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fixed geoseries.dashboard gridspec and docstring #440

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Jun 12, 2023
Merged

fixed geoseries.dashboard gridspec and docstring #440

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91 changes: 58 additions & 33 deletions pyleoclim/core/geoseries.py
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Original file line number Diff line number Diff line change
Expand Up @@ -305,13 +305,13 @@ def map(self, projection='Orthographic', proj_default=True,

import pyleoclim as pyleo
ts = pyleo.utils.datasets.load_dataset('EDC-dD')
fig, ax = ts.map(lgd_kwargs={'bbox_to_anchor':(1, 1)}) # by default, the legend conflicts with the map, but it's easy to push it outside with this keyword argument'
fig, ax = ts.map() # by default, the legend conflicts with the map, but it's easy to push it outside with this keyword argument'

'''
if markersize != None:
scatter_kwargs['markersize'] = markersize

fig, ax = mapping.scatter_map(self, hue=hue, size=size, marker=marker, projection=projection,
fig, ax_d = mapping.scatter_map(self, hue=hue, size=size, marker=marker, projection=projection,
proj_default=proj_default,
background=background, borders=borders, rivers=rivers, lakes=lakes,
ocean=ocean,
Expand All @@ -320,7 +320,7 @@ def map(self, projection='Orthographic', proj_default=True,
lgd_kwargs=lgd_kwargs, legend=legend, colorbar=colorbar,
cmap=cmap, edgecolor=edgecolor,
fig=fig, gs_slot=gridspec_slot)
return fig, ax
return fig, ax_d

# scatter_kwargs = {} if scatter_kwargs is None else scatter_kwargs.copy()
# # get the information from the timeseries
Expand Down Expand Up @@ -406,8 +406,10 @@ def map(self, projection='Orthographic', proj_default=True,
#
# return res

def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spectral_kwargs=None,
spectralsignif_kwargs=None, spectralfig_kwargs=None, map_kwargs=None,gridspec_kwargs=None,
def dashboard(self, figsize=[11, 8], gs=None, plt_kwargs=None, histplt_kwargs=None, spectral_kwargs=None,
spectralsignif_kwargs=None, spectralfig_kwargs=None, map_kwargs=None,
hue='archiveType', marker='archiveType', size=None, scatter_kwargs=None,
gridspec_kwargs=None,
savefig_settings=None):
'''

Expand All @@ -417,6 +419,15 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect
figsize : list or tuple, optional
Figure size. The default is [11,8].

gs : matplotlib.gridspec object, optional
Requires at least two rows and 4 columns.
- top row, left: timeseries
- top row, right: histogram
- bottom left: map
- bottom right: PSD
See [matplotlib.gridspec.GridSpec](https://matplotlib.org/stable/tutorials/intermediate/gridspec.html) for details.


plt_kwargs : dict, optional
Optional arguments for the timeseries plot. See Series.plot() or EnsembleSeries.plot_envelope(). The default is None.

Expand All @@ -433,11 +444,31 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect
Optional arguments for the power spectrum figure. See PSD.plot() or MultiplePSD.plot_envelope(). The default is None.

map_kwargs : dict, optional
Optional arguments for the map and point plotted on map.
- scatter_kwargs: dict of values for configuring how data are plotted on a map
- gridspec_kwargs: dict of values for how the map gridspec is configured
Optional arguments for map configuration
- projection: str; Optional value for map projection. Default 'auto'.
- proj_default: bool
- lakes, land, ocean, rivers, borders, coastline, background: bool or dict;
- lgd_kwargs: dict; Optional values for how the map legend is configured
- gridspec_kwargs: dict; Optional values for adjusting the arrangement of the colorbar, map and legend in the map subplot
- legend: bool; Whether to draw a legend on the figure. Default is True
- colorbar: bool; Whether to draw a colorbar on the figure if the data associated with hue are numeric. Default is True
The default is None.

hue : str, optional
Variable associated with color coding for points plotted on map. May correspond to a continuous or categorical variable.
The default is 'archiveType'.

size : str, optional
Variable associated with size. Must correspond to a continuous numeric variable.
The default is None.

marker : string, optional
Grouping variable that will produce points with different markers. Can have a numeric dtype but will always be treated as categorical.
The default is 'archiveType'.

scatter_kwargs : dict, optional
Optional arguments configuring how data are plotted on a map. See description of scatter_kwargs in pyleoclim.utils.mapping.scatter_map

gridspec_kwargs : dict, optional
Optional dictionary for configuring dashboard layout using gridspec
For information about Gridspec configuration, refer to `Matplotlib documentation <https://matplotlib.org/3.5.0/api/_as_gen/matplotlib.gridspec.GridSpec.html#matplotlib.gridspec.GridSpec>_. The default is None.
Expand Down Expand Up @@ -481,7 +512,7 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect

pyleoclim.core.geoseries.GeoSeries.map : map location of dataset

pyleoclim.utils.mapping.map : Underlying mapping function for Pyleoclim
pyleoclim.utils.mapping.scatter_map : Underlying mapping function for Pyleoclim

