def plot_figure1(experiment,
level='strain',
err_type='stderr',
ONSET=True,
num_mins=15,
tbin_size=5,
ADD_SOURCE=True):
"""breakfast hypothesis
"""
E = experiment
use_days = ['chow', 'HiFat']
all_avgs, all_errs = load_data(E, level, err_type, ONSET, num_mins,
tbin_size)
# directory
text = 'AS_onset' if ONSET else 'AS_offset'
on_text = 'from %s' % text if ONSET else 'to %s' % text
dirname = E.figures_dir_subpar + 'breakfast/fig1/%s/' % text
if not os.path.isdir(dirname): os.makedirs(dirname)
if level == 'strain':
fig_title = 'Probability of feeding and drinking %s, DC vs. LC\n%d strains, avg$\pm$%s' % (
on_text, E.num_strains, err_type)
subtitles = [
'%s: %s' % (x, y) for y in use_days for x in E.strain_names
]
fig = draw_subplot1(E, all_avgs, all_errs, fig_title, subtitles, ONSET,
num_mins)
fname = dirname + '%s_probability_DC_LC_%dstrains_first_%dmins_binsize%ds_%s' % (
text, E.num_strains, num_mins, tbin_size, err_type)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, ypad=-0.04)
def plot_breakfast_cycles(experiment,
level='strain',
err_type='stdev',
ONSET=True,
num_mins=15,
tbin_size=5,
days=None,
ADD_SOURCE=True):
"""breakfast hypothesis
"""
E = experiment
cycles = E.cycles
days_to_use = E.daysToUse if days is None else days
print "days_to_use: %s" % days_to_use
num_items = get_num_items(E, level)
all_avgs = np.zeros(
(len(cycles), num_items, num_mins * 60 / tbin_size, 2)) # F, W
all_errs = np.zeros((len(cycles), num_items, num_mins * 60 / tbin_size, 2))
for c, cycle in enumerate(cycles):
avgs, errs, labels = get_breakfast_data(E,
level,
err_type,
ONSET=ONSET,
cycle=cycle,
num_mins=num_mins,
days=days_to_use)
all_avgs[c], all_errs[c] = avgs, errs
# directory
text = 'AS_onset' if ONSET else 'AS_offset'
dirname = E.figures_dir_subpar + 'breakfast/all_cycles/%s/%s_days/' % (
text, E.use_days)
if not os.path.isdir(dirname): os.makedirs(dirname)
if level == 'strain':
fig_title = 'Probability of feeding and drinking, 24H-DC-LC\n%s_days: %d to %d' %(
E.use_days, E.daysToUse[0], E.daysToUse[-1]) \
+ '\nstrains, avg$\pm$%s' %err_type
subtitles = [x for x in E.strain_names]
fig = draw_subplot(E,
all_avgs,
all_errs,
fig_title,
subtitles,
ONSET,
num_mins,
ADD_SOURCE=ADD_SOURCE)
fname = dirname + 'all_cycles_%s_probability_%dstrains_first_%dmins_binsize%ds_%s' % (
text, E.num_strains, num_mins, tbin_size, err_type)
save_plot(fname, fig)
def plot_breakfast_comparison(experiment,
level='strain',
err_type='stderr',
ONSET=True,
num_mins=15,
tbin_size=5,
days=None,
ADD_SOURCE=True):
""" all groups in one plot
"""
E = experiment
print "%s..\nlevel: %s\nerr_type: %s\nONSET: %s" % (
plot_breakfast.__name__, level, err_type, ONSET)
if ONSET:
print "num_mins: %d" % num_mins
# days to use
days_to_use = E.daysToUse if days is None else days
_, num_md_ok = E.count_mousedays(days=days_to_use)
# load data
avgs, errs, labels = get_breakfast_data(E,
level,
err_type,
ONSET=ONSET,
num_mins=num_mins,
days=days_to_use)
# directory
text = 'AS_onset' if ONSET else 'AS_offset'
dirname = E.figures_dir_subpar + 'breakfast/%s/%s_days/' % (text,
E.use_days)
if not os.path.isdir(dirname): os.makedirs(dirname)
if level == 'strain':
fig_title = 'Probability of feeding and drinking, across 24H\n%s_days: %d to %d' %(
E.use_days, E.daysToUse[0], E.daysToUse[-1]) \
+ '\nstrains, avg$\pm$%s' %err_type
subtitles = ['Feeding', 'Drinking']
fig = draw_subplot_compare(E,
avgs,
errs,
fig_title,
subtitles,
ONSET,
num_mins,
ADD_SOURCE=ADD_SOURCE)
fname = dirname + 'group_comparison_%s_probability_24H_%dstrains_first_%dmins_binsize%ds_%s' % (
text, E.num_strains, num_mins, tbin_size, err_type)
save_plot(fname, fig)
def plot_breakfast(experiment,
cycle='24H',
level='group',
err_type='sd',
ONSET=True,
num_mins=15,
tbin_size=5,
days=None,
plot_type='breakfast',
ADD_SOURCE=True):
"""breakfast hypothesis
"""
E = experiment
# directory
text = 'AS_onset' if ONSET else 'AS_offset'
dirname = E.figures_dir + 'breakfast/%s/' % text
if not os.path.isdir(dirname): os.makedirs(dirname)
print "%s, level: %s, err_type: %s, cycle: %s" % (plot_breakfast.__name__,
level, err_type, cycle)
data_F, _ = E.generate_breakfast_data(cycle,
level,
act='F',
err_type=err_type,
ONSET=ONSET,
days=days)
data_W, labels = E.generate_breakfast_data(cycle,
level,
act='W',
err_type=err_type,
ONSET=ONSET,
days=days)
stop
# data = np.tile(np.zeros_like(data[:, :, np.newaxis]), (1,1,2))
if level == 'group':
# fig_title = 'Probability of feeding and drinking, across %s\n%s_days: %d to %d' %(
# cycle, E.use_days, E.daysToUse[0], E.daysToUse[-1]) \
# + '\nstrains, avg$\pm$%s' %err_type
# subtitles = [x for x in E.strain_names]
fname = dirname + '%s_%s_%dstrains_%s' % (plot_type, text,
E.num_strains, cycle)
fig = draw_subplot(E, data, ONSET, num_mins, fname)
save_plot(fname, fig)
def plot_first_ASs(experiment,
level='strain',
days=None,
num_AS=5,
num_mins=5,
ADD_SOURCE=True):
E = experiment
days_to_use = E.daysToUse if days is None else days
text = 'all ASs' if num_AS is None else str(num_AS)
print "%s\nlevel: %s\ndays: %r\nnum_AS: %s\nnum_min: %d" % (
plot_first_ASs.__name__, level, days, text, num_mins)
text2 = 'all_ASs' if num_AS is None else 'first_%dASs' % num_AS
if level == 'strain':
dirname = E.figures_dir_subpar + 'within_AS/%s_days/' % E.use_days
if not os.path.isdir(dirname): os.makedirs(dirname)
fig, axes = plt.subplots(nrows=len(days_to_use),
ncols=len(E.groups),
figsize=(7, 10),
sharex=True,
sharey=True)
c = 0
for day in days_to_use:
for group in E.groups:
