diff --git a/postprocessor/routines/boxplot.py b/postprocessor/routines/boxplot.py
index 3a3523b55448e8868bb34def90d182f9f34347e7..ea5e9ba17bbb66bd2c2f403a3a5392a4c8813d6b 100644
--- a/postprocessor/routines/boxplot.py
+++ b/postprocessor/routines/boxplot.py
@@ -14,13 +14,13 @@ class _BoxplotPlotter(BasePlotter):
self,
trace_df,
trace_name,
- sampling_period,
+ unit_scaling,
box_color,
xtick_step,
xlabel,
plot_title,
):
- super().__init__(trace_name, sampling_period, xlabel, plot_title)
+ super().__init__(trace_name, unit_scaling, xlabel, plot_title)
# Define attributes from arguments
self.trace_df = trace_df
self.box_color = box_color
@@ -31,9 +31,11 @@ class _BoxplotPlotter(BasePlotter):
# Define horizontal axis ticks and labels
# hacky! -- redefine column names
- trace_df.columns = trace_df.columns * self.sampling_period
+ trace_df.columns = trace_df.columns * self.unit_scaling
self.fmt = ticker.FuncFormatter(
- lambda x, pos: "{0:g}".format(x / (self.xtick_step / self.sampling_period))
+ lambda x, pos: "{0:g}".format(
+ x / (self.xtick_step / self.unit_scaling)
+ )
)
def plot(self, ax):
@@ -47,24 +49,59 @@ class _BoxplotPlotter(BasePlotter):
ax=ax,
)
ax.xaxis.set_major_locator(
- ticker.MultipleLocator(self.xtick_step / self.sampling_period)
+ ticker.MultipleLocator(self.xtick_step / self.unit_scaling)
)
def boxplot(
trace_df,
trace_name,
- sampling_period=5,
+ unit_scaling=1,
box_color="b",
xtick_step=60,
xlabel="Time (min)",
plot_title="",
ax=None,
):
+ """Draw series of boxplots from an array of time series of traces
+
+ Draw series of boxplots from an array of time series of traces, showing the
+ distribution of values at each time point over time.
+
+ Parameters
+ ----------
+ trace_df : pandas.DataFrame
+ Time series of traces (rows = cells, columns = time points).
+ trace_name : string
+ Name of trace being plotted, e.g. 'flavin'.
+ unit_scaling : int or float
+ Unit scaling factor, e.g. 1/60 to convert minutes to hours.
+ box_color : string
+ matplolib colour string, specifies colour of boxes in boxplot
+ xtick_step : int or float
+ Interval length, in unit time, to draw x axis ticks.
+ xlabel : string
+ x axis label.
+ plot_title : string
+ Plot title.
+ ax : matplotlib Axes
+ Axes in which to draw the plot, otherwise use the currently active Axes.
+
+ Returns
+ -------
+ ax : matplotlib Axes
+ Axes object with the heatmap.
+
+ Examples
+ --------
+ FIXME: Add docs.
+
+ """
+
plotter = _BoxplotPlotter(
trace_df,
trace_name,
- sampling_period,
+ unit_scaling,
box_color,
xtick_step,
xlabel,
diff --git a/postprocessor/routines/heatmap.py b/postprocessor/routines/heatmap.py
index bacf514998255bb46cba0e8bbeed90aca00e04aa..d2a8927c607150638ca2cfc182bce0a82feeb449 100644
--- a/postprocessor/routines/heatmap.py
+++ b/postprocessor/routines/heatmap.py
@@ -2,7 +2,7 @@
import numpy as np
import matplotlib.pyplot as plt
-from matplotlib import cm, colors
+from matplotlib import cm, colors, ticker
from postprocessor.core.processes.standardscaler import standardscaler
from postprocessor.routines.plottingabc import BasePlotter
@@ -17,14 +17,14 @@ class _HeatmapPlotter(BasePlotter):
trace_name,
births_df,
cmap,
- sampling_period,
+ unit_scaling,
xtick_step,
scale,
robust,
xlabel,
plot_title,
):
- super().__init__(trace_name, sampling_period, xlabel, plot_title)
+ super().__init__(trace_name, unit_scaling, xlabel, plot_title)
# Define attributes from arguments
self.trace_df = trace_df
self.births_df = births_df
@@ -59,12 +59,17 @@ class _HeatmapPlotter(BasePlotter):
self.vmin = None
self.vmax = None
+ # Define horizontal axis ticks and labels
+ # hacky! -- redefine column names
+ trace_df.columns = trace_df.columns * self.unit_scaling
+ self.fmt = ticker.FuncFormatter(
+ lambda x, pos: "{0:g}".format(x * self.unit_scaling)
+ )
+
def plot(self, ax, cax):
"""Draw the heatmap on the provided Axes."""
