, 6, 7, 8] for GPU0 of node B
[0, 2, 4, 6] for GPU1 of node B
I tried
torch.distributed.reduce()
to get a sum of these 4:
[26, 10, 15, 35]
But what I want is a concatenated version like this
[[20, 0, 1, 17], [1, 2, 3, 4] , [5, 6, 7, 8] , [0, 2, 4, 6]]
Or
[20, 0, 1, 17, 1, 2, 3, 4, 5, 6, 7, 8, 0, 2, 4, 6]
is also OK with me.
Is it possible to achieve this from torch.distributed?
You can use dist.all_gather to do this:
import torch
import torch.distributed as dist
q = torch.tensor([20, 0, 1, 17]) # generated on each gpu (with different values) as you mentioned
all_q = [torch.zeros_like(q) for _ in range(world_size)] # world_size is the total number of gpu processes you are running. 4 in your case.
all_q = dist.all_gather(all_q, q)
all_q would then have the following:
[torch.tensor([20, 0, 1, 17]), torch.tensor([1, 2, 3, 4]), torch.tensor([5, 6, 7, 8]), torch.tensor([0, 2, 4, 6])]
You can then use torch.cat to collapse all elements into one array if you like.
You can use dist.all_gather_multigpu if you list of lists of tensors.
I want to apply a function to the variable x and saved as y. But why the x is also changed? How to prevent it?
import torch
def minus_min(raw):
for col_i in range(len(raw[0])):
new=raw
new[:,col_i] = (raw[:,col_i] - raw[:,col_i].min())
return new
x=torch.tensor([[0,1,2,3,4],
[2,3,4,0,8],
[0,1,2,3,4]])
y=minus_min(x)
print(y)
print(x)
output:
tensor([[0, 0, 0, 3, 0],
[2, 2, 2, 0, 4],
[0, 0, 0, 3, 0]])
tensor([[0, 0, 0, 3, 0],
[2, 2, 2, 0, 4],
[0, 0, 0, 3, 0]])
Because this assignment:
new[:,col_i] = (raw[:,col_i] - raw[:,col_i].min())
is an in-place operation. Therefore, x and y will share the underlying .data.
The smallest change that would solve this issue would be to make a copy of x inside the function:
def minus_min(raw):
new = raw.clone() # <--- here
for col_i in range(len(raw[0])):
new[:,col_i] = raw[:,col_i] - raw[:,col_i].min()
return new
If you want, you can simplify your function (and remove the for loop):
y = x - x.min(dim=0).values
In my script I save python 2D list(all are float values) in a json file. When I run the script in my machine saved json file contains the correct data. But when I run the python script in xampp server, json file only contains integer values.
I checked the code but no issue found. And the same code outputs two different json files.
When I run script in my machine;
{"arr": [[5.7, 7.14, 5.72, 10.96, 15.82, 10.96, 15.78, 7.08], [5.76, 7.2, 15.72, 7.14, 15.76, 10.88, 5.8, 10.9], [4.98, 1.46, 4.98, 11.7, 14.38, 11.7, 14.44, 15.2, 29.14, 15.22, 29.12, 5.7, 21.42, 5.68, 21.34, 1.44], [17.52, 8.76, 23.18, 8.8, 23.16, 15.14, 17.46, 15.1], [21.4, 6.14, 28.74, 6.08, 28.78, 7.54, 21.44, 7.56], [5.02, 6.4, 15.82, 6.36, 15.88, 1.5, 21.28, 1.5, 21.36, 7.62, 29.06, 7.64, 29.06, 15.12, 23.28, 15.14, 23.24, 8.72, 17.48, 8.7, 17.4, 15.12, 14.52, 15.14, 14.46, 11.64, 5.06, 11.64], [5.02, 1.56, 15.72, 1.5, 15.76, 6.28, 5.06, 6.28]]}
When I run script in xampp server;
{"arr": [[5, 7, 5, 10, 15, 10, 15, 7], [5, 7, 15, 7, 15, 10, 5, 10], [4, 1, 4, 11, 14, 11, 14, 15, 29, 15, 29, 5, 21, 5, 21, 1], [17, 8, 23, 8, 23, 15, 17, 15], [21, 6, 28, 6, 28, 7, 21, 7], [5, 6, 15, 6, 15, 1, 21, 1, 21, 7, 29, 7, 29, 15, 23, 15, 23, 8, 17, 8, 17, 15, 14, 15, 14, 11, 5, 11], [5, 1, 15, 1, 15, 6, 5, 6]]}
This is my code.