print 'day%d, group:%d, %s' % (day, group.number, group.name)
ax = axes.flatten()[c]
AS_list = group.generate_AS_structure(day, num_AS)
plot_strain_AS_structure(E, level, group, ax, AS_list, day,
num_AS, num_mins)
c += 1
plt.subplots_adjust(bottom=.08, top=.92, hspace=.4)
fig_title = 'Within-AS structure\n%s\nacclimation to transition days: %dto%d' % (
text2, days_to_use[0], days_to_use[-1])
xlabel = 'Time from AS onset [min]'
ylabel = 'AS sorted by duration'
subplot_labels(fig, xlabel, ylabel, fig_title, ADD_SOURCE)
fname = dirname + 'within_AS_structure_strains_%s_%s_first_%dmin.pdf' % (
E.use_days, text2, num_mins)
save_plot(fname, fig)
def draw_group_features(E, data, labels, features, bin_type, err_type, fname,
plot_type='features', ADD_SOURCE=False):
figsize = (16, 4.8)
nrows, ncols = 4, 7
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=True)
other_color = E.fcolors['other'][0]
xs = get_CT_xs(bin_type, SHIFT=E.BIN_SHIFT, tshift=E.binTimeShift)
cnt = 0
for n in xrange(nrows):
for m in xrange(ncols):
ax = axes.flatten()[n*ncols + m]
if n == 0 and m >= 3:
ax.axis('off')
continue
feature = features[cnt]
colors = get_two_group_features_colors(E, feature)
subtitle = '%s %s' %(feature, E.plot_settings_dict[feature]['unit'])
for g in xrange(E.num_strains):
if bin_type.endswith('bins'):
tkw = {'fmt':'o-', 'ms':2}#, 'elinewidth':.5, 'capsize':1}
mec = '.3' if g == 1 else colors[g]
ax.errorbar(xs, data[g, cnt, :, 0], yerr=data[g, cnt, :, 1],
color=colors[g], mec=mec, **tkw)
elif bin_type.endswith('cycles'):
bar_width = .25
ax.bar(xs+bar_width*g, data[g, cnt, :, 0], bar_width,
yerr=[[0,0,0], data[g, cnt, :, 1]],
color=colors[g],
capsize=2,
ecolor=colors[g],
)
set_axis_layout(E, ax, bin_type)
ax.set_title(subtitle, fontsize=10)
cnt += 1
set_panel_layout(E, fig, err_type, bin_type)
plt.subplots_adjust(hspace=.6, wspace=.3)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.02)
def draw_subplot(experiment,
avgs,
labels,
level,
cycle,
err_type,
fname,
plot_subtype,
plot_type,
ADD_SOURCE=True):
E = experiment
figsize, nrows, ncols, _, _ = get_subplot_specs(E,
num_subplots=len(E.groups))
fig, axes = plt.subplots(nrows, ncols, figsize=figsize)
slice_labels = ['M', 'F', 'W', 'other', 'IS']
colors = [E.fcolors[x][0] for x in slice_labels]
title, subtitles = get_figure_titles(E, labels, level, cycle, err_type,
plot_type)
for c in xrange(avgs.shape[0]):
try:
ax = axes.flatten()[c]
if plot_subtype == 'bar':
stop
elif plot_subtype == 'pie':
plot_as_a_pie(ax, avgs[c], colors, slice_labels, subtitles[c])
if c == 0:
h, l = ax.get_legend_handles_labels()
except IndexError:
ax.axis('off')
continue
set_legend(fig, h, l)
# plt.subplots_adjust(hspace=.4)
add_titles_notes(E, fig, title=title, typad=-.15, tlxpad=0, tlypad=-.15)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, labelsize=6, sypad=.25)
def draw_mouse_features(E, data, labels, features, bin_type, err_type, fname,
plot_type='features', ADD_SOURCE=False):
figsize = (14.4, 4.8)
nrows, ncols = 4, 7
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=True)
other_color = E.fcolors['other'][0]
xticks, xlabels = get_CT_ticks_labels(bin_type='12bins', SHIFT=E.BIN_SHIFT, tshift=E.binTimeShift)
xs = xticks[:-1] +1
for g in xrange(E.num_strains):
cnt = 0
for n in xrange(nrows):
for m in xrange(ncols):
ax = axes.flatten()[n*ncols + m]
if n == 0 and m >= 3:
ax.axis('off')
continue
feature = features[cnt]
colors = get_two_group_features_colors(E, feature)
subtitle = '%s %s' %(feature, E.plot_settings_dict[feature]['unit'])
idx = labels[:, 0] == g
data_, labels_ = data[idx], labels[idx]
if bin_type.endswith('bins'):
tkw = {'fmt':'o-', 'ms':2, 'elinewidth':.5, 'capsize':1}
for mouse in xrange(idx.sum()):
ax.errorbar(xs, data[mouse, cnt, :, 0], yerr=data[mouse, cnt, :, 1],
color=colors[g], mec=colors[g], **tkw)
else:
stop
set_axis_layout(E, ax, bin_type)
ax.set_title(subtitle, fontsize=10)
cnt += 1
set_panel_layout(E, fig, err_type, tbin_type='24H')
save_plot(fname + '_group%d' %g, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.02)
plt.close()
def plot_figure(experiment, level='strain', err_type='stdev', plot_type='pie', ADD_SOURCE=True):
E = experiment
cycles = E.cycles
use_days = ['chow', 'HiFat']
days_to_use = [E.chowDayNumbers, E.HiFatDayNumbers]
print "days_to_use: %s" %days_to_use
# load data
num_items = get_num_items(E, level)
num_slices = 5
all_avgs = np.zeros((num_items, len(days_to_use), len(cycles), num_slices)) # DC/LC
all_errs = np.zeros((num_items, len(days_to_use), len(cycles), num_slices))
for d, days in enumerate(days_to_use):
for c, cycle in enumerate(cycles):
avgs, errs, labels = get_time_budgets_data(
E, level, err_type,
cycle=cycle, days=days)
all_avgs[:, d, c, :], all_errs[:, d, c, :] = avgs, errs
idx = [0, 2, 1, 3]
all_avgs = all_avgs.reshape(-1, len(cycles), num_slices)[idx]
all_errs = all_errs.reshape(-1, len(cycles), num_slices)[idx]
# directory
dirname = E.figures_dir_subpar + 'time_budgets/fig2/'
if not os.path.isdir(dirname): os.makedirs(dirname)
if level == 'strain':
for c, cycle in enumerate(cycles):
# fig_title = ''
fig_title = 'Time budgets, %s\n%d strains avgs' %(cycle, E.num_strains)
subtitles = ['%s: %s, %s' %(x, y, cycle) for y in use_days for x in E.strain_names]
fig = draw_subplot(E, all_avgs[:, c, :], fig_title, subtitles, plot_type)
fname = dirname + 'time_budgets_%s_%dstrains_%s' %(cycle, E.num_strains, plot_type)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, xpad=.05, ypad=0)
