def view_pair(self, p, table_positive):
fig1 = new_figure(300,300)
axes.kde2d_color_hist(fig1, table_positive, (p[0], p[1]), None, None, 0.001)
fig = new_figure(300,300)
axes.kde2d_color_hist(fig, table_positive, (p[0], p[1]), None, 'y', 0.001)
#ax_dis = new_axes(300,300)
dis_points = find_discontinuities(table_positive, p[0], p[1], None)
return stack_lines(
self.widgets.kde2d_fig.view(fig1),
self.widgets.kde2d_fig.view(fig),
# self.widgets.kde2d_fig.view(ax_dis.figure),
dis_points,
self.widgets.pair_fit_split.view(table_positive, p[0], p[1]))
def view_pair(self, p, table_positive):
fig1 = new_figure(300, 300)
axes.kde2d_color_hist(fig1, table_positive, (p[0], p[1]), None, None,
0.001)
fig = new_figure(300, 300)
axes.kde2d_color_hist(fig, table_positive, (p[0], p[1]), None, 'y',
0.001)
#ax_dis = new_axes(300,300)
dis_points = find_discontinuities(table_positive, p[0], p[1], None)
return stack_lines(
self.widgets.kde2d_fig.view(fig1),
self.widgets.kde2d_fig.view(fig),
# self.widgets.kde2d_fig.view(ax_dis.figure),
dis_points,
self.widgets.pair_fit_split.view(table_positive, p[0], p[1]))
def view(self, pairs, table, mi_table=None):
lines = []
logging.info('Creating pairtable for %d pairs...' % len(pairs))
timer = MultiTimer(len(pairs))
for p in pairs:
gc.collect()
line = []
line.append(p[0])
line.append(p[1])
if mi_table:
i1 = mi_table.dims.index(p[0])
i2 = mi_table.dims.index(p[1])
line.append(mi_table.data[i1, i2])
else:
line.append('')
table_positive = table.remove_bad_cells(p[0], p[1])
#table_positive = table
print ' (%d cells)' % table_positive.num_cells
if table_positive.num_cells > 100:
fig = new_figure(300,300)
axes.kde2d_color_hist(fig, table_positive, (p[0], p[1]), None, 'y', 0.001)
#ax_dis = new_axes(300,300)
dis_points = find_discontinuities(table_positive, p[0], p[1], None)
line.append(self.view_pair(p, table_positive))
line.append(self.view_pair((p[1], p[0]), table_positive))
ax = new_axes(300,300)
axes.scatter(ax, table_positive, (p[0], p[1]), norm_axis=None, no_bins=300j)
line.append(self.widgets.kde2d_fig.view(ax.figure))
lines.append(line)
timer.complete_task('%s, %s' % tuple(p[:2]))
return self.widgets.table.view(
['Dimension 1', 'Dimension 2', 'Mutual Information', 'Normalized Plot1','Normalized Plot2','Scatter Plot'],
lines, None, [('Mutual Information', 'desc')])
def _draw_figures_internal(self, table, dim_x, dim_y, range):
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
try:
axes.kde2d_color_hist(fig, table, (dim_x, dim_y), range)
return {'fig': fig}
except Exception as e:
logging.exception('Exception in DensityPlot')
return {'fig': (None, View(self, str(e)))}
def _draw_figures_internal(self, table, dim_x, dim_y, range):
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
try:
axes.kde2d_color_hist(fig, table, (dim_x, dim_y), range)
return {'fig': fig}
except Exception as e:
logging.exception('Exception in DensityPlot')
return {'fig': (None, View(self, str(e)))}
def view(self):
#cluster = 'B-cells CD20+'
cluster = 'Progenitor cells CD38+'
stim = 'PVO4' #'All'
index = DataIndex.load(r'c:\cytof54_clustered\cytof54.index')
t = index.load_table(cluster_name=cluster, stim=stim)
dims = t.get_markers('signal')
width = 800
height = 800
left_space = 80. / width
top_space = 80. / height
sub_width = (1. - left_space) / len(dims)
sub_height = (1. - top_space) / len(dims)
fig = new_figure(width, height)
for i in xrange(len(dims)):
y_pos = 1 - sub_height - top_space - i * sub_height
x_pos = 0
ax = fig.add_axes((x_pos, y_pos, left_space, sub_height))
ax.text(0.5,
0.5,
dims[i],
fontsize='xx-small',
rotation='horizontal',
horizontalalignment='center',
verticalalignment='center',
transform=ax.transAxes)
axes.remove_ticks(ax)
for j in xrange(len(dims)):
y_pos = 1 - top_space