super().plot(ax)
- # Horizontal axis labels as multiples of xtick_step
- ax.xaxis.set_major_locator(plt.MultipleLocator(self.xtick_step))
-
+ ax.xaxis.set_major_formatter(self.fmt)
# Draw trace heatmap
trace_heatmap = ax.imshow(
self.trace_scaled,
@@ -73,7 +78,11 @@ class _HeatmapPlotter(BasePlotter):
vmin=self.vmin,
vmax=self.vmax,
)
-
+ # Horizontal axis labels as multiples of xtick_step, taking
+ # into account unit scaling
+ ax.xaxis.set_major_locator(
+ ticker.MultipleLocator(self.xtick_step / self.unit_scaling)
+ )
# Overlay births, if present
if self.births_df is not None:
# Must be masked array for transparency
@@ -86,7 +95,6 @@ class _HeatmapPlotter(BasePlotter):
births_heatmap_mask,
interpolation="none",
)
-
# Draw colour bar
colorbar = ax.figure.colorbar(
mappable=trace_heatmap, cax=cax, ax=ax, label=self.colorbarlabel
@@ -98,7 +106,7 @@ def heatmap(
trace_name,
births_df=None,
cmap=cm.RdBu,
- sampling_period=5,
+ unit_scaling=1,
xtick_step=60,
scale=True,
robust=True,
@@ -120,8 +128,8 @@ def heatmap(
0 or 1.
cmap : matplotlib ColorMap
Colour map for heatmap.
- sampling_period : int or float
- Sampling period, in unit time.
+ unit_scaling : int or float
+ Unit scaling factor, e.g. 1/60 to convert minutes to hours.
xtick_step : int or float
Interval length, in unit time, to draw x axis ticks.
scale : bool
@@ -154,7 +162,7 @@ def heatmap(
trace_name,
births_df,
cmap,
- sampling_period,
+ unit_scaling,
xtick_step,
scale,
robust,
diff --git a/postprocessor/routines/histogram.py b/postprocessor/routines/histogram.py
index 4533d66c1bdcf4ba700dbd5d052abf10590703f2..6d3957463c446e1ebe37a4ff2df50d5ff99688d3 100644
--- a/postprocessor/routines/histogram.py
+++ b/postprocessor/routines/histogram.py
@@ -12,7 +12,6 @@ class _HistogramPlotter:
values,
label,
color,
- sampling_period,
binsize,
lognormal,
lognormal_base,
@@ -24,7 +23,6 @@ class _HistogramPlotter:
self.values = values
self.label = label
self.color = color
- self.sampling_period = sampling_period
self.binsize = binsize
self.lognormal = lognormal
self.lognormal_base = lognormal_base
@@ -39,7 +37,9 @@ class _HistogramPlotter:
if self.lognormal:
self.bins = np.logspace(
0,
- np.ceil(np.log(np.nanmax(values)) / np.log(self.lognormal_base)),
+ np.ceil(
+ np.log(np.nanmax(values)) / np.log(self.lognormal_base)
+ ),
base=self.lognormal_base,
) # number of bins will be 50 by default, as it's the default in np.logspace
else:
@@ -77,7 +77,6 @@ def histogram(
values,
label,
color="b",
- sampling_period=5,
binsize=5,
lognormal=False,
lognormal_base=10,
@@ -96,8 +95,6 @@ def histogram(
Name of value being plotting, e.g. cell division cycle length.
color : string
Colour of bars.
- sampling_period : float
- Sampling period, in unit time.
binsize : float
Bin size.