print "figures saved to: %s" %fname
def plot_explained_variance_ratio(experiment, X, pca, level, lastcomp, fname,
EXCLUDE_SS):
E = experiment
components = pca.components_
num_components = pca.n_components_
expl_variance = pca.explained_variance_ratio_
figsize, nrows, ncols, _, _ = get_subplot_specs(E, num_subplots=2)
fig, (ax0, ax1) = plt.subplots(nrows=nrows, ncols=ncols, figsize=figsize)
ax0.plot(range(len(components)), expl_variance, color='.4')
ax1.plot(range(len(components))[-lastcomp:],
expl_variance[-lastcomp:],
color='.4')
ax0.set_ylim([0, .35])
ax1.set_ylim([0, .0006])
ax1.xaxis.set_major_locator(MultipleLocator(1))
for ax in [ax0, ax1]:
ax.xaxis.set_major_formatter(FormatStrFormatter('%d'))
ax_cleanup(ax)
# annotate close-up
text = 'close up,\nlast %d components' % lastcomp
ax1.text(.5, .7, text, fontsize=8, transform=ax1.transAxes)
text = '%d strains, ' %E.num_strains if not EXCLUDE_SS \
else '%d strains (no AKR, CAST, CZECH), ' %(E.num_strains-3)
level_ = 'mice' if level == 'mouse' else level
fig_title = 'Explained variance ratio, %d principal components\n%s%d %s, 24H avg data' % (
num_components, text, X.shape[0], level_)
subplot_labels(E,
fig,
xlabel='Principal component',
ylabel='explained variance',
fig_title=fig_title)
plt.subplots_adjust(bottom=.15, wspace=.4)
save_plot(fname, fig)
def plot_features_panel_DC_LC(experiment,
level='group',
bin_type='3cycles',
err_type='sem',
plot_type='features',
ADD_SOURCE=True):
E = experiment
print "%s, level: %s, bin_type: %s, err_type: %s, days: %s" % (
plot_features_panel_DC_LC.__name__, level, bin_type, err_type,
E.daysToUse)
features = E.features_by_activity
num_features = len(features)
days_to_use = E.daysToUse
dirname = E.figures_dir + '%s/vectors/panels_expdays/%s/%s_days/' % (
plot_type, bin_type, E.use_days)
if not os.path.isdir(dirname): os.makedirs(dirname)
fname = dirname + '%s_panel_expdays_DC_LC_group_%s' % (plot_type, err_type)
# groups, features, days, cycles, avg/err
data = E.generate_feature_vectors_expdays(features, level, bin_type,
err_type)
new_data = data[:, :, :, 1:, :]
figsize = (14.4, 4.8)
nrows, ncols = 4, 7
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=True)
xs = days_to_use
cnt = 0
for n in xrange(nrows):
for m in xrange(ncols):
ax = axes.flatten()[n * ncols + m]
if n == 0 and m >= 3:
ax.axis('off')
continue
feature = features[cnt]
# get colors
if feature.startswith('AS'):
color1, color2 = [E.fcolors['AS'].values()[x] for x in [1, 3]]
elif feature.startswith('T'):
color1, color2 = [
E.fcolors[feature[1:]].values()[x] for x in [1, 3]
]
else:
color1, color2 = [
E.fcolors[feature[:1]].values()[x] for x in [1, 3]
]
colors = ['.4', '.7', color1, color2]
subtitle = '%s %s' % (feature,
E.plot_settings_dict[feature]['unit'])
for g in xrange(E.num_strains):
tkw = {'fmt': 'o-', 'ms': 2, 'elinewidth': .5, 'capsize': 1}
# DC
mec = '0' if g == 0 else colors[2 * g]
ax.errorbar(xs,
new_data[g, cnt, :, 0, 0],
yerr=new_data[g, cnt, :, 0, 1],
color=colors[2 * g],
mec=mec,
**tkw)
#LC
mc = '0' if g == 0 else colors[2 * g + 1]
ax.errorbar(xs,
new_data[g, cnt, :, 1, 0],
yerr=new_data[g, cnt, :, 1, 1],
color=colors[2 * g + 1],
mec=mec,
**tkw)
if E.short_name == 'HFD2':
d_day = E.dietChangeDayNumbers[0]
ax.axvspan(xmin=d_day,
xmax=days_to_use[-1],
color='.9',
zorder=0)
xlims = ax.get_xlim()
ax.set_xlim((4, xlims[1]))
ax.set_ylim([0, ax.get_ylim()[1]])
ax_cleanup(ax)
ax.set_title(subtitle, fontsize=10)
cnt += 1
fig.text(.6,
.9,
'0: %s, control (grayscale)\nDC:black, LC: gray' %
E.strain_names[0],
fontsize=8)
fig.text(.6,
.83,
'1: %s, knock-out (colors)\nDC: dark, LC: light ' %
E.strain_names[1],
fontsize=8)
fig.text(.6, .78, 'gray background: diet change', fontsize=8)
xlabel = 'Experiment Day'
add_xylabels(fig, xlabel=xlabel, xypad=-.02, labelsize=10)
days_string = E.get_days_to_use_text()
fig_title = '%s Experiment\nFeatures, DC vs. LC, %s avg and %s\nacross %s days: %s' % (
E.short_name, level, err_type, E.use_days.replace(
'_', '-').title(), days_string)
add_titles_notes(E, fig, title=fig_title)
plt.subplots_adjust(hspace=.6, wspace=.34)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.02)
def plot_features_panel_12bins(experiment,
level='group',
bin_type='12bins',
err_type='sem',
plot_type='features',
ADD_SOURCE=True):
E = experiment
print "%s, level: %s, bin_type: %s, err_type: %s, days: %s" % (
plot_features_panel_12bins.__name__, level, bin_type, err_type,
E.daysToUse)
features = E.features_by_activity
num_features = len(features)
days_to_use = E.daysToUse
num_bins = int(bin_type.strip('bins'))
tbins = my_utils.get_tbins_string(bin_type)
dirname = E.figures_dir + '%s/vectors/panels_expdays/%s/%s_days/' % (
plot_type, bin_type, E.use_days)
if not os.path.isdir(dirname): os.makedirs(dirname)
data = E.generate_feature_vectors_expdays(features, level, bin_type,
err_type)
ymaxs = get_ymaxs(data)
# stop
for b in xrange(num_bins):
new_data = data[:, :, :, b, :]
figsize = (14.4, 4.8)
nrows, ncols = 4, 7
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=True)
xs = days_to_use
cnt = 0
for n in xrange(nrows):
for m in xrange(ncols):
ax = axes.flatten()[n * ncols + m]
if n == 0 and m >= 3:
ax.axis('off')
continue
feature = features[cnt]
colors = get_two_group_features_colors(E, feature)
subtitle = '%s %s' % (feature,
E.plot_settings_dict[feature]['unit'])
for g in xrange(E.num_strains):
tkw = {
'fmt': 'o-',
'ms': 2,
'elinewidth': .5,
'capsize': 1
}
ax.errorbar(xs,
new_data[g, cnt, :, 0],
yerr=new_data[g, cnt, :, 1],
