Visualizes datasets from NASA Java Mission-planning and Analysis for Remote Sensing (JMARS). Current features include the ability to generate 3D graphs of DTM (LAMO) parameters, heatmaps based on the regolith temperature, thermal imaging representations of the surfaces, shortest paths, and top views of terrain elevation. The program contains error correction functions for missing data points.
Developed by: Kevin Mora.
pip install numpy
(if the command above does not work, run: py -3 -m pip install numpy)
pip install matplotlib
(if the command above does not work, run: py -3 -m pip install matplotlib)
>>> pip install --upgrade matplotlib
>>> import mpl_toolkits
pip install -U scipy
(py -3 -m pip install -U scipy)
pip install tqdm
(py -3 -m pip install tqdm)
NOTE: Last two are not required, but recommended in order to use
additional features from "spicy" (such as cdist, dijkstra and
csr_matrix). Finally, the only usage of "tqdm" is trange.
In JMARS, navigate to the region of your interest. Now, go to Add a Polygon
and click once around the area you would like to export and visualize. The end result should be a red polygon surrounding the area you want to visualize.
After that, do the following:
Right click on the surface
-->
Go to: Polygon Functions
-->
Click on: Export Pixels Data for Polygon
A little window called Pixel Data CSV Export
will appear. Now do the following:
Uncheck :: Pixel ID
Check :: Latitude
Check :: Longitude
Click now on "Add Source" and select the desired dataset for the body you are working with.
Leave Sampling PPD with the default value.
Click on Select File
to choose where to save the file and give it a name. Press the Save
button to complete this operation, and delete the first line of the file. Congratulations, you now have the dataset for the selected area.
- Install all the libraries and dependencies.
- Add your dataset to the
datasets
folder.- i.e.,:
filename = "datasets/name_of_dataset.csv"
- i.e.,:
- Run the desired class using
python class_name.py
.- e.g.,:
python topographic-surface.py
gives us the result below.
- e.g.,:
Ahuna Mons in Ceres represented by JMARS 3D Visualizer