#!/usr/bin/env python
import sys;
import cv2
import codecs, json
dataset=[]
image = cv2.imread("C:/xampp/htdocs/"+sys.argv[1])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (3, 3), 0)
edged = cv2.Canny(gray, 10, 250)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (20, 20))
closed = cv2.morphologyEx(edged, cv2.MORPH_CLOSE, kernel)
cv2.waitKey(0)
(_, cnts, _) = cv2.findContours(closed.copy(), cv2.RETR_CCOMP,
cv2.CHAIN_APPROX_SIMPLE)
total = 0
lengths = 0;
i = 0
for c in cnts:
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
converted_cnts_rooms = approx.squeeze()
dataset.append([])
for iterate in converted_cnts_rooms:
x1, y1 = iterate.ravel()
dataset[i].append(x1/50)
dataset[i].append(y1/50)
total += 1
i += 1
cv2.waitKey(0)
converted_cnts = approx.squeeze()
for iterate in converted_cnts:
x1,y1 = iterate.ravel()
data = {}
data.update({"arr":dataset})
with open('dataset.json', 'w') as outfile:
json.dump(data, outfile)
Appreciate your help...!!!
I need to create a python function, which will recursively store fibonacci values in a list, and then return that list to me. Then, I can print that list. Here is what I have.
def recFib(x):
result = []
if x == 1:
return result.append(1)
if x == 2:
return result.append(2)
for i in range(2,x):
result.append(recFib(i-1)+recFib(i-2))
return result
I am new to Python, so alot of concepts are new to me and I seem to be unable to figure out what I'm doing wrong.
Here is a solution based on the #Akavall's anwer
def recFib(x):
fibArray = [0, 1]
def fib(x):
if x < len(fibArray):
return fibArray[x]
temp = fib(x - 1) + fib(x - 2)
fibArray.append(temp)
return temp
return fib(x)
There a few issues with you code, for example:
return result.append(1)
will return None, not result with 1 appended to it.
Also,
def recFib(x):
result = []
Will set result to [] every time recFib is called, I don't think that's what you wanted.
And I am not sure that I understand your entire logic, sorry.
A possible solution is something like this:
def recFib(x):
n_to_fib = {0: 0, 1: 1}
def fib(x):
if x in n_to_fib:
return n_to_fib[x]
temp = fib(x - 1) + fib(x - 2)
n_to_fib[x] = temp
return temp
return fib(x)
if __name__ == "__main__":
result = [recFib(i) for i in range(8)]
print result
Result:
[0, 1, 1, 2, 3, 5, 8, 13]
And calculating new values is fast because the previous values are stored in n_to_fib dict and thus don't have to be recomputed.
We can also modify recFib to return the list directly:
fib(x)
return sorted(n_to_fib.values())
instead of:
return fib(x)
Try this:
def recFib(n):
if n == 1:
return [0]
elif n == 2:
return [0, 1]
else:
a = recFib(n-1)
return a + [a[-1] + a[-2]]
The key in the program is here:
return a + [a[-1] + b[-1]]
a # This gets the most recently created list, since it's `recFib(n-1)`
+ # Append to the next list (but does not return `None`)
[ a[-1] # Last value of `recFib(n-1)`, which is the previous value.
+ # Add to
a[-2]] # Second last value of `recFib(n-1)`, which is the second previous value.
Here are the breakpoints for recFib(5):
n = 3
a[-1]: 1
a[-2]: 0
n = 4
a[-1]: 1
a[-2]: 1
n = 5
a[-1]: 2
a[-2]: 1
[0, 1, 1, 2, 3]
It doesn't require two functions. I sort of find that as cheating:
>>> recFib(20)
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181]
>>> recFib(10)
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
>>> recFib(19)
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584]
Generating a list by for looping a recursive function is very inefficient. You are recalculating the whole sequence every time you use the function.