lognormal : bool
@@ -127,7 +124,6 @@ def histogram(
values,
label,
color,
- sampling_period,
binsize,
lognormal,
lognormal_base,
diff --git a/postprocessor/routines/mean_plot.py b/postprocessor/routines/mean_plot.py
index a3af66d6ac78729f62692f78c4051eb3e1699ee5..e25944830950affdb64019e554e14322999e4130 100644
--- a/postprocessor/routines/mean_plot.py
+++ b/postprocessor/routines/mean_plot.py
@@ -13,7 +13,7 @@ class _MeanPlotter(BasePlotter):
self,
trace_df,
trace_name,
- sampling_period,
+ unit_scaling,
label,
mean_color,
error_color,
@@ -22,7 +22,7 @@ class _MeanPlotter(BasePlotter):
ylabel,
plot_title,
):
- super().__init__(trace_name, sampling_period, xlabel, plot_title)
+ super().__init__(trace_name, unit_scaling, xlabel, plot_title)
# Define attributes from arguments
self.trace_df = trace_df
self.label = label
@@ -35,7 +35,7 @@ class _MeanPlotter(BasePlotter):
self.ylabel = ylabel
# Mean and standard error
- self.trace_time = np.array(self.trace_df.columns) * self.sampling_period
+ self.trace_time = np.array(self.trace_df.columns) * self.unit_scaling
self.mean_ts = self.trace_df.mean(axis=0)
self.stderr = self.trace_df.std(axis=0) / np.sqrt(len(self.trace_df))
@@ -64,7 +64,7 @@ class _MeanPlotter(BasePlotter):
def mean_plot(
trace_df,
trace_name="flavin",
- sampling_period=5,
+ unit_scaling=1,
label="wild type",
mean_color="b",
error_color="lightblue",
@@ -82,8 +82,8 @@ def mean_plot(
Time series of traces (rows = cells, columns = time points).
trace_name : string
Name of trace being plotted, e.g. 'flavin'.
- sampling_period : int or float
- Sampling period, in unit time.
+ unit_scaling : int or float
+ Unit scaling factor, e.g. 1/60 to convert minutes to hours.
label : string
Name of group being plotted, e.g. a strain name.
mean_color : string
@@ -109,7 +109,7 @@ def mean_plot(
plotter = _MeanPlotter(
trace_df,
trace_name,
- sampling_period,
+ unit_scaling,
label,
mean_color,
error_color,
diff --git a/postprocessor/routines/median_plot.py b/postprocessor/routines/median_plot.py
index 4b3205c576417f198d62508764dbb433af4919f6..573263b375c92528910a3f30f0bc0ec2f15a86ce 100644
--- a/postprocessor/routines/median_plot.py
+++ b/postprocessor/routines/median_plot.py
@@ -13,7 +13,7 @@ class _MedianPlotter(BasePlotter):
self,
trace_df,
trace_name,
- sampling_period,
+ unit_scaling,
label,
median_color,
error_color,
@@ -22,7 +22,7 @@ class _MedianPlotter(BasePlotter):
ylabel,
plot_title,
):
- super().__init__(trace_name, sampling_period, xlabel, plot_title)
+ super().__init__(trace_name, unit_scaling, xlabel, plot_title)
# Define attributes from arguments
self.trace_df = trace_df
self.label = label
@@ -35,7 +35,7 @@ class _MedianPlotter(BasePlotter):
self.ylabel = ylabel
# Median and interquartile range
- self.trace_time = np.array(self.trace_df.columns) * self.sampling_period
+ self.trace_time = np.array(self.trace_df.columns) * self.unit_scaling
self.median_ts = self.trace_df.median(axis=0)
self.quartile1_ts = self.trace_df.quantile(0.25)
self.quartile3_ts = self.trace_df.quantile(0.75)
@@ -65,7 +65,7 @@ class _MedianPlotter(BasePlotter):
def median_plot(
trace_df,
trace_name="flavin",
- sampling_period=5,
+ unit_scaling=1,
label="wild type",
median_color="b",
error_color="lightblue",
@@ -83,8 +83,8 @@ def median_plot(
Time series of traces (rows = cells, columns = time points).
trace_name : string
Name of trace being plotted, e.g. 'flavin'.
- sampling_period : int or float
- Sampling period, in unit time.
+ unit_scaling : int or float
+ Unit scaling factor, e.g. 1/60 to convert minutes to hours.
label : string
Name of group being plotted, e.g. a strain name.