x_pos = left_space + j * sub_width
ax = fig.add_axes((x_pos, y_pos, sub_width, top_space))
ax.text(0.5,
0.5,
dims[j],
fontsize='xx-small',
rotation='vertical',
horizontalalignment='center',
verticalalignment='center',
transform=ax.transAxes)
axes.remove_ticks(ax)
timer = MultiTimer(len(dims)**2 - len(dims))
for i in xrange(len(dims)):
for j in xrange(len(dims)):
if i == j:
continue
dim1 = dims[i]
dim2 = dims[j]
table_positive = t.remove_bad_cells(dim1, dim2)
y_pos = 1 - sub_height - top_space - i * sub_height
x_pos = left_space + j * sub_width
ax = fig.add_axes((x_pos, y_pos, sub_width, sub_height),
axisbg=cm.jet(0))
#print ''
#print (x_pos,y_pos, sub_width, sub_height)
axes.kde2d(ax, table_positive, (dim1, dim2), None, 'y', 0.001)
axes.remove_ticks(ax)
timer.complete_task('%s, %s' % (dim1, dim2))
return self.widgets.kde2d_fig.view(fig)
def _draw_figures_internal(self, table, dim_x, dim_y, range):
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
try:
axes.kde2d_color_hist(fig, table, (dim_x, dim_y), range, 'y', self.widgets.min_density_in_column.value_as_float())
corr_view = View(None, 'corr: %.2f; mi: %.2f' % (table.get_correlation(dim_x, dim_y), table.get_mutual_information(dim_x, dim_y)))
return {'fig': (fig, corr_view)}
except Exception as e:
logging.exception('Exception in DensityPlot')
return {'fig': (None, View(self, str(e)))}
def _draw_figures_internal(self, table, dim_x, dim_y, range):
res = float(self.widgets.resolution.get_choice())
ax_width, ax_height = self.get_planned_axes_width()
ax_width /= res
ax_height /= res
if res == 1:
interpolation = 'nearest'
else:
interpolation = 'blackman'
colors = self.widgets.color.values.choices
min_cells = int(self.widgets.min_cells_in_bin.values.value) - 1
ret = OrderedDict()
for color in colors:
try:
if color == 'none':
color = None
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
ax = fig.add_subplot(111)
hist, extent = axes.histogram_scatter(
ax,
table, (dim_x, dim_y),
range,
color,
min_cells_per_bin=min_cells,
no_bins_x=ax_width * 1j,
no_bins_y=ax_height * 1j,
interpolation=interpolation)
if self.widgets.contour.get_choices()[0] == 'regular':
cs = ax.contour(hist, extent=extent, origin='lower')
#ax.clabel(cs, inline=1, fontsize=10)
elif self.widgets.contour.get_choices()[0] == 'smooth':
display_data, extent, density, X, Y = axes.kde2d_data(
table, (dim_x, dim_y), range, res=ax_width)
#np.r_[0:np.max(display_data):10j][1:]
levels = np.array([
0.1, 0.2, 0.3, 0.35, 0.4, 0.5, 0.6, 0.8, 1
]) * np.max(display_data)
if color != None:
cs = ax.contour(display_data,
extent=extent,
origin='lower',
levels=levels,
colors='black')
else:
cs = ax.contour(display_data,
extent=extent,
origin='lower',
levels=levels)
#ax.clabel(cs, inline=1, fontsize=10)
ret[str(color)] = fig
except Exception as e:
logging.exception('Exception in ScatterPlot')
ret[str(color)] = (None, View(self, str(e)))
return ret
def view(self):
#cluster = 'B-cells CD20+'
cluster = 'Progenitor cells CD38+'
stim='PVO4' #'All'
index = DataIndex.load(r'c:\cytof54_clustered\cytof54.index')
t = index.load_table(cluster_name=cluster, stim=stim)
dims = t.get_markers('signal')
width = 800
height = 800
left_space = 80./width
top_space = 80./height
sub_width = (1. - left_space) / len(dims)
sub_height =(1. - top_space) / len(dims)
fig = new_figure(width, height)
for i in xrange(len(dims)):
y_pos = 1 - sub_height - top_space - i * sub_height
x_pos = 0
ax = fig.add_axes((x_pos,y_pos, left_space, sub_height))
ax.text(
0.5, 0.5,dims[i],
fontsize='xx-small',
rotation='horizontal',
horizontalalignment='center',
verticalalignment='center',
transform = ax.transAxes)
axes.remove_ticks(ax)
for j in xrange(len(dims)):
y_pos = 1 - top_space
x_pos = left_space + j * sub_width
