def test_stats_devices(self):
from pyadlml.dataset.stats.devices import device_tcorr, devices_trigger_count, \
device_triggers_one_day, trigger_time_diff, devices_on_off_stats, duration_correlation
df = self.data.df_devices
lst = self.data.lst_devices
# tcorr = device_tcorr(df)
tcorr = device_tcorr(df, lst)
assert tcorr.shape[0] == len(lst) and tcorr.shape[1] == len(lst)
trigg_c = devices_trigger_count(df)
assert len(trigg_c) == self.num_rec_devs
trigg_c = devices_trigger_count(df, lst)
assert len(trigg_c) == len(lst)
trigg_od = device_triggers_one_day(df)
assert len(trigg_od.columns) == self.num_rec_devs
trigg_od = device_triggers_one_day(df, lst)
assert len(trigg_od.columns) == len(lst)
trigg_td = trigger_time_diff(df)
assert len(trigg_td) == len(df) - 1
onoff = devices_on_off_stats(df)
assert len(onoff) == self.num_rec_binary_devs
onoff = devices_on_off_stats(df, lst)
assert len(onoff) == len(lst)
dc = duration_correlation(df)
assert len(dc) == self.num_rec_binary_devs
dc = duration_correlation(df, lst)
assert len(dc) == len(lst)
def heatmap_trigger_time(df_dev, t_window='5s', figsize=(8, 8), z_scale=None):
color = 'trigger count'
cbarlabel = 'counts'
# get the list of cross tabulations per t_window
df = device_tcorr(df_dev, t_window)[0]
vals = df.astype(int).values.T
devs = list(df.index)
fig, ax = plt.subplots(figsize=figsize)
log = True if z_scale == 'log' else False
valfmt = "{x:.0f}"
im, cbar = heatmap_square(
vals,
devs,
devs,
ax=ax, #cmap='viridis',
cbarlabel=cbarlabel,
log=log) #, cbar_kw=cbar_kw)
texts = annotate_heatmap(im,
textcolors=("white", "black"),
log=log,
valfmt=valfmt)
ax.set_title("Triggercount with sliding window of " + t_window)
fig.tight_layout()
plt.show()
def heatmap_trigger_time(df_devs=None,
lst_devs=None,
df_tcorr=None,
t_window='5s',
figsize=None,
z_scale="linear",
cmap=None,
numbers=None,
file_path=None):
"""
Plot todo
Parameters
----------
df_devs : pd.DataFrame, optional
recorded devices from a dataset. Fore more information refer to the
:ref:`user guide<device_dataframe>`.
lst_devs : lst of str, optional
A list of devices that are included in the statistic. The list can be a
subset of the recorded activities or contain activities that are not recorded.
df_tcorr : pd.DataFrame
A precomputed correlation table. If the *df_tcorr* parameter is given, parameters
*df_devs* and *lst_devs* are ignored. The transition table can be computed
in :ref:`stats <stats_devs_tcorr>`.
t_window : str of {'[1-12]h', default='1h'
the resolution, time_bins in hours. The number are
figsize : (float, float), default: None
width, height in inches. If not provided, the figsize is inferred by automatically.
z_scale : {"log", "linear"}, default: None
The axis scale type to apply.
numbers : bool, default: True
Whether to display numbers inside the heatmaps fields or not.
cmap : str or Colormap, optional
The Colormap instance or registered colormap name used to map scalar
data to colors. This parameter is ignored for RGB(A) data.
Defaults 'viridis'.
file_path : str, optional
If set, saves the plot under the given file path and return *None* instead
of returning the figure.
Examples
--------
>>> from pyadlml.plots import plot_device_hm_time_trigger
>>> plot_device_hm_time_trigger(data.df_devices, t_res='1h')
.. image:: ../_static/images/plots/dev_hm_trigger_one_day.png
:height: 300px
:width: 500 px
:scale: 100 %
:alt: alternate text
:align: center
Returns
-------
res : fig or None
Either a figure if file_path is not specified or nothing.
"""
assert not (df_devs is None and df_tcorr is None)
title = "Triggercount with sliding window of " + t_window
color = 'trigger count'
cbarlabel = 'counts'
if df_tcorr is None:
df = device_tcorr(df_devs, lst_devs=lst_devs, t_window=t_window)
else:
df = df_tcorr
# get the list of cross tabulations per t_window
vals = df.astype(int).values.T
devs = list(df.index)
num_dev = len(devs)
figsize = (_num_items_2_heatmap_square_figsize_ver2(num_dev)
if figsize is None else figsize)
cmap = (get_sequential_color() if cmap is None else cmap)
fig, ax = plt.subplots(figsize=figsize)
log = True if z_scale == 'log' else False
valfmt = "{x:.0f}"
im, cbar = heatmap_square(vals,
devs,
devs,
ax=ax,
cmap=cmap,
cbarlabel=cbarlabel,
log=log) #, cbar_kw=cbar_kw)
# show numbers for small sizes
if numbers is None:
if num_dev < 20:
texts = annotate_heatmap(im,
textcolors=("white", "black"),
log=log,
valfmt=valfmt)
elif numbers:
texts = annotate_heatmap(im,
textcolors=("white", "black"),
log=log,
valfmt=valfmt)
ax.set_title(title)
fig.tight_layout()
if file_path is not None:
savefig(fig, file_path)
return
else:
return fig