Hi Roberta,
Thanks for your report and your great work !
Here are a few remarks:
- You have a -t flag with description "Do not delete temporary files".
Is this only for debugging purposes (and which temporary files are
created), or does this have any real use for the user ? If the
former, this should probably not be part of the module UI, if the
latter, it should be explained in the man page.
- I have several comments concerning your input_file parameter
- The syntax of this file has to be explained in the man page,
including the precise variable names (blue, not Blue, not
BLUE, etc)
- The code for reading this file can probably be simplified
quite easily by using something like this:
for line in file(input_file):
a = line.split('=')
if len(a) <> 2 or a[0] not in ['blue', 'red', etc ]:
gscript.fatal("Syntax error in the txt file.")
a[1] = a[1].strip()
bands[a[0]] = a[1]
- Again a (minor) remark on readability of the code. When you use named
variables in format(), I would suggest that you use the actual names.
i.e. instead of
gscript.mapcalc('{r} = 1.0 * ({a})/{c}'.format(
r=("{}_{}".format(b, d)),
a=b, c=scale_fac),
overwrite=True)
why not use this:
gscript.mapcalc('{r} = 1.0 * ({b})/{scale_fac}'.format(
r=("{}_{}".format(b, d)),
b=b, scale_fac=scale_fac),
overwrite=True)
?
I think it makes the formula more easily readable.
- Some remarks on your handling of temporary maps:
- You use
processid = "{:.2f}".format(time.time())
processid = processid.replace(".", "_")
why not simply:
processid = os.getpid() ?
- Instead of having to check for the type of every single map
in the cleanup function, you could include the type in the
info, i.e. something like this:
r = 'raster'
v = 'vector'
tmp["cloud_v"] = ["cloud_v_" + processid, v]
(I personally use "cloud_v_%i" % processid; not sure
what is preferable)
which then allows you to do something like this in cleanup():
for temp_map, maptype in tmp:
if gscript.find_file(temp_map, element=maptype)['name']:
gscript.run_command('g.remove',
flags='f',
type=maptype,
name=temp_map,
quiet=True)
- In its final version your man page should contain an example,
ideally a complete example starting with i.sentinel.download and
going all the way to i.sentinal.mask in order to show the use of the
module within a reproducible workflow, best using a North Carolina
example to fit with the demo dataset.
Moritz
Le Sun, 10 Jun 2018 10:58:37 +0200,
Roberta Fagandini <[email protected]> a écrit :
> Hi all!
> I'm Roberta Fagandini and I'm working on my GSoC project, a GRASS GIS
> module for Sentinel-2 cloud and shadow detection.
> This is my report for the fourth week of coding.
>
> *1) What did I complete this week?*
>
> - Implemented some changes from dev feedback (e.g. added a new
> flag to manage the two procedure separately and added the text file
> option to specify input bands)
> - Tested the modified python script and fixed bugs (e.g. solved a
> bug for -s flag)
> - Created a real complete GRASS GIS module that can be installed
> with g.extension
> - Finished implementing the GUI
> - Tested the GUI and fixed bugs
> - Cleaned up the code from the style point of view in order to
> make it more readable (followed PEP8 style guide and GRASS Python
> Scripting Library rules, converted python lists into dictionaries,
> added comments, messages and warnings, etc.)
> - Started writing the manual page
> - Solved a problem with g.extension thanks to dev community
> suggestions
> - Discussed future improvements with the dev community
> - Frequently added the new version of the code to my GitHub
> repository [0]
> - Shared progress with the community
>
> *2) What am I going to achieve for next week?*
>
> - Implement any change from discussions and feedback
> - Test and fix bugs
> - Finish writing the manual page
> - Check the code with mentors
> - Prepare deliverable for the evaluation
>
> *3) Is there any blocking issue?*
> No at the moment.
>
> Here the links to my wiki page [1] and GitHub repository [0]
>
> Kind regards,
> Roberta
>
> [0] https://github.com/RobiFag/GRASS_clouds_and_shadows
> [1]
> https://trac.osgeo.org/grass/wiki/GSoC/2018/CloudsAndShadowsDetection
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