ax = fig.add_axes((x_pos,y_pos, sub_width, top_space))
ax.text(
0.5, 0.5,dims[j],
fontsize='xx-small',
rotation='vertical',
horizontalalignment='center',
verticalalignment='center',
transform = ax.transAxes)
axes.remove_ticks(ax)
timer = MultiTimer(len(dims)**2 - len(dims))
for i in xrange(len(dims)):
for j in xrange(len(dims)):
if i==j:
continue
dim1 = dims[i]
dim2 = dims[j]
table_positive = t.remove_bad_cells(dim1, dim2)
y_pos = 1 - sub_height - top_space - i * sub_height
x_pos = left_space + j * sub_width
ax = fig.add_axes((x_pos,y_pos, sub_width, sub_height), axisbg=cm.jet(0))
#print ''
#print (x_pos,y_pos, sub_width, sub_height)
axes.kde2d(
ax, table_positive, (dim1, dim2), None, 'y', 0.001)
axes.remove_ticks(ax)
timer.complete_task('%s, %s' % (dim1,dim2))
return self.widgets.kde2d_fig.view(fig)
def get_planned_axes_width(self):
# We need to calculate the pixel size for the figure
# so we create a fake figure and add to it a colorbar
# and axes the same way the scatter function sdoes:
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
ax = fig.add_subplot(111)
ax.set_xlabel('temp', size='x-small')
ax.set_ylabel('temp', size='x-small')
ax.figure.subplots_adjust(bottom=0.15)
cbar = ax.figure.colorbar(ax.imshow([[0]]))
# Now we know the future width, height.
return axes.ax_size_pixels(ax)
def get_planned_axes_width(self):
# We need to calculate the pixel size for the figure
# so we create a fake figure and add to it a colorbar
# and axes the same way the scatter function sdoes:
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
ax = fig.add_subplot(111)
ax.set_xlabel('temp', size='x-small')
ax.set_ylabel('temp', size='x-small')
ax.figure.subplots_adjust(bottom=0.15)
cbar = ax.figure.colorbar(ax.imshow([[0]]))
# Now we know the future width, height.
return axes.ax_size_pixels(ax)
def _draw_figures_internal(self, table, dim_x, dim_y, range):
ret = OrderedDict();
try:
if table.num_cells > 10000:
raise Exception('table is too big')
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
ax = fig.add_subplot(111)
axes.points(ax, table, (dim_x, dim_y), range)
ret[0] = fig;
except Exception as e:
logging.exception('Exception in ScatterPlot')
ret[0] = (None, View(self, str(e)))
return ret
def _draw_figures_internal(self, table, dim_x, dim_y, range):
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
try:
axes.kde2d_color_hist(
fig, table, (dim_x, dim_y), range, 'y',
self.widgets.min_density_in_column.value_as_float())
corr_view = View(
None, 'corr: %.2f; mi: %.2f' % (table.get_correlation(
dim_x, dim_y), table.get_mutual_information(dim_x, dim_y)))
return {'fig': (fig, corr_view)}
except Exception as e:
logging.exception('Exception in DensityPlot')
return {'fig': (None, View(self, str(e)))}
def _draw_figures_internal(self, table, dim_x, dim_y, range):
ret = OrderedDict()
try:
if table.num_cells > 10000:
raise Exception('table is too big')
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
ax = fig.add_subplot(111)
axes.points(ax, table, (dim_x, dim_y), range)
ret[0] = fig
except Exception as e:
logging.exception('Exception in ScatterPlot')
ret[0] = (None, View(self, str(e)))
return ret
def create_and_adjust_figure(self, tables): X_SIZE_FOR_HISTOGRAMS = 300 X_SIZE_PER_NAME_LETTER = 6 Y_SIZE_PER_CURVE = 35 MIN_Y = 300 # first let's calculate the width. texts = [str(t.get_tags(self.widgets.text.values.choices)) for t in tables] max_text_length = max([len(t) for t in texts]) x_size_for_text = X_SIZE_PER_NAME_LETTER * max_text_length x_size = x_size_for_text + X_SIZE_FOR_HISTOGRAMS y_size = len(tables) * Y_SIZE_PER_CURVE y_size = max(MIN_Y, y_size) fig = axes.new_figure(x_size, y_size) fig.subplots_adjust(left=x_size_for_text / float(x_size)) return fig
def create_and_adjust_figure(self, tables):