color=colors[g],
mec=colors[g],
**tkw)
if E.short_name == 'HFD2':
d_day = E.dietChangeDayNumbers[0]
ax.axvspan(xmin=d_day,
xmax=days_to_use[-1],
color='.9',
zorder=0)
# xmin, xmax = ax.get_xlim()
# ax.set_xlim((xmin-.5, xmax+.5))
# ax.set_ylim([0, ymaxs[cnt]])
ax_cleanup(ax)
ax.set_title(subtitle, fontsize=10)
cnt += 1
xmin, xmax = ax.get_xlim()
ax.set_xlim((xmin - .5, xmax + .5))
fig.text(.6,
.9,
'0: %s, control, %s (grayscale)' %
(E.strain_names[0], tbins[b]),
fontsize=8)
fig.text(.6,
.85,
'1: %s, knock-out, %s (colors)' %
(E.strain_names[1], tbins[b]),
fontsize=8)
fig.text(.6, .8, 'gray background: diet change', fontsize=8)
xlabel = 'Experiment Day'
add_xylabels(fig, xlabel=xlabel, xypad=-.02, labelsize=10)
days_string = E.get_days_to_use_text()
fig_title = '%s Experiment\nFeatures, %s %s avg$\pm$%s, %s\nacross %s days: %s' % (
E.short_name, bin_type, level, err_type, tbins[b],
E.use_days.replace('_', '-').title(), days_string)
add_titles_notes(E, fig, title=fig_title)
plt.subplots_adjust(hspace=.6, wspace=.34)
fname = dirname + '%s_panel_expdays_%s_group_%s_bin%d' % (
plot_type, bin_type, err_type, b)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.02)
def draw_group_features_days_collapse(E,
data,
act,
features,
bin_type,
err_type,
fname,
plot_type='features',
ADD_SOURCE=False):
figsize = (17.6, 2.4)
nrows, ncols = E.num_strains, len(features)
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=True)
other_color = E.fcolors['other'][0]
xticks, xlabels = get_CT_ticks_labels(bin_type='12bins',
SHIFT=E.BIN_SHIFT,
tshift=E.binTimeShift)
xs = xticks[:-1] + 1
ymaxs = get_ymaxs(data)
cnt = 0
for n in xrange(nrows):
for m in xrange(ncols):
ax = axes.flatten()[cnt]
feature = features[m]
subtitle = '%s %s' % (feature,
E.plot_settings_dict[feature]['unit'])
# idx = [0, 1, 2, 3]
# colors = [E.fcolors['AS'].values()[x] for x in idx] if m < 3 else [E.fcolors['F'].values()[x] for x in idx]
colors = E.fcolors['AS'].values(
) if m < 3 else E.fcolors[act].values()
colors[0] = '.4'
colors[3] = '.7'
zord = [0, 1, 2, 0]
if bin_type.endswith('bins'):
tkw = {'fmt': 'o-', 'ms': 2, 'elinewidth': .5, 'capsize': 1}
for d in xrange(len(E.daysToUse)):
ax.errorbar(xs,
data[n, d, m, :, 0],
yerr=data[n, d, m, :, 1],
color=colors[d],
mec=colors[d],
label='day%d' % E.daysToUse[d],
zorder=zord[d],
**tkw)
else:
stop
# same y-axis, per feature
ax.set_ylim([0, ymaxs[m]])
set_axis_layout(E, ax, bin_type)
if m < 1:
texts = [
'0: %s\ncontrol' % E.strain_names[0],
'1: %s\nknock-out' % E.strain_names[1]
]
bbox = ax.get_position()
fig.text(.06,
bbox.y1 - (bbox.y1 - bbox.y0) / 2.,
texts[n],
ha='left',
va='center',
fontsize=10)
if n < 1:
# plot subtitle
ax.set_title(subtitle, fontsize=10, y=1.05)
# legend
if m in [0, 3]:
# legend
ltkw = {
'numpoints': 1,
'bbox_to_anchor': [.25, 2, .1, .05],
'fontsize': 6,
'handletextpad': .8,
'labelspacing': .3,
'borderaxespad': .5,
'frameon': False
}
ax.legend(**ltkw)
cnt += 1
set_panel_layout(E, fig, err_type, tbin_type='12bins')
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.15)
plt.close()
def draw_subplot(experiment,
data,
labels,
data_rescaled,
fname,
act='F',
level='mouse',
sub_type='line',
plot_type='ingestion',
ADD_SOURCE=False):
E = experiment
i_act = 0 if act == 'F' else 1
units = ['mg/s', 'g', 'min']
# var_names = [E.HCM_variables[x][i_act] for x in var_types]
varTypes = ['coeffs', 'tots', 'durs']
varNames = [E.HCM_derived['events'][plot_type][x][0] for x in varTypes]
m_labels = np.unique(labels[:, 1])
figsize, nrows, ncols, sharex, sharey = get_subplot_specs(
num_subplots=len(m_labels))
fig, axes = plt.subplots(nrows,
ncols,
figsize=figsize,
sharex=sharex,
sharey=sharey)
colors = [E.fcolors[act].values()[x] for x in [1, 0, 2]]
title, subtitles = get_figure_titles(E,
labels,
act=act,
plot_type=plot_type)
hls = []
for m, mouse in enumerate(m_labels):
try:
ax = axes.flatten()[m]
idx = labels[:, 1] == mouse
arr = data_rescaled[idx]
if sub_type == 'line':
for k, var in enumerate(varNames):
ax.plot(arr[:, k], lw=.5, color=colors[k], label=var)
# ax.axhline(y=arr.mean()[k], c='grey', alpha='.5', label='')
# stop
make_annotation(ax, arr, data, k, idx, colors, units)
elif sub_type == 'bar':
pass
# bar_width = .2
# for k, var in enumerate(varNames):
# ind = np.arange(len(arr)) + k * bar_width -.1
# tkw = {'lw':.2, 'label':var,
# 'color':colors[k], 'edgecolor':None,
# }
# ax.bar(ind, arr[:, k], bar_width, **tkw)
set_layout(E, ax)
ax.set_title(subtitles[m], fontsize=10)
if m == 0:
h, l = ax.get_legend_handles_labels()
except IndexError:
ax.axis('off')
continue
# legend
tkw = {
'ncol': 3,
'fontsize': 8,
'bbox_to_anchor': [0.85, .08],
'frameon': False
}
legend = fig.legend(h, l, **tkw)
for label in legend.get_lines():
label.set_linewidth(3) # the legend line width
# set subplot labels
xlabel = 'Experiment Day'
ylabel = '%s Coefficient' % act
add_xylabels(fig, xlabel, ylabel) #, xypad=0, yxpad=0, labelsize=10)
add_titles_notes(
E,
fig,
title=title,
# typad=typad,
# tlxpad=tlxpad,
# tlypad=typad
)
plt.subplots_adjust(bottom=.12, hspace=0.6, wspace=0.4)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE) #, sypad=-.05)
def draw_histogram_plot(E, mouse_data, arr_preFast, arr_postFast, mouseNumbers,
fname, plot_type, ADD_SOURCE):
# ZeroLight is one group only
# for m in xrange(num_mice):
# data = mouse_data[m]
# label = mouseNumbers[m]
# data_pre, data_post = arr_preFast[m], arr_postFast[m]
# stop
# i_act = 0 if act == 'F' else 1
units = ['mg/s', 'g', 'min']
