I want to call the API to get the (Cost vs. ROAS) forecast.
It's visible on GA-FE, but the response object doesn't contain the ROAS or any value metric.
GA_FE:
API:
https://developers.google.com/google-ads/api/reference/rpc/v11/ForecastMetrics?hl=en
Any idea how can I calculate the (Cost vs. ROAS) forecast.
Related
I am using parameter variation in AnyLogic (in a system dynamics model). I am interested in how one parameter changes with the various iterations. The parameter is binary: 0 when supply of water is greater than demand and 1 when supply is lower than demand. The parameters being varied are a given percentage of decrease in outdoor irrigation, a given percentage of decrease in indoor water-use, and a given percentage of households that have rainwater harvesting systems. Visually, I need a time plot where on the x-axis is time (10,950 days; i.e. 30 years) and the binary on the y-axis. This should essentially show which iteration pushes a 1 further into the future.
I have watched videos and seen how histograms and 2D data are used to visualize the results of the iterations, but this does not show which iteration produced which output specifically. Is there a way to first, visually show the output as I have described above and second, return the data for a specific iteration?
Many thanks!
Parameter variation experiments have After Iteration and After Simulation run actions that are executed after each iteration and simulation respectively. Here, it is possible to access the values inside the simulation object after it finished but before it is destroyed. There is also a getCurrentIteration() method which can be used to control the parameter variation experiment and retrieve the data.
For more detail please consult here and see "SIR Agent Based Calibration" example model in AnyLogic example models library (Help -> Example Models).
I am trying to find time series outlier using Tableau forecast. I need to compare the actual value with the 95% confidence level in forecast results to determine if it is an outlier.
I understand I can view the forecast results on the chart. But I want to use the forecast results in calculated measure. Is there any way to do it? I cannot find any Tableau functions to retrieve the forecast results.
Xuefei. Doesn't look like there is a way currently, at least going by their help page - https://help.tableau.com/v2019.1/pro/desktop/en-us/forecast_options.htm. If you haven't already considered this - integration with R is easy and that way you could just model it in R (accounting for additive/multiplicative, trend/cyclicity/seasonality) and access the forecast values from R. Integration with Python is also supposed to be easy, although I haven't tried it myself.
Example of code in Tableau to incorporate R code for linear regression (this is the formula for the calc field in Tableau)
SCRIPT_REAL("
fv=log(.arg1)
fpri=.arg2
fit=lm(fv~fpri)
exp(fit$fitted)",SUM([Impressions]),SUM([CPM]))
Background: Soon after my performance test, the response time details of the business transactions will be fed into splunk, from where I need to generate trend graph for couple of transactions for certain period of time.
Now I am able to group the response time data for these transactions but in visualization, not able to generate the chart.
Refer:SS01.jpg for more details.
query used: index=xyz source=abc (Period!=Period) Transaction_Name=Search OR Address_Book OR Policy | chart values(Average) as Average by Transaction_Name
I want the chart to appear in either format A or B as it appears on SS02.jpg.
Please help me on this.
Thanks.
You have very low values (i.e. 0.046, 0.099, etc) in the query output and very high value in the chart Y axis (100), in order to get the desired picture just reduce the maximum value for the vertical axis like:
To make the changes permanent you can amend charting.secondaryAxis.maximumNumber parameter value like it described in Controlling chart (y axis) range
Personally I prefer BM.Sense output for performance test results analysis.
I am using Google Fit REST API (via Google Java Client Library) to post an activity into Google Fit.
In summary what I am doing is creating three DataSets covering the given time period:
"com.google.location.sample" - Location
"com.google.step_count.delta" - Steps
"com.google.calories.expended" - Calories
... then creating a Session, and finaly a DataSet with a single Activity Segment (in this case all the time is walking).
This basically all seems to work - I can looking in http://fit.google.com, and I can see the activity, with the correct time, location, duration, steps and calories. The problem is with the map... all it shows is a shaded circle over the whole area of the walking - it doesn't show the track/path that I included in the location DataSet.
EDIT... Here is an example of what it looks like (in web UI).
Why would this not be showing up correctly, when all of the rest of the activity shows up perfectly?
These are some of my suspicions
My data does not have either altitude or accuracy - which are two of the fields needed by "com.google.location.sample". So I set altitude to 0.0 (metres), and set accuracy to 5.0 (metres). I particularly wonder if Google is reacting badly to me setting the altitude to 0.0 for each point?
My location DataSet has say 100 DataPoints in it, whereas by steps and calories DataSets only have one DataPoint in each - i.e. I only have total steps, and total calories, for the walk. So there's an inconsistency (the earliest start and latest end dates are the same for each data set)
Can anybody give any guidance about why this is happening please?
Think this may be due to conflicting data points. As stated here. Although this is for the API for Android, I think it holds true too when using the REST API.
Each DataPoint in your app's DataSet must have a startTime and an
endTime that defines a unique interval within that DataSet, with no
overlap between DataPoint instances. If your app attepts to insert a
new DataPoint that conflicts with an existing DataPoint instance, the
new DataPoint is discarded. To insert a new DataPoint that may overlap
existing data points, use the HistoryApi.updateData method described in
Update data.
You mentioned that the dates are the same across data points. Thus overriding the others and it is only treated as one.
For your com.google.location.sample data type fields. Think it's better to leave them as is. Try not to place a static value and for altitude and accuracy.
The xively (Cosm) web interface issues the following function for averaged historical datapoints
// For averaged historical datapoints
https://www.xively.com/feeds/<feedId>/datastreams/Humidity/graph.json&duration=21600seconds&interval=30&limit=1000&find_previous=true&function=average
I would like to fetch averaged historical data points (That is if there are multiple samples within the interval I am asking then return an averaged rollup as representative point of the interval) using Xively REST API
However this seems to return the raw data points (They just pick one datapoint to represent the sample interval)
https://api.xively.com/v2/feeds/127181539.json?datastreams=TEMP&duration=1month&interval=21600&limit=200&function=average
So questions
1) How can I return averaged data points like the Xively web interface? what parameter is needed for feed API call?
2) Does anyone know about the parameter interval_type? I have read what is here (https://xively.com/dev/docs/api/quick_reference/historical_data/) about 50 times now but I still don't get it!
Update
function=sum as well as function=average works for
/datastreams/TEMP.json endpoint. Also, they are discrete by default.
The function=average does not works with /feeds/feed_id.json
endPoint. Maybe a Bug?
If you've got "function=average" (which you have) as a query parameter, then the points you get back should be bucketed to the interval you specified (21600 seconds / 6 hours). Each point represents the average value for that period.
It might be worth making this query against the datastreams endpoint though, e.g.
https://api.xively.com/v2/feeds/127181539/datastreams/TEMP.json?duration=1month&interval=21600&limit=200&function=average
Hope this helps!