I want to suppress any text output when I run Jupyter Notebook cell. Specifically I output some figures and each is accompanied by something like:
<Figure size 432x288 with 0 Axes>
I have seen that if I put a ; at the end of a line, it should suppress the output, but it is not working in my case.
The code:
for i in tqdm_notebook(range(data.shape[0])):
print('BIN:',i)
fig = plt.figure(figsize=(15,4))
plt.tight_layout()
gs = gridspec.GridSpec(2,1)
ax1 = fig.add_subplot(gs[0, 0])
ax1.plot(match[window_begin:window_end],'k')
plt.vlines(i,-np.max(match[window_begin:window_end])*0.05,np.max(match[window_begin:window_end])*1.05,'r',linewidth=4,alpha=0.2)
ax1.set_xlim(0-1,post_bin_match_median[window_begin:window_end].shape[0])
ax1.set_ylim(-np.max(match[window_begin:window_end])*0.05,np.max(match[window_begin:window_end])*1.05)
plt.tick_params(axis='y', which='both', left=True, labelleft=False)
ax1.tick_params(axis='x', which='both', bottom=False, labelbottom=False)
plt.grid()
ax2 = fig.add_subplot(gs[1, 0])
fig.subplots_adjust(hspace=0.0)
ax2.plot(gp_mjds[:],gp_data[i,:],'k')
ax2.errorbar(remain, all[i,:], yerr=all_noise[i], fmt=".k", capsize=0);
ax2.fill_between(gp[:], gp2[i,:] - np.sqrt(gp_var[i,:]), gp2[i,:] + np.sqrt(gp_var[i,:]),color="k", alpha=0.2)
ax2.set_xlim(gp[0],gp[-1])
plot_y_min = np.minimum(np.min(gp2[:,:] - np.sqrt(gp_var[:,:])),np.min(all_profile_residuals[:,:]-y_noise))
plot_y_max = np.maximum(np.max(gp2[:,:] + np.sqrt(gp_var[:,:])), np.max(all[:,:]+y_noise))
ax2.set_ylim(plot_y_min,plot_y_max)
plt.grid()
plt.show()
plt.clf()
plt.close(fig);
The semi-colon would work if the typical output from the last line of the cell is what you are trying to suppress. As succinctly summarized by #kynan here, "The reason this works is because the notebook shows the return value of the last command. By adding ; the last command is "nothing" so there is no return value to show."
However, you have a loop inside a cell generating objects.
The culprit seems to be plt.clf(). Comment out that line or remove it from your code, and it should fix it.
Plus, I'd remove plt.show() as it isn't necessary when plt.clf() is removed, and I am seeing it being in the loop causing fig = plt.figure(figsize=(15,4)) to also show output text like you posted in your issue.
(I'll add for others looking at this later, that it is important have %matplotlib inline or %matplotlib notebook at the start of the cell (or at the start of a cell somewhere above this one.))
A complete guide on how to hide or remove content in Jupyter is available from the official documentation: https://jupyterbook.org/interactive/hiding.html#
For removing the single output line, you can tweak the command lines by adding a _ = [command ] assignment as suggested in this blog: https://www.tutorialguruji.com/python/suppress-output-in-matplotlib/.
The underscore there is a throwaway variable, actually an unidentified variable "when not in interactive mode". See the official Python documentation: https://docs.python.org/3.9/reference/lexical_analysis.html#reserved-classes-of-identifiers
Related
I am trying to write a simple if-then-else statement using the Pine language under Tradingview. What the code does is based upon user input.
If the box is checked, the plot the line.
If the box is not checked do not plot the line.
This is the code I have:
notPlot = -2000
var ch382= input(true, ".382")
if ch382
plot( ch382? bottom + diff * .382: noPlot, title="fib-.236", linewidth=3, color=color.orange )
How can I write this in a proper way?
If I try to run it, I get: “cannot use 'plot' in a local scope”
Any assistance would be greatly appreciated.
ETA: I found this thread below
How to put plot statement inside if statement
but -
what I need to do is to plot if the box is checked and ~not plot~ if the box is not checked.
ETA: figured out the issue. One would use "na" (in the case of plotting) to note that the line should not be displayed - my mistake ...
var ch382 = input(true, ".382")
plot( ch382? bottom + diff * .382: na, title="fib-.382", linewidth=3, color=color.orange )
I have a list of pandas dataframes I named entries, which I want to visualize after running code from the same cell. Below is the code I used :
alt.data_transformers.disable_max_rows()
for entry in entries :
entry['ds'] = entry.index
entry['y'] = entry['count']
entry['floor'] = 0
serie = alt.Chart(entry).mark_line(size=2, opacity=0.7, color = 'Black').encode(
x=alt.X('ds:T', title ='date'),
y='y'
).interactive().properties(
title='Evolution of '+entry.event.iloc[0]+' events over time'
)
alt.layer(serie)\
.properties(width=870, height=450)\
.configure_title(fontSize=20)
When i run the same code out of the 'for' loop, I get to see the one chart that corresponds to one dataframe, but once I run the code above, I don't get any graphs at all.