Examples
--------
Expand All @@ -498,16 +529,12 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect
# start plotting
fig = plt.figure(figsize=figsize)

gridspec_kwargs = {} if type(gridspec_kwargs) != dict else gridspec_kwargs
gridspec_defaults = dict(wspace=0, width_ratios=[1,1,1,.25,1,1,1],
height_ratios=[1,.1,1], left=0, right=1.1)

gridspec_defaults.update(gridspec_kwargs)
gs = gridspec.GridSpec(len(gridspec_defaults['height_ratios']), len(gridspec_defaults['width_ratios']), **gridspec_defaults)

# gs = gridspec.GridSpec(2, 6, wspace=0)
# gs.update(left=0, right=1.1)

if gs == None:
gridspec_kwargs = {} if type(gridspec_kwargs) != dict else gridspec_kwargs
gridspec_defaults = dict(wspace=0, width_ratios=[3, .25, 2, 1],
height_ratios=[1, .1, 1], left=0, right=1.1)
gridspec_defaults.update(gridspec_kwargs)
gs = gridspec.GridSpec(len(gridspec_defaults['height_ratios']), len(gridspec_defaults['width_ratios']), **gridspec_defaults)

ax = {}
# Plot the timeseries
Expand Down Expand Up @@ -557,14 +584,9 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect
coastline = map_kwargs.pop('coastline', True)
background = map_kwargs.pop('background', True)

gridspec_kwargs = map_kwargs.pop('gridspec_kwargs', {})
scatter_kwargs = map_kwargs.pop('scatter_kwargs', {})
map_gridspec_kwargs = map_kwargs.pop('gridspec_kwargs', {})
lgd_kwargs = map_kwargs.pop('lgd_kwargs', {})

marker = scatter_kwargs.pop('marker', 'archiveType')
hue = scatter_kwargs.pop('hue', 'archiveType')
size = scatter_kwargs.pop('size', None)

if 'edgecolor' in map_kwargs.keys():
scatter_kwargs.update({'edgecolor': map_kwargs['edgecolor']})

Expand All @@ -573,13 +595,13 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect
colorbar = map_kwargs.pop('colorbar', False)

if legend == False:
gridspec_kwargs['width_ratios'] = [.5,16, 1]
map_gridspec_kwargs['width_ratios'] = [.5,16, 1]

_, ax['map'] =mapping.scatter_map(self, hue=hue, size=size, marker=marker, projection=projection, proj_default=proj_default,
background=background, borders=borders, coastline=coastline, rivers=rivers, lakes=lakes, ocean=ocean, land=land,
figsize=None, scatter_kwargs=scatter_kwargs,gridspec_kwargs = gridspec_kwargs,
figsize=None, scatter_kwargs=scatter_kwargs,gridspec_kwargs = map_gridspec_kwargs,
lgd_kwargs=lgd_kwargs, legend=legend, cmap=cmap, colorbar=colorbar,
fig=fig, gs_slot=gs[-1, 0:-4])
fig=fig, gs_slot=gs[-1, 0:1])

# make the map - brute force since projection is not being returned properly
# lat = [self.lat]
Expand Down Expand Up @@ -675,7 +697,7 @@ def dashboard(self, figsize=[11, 8], plt_kwargs=None, histplt_kwargs=None, spect
else:
spectral_kwargs.update({'freq_method': 'lomb_scargle'})

ax['spec'] = fig.add_subplot(gs[-1, -3:])
ax['spec'] = fig.add_subplot(gs[-1, -2:])
spectralfig_kwargs = {} if spectralfig_kwargs is None else spectralfig_kwargs.copy()
spectralfig_kwargs.update({'ax': ax['spec']})

Expand Down Expand Up @@ -733,10 +755,13 @@ def resample(self, rule, keep_log = False, **kwargs):

Examples
--------
>>> ts = pyleo.utils.load_dataset('EDC-dD').convert_time_unit('ky BP')
>>> ts5k = ts.resample('1ka').mean()
>>> fig, ax = ts.plot()
>>> ts5k.plot(ax=ax,color='C1')

.. jupyter-execute::

ts = pyleo.utils.load_dataset('EDC-dD').convert_time_unit('ky BP')
ts5k = ts.resample('1ka').mean()
fig, ax = ts.plot()
ts5k.plot(ax=ax,color='C1')

"""
search = re.search(r'(\d*)([a-zA-Z]+)', rule)
Expand Down