# var_names = [E.HCM_variables[x][i_act] for x in var_types]
varTypes = ['coeffs', 'tots', 'durs']
varNames = [E.HCM_derived['events'][plot_type][x][0] for x in varTypes]
num_mice = len(mouseNumbers)
figsize = (12.8, 3.6)
nrows, ncols = len(varNames), num_mice
fig, axes = plt.subplots(nrows,
ncols,
figsize=figsize,
sharex=True,
sharey=False)
colors = [E.fcolors['F'].values()[x] for x in [1, 0, 2]]
# title, subtitles = get_figure_titles(E, labels, act=act, plot_type=plot_type)
hls = []
cnt = 0
for m in xrange(nrows): # FC, FT, FD
data = mouse_data[:, :, m]
pre, post = arr_preFast[:, m], arr_postFast[:, m]
for n in xrange(ncols): # mouseNumbers
ax = axes.flatten()[cnt]
# plot quantity across days for each mouse
ax.plot(data[n, :], lw=.5, color=colors[m])
if m == 0:
xmin, xmax = ax.get_xlim()
ax.axhline(xmin=xmin,
xmax=xmax,
y=data[n].mean(0),
linestyle='-',
color=colors[m],
zorder=0,
label='average FC - up to day 35 value')
ax.axhline(xmin=xmin,
xmax=xmax,
y=pre[n],
linestyle='--',
color='g',
zorder=1,
label='day%d, FC 4h-preFast value' %
E.fastDayNumbers[0])
ax.axhline(xmin=xmin,
xmax=xmax,
y=post[n],
linestyle=':',
color='r',
zorder=2,
label='day%d FC 1h-postFast value' %
E.fastDayNumbers[0])
ax.set_title('M%d' % mouseNumbers[n], fontsize=10)
if n == 0:
h, l = ax.get_legend_handles_labels()
if n == 0:
ax.set_ylabel('%s [%s]' % (varNames[m], units[m]), fontsize=10)
ax.set_ylim([.9 * data.min(), 1.1 * data.max()])
set_layout2(E, ax, m, n)
cnt += 1
# legend
tkw = {'fontsize': 8, 'bbox_to_anchor': [0.8, .15], 'frameon': False}
legend = fig.legend(h, l, **tkw)
for label in legend.get_lines():
label.set_linewidth(3) # the legend line width
# set subplot labels
xlabel = 'Experiment Day'
add_xylabels(fig, xlabel)
add_titles_notes(
E,
fig,
title='F-Coefficient, F-Total Amounts, F-Total PhotoBeam BreakTime')
plt.subplots_adjust(bottom=.12) #, hspace=0.6, wspace=0.4)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.03)
def plot_loadings(experiment,
X,
pca_components,
feature_names,
level,
comps_idx,
fname,
plot_type,
EXCLUDE_SS,
ADD_SOURCE=True):
E = experiment
num_items = X.shape[0]
num_components = len(pca_components)
num_features = len(feature_names)
assert num_features == num_components, 'wtf'
# select components
selected_comps = pca_components[comps_idx]
fig, ax = plt.subplots(figsize=(7, 3))
bar_width = .03 if len(comps_idx) == num_components else .1
colors = [E.plot_settings_dict[feat]['color'] for feat in feature_names]
if plot_type == 'bar':
for c, comp in enumerate(selected_comps):
ind = np.arange(num_features) + c * bar_width
alpha_step = .03 * comp if len(
comps_idx) == num_components else .2 * comp
tkw = {
'lw': .2,
'alpha': (1 - alpha_step),
'color': colors,
'edgecolor': None,
'label': 'PC%d' % comp
}
ax.bar(ind, pca_components[-(comp + 1)], bar_width, **tkw)
elif plot_type == 'line':
colors = get_16_colors()[1::4]
tkw = {
'numpoints': 1,
'fontsize': 6,
'handletextpad': 1.2,
'labelspacing': .8,
'borderaxespad': 1.5,
'frameon': False,
'bbox_to_anchor': (1., 1.2),
'bbox_transform': ax.transAxes
}
for c, comp in enumerate(selected_comps):
ax.plot(comp, color=colors[c], label='comp%d' % (comps_idx[c]))
leg = ax.legend(**tkw)
ax.set_xticks(range(num_features))
ax.set_xticklabels([])
ax.set_ylim(-1, 1)
ax.axhline(xmin=0, xmax=num_features, lw=.5, color='k')
ax.spines['bottom'].set_position('zero')
ax.spines['bottom'].set_visible(False)
ax_cleanup(ax)
# display feature names on top of bars
xpos = np.arange(num_features) + .2
heights = selected_comps.max(axis=0) + .04
heights[5] = heights[4] + .05 # correct FBASR
if plot_type == 'line': heights += .1
for p, feat in enumerate(feature_names):
ax.text(xpos[p],
heights[p],
feat,
fontsize=6,
ha='center',
transform=ax.transData)
# annotate
if plot_type == 'hist':
annotation = 'Color-code by feature type.\n' \
+ 'AS:purple, Feeding:orange, Drinking:blue, Move:green.\n' \
+ 'For each feature, components from %d (opaque) to\n' %comps_idx[0] \
+ '%dth (transparent) are shown on a sliding\ntransparency scale.' %comps_idx[-1]
ax.text(13.8,
ax.get_ylim()[0],
annotation,
fontsize=6,
va='center',
transform=ax.transData)
# title
text = '%d strains, ' %E.num_strains if not EXCLUDE_SS \
else '%d strains (no AKR, CAST, CZECH), ' %(E.num_strains-3)
level_ = 'mice' if level == 'mouse' else level
fig_title = 'Principal Component loadings, components: %s of %d total\n%s%d %s, 24H avg data\n%s days:%dto%d' % (
comps_idx, num_components, text, num_items, level_, E.use_days,
E.daysToUse[0], E.daysToUse[-1])
subplot_labels(E, fig, xlabel='', ylabel='Loading', fig_title=fig_title)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE)
def plot_component_loadings(E,
X,
pca_components,
feature_names,
level,
fname,
EXCLUDE_SS=False,
BY_STRAIN=False,
strain=None,
ADD_SOURCE=True):
num_items = X.shape[0]
num_components = len(pca_components)
num_features = len(feature_names)
figsize, nrows, ncols, sharex, sharey = get_subplot_specs(
E, num_subplots=num_components)
fig, axes = plt.subplots(nrows,
ncols,
figsize=figsize,
sharex=sharex,
sharey=sharey)
xs = range(1, num_components + 1)
for c, comp in enumerate(pca_components):
ax = axes.flatten()[c]
ax.plot(xs, comp, color='.4')
ax.set_xlim(0, ax.get_xlim()[1])
ax.set_xticks(range(num_features))
ax.set_xticklabels([])
ax.set_title('PC%d' % c, fontsize=8, position=(.5, 1.15), ha='center')
ax.axhline(xmin=0, xmax=num_features, lw=.5, color='k')
ax.spines['bottom'].set_position('zero')
ax.spines['bottom'].set_visible(False)
ax_cleanup(ax)