Does anyone know why It's not working or how to solve this issue?
TLDR: use chart.display()
Unless a chart appears at the end of the cell, you must manually display it.
By analogy, if you run
x + 1
by itself, Python will display the result. However, if you run
for x in range(10):
x + 1
Python will not display anything, because the last statement in the cell (in this case the for loop) has no return value to display. Instead you have to write
for x in range(10):
print(x + 1)
For altair, the mechanism is similar: if the chart is defined in the last statement in the cell, it will be automatically displayed. Otherwise, you have to manually trigger the display, which you can do using the display method:
for i in range(10:
chart = alt.Chart(...)
chart.display()
For more information on display troubleshooting in Altair, see https://altair-viz.github.io/user_guide/troubleshooting.html
This is a new question related to a previous question I asked:
holoviews can't find flexx when using a Dimension value_format callback
Thanks to downgrading my version of flexx, I am no longer getting the warning message. However, the callback function is not working. Here is the code:
%%output size=200
%%opts Curve [width=600 height=250] {+framewise}
%%opts Curve.Load.Ticket (color='red')
def xformat(x):
# update the default tick label to append an 'a'
new = x + 'a'
return(new)
kdims=hv.Dimension('Day Section', label='Week Day and Hour', value_format=xformat)
tload = hv.Curve(simple_pd,vdims=[('Max Ticket Load', 'Maxiumum Ticket Load')],kdims=kdims,group='Load',label='Ticket')
tload
When I run with the above code, I expect to see the same amount of x axis tick labels, however, each label should have an 'a' appended to the end. However, what I am seeing is no rendering of the element at all in my notebook. I have tried a number of variations of modifying the value, and the same thing happens.
Strangely, the issue appears to be the use of the variable name new in the xformat function. If I change the name of the variable it works fine. It doesn't appear as though new is a reserved work in python though, so I am not sure why its causing a problem.
Note that using the matplotlib extension does not have the same problem, only Bokeh.
I'm using Atom with soft wrap turned on. In most simple editors such as gedit, Ctrl-Down would be used to skip ahead to the true next line, ignoring any wrapped lines below (same as j and k in Vim).
However in Atom this shortcut produces the result of moving the line itself around, which is less useful to me. I'd like to remap Ctrl-Up and Ctrl-Down to move the cursor up or down to the next true line, as described above.
I'm familiar with editing my keymap file, but I simply can't find any command that would be the equivalent of moving ahead one full line.
You could write a custom command in your init.coffee like this:
atom.workspaceView.command 'custom:move-next-buffer-line', ->
editor = atom.workspace.getActiveEditor()
editor.moveCursorToEndOfLine()
editor.moveCursorRight()
And then just reverse it for moving to the previous buffer line. You can then map the custom command in your keymap, which you said you're familiar with.
If you're using the vim-mode-plus package, then just modify your keymap.cson file by adding
# except insert
# -------------------------
'atom-text-editor.vim-mode-plus:not(.insert-mode)':
# Motions
# -------------------------
'k': 'vim-mode-plus:move-up-screen'
'j': 'vim-mode-plus:move-down-screen'
See for details https://github.com/t9md/atom-vim-mode-plus/blob/master/keymaps/vim-mode-plus.cson
I (sort of) already know the answer to this question. But I figured it is one that gets asked so frequently on the R Users list, that there should be one solid good answer. To the best of my knowledge there is no multiline comment functionality in R. So, does anyone have any good workarounds?
While quite a bit of work in R usually involves interactive sessions (which casts doubt on the need for multiline comments), there are times when I've had to send scripts to colleagues and classmates, much of which involves nontrivial blocks of code. And for people coming from other languages it is a fairly natural question.
In the past I've used quotes. Since strings support linebreaks, running an R script with
"
Here's my multiline comment.
"
a <- 10
rocknroll.lm <- lm(blah blah blah)
...
works fine. Does anyone have a better solution?
You can do this easily in RStudio:
select the code and click CTR+SHIFT+C
to comment/uncomment code.
