Comments (8)
jankatins
commented on August 17, 2024
Could you add the code which produces the error (and the wrong plot)? There is non visible in the bugreport.
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eduardflorinescu
commented on August 17, 2024
Updated issue with the requested info.
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zachcp
commented on August 17, 2024
Looks like the column is being treated as a text column and not numerical so it is getting a discrete scale instead of a continuous one. i would check your pandas dataframe and see if it is using the first line as a column or if it is making the entire column into a string.
something like:
spowd = pd.read_csv(INPUT_FILE, header=TRUE)
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zachcp
commented on August 17, 2024
This is a mishandling of continuous color scales. The error is reproducible here:
from ggplot import *
ggplot(diamonds, aes('carat', 'price', color='price')) + \
geom_point(alpha=1/20.) + \
ylim(0, 20000)
#line 334 ggplot.oy
if 'color' in mapping._get_numeric_data().columns:
mapping['cmap'] = self.colormap
I don't see mapping.cmap get used again. I think the colormap needs to be put back into the mapping.color value to be picked up by ggplot.__repr__. This would require using the values held in 'mapping.color' to use the 'cmap'. I'm not sure how to do this. Is anyone familiar with matplotlib colormaps?
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zachcp
commented on August 17, 2024
walking through the code, I think the color mapping is fine. The color differences in python vs. R are due to an inverted scale and a legend that is displayed as quantile instead of as a continuous variable. I don't think either of those have been implemented yet in this version of ggplot. Your specific error I couldn't track down but it believe it is due to some cross talk between aes groupings. Coloring by voltage, by itse,f for example , works jsut fine. It is only when bothcolor and shape are used that there is an issue:
## Single Values: These all wor
ggplot(aes(x='TIME', y='Watts', color="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
#Shape and Color where Color is category: These work
ggplot(aes(x='TIME', y='Watts', shape="category", color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="Volts", color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
## Shape and Color where color is Volt. These fail
ggplot(aes(x='TIME', y='Watts', shape="category", color="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="Volts", color="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
The plot_layer function is only being passed a single color value for the last two. Why? I'm not sure why the color values are correctly assigned in most cases but not the last two.
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eduardflorinescu
commented on August 17, 2024
The below case where shape="Volts" doesn't work for me:
ggplot(aes(x='TIME', y='Watts', shape="Volts", color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()gives:
Traceback (most recent call last):
File "test_aestheticmappings.py", line 39, in <module>
ylab("Watts")
File "C:\PYTHON27\lib\site-packages\ggplot\ggplot.py", line 206, in __repr__
for layer in self._get_layers(self.data):
File "C:\PYTHON27\lib\site-packages\ggplot\ggplot.py", line 318, in _get_layers
mapping['marker'] = mapping['shape'].replace(shape_mapping)
File "C:\PYTHON27\lib\site-packages\pandas\core\series.py", line 2741, in replace
_rep_dict(result, to_replace)
File "C:\PYTHON27\lib\site-packages\pandas\core\series.py", line 2735, in _rep_dict
_rep_one(rs, sset, d)
File "C:\PYTHON27\lib\site-packages\pandas\core\series.py", line 2715, in _rep_one
com._maybe_upcast_putmask(s.values,mask,v,change=change)
File "C:\PYTHON27\lib\site-packages\pandas\core\common.py", line 813, in _maybe_upcast_putmask
return changeit()
File "C:\PYTHON27\lib\site-packages\pandas\core\common.py", line 767, in changeit
om = other[mask]
TypeError: only integer arrays with one element can be converted to an index
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naught101
commented on August 17, 2024
Here's the same graph as above, with a more recent version of ggplot:
Main problems remaining:
- Axis ticks go right to the ends of the axis (uneccessary rounding, also makes it more likely for x/y axis ticks to clash).
- There isn't a continuous colourbar
- The default colourscheme is inverted, and the contrast is too high
Everything else is looking pretty good though :)
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eduardflorinescu
commented on August 17, 2024
@naught101 Thanks for updating, I think the spectrum color-bar is the greatest visual inconsistency.
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