# display feature names on top
heights = list(np.linspace(1.05, .55, 4)) * 8
for p, feat in enumerate(feature_names):
ax.text(xs[p],
heights[p],
feat,
fontsize=4,
ha='center',
transform=ax.transData)
ax.axvline(x=xs[p], ymin=.4, ymax=heights[p], lw=.2, color='.5')
# title
text = '%d strains,' %E.num_strains if not EXCLUDE_SS \
else '%d strains (no AKR, CAST, CZECH),' %(E.num_strains-3)
level_ = 'mice' if level == 'mouse' else level
fig_title = 'Principal Component loadings, %d components\n' %num_components \
+ '%s %d %s, 24H avg data\n%s days:%dto%d' %(
text, num_items, level_, E.use_days, E.daysToUse[0], E.daysToUse[-1])
if BY_STRAIN:
fig_title = 'Principal Component loadings, %d components\n' %num_components \
+ '%s %d %s, 24H avg data\ngroup%d: %s\n%s days:%dto%d' %(
text, num_items, level_, strain, E.strain_names[strain],
E.use_days, E.daysToUse[0], E.daysToUse[-1])
subplot_labels(E, fig, xlabel='', ylabel='Loading', fig_title=fig_title)
plt.subplots_adjust(hspace=.4, wspace=.3)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE)
def plot_features_panel_LC_DC_ratio(experiment,
level='group',
bin_type='3cycles',
err_type='sem',
plot_type='features',
ADD_SOURCE=True):
E = experiment
print "%s, level: %s, bin_type: %s, err_type: %s, days: %s" % (
plot_features_panel_LC_DC_ratio.__name__, level, bin_type, err_type,
E.daysToUse)
features = E.features_by_activity
num_features = len(features)
days_to_use = E.daysToUse
dirname = E.figures_dir + '%s/vectors/panels_expdays/%s/%s_days/' % (
plot_type, bin_type, E.use_days)
if not os.path.isdir(dirname): os.makedirs(dirname)
fname = dirname + '%s_panel_expdays_LC_DC_ratio' % (plot_type
) #s, err_type)
# using mouseday value
# ratios = E.generate_feature_vectors_LC_DC_ratio_expdays(features, level, bin_type, err_type)
# using group averages value
data_ = E.generate_feature_vectors_expdays(features, level, bin_type,
err_type)
ratios_ = data_[:, :, :, 2, 0] / data_[:, :, :, 1, 0] # LC/DC, avgs
figsize = (14.4, 4.8)
nrows, ncols = 4, 7
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=True)
xs = days_to_use
cnt = 0
for n in xrange(nrows):
for m in xrange(ncols):
ax = axes.flatten()[n * ncols + m]
if n == 0 and m >= 3:
ax.axis('off')
continue
feature = features[cnt]
colors = get_two_group_features_colors(E, feature)
subtitle = '%s %s' % (feature,
E.plot_settings_dict[feature]['unit'])
for g in xrange(E.num_strains):
# # using mouseday values
# tkw = {'fmt':'o-', 'ms':2, 'elinewidth':.5, 'capsize':1}
# ax.errorbar(xs, ratios[g, cnt, :, 0], yerr=ratios[g, cnt, :, 1],
# color=colors[g], mec=colors[g], **tkw)
# using group averages value
tkw = {'marker': 'o', 'ms': 2, 'zorder': 0}
ax.plot(xs,
ratios_[g, cnt, :],
color=colors[g],
mec=colors[g],
**tkw)
# use when plotting all for comparison
# colors_ = ['r', 'y']
# ax.plot(xs, ratios_[g, cnt, :], color=colors_[g], mec=colors_[g], **tkw)
if E.short_name == 'HFD2':
d_day = E.dietChangeDayNumbers[0]
ax.axvspan(xmin=d_day,
xmax=days_to_use[-1],
color='.9',
zorder=0)
xlims = ax.get_xlim()
ax.set_xlim((4, xlims[1]))
ax.set_ylim((0, ax.get_ylim()[1]))
ax_cleanup(ax)
ax.set_title(subtitle, fontsize=10)
cnt += 1
fig.text(.6,
.9,
'0: %s, control, 24H (grayscale)' % E.strain_names[0],
fontsize=8)
fig.text(.6,
.85,
'1: %s, knock-out, 24H (colors)' % E.strain_names[1],
fontsize=8)
fig.text(.6, .8, 'gray background: diet change', fontsize=8)
xlabel = 'Experiment Day'
add_xylabels(fig, xlabel=xlabel, xypad=-.02, labelsize=10)
days_string = E.get_days_to_use_text()
fig_title = '%s Experiment\nFeatures vs days, LC/DC ratio %s avg$\pm$%s\nacross %s days: %s' % (
E.short_name, level, err_type, E.use_days.replace(
'_', '-').title(), days_string)
add_titles_notes(E, fig, title=fig_title)
plt.subplots_adjust(hspace=.6, wspace=.34)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.02)
def plot_raster_groups(E, group_list, bin_type='12bins', SHOW_DAYS=True,
plot_type='raster', ADD_SOURCE=True):
""" does not plot ignored mice/mousedays
"""
dirname_out = E.figures_dir + '%ss/%s/group/%s_days/' %(plot_type, bin_type, E.use_days)
if not os.path.isdir(dirname_out): os.makedirs(dirname_out)
print "%s, %s days.." %(plot_raster_groups.__name__, E.use_days)
y_sep = 10
for strain in group_list:
group = E.get_group_object(groupNumber=strain)
num_mice = len(group.count_mice()[0]) # mice ok
if num_mice > 12 and num_mice <=16:
nrows, ncols = (4,4)
elif num_mice > 8 and num_mice <=12:
nrows, ncols = (3, 4)
figsize = (12.8, 6.4)
fig, axes = plt.subplots(nrows, ncols, figsize=figsize)
m = 0 # mouse counter
for mouse in group.individuals:
ax = axes.flatten()[m]
if mouse.ignored:
print mouse, 'excluded'
ax.text(.5, .6, 'M%d\nexcluded' %mouse.mouseNumber,
fontsize=12, color='.5', ha='center', va='center')
ax.axis('off')
else:
cnt = 0
for MD in mouse.mouse_days:
if MD.dayNumber in E.daysToUse:
y_offset = y_sep * (-cnt)
if MD.ignored:
print MD, 'excluded'
ax.text(18, y_offset-5, 'D%d excluded' %MD.dayNumber,
fontsize=8, color='.5', ha='center', va='center')
ax.axis('off')
else:
print MD
plot_events(MD, fig, ax, y_offset)
if SHOW_DAYS:
if m%4 == 0:
show_days(MD, ax, y_offset,
labelsize=8)
cnt += 1
# subtitle
ax.set_title('M%d' %mouse.mouseNumber, y=1.1, fontsize=10)
set_raster_layout(fig, ax, num_days=len(E.daysToUse)),
add_DC_rectangle_to_raster(ax, ypos=5, height=1.5)
m += 1
remove_axes_not_used(group, axes, nrows, ncols, m)
add_titles_notes(E, fig, title=group.get_figtitle())
plt.subplots_adjust(hspace=0.4)
print "saving.."