This does come up on the mailing list fairly regularly, see for example this recent thread on r-help. The consensus answer usually is the one shown above: that given that the language has no direct support, you have to either
work with an editor that has region-to-comment commands, and most advanced R editors do
use the if (FALSE) constructs suggested earlier but note that it still requires complete parsing and must hence be syntactically correct
A neat trick for RStudio I've just discovered is to use #' as this creates an self-expanding comment section (when you return to new line from such a line or insert new lines into such a section it is automatically comment).
[Update] Based on comments.
# An empty function for Comments
Comment <- function(`#Comments`) {invisible()}
#### Comments ####
Comment( `
# Put anything in here except back-ticks.
api_idea <- function() {
return TRUE
}
# Just to show api_idea isn't really there...
print( api_idea )
`)
####
#### Code. ####
foo <- function() {
print( "The above did not evaluate!")
}
foo()
[Original Answer]
Here's another way... check out the pic at the bottom. Cut and paste the code block into RStudio.
Multiline comments that make using an IDE more effective are a "Good Thing", most IDEs or simple editors don't have highlighting of text within simple commented -out blocks; though some authors have taken the time to ensure parsing within here-strings. With R we don't have multi-line comments or here-strings either, but using invisible expressions in RStudio gives all that goodness.
As long as there aren't any backticks in the section desired to be used for a multiline comments, here-strings, or non-executed comment blocks then this might be something worth-while.
#### Intro Notes & Comments ####
invisible( expression( `
{ <= put the brace here to reset the auto indenting...
Base <- function()
{ <^~~~~~~~~~~~~~~~ Use the function as a header and nesting marker for the comments
that show up in the jump-menu.
--->8---
}
External <- function()
{
If we used a function similar to:
api_idea <- function() {
some_api_example <- function( nested ) {
stopifnot( some required check here )
}
print("Cut and paste this into RStudio to see the code-chunk quick-jump structure.")
return converted object
}
#### Code. ####
^~~~~~~~~~~~~~~~~~~~~~~~~~ <= Notice that this comment section isnt in the jump menu!
Putting an apostrophe in isn't causes RStudio to parse as text
and needs to be matched prior to nested structure working again.
api_idea2 <- function() {
} # That isn't in the jump-menu, but the one below is...
api_idea3 <- function() {
}
}
# Just to show api_idea isn't really there...
print( api_idea )
}`) )
####
#### Code. ####
foo <- function() {
print( "The above did not evaluate and cause an error!")
}
foo()
## [1] "The above did not evaluate and cause an error!"
And here's the pic...
I can think of two options. The first option is to use an editor that allows to block comment and uncomment (eg. Eclipse). The second option is to use an if statement. But that will only allow you to 'comment' correct R syntax. Hence a good editor is the prefered workaround.
if(FALSE){
#everything in this case is not executed
}
If find it incredible that any language would not cater for this.
This is probably the cleanest workaround:
anything="
first comment line
second comment line
"
Apart from using the overkilled way to comment multi-line codes just by installing RStudio, you can use Notepad++ as it supports the syntax highlighting of R
(Select multi-lines) -> Edit -> Comment/Uncomment -> Toggle Block Comment
Note that you need to save the code as a .R source first (highlighted in red)
I use vim to edit the R script.
Let's say the R script is test.R, containing say "Line 1", "Line 2", and "Line 3" on 3 separate lines.
I open test.R on the command line with Vim by typing "vim test.R".
Then I go to the 1st line I want to comment out, type "Control-V", down arrow to the last line I want to comment out, type a capital I i.e. "I" for insert, type "# ", and then hit the Escape key to add "# " to every line that I selected by arrowing down. Save the file in Vim and then exit Vim by typing ":wq". Changes should show up in Rstudio.
To delete the comments in Vim, start at the first line on top of the character "#" you want to delete, again do "Control-V", and arrow down to the last line you want to delete a "#" from. Then type "dd". The "#" signs should be deleted.
There's seconds-worth of lag time between when changes to test.R in Vim are reflected in Rstudio.
Now there is a workaround, by using package ARTofR or bannerCommenter
Examples here:
In RStudio an easy way to do this is to write your comment and once you have used CTRL + Shift + C to comment your line of code, then use CTRL + SHIFT + / to reflow you comment onto multiple lines for ease of reading.
In RStudio you can use a pound sign and quote like this:
#' This is a comment
Now, every time you hit return you don't need to add the #', RStudio will automatically put that in for you.
Incidentally, for adding parameters and items that are returned, for standardization if you type an # symbol inside those comment strings, RStudio will automatically show you a list of codes associated with those comment parameters:
#' #param tracker_df Dataframe of limit names and limits
#' #param invoice_data Dataframe of invoice data
#' #return return_list List of scores for each limit and rejected invoice rows