X_SIZE_FOR_HISTOGRAMS = 300
X_SIZE_PER_NAME_LETTER = 6
Y_SIZE_PER_CURVE = 35
MIN_Y = 300
# first let's calculate the width.
texts = [
str(t.get_tags(self.widgets.text.values.choices)) for t in tables
]
max_text_length = max([len(t) for t in texts])
x_size_for_text = X_SIZE_PER_NAME_LETTER * max_text_length
x_size = x_size_for_text + X_SIZE_FOR_HISTOGRAMS
y_size = len(tables) * Y_SIZE_PER_CURVE
y_size = max(MIN_Y, y_size)
fig = axes.new_figure(x_size, y_size)
fig.subplots_adjust(left=x_size_for_text / float(x_size))
return fig
def _draw_figures_internal(self, table, dim_x, dim_y, range):
res = float(self.widgets.resolution.get_choice())
ax_width, ax_height = self.get_planned_axes_width()
ax_width /= res
ax_height /= res
if res == 1:
interpolation = 'nearest'
else:
interpolation = 'blackman'
colors = self.widgets.color.values.choices
min_cells = int(self.widgets.min_cells_in_bin.values.value)-1
ret = OrderedDict()
for color in colors:
try:
if color == 'none':
color = None
fig = axes.new_figure(FIG_SIZE_X, FIG_SIZE_Y)
ax = fig.add_subplot(111)
hist, extent = axes.histogram_scatter(ax, table, (dim_x, dim_y), range, color, min_cells_per_bin = min_cells, no_bins_x=ax_width*1j, no_bins_y=ax_height*1j, interpolation=interpolation)
if self.widgets.contour.get_choices()[0] == 'regular':
cs = ax.contour(hist, extent=extent, origin='lower')
#ax.clabel(cs, inline=1, fontsize=10)
elif self.widgets.contour.get_choices()[0] == 'smooth':
display_data, extent, density, X, Y = axes.kde2d_data(table, (dim_x, dim_y), range, res=ax_width)
#np.r_[0:np.max(display_data):10j][1:]
levels = np.array([0.1, 0.2, 0.3, 0.35, 0.4, 0.5, 0.6, 0.8, 1]) * np.max(display_data)
if color!=None:
cs = ax.contour(display_data, extent=extent, origin='lower', levels=levels, colors='black')
else:
cs = ax.contour(display_data, extent=extent, origin='lower', levels=levels)
#ax.clabel(cs, inline=1, fontsize=10)
ret[str(color)] = fig
except Exception as e:
logging.exception('Exception in ScatterPlot')
ret[str(color)] = (None, View(self, str(e)))
return ret
def view(self, pairs, table, mi_table=None):
lines = []
logging.info('Creating pairtable for %d pairs...' % len(pairs))
timer = MultiTimer(len(pairs))
for p in pairs:
gc.collect()
line = []
line.append(p[0])
line.append(p[1])
if mi_table:
i1 = mi_table.dims.index(p[0])
i2 = mi_table.dims.index(p[1])
line.append(mi_table.data[i1, i2])
else:
line.append('')
table_positive = table.remove_bad_cells(p[0], p[1])
#table_positive = table
print ' (%d cells)' % table_positive.num_cells
if table_positive.num_cells > 100:
fig = new_figure(300, 300)
axes.kde2d_color_hist(fig, table_positive, (p[0], p[1]), None,
'y', 0.001)
#ax_dis = new_axes(300,300)
dis_points = find_discontinuities(table_positive, p[0], p[1],
None)
line.append(self.view_pair(p, table_positive))
line.append(self.view_pair((p[1], p[0]), table_positive))
ax = new_axes(300, 300)
axes.scatter(ax,
table_positive, (p[0], p[1]),
norm_axis=None,
no_bins=300j)
line.append(self.widgets.kde2d_fig.view(ax.figure))
lines.append(line)
timer.complete_task('%s, %s' % tuple(p[:2]))
return self.widgets.table.view([
'Dimension 1', 'Dimension 2', 'Mutual Information',
'Normalized Plot1', 'Normalized Plot2', 'Scatter Plot'
], lines, None, [('Mutual Information', 'desc')])
def view(self, tables):
""" The view method of this module draws the control panel and the histograms.
