osmosis | Models for diffusion data | Data Visualization library

Increasing the weight of the path works exactly as expected :

First, always reference column by name in aes and not by [ or $ of the same data frame. Second, you need to clean up your columns, ELEMENT_LABEL and plot_order, before plotting.

• Run droplevels as ELEMENT_LABEL currently has 54 levels for only 28 observations! Likely, your plotting data frame derives from a filtered version of original. After doing so, you reduce to 8 levels across 28 observations.
• Re-assign values of plot_order column by the unique values, not simply an integer sequence across length of rows. Specifically, plot_order must order the 8 unique values to correspond to each unique occurrence of ELEMENT_LABEL. You can achieve this with inline aggregation like ave calling min to take lowest number for same ELEMENT_LABEL.

Once you clean up these two columns, plotting then should adjust:

Your build.gradle (Module:app) should look like this

Ok, usging JOSM to validate the data seemed to do the trick.

Thanks for the help.

It appears that the documentation provided by Google for these methods is incorrect!

The QuizFeedback class has incorrect methods listed in the code blocks which is why you are receiving errors in your code.

The method FormApp.createFeedback() returns a QuizFeedbackBuilder object - an object which does not have a setDisplayText() method. This is the cause of the first error: TypeError: Function setDisplayText not found in object FreebirdFeedbackBuilder.

The second error, Method setFeedbackForIncorrect (FormApp.QuizFeedbackBuilder) not found., has a similar origin - the TextItem Class does not have a method called setFeedbackForIncorrect().

This is however a method of the MultipleChoiceItem class, a specific type of question item. Sadly, this is only a method of MultipleChoiceItem and so you can not set an incorrect message for TextItem responses.

You can however set general feedback, which shows regardless of whether the question was correct or not. This I have displayed in the code below. QuizFeedbackBuilder objects need to be built before adding them using the .setGeneralFeedback() method, however.

In order to fix this some code needs to be re-written:

Make files are no python scripts. Jupyter expects python scripts. You probably need to use the makefile from the terminal.

Not sure how well make files work on windows you probably need to do this on Linux.

That's just what I assume though I didn't read the documentation.

Shade plugin cannot help here. Quoting it's documentation:

This plugin provides the capability to package the artifact in an uber-jar, including its dependencies and to shade - i.e. rename - the packages of some of the dependencies

This is not what you need. You need to separate classpath with one version of protobuf from classpath with another version. This is a complicated thing, you'd have to play around with classloaders or some modularizarion mechanism like OSGi.

But I'd try first to just explicitly declare newest version of those two protobuf versions, and check if it is backward compatible.

When you create a container from your image, you mount a volume, using the -v option: docker run -v openstreetmap-data:/var/lib/postgresql/10/main SampleMap import

Your persistent data is stored in openstreetmap-data. That file/folder is not in your container (that is created every time), it is mounted from your host's filesystem. That's why it persists

You forgot to add the .set after the .find method in your chain.