fname = dirname_out + '%s_group%d' %(plot_type, group.number)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=.03)
def plot_events(MD, fname, plot_type, bin_type='12bins', FLAG_IGNORED=False):
E = MD.experiment
varNames, colors, offsets, heights, labels, label_offsets = \
get_settings_and_annotations(MD)
figsize = (12., 3.6)
fig, ax = plt.subplots(figsize=figsize)
other_color = E.fcolors['other'][0]
c = 0
for tup in zip(varNames, colors, offsets, heights, labels, label_offsets):
name, color, offset, height, label, label_offset = tup
events = MD.load(name) / 3600. - 7 # why here did I use -6.5 ??
if name in ['CT_out_HB', 'CT_at_HB']:
ax.scatter(events,
offset * np.ones(events.shape[0]),
c=color,
marker='|',
s=150,
lw=0.01,
edgecolor=None)
else:
for x in events:
event_patch = patches.Rectangle(
(x[0], offset),
x[1] - x[0],
height, # xy lower left corner, width, height
lw=0.001,
fc=color,
ec=color)
ax.add_patch(event_patch)
if name in [
'AS_timeSet', 'FB_timeSet', 'WB_timeSet', 'MB_timeSet'
]:
print_duration(ax, events, offset, name, color)
ax.text(4.5,
label_offset,
label,
color=color,
ha='right',
va='center',
fontsize=8,
clip_on=False)
set_raster_layout(fig,
ax,
num_days=len(E.daysToUse),
bin_type=bin_type,
SHIFT=E.BIN_SHIFT,
tshift=E.binTimeShift)
add_DC_rectangle_to_raster(ax, ypos=-.3, height=.3)
add_titles_notes(
E,
fig,
title=MD.get_figtitle() + ', %s' % bin_type,
TL_NOTE=True,
)
if MD.ignored:
fig.text(.3,
1.02,
'MD excluded',
fontsize=18,
color='.5',
ha='right',
va='bottom',
transform=ax.transAxes)
# begin/end fast
if E.short_name == '2CFast':
if MD.dayNumber in E.fastDayNumbers + E.reFeedDayNumbers:
text = '"FAST"' if MD.dayNumber in E.fastDayNumbers else '"REFEED"'
fig.text(.15,
1.05,
text,
fontsize=18,
color=other_color,
ha='left',
va='bottom',
transform=ax.transAxes)
show_fast_times(E,
ax,
day_num=MD.dayNumber,
TEXT=True,
color=other_color)
print "saving.."
save_plot(fname, fig, ADD_SOURCE=True)
def draw_position_density_tbins2(E,
data,
mouseNumbers,
tbin_type,
err_type,
xbins,
ybins,
fig_title,
fname,
rect_HB=None,
obs_rect=None,
plot_type='position_density',
ADD_SOURCE=False):
C = Cage()
# figure
figsize = (6.4, 6.4)
nrows, ncols = data.shape[0], data.shape[1]
fig, axes = plt.subplots(nrows, ncols, figsize=figsize)
cmap = plt.get_cmap("viridis")
vmin, vmax = .0001, 1.
if (xbins, ybins) == (2, 4):
vmin = 0.01
extent = [C.CMXLower, C.CMXUpper, C.CMYLower, C.CMYUpper]
percent_time_color = E.fcolors['other'][0]
row_labels = ['M%d' % m for m in mouseNumbers]
column_labels = ['D%d' % d for d in E.daysToUse]
for r in xrange(nrows):
# display row labels
top, bottom, left, right = [
getattr(fig.subplotpars, x)
for x in ['top', 'bottom', 'left', 'right']
]
yy = top - .025 - (top - bottom) * r / nrows
fig.text(left - .1, yy, row_labels[r], va='center', fontsize=8)
for c in xrange(ncols):
# display column labels
if r < 1:
xx = left + .02 + (right - left) * c / ncols
fig.text(xx,
top + .02,
column_labels[c],
ha='center',
fontsize=8)
try:
ax = axes[r, c] if type(
axes) is np.ndarray else axes # when just one axis
Z3 = data[r, c, :, :, 0] # plt average only for the moment
if np.isnan(Z3).all():
ax.axis('off')
else:
Z3_ = Z3.copy()
Z3_[Z3 <
1e-4] = 1e-4 # round small numbers to almost zero for plotting
im = ax.imshow(Z3_,
interpolation='nearest',
cmap=cmap,
norm=LogNorm(vmin=vmin,
vmax=vmax)) #, extent=extent)
set_position_density_layout(fig, ax, im)
if (xbins, ybins) == (2, 4):
draw_homebase_star(ax,
rect_HB[r, c],
color=percent_time_color)
if r * c < 1:
hh, ll = ax.get_legend_handles_labels()
except IndexError:
ax.axis('off')
continue
set_colorbar(fig, ax, im)
set_legend(fig, hh, ll, xbins, ybins, text_color=percent_time_color)
add_titles_notes(E,
fig,
title=fig_title,
titlesize=14,
typad=.08,
TL_NOTE=False)
plt.subplots_adjust(hspace=.2, wspace=.05)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=.03)
def draw_position_density_tbins(E,
data,
labels,
tbin_type,
level,
err_type,
xbins,
ybins,
fname,
rect_HB=None,
obs_rect=None,
plot_type='position_density',
ADD_SOURCE=False):
C = Cage()
# figure
figsize, nrows, ncols = get_subplot_specs(E,
num_subplots=data.shape[0],
plot_type=plot_type,
sub_type=tbin_type)
fig, axes = plt.subplots(nrows, ncols, figsize=figsize)
cmap = plt.get_cmap("viridis")
vmin, vmax = .0001, 1.
