kandi X-RAY | amygdala Summary
kandi X-RAY | amygdala Summary
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amygdala Examples and Code Snippets
Trending Discussions on amygdala
I'm trying to build an app in Python with Google App Engine that fetches followers of specific accounts and then their tweets. I'm basing it on this template and changing it to adapt it to what I need.
The issue at the moment is that when I try to fetch followers, I get an
DeadlineExceededError due to the Twitter API waiting time.
I have found this post on how to fix the same problem and I think that in my case the best solution would be to use backends, but I noticed that they are deprecated.
Does someone know how I can achieve the same result without the deprecated module?...
ANSWERAnswered 2018-Sep-05 at 16:30
Backends (modules) have been deprecated in favor of Services:
For the Service you want to be able to handle requests longer than 60 seconds, set it to Manual Scaling. Then, a request can run for up to 24 hours (or until you shut it down). See:
Of course, your costs may go up with long running instances and request.
Hi I have a large dataframe with many columns. I want to replace outliers as "NA" based on value of each column+/- 3*IQR for all the columns in the dataset. I have tried something like this but everything goes FALSE. Would appreciate any advice. I get the following error message using the code below. In match.fun(FUN) : argument "FUN" is missing, with no default...
ANSWERAnswered 2020-Apr-02 at 21:09
Here's one method to use IQR on each column.
I find it typically very useful to come up with a simple "verb" function that can be easily tested and demonstrated, and then applied as many times as needed.
I have a large data set of genes and tissues of 3000 rows and 53 columns .
when i try to create a heatmap using
pheatmap in R for small number of columns it is successful.
but when i try to add the
annotation_col and row with color bar to heatmap, I get errors.
"Error in annotation_colors[[colnames(annotation)[i]]] : subscript out of bounds"
Any help will be appreciated....
ANSWERAnswered 2019-Aug-30 at 22:36
You need to define the same row names for
I am trying to create a pandas dataframe with iteratively counting statisitcs from another dataframe, it goes through columns (that filtered with regex). How could i create a result Dataframe? Input dataframe:...
ANSWERAnswered 2019-May-21 at 17:19
I still cannot really understand how and where, but you showed that somewhere in the function you were able to build a float64 Series containing for example
Left-Amygdala_Volume_mm3 as index and
-0.29729 as value. And I assume that at the same time, you have the value of
meand for the same index value.
More exactly I will assume:
I have a key and a massive metadata table. There's a column in the metadata table which contains values such as the following:...
ANSWERAnswered 2019-Jan-22 at 21:54
Here is a solution:
I'm sorry if this question has been asked before, I just didn't know how to word it as a search query.
I have a set of folders that look like this:...
ANSWERAnswered 2019-Jan-21 at 17:41
Not a full answer, but it should address some of your concerns:
a) to isolate the first word of a string, leading up to the first
.: use Parameter Expansions
I have a table named
NE that contains spliced RNA junctions:
ANSWERAnswered 2019-Jan-15 at 17:59
body_site, you get a vector of
Sample_Names corresponding to each
body_site. Then you just need to
intersect this with the names of
NE for each
body_site, and select the columns resulting from that intersection. The result is a named list of data tables. The names are the
I have been trying to run a cron job with GAE (code developed in Python), but when I trigger the job, it fails without any error message -- I can't find anything at all in the logs.
This is happening for a service for which I'm using the flexible environment.
This is the structure of my files:
my_service.yaml looks like this:
ANSWERAnswered 2018-Oct-04 at 19:05
def get(self): may have some issues.
get may be reserved. Second, you aren't able to send
self to that function. Change that to:
You also need to
import logging at the top of any page that uses it. And, you have not imported
Flask and its components:
When using google cloud ML to train models:
The official examples https://github.com/GoogleCloudPlatform/cloudml-samples/blob/master/census/tensorflowcore/trainer/task.py uses hooks, is_client, MonitoredTrainingSession and some other complexity.
Is this required for cloud ml or is using this example enough: https://github.com/amygdala/tensorflow-workshop/tree/master/workshop_sections/wide_n_deep?
The documentation is a bit limited in terms of best practices and optimisation, will GCP ML handle the client/worker mode or do we need to set devices e.g.
replica_device_setter and so on?
ANSWERAnswered 2017-May-09 at 20:21
CloudML Engine is largely agnostic to how you write your TensorFlow programs. You provide a Python program, and the service executes it for you, providing it with some environment variables you can use to perform distributed training (if necessary), e.g., task index, etc.
census/tensorflowcore demonstrates how to do things with the "core" TensorFlow library -- how to do everything "from scratch", including using
MonitoredTrainingSessions, etc.. This may be necessary sometimes for ultimate flexibility, but can be tedious.
Alongside the census/tensorflowcore example, you'll also see a sample called census/estimator. This example is based on a higher level library, which unfortunately is in
contrib and therefore does not yet have a fully stable API (expect lots of deprecation warnings, etc.). Expect it to stabilize in a future version of TensorFlow.
That particularly library (known as
Estimators) is a higher level API that takes care of a lot of the dirty work for you. It will parse
TF_CONFIG for you and setup the
replica_device_setter as well as handle the
MonitoredTrainingSession and necessary
Hooks, while remaining fairly customizable.
This is the same library that the wide and deep example you pointed to is based on and they are fully supported on the service.
No vulnerabilities reported
To create a new store, define the few possible settings listed below and your API schema. When you want to include related data under a single request, for example, to minimize HTTP requests, having schema relations allows you to still have a clean separation when interacting with the data locally.
apiUrl - Full path to your base API url (required).
idAttribute - global primary key attribute (required).
headers - Any headers that you need to pass on each API request.
localStorage - enable/disable the persistent localStorage cache.
url - relative path for each "table" (required)
orderBy - order by which you want to retrieve local cached data. eg (name, -name (for reverse))
parse - Accepts a parse method for cases when your API also returns extra meta data.
idAttribute - overrides key attribute (if different in this schema)
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