median_color : string
@@ -110,7 +110,7 @@ def median_plot(
plotter = _MedianPlotter(
trace_df,
trace_name,
- sampling_period,
+ unit_scaling,
label,
median_color,
error_color,
diff --git a/postprocessor/routines/plottingabc.py b/postprocessor/routines/plottingabc.py
index 1990df9f8854b7f4880b473b610218ac45cbe046..97b89aa7e95e01e5b937003233f8ba3d37da7f52 100644
--- a/postprocessor/routines/plottingabc.py
+++ b/postprocessor/routines/plottingabc.py
@@ -6,10 +6,10 @@ from abc import ABC
class BasePlotter(ABC):
"""Base class for plotting handler classes"""
- def __init__(self, trace_name, sampling_period, xlabel, plot_title):
+ def __init__(self, trace_name, unit_scaling, xlabel, plot_title):
"""Common attributes"""
self.trace_name = trace_name
- self.sampling_period = sampling_period
+ self.unit_scaling = unit_scaling
self.xlabel = xlabel
self.ylabel = None
diff --git a/postprocessor/routines/single_birth_plot.py b/postprocessor/routines/single_birth_plot.py
index 6d1a405cf3223080db98d670d295962f56ec9ee3..671cfec04d87b5b33b46731de1c86b10b7e96a45 100644
--- a/postprocessor/routines/single_birth_plot.py
+++ b/postprocessor/routines/single_birth_plot.py
@@ -14,7 +14,7 @@ class _SingleBirthPlotter(_SinglePlotter):
trace_values,
trace_name,
birth_mask,
- sampling_period,
+ unit_scaling,
trace_color,
birth_color,
trace_linestyle,
@@ -27,7 +27,7 @@ class _SingleBirthPlotter(_SinglePlotter):
trace_timepoints,
trace_values,
trace_name,
- sampling_period,
+ unit_scaling,
trace_color,
trace_linestyle,
xlabel,
@@ -40,7 +40,7 @@ class _SingleBirthPlotter(_SinglePlotter):
def plot(self, ax):
"""Draw the line plots on the provided Axes."""
- trace_time = self.trace_timepoints * self.sampling_period
+ trace_time = self.trace_timepoints * self.unit_scaling
super().plot(ax)
birth_mask_bool = self.birth_mask.astype(bool)
for occurence, birth_time in enumerate(trace_time[birth_mask_bool]):
@@ -62,7 +62,7 @@ def single_birth_plot(
trace_values,
trace_name="flavin",
birth_mask=None,
- sampling_period=5,
+ unit_scaling=1,
trace_color="b",
birth_color="k",
trace_linestyle="-",
@@ -84,8 +84,8 @@ def single_birth_plot(
birth_mask : array_like
Mask to indicate where births are. Expect values of '0' and '1' or
'False' and 'True' in the elements.
- sampling_period : int or float
- Sampling period, in unit time.
+ unit_scaling : int or float
+ Unit scaling factor, e.g. 1/60 to convert minutes to hours.
trace_color : string
matplotlib colour string for the trace
birth_color : string
@@ -116,7 +116,7 @@ def single_birth_plot(
trace_values,
trace_name,
birth_mask,
- sampling_period,
+ unit_scaling,
trace_color,
birth_color,
trace_linestyle,
diff --git a/postprocessor/routines/single_plot.py b/postprocessor/routines/single_plot.py
index 11ee940609e4b6c524ad2f31da494137e628a238..68e7d76019c2bf2f3dd0dc3a6820a96597514494 100644
--- a/postprocessor/routines/single_plot.py
+++ b/postprocessor/routines/single_plot.py
@@ -13,13 +13,13 @@ class _SinglePlotter(BasePlotter):
trace_timepoints,
trace_values,
trace_name,
- sampling_period,
+ unit_scaling,
trace_color,
trace_linestyle,
xlabel,
plot_title,
):
- super().__init__(trace_name, sampling_period, xlabel, plot_title)
+ super().__init__(trace_name, unit_scaling, xlabel, plot_title)
# Define attributes from arguments
self.trace_timepoints = trace_timepoints
self.trace_values = trace_values
@@ -33,7 +33,7 @@ class _SinglePlotter(BasePlotter):
"""Draw the line plot on the provided Axes."""
super().plot(ax)
ax.plot(
- self.trace_timepoints * self.sampling_period,
+ self.trace_timepoints * self.unit_scaling,
self.trace_values,
color=self.trace_color,
linestyle=self.trace_linestyle,
@@ -45,7 +45,7 @@ def single_plot(
trace_timepoints,
trace_values,
trace_name="flavin",
- sampling_period=5,
+ unit_scaling=1,
trace_color="b",
trace_linestyle="-",
xlabel="Time (min)",
@@ -62,8 +62,8 @@ def single_plot(
Trace to plot.
trace_name : string
Name of trace being plotted, e.g. 'flavin'.
- sampling_period : int or float
- Sampling period, in unit time.
+ unit_scaling : int or float
+ Unit scaling factor, e.g. 1/60 to convert minutes to hours.
trace_color : string
matplotlib colour string, specifies colour of line plot.
trace_linestyle : string
@@ -89,7 +89,7 @@ def single_plot(
trace_timepoints,
trace_values,
trace_name,
- sampling_period,
+ unit_scaling,
trace_color,
trace_linestyle,
xlabel,