if (xbins, ybins) == (2, 4):
vmin = 0.01
extent = [C.CMXLower, C.CMXUpper, C.CMYLower, C.CMYUpper]
percent_time_color = E.fcolors['other'][0]
title, subtitles = get_figure_titles(E,
labels=labels,
level=level,
tbin_type=tbin_type,
err_type=err_type,
plot_type=plot_type)
data_ = data.swapaxes(0, 1)
arr = my_utils.get_CT_bins(
bin_type=tbin_type) / 3600 - 7 # CT in hours. num_tbins=arr.shape[0]
row_labels = ['CT%d-%d' % (row[0], row[1]) for row in arr]
column_labels = subtitles
for r in xrange(nrows):
# row labels
top, bottom, left, right = [
getattr(fig.subplotpars, x)
for x in ['top', 'bottom', 'left', 'right']
]
yy = top - .03 - (top - bottom) * r / nrows
fig.text(left - .1, yy, row_labels[r], va='center', fontsize=8)
for c in xrange(ncols):
# column labels
if r < 1:
xx = left + .01 + (right - left) * c / ncols
fig.text(xx, top + .03, column_labels[c], fontsize=8)
bin_data = data_[r, c, :, :]
try:
ax = axes[r, c] if type(
axes) is np.ndarray else axes # when just one axis
Z3 = bin_data[:, :, 0] # plt average only for the moment
if np.isnan(Z3).all():
# ax.text(.5, .5, subtitles[r] + ' excluded',
# fontsize=12, color='.5', ha='center', va='center')
ax.axis('off')
else:
Z3_ = Z3.copy()
Z3_[Z3 <
1e-4] = 1e-4 # round small numbers to almost zero for plotting
im = ax.imshow(Z3_,
interpolation='nearest',
cmap=cmap,
norm=LogNorm(vmin=vmin,
vmax=vmax)) #, extent=extent)
# ax.set_title(subtitles[c])
set_position_density_layout(fig, ax, im)
if (xbins, ybins) == (2, 4):
draw_homebase_star(ax,
rect_HB[c],
color=percent_time_color)
if r * c < 1:
hh, ll = ax.get_legend_handles_labels()
except IndexError:
ax.axis('off')
continue
set_colorbar(fig, ax, im)
set_legend(fig, hh, ll, xbins, ybins, text_color=percent_time_color)
typad = .15 #if level == 'group' else 0
add_titles_notes(E,
fig,
title=title,
typad=typad,
titlesize=14,
TL_NOTE=False)
plt.subplots_adjust(hspace=.2, wspace=.05)
sypad = -.05 if level == 'group' else .05
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=sypad)
def plot_HCM_system_time(E, ttype='maintenance', ADD_SOURCE=True):
"""plots system_on_off
"""
if ttype == 'maintenance':
HCM_time, labels = E.get_HCM_maintenance_time()
xlims = [2, 8]
xticks = range(2, 10+1, 2)
xticklabels = xticks
elif ttype == 'recording':
HCM_time, labels = E.get_HCM_recording_time()
xlims = [2, 34]
xticks = range(4, 32+1, 4)
xticklabels = [str(x) for x in range(4, 24+1, 4)] \
+ [str(x) for x in range(4, 10+1, 4)]
print "%s, %s days.." %(plot_HCM_system_time.__name__, E.use_days)
figsize, nrows, ncols, sharex, sharey = \
get_subplot_specs(E, num_subplots=len(E.groups), plot_type='subplot')
fig, axes = plt.subplots(nrows, ncols, figsize=figsize, sharex=sharex, sharey=sharey)
for strain in range(nrows * ncols):
ax = axes.flatten()[strain] if type(axes) == np.ndarray else axes
idx = labels [:, 0] == strain
data = HCM_time[idx] / 3600. - 7
c = 0
for row in data:
ax.plot([row[0], row[1]], [c, c], lw=0.5, color='0.5')
c += 1
ax.set_xlim(xlims)
ax.set_xticks(xticks)
ax.set_xticklabels(xticklabels)
if ttype == 'maintenance':
text = 'avg:\n%1.1fmin' %(np.diff(data).mean() * 60)
elif ttype == 'recording':
text = 'avg:\n%1.2fhrs' %np.diff(data).mean()
ax.axvline(x=12, linestyle='--', color='k')
ax.axvline(x=24, linestyle='--', color='k')
ax.text(.9, .9, text, fontsize=10,
ha='center', transform=ax.transAxes)
ax.set_xlabel('Circadian Time')
ax.set_ylabel('Obs. days', labelpad=10)
ax.set_title('group%d: %s' %(strain, E.strain_names[strain]), y=1.05)
ax_cleanup(ax, labelsize=10)
title = '%sExp\n%s days\nDaily %s Time' %(
E.short_name, E.use_days.replace('_', '-').title(), ttype.title())
add_titles_notes(E, fig,
title=title,
typad=.18,
tlxpad=-.1,
tlypad=.15,
HP_TEXT=False)
plt.subplots_adjust(wspace=0.4)
# save
dirname_out = E.figures_dir + 'HCM_recording_time/%s_days/' %E.use_days
if not os.path.isdir(dirname_out): os.makedirs(dirname_out)
fname = dirname_out + 'HCMsystem_%s_time_%s_days' %(ttype, E.use_days)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, sypad=-.1)
def plot_within_AS_structure(experiment,
level='strain',
EARLY=True,
num_mins=15,
days=None,
cycle='24H',
ADD_SOURCE=True): #, s_start=0):
E = experiment
print "%s, level: %s, EARLY: %s, %s" % (plot_within_AS_structure.__name__,
level, EARLY, cycle)
if EARLY: print "first %d minutes" % num_mins
text = 'full_AS' if not EARLY else 'first_%dmin' % num_mins
labels = ['F', 'W', 'M', 'other']
colors = [E.fcolors[x][0] for x in labels]
colors[3] = E.fcolors['other'][1]
if level == 'strain':
# dirname = E.figures_dir_subpar + 'within_AS/examples/'
dirname = E.figures_dir_subpar + 'within_AS/%s_days/%s/%s/%s/' % (
E.use_days, level, cycle, text)
if not os.path.isdir(dirname): os.makedirs(dirname)
for group in E.groups: #[s_start:s_start+4]:
print '%d: %s' % (group.number, group.name)
mice = E.get_mouseNumbers_from_groupNumber(group.number)
figsize, nrows, ncols, sharex, sharey = get_subplot_specs(
E, num_subplots=len(mice))
fig, axes = plt.subplots(nrows,
ncols,
figsize=figsize,
sharex=sharex,
sharey=sharey)
m = 0
for mouse in group.individuals:
if not mouse.ignored:
print mouse
ax = axes.flatten()[m]
plot_mouse_AS_structure(E, level, mouse, ax, colors, EARLY,
num_mins, days, cycle)
m += 1
remove_axes_not_used(group, axes, nrows, ncols, m)
set_legend(fig, colors)
title = '%s: %s, %s' % (group.name, E.use_days, cycle)
fig.suptitle(title, y=1.03)
fig_title = ''
# fig_title = 'Within-AS structure, across %s\ngroup%d: %s\n%s_days: %d to %d' %(
# cycle, group.number, E.strain_names[group.number], E.use_days, E.daysToUse[0], E.daysToUse[-1])
xlabel = 'Time from AS onset [min]'
ylabel = 'AS sorted by duration'
subplot_labels(E,
fig,
xlabel,
ylabel,
fig_title,
txpad=-0.03,
typad=.03)
fname = dirname + 'within_AS_structure_strain%d_%s_%s' % (
group.number, text, cycle)
save_plot(fname, fig, ADD_SOURCE=ADD_SOURCE, ypad=-.04)
elif level == 'mouse':
for group in E.groups: #[s_start:s_start+4]:
print '%d: %s' % (group.number, group.name)
dirname = E.figures_dir_subpar + 'within_AS/%s_days/%s/%s/%s/strain%d/' % (
E.use_days, level, cycle, text, group.number)
if not os.path.isdir(dirname): os.makedirs(dirname)
for mouse in group.individuals:
if not mouse.ignored:
print mouse
figsize = get_subplot_specs(E)
fig, ax = plt.subplots(figsize=figsize)
plot_mouse_AS_structure(E, level, mouse, ax, colors, EARLY,
num_mins, days, cycle)
fig_title = 'Within-AS structure, across %s\ngroup %d: %s\n%s_days: %d to %d' % (
cycle, group.number, E.strain_names[group.number],
E.use_days, E.daysToUse[0], E.daysToUse[-1])
xlabel = 'Time from AS onset [min]'
ylabel = 'AS sorted by duration'
subplot_labels(E, fig, xlabel, ylabel, fig_title)
if ADD_SOURCE:
add_source(fig)
fname = dirname + 'within_AS_structure_individual%d_%s_%s' % (
mouse.mouseNumber, text, cycle)
save_plot(fname, fig)