We need at least one input to be able to draw something.
"""
if not tables:
return View(self, 'No tables to show.')
self.widgets.color.guess_or_remember(('histogram text', tables), ['name'])
self.widgets.text.guess_or_remember(('histogram colors', tables), ['name'])
self.widgets.shift.guess_or_remember(('histogram shift', tables), '0.2')
self.widgets.sort_inside.guess_or_remember(('histogram sort inside', tables), ['similarity'])
self.widgets.sort_outside.guess_or_remember(('histogram sort outside', tables), ['sort'])
self.widgets.trim.guess_or_remember(('histogram trim', tables), ['no'])
self.widgets.trim_thresh.guess_or_remember(('histogram trim thresh', tables), '0')
sort_inside_options = [('unsort', 'Keep original order'), ('similarity', 'Put similar curves together')]
sort_inside_options += [(x, 'Sort by %s' % x) for x in tables[0].tags.keys()]
# Create the control panel view. This will enable users to choose the dimensions.
control_panel_view = stack_lines(
self.widgets.dims.view('Dimension', self.widgets.apply, options_from_table(tables[0])),
self.widgets.text.view('Text by', self.widgets.apply, tables[0].tags.keys()),
self.widgets.color.view('Color by', self.widgets.apply, tables[0].tags.keys()),
self.widgets.shift.view('Shift for multiple curves', self.widgets.apply),
self.widgets.sort_inside.view('Curve sorting', self.widgets.apply,
sort_inside_options,
multiple=False),
self.widgets.sort_outside.view('Plot sorting', self.widgets.apply,
[('sort', 'Put plots with many differences first'), ('unsort', 'Keep original order')],
multiple=False),
self.widgets.trim.view('Trim plots', self.widgets.apply,
[('yes', 'Convert values lower than threshold to 0'), ('no', 'Don\'t trim')], multiple=False),
self.widgets.trim_thresh.view('Trim threshold', self.widgets.apply),
self.widgets.apply.view())
main_views = []
shift = self.widgets.shift.value_as_float()
plots_for_legend = OrderedDict()
colorer = axes.Colorer()
# Check that the user has already chosen dimensions. Otherwise, ask him
# to do so.
if self.widgets.dims.values.choices:
timer = MultiTimer(len(self.widgets.dims.values.choices))
for i, dim in enumerate(self.widgets.dims.values.choices):
try:
# Go over every dimension and create the histogram:
# First create a new figure:
fig = self.create_and_adjust_figure(tables)
ax = fig.add_subplot(111)
# Draw the histogram for every input
plots = []
sorted_tables = tables
sort_method = self.widgets.sort_inside.values.choices[0]
if sort_method == 'unsort':
sorted_tables = tables
elif sort_method == 'similarity':
thresh = None
if self.widgets.trim.get_choices()[0] == 'yes':
thresh = self.widgets.trim_thresh.value_as_float()
# get distances table:
distances = datatable.ks_distances(tables, dim, thresh)
# sort by distance
sorted_tables = greedy_distance_sort(distances, tables)
else:
# we need to sort by tags:
tag_for_sort = self.widgets.sort_inside.values.choices[0]
sorted_tables = sorted(tables, key=lambda table: table.tags[tag_for_sort])
for i, table in enumerate(sorted_tables):
color_tags = self.widgets.color.values.choices
color_key = tuple([table.tags[c] for c in color_tags])
min_x = None
if self.widgets.trim.get_choices()[0] =='yes':
min_x = self.widgets.trim_thresh.value_as_float()
plot = axes.kde1d(ax, table, dim,
color=colorer.get_color(color_key),
min_x=min_x,
shift=shift*i)
plots_for_legend[color_key] = plot
# Add ticks with table names:
if self.widgets.shift.value_as_float() > 0:
ax.set_yticks(np.arange(0, len(tables)*shift, shift))
ax.set_yticklabels([t.get_tags(self.widgets.text.values.choices) for t in sorted_tables], size='xx-small')
# set axes y range:
ax.set_ylim(bottom = -0.1, top=0.8+shift*(len(sorted_tables)-1))
# Make sure we don't create the same widget twice. We create a new widget
# for every dimension asked.
widget_key = self._normalize_id(dim)
if not widget_key in self.widgets:
self._add_widget(widget_key, Figure)
figure_widget = self.widgets[widget_key]
if len(tables) > 1:
from scipy.stats import ks_2samp
ks, p_ks = ks_2samp(tables[0].get_cols(dim)[0], tables[1].get_cols(dim)[0])
ks_view = View(self, 'ks: %.3f, p_ks: %.10f' % (ks, p_ks))
final_view = stack_lines(ks_view, figure_widget.view(fig))
else:
ks, p_ks = 0, 0
final_view = figure_widget.view(fig)
# Add the new widget's view
main_views.append((ks, p_ks, final_view))
except Exception as e:
logging.exception('Exception when drawing histogram')
main_views.append((0, 0, View(self, str(e))))
timer.complete_task(dim)
# sort by the ks test:
main_views = sorted(main_views, key=itemgetter(0), reverse=True)
main_views = [v[2] for v in main_views]
# create legend:
legened_titles = plots_for_legend.keys()
print len(legened_titles)
max_title_len = max([len(str(t)) for t in legened_titles] + [0])
print max_title_len
WIDTH_PER_LETTER = 7
EXTRA_WIDTH = 60
HEIGHT_PER_LINE = 30
EXTRA_HEIGHT = 50
MIN_X = 300
MIN_Y = 100
legend_x = max(MIN_X, EXTRA_WIDTH + WIDTH_PER_LETTER * max_title_len)
legend_y = max(MIN_Y, EXTRA_HEIGHT + HEIGHT_PER_LINE * len(legened_titles))
fig = axes.new_figure(legend_x, legend_y)
ax = fig.add_subplot(111)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.legend(plots_for_legend.values(),
plots_for_legend.keys(),
loc='center',
mode='expand',
frameon=False,
prop={'size' : 'xx-small'})
main_views = [self.widgets.legend_figure.view(fig)] + main_views
main_view = view.stack_left(*main_views)
else:
main_view = View(None, 'Please select dimensions')
# combine the control panel and the main view togeteher:
return self.widgets.layout.view(main_view, control_panel_view)
def view(self, tables):
""" The view method of this module draws the control panel and the histograms.
We need at least one input to be able to draw something.
"""
if not tables:
return View(self, 'No tables to show.')
self.widgets.color.guess_or_remember(('histogram text', tables),
['name'])
self.widgets.text.guess_or_remember(('histogram colors', tables),
['name'])
self.widgets.shift.guess_or_remember(('histogram shift', tables),
'0.2')
self.widgets.sort_inside.guess_or_remember(
('histogram sort inside', tables), ['similarity'])
self.widgets.sort_outside.guess_or_remember(
('histogram sort outside', tables), ['sort'])
self.widgets.trim.guess_or_remember(('histogram trim', tables), ['no'])
self.widgets.trim_thresh.guess_or_remember(
('histogram trim thresh', tables), '0')
sort_inside_options = [('unsort', 'Keep original order'),
('similarity', 'Put similar curves together')]
sort_inside_options += [(x, 'Sort by %s' % x)
for x in tables[0].tags.keys()]
# Create the control panel view. This will enable users to choose the dimensions.
control_panel_view = stack_lines(
self.widgets.dims.view('Dimension', self.widgets.apply,
options_from_table(tables[0])),
self.widgets.text.view('Text by', self.widgets.apply,
tables[0].tags.keys()),
self.widgets.color.view('Color by', self.widgets.apply,
tables[0].tags.keys()),
self.widgets.shift.view('Shift for multiple curves',
self.widgets.apply),
self.widgets.sort_inside.view('Curve sorting',
self.widgets.apply,
sort_inside_options,
multiple=False),
self.widgets.sort_outside.view(
'Plot sorting',
self.widgets.apply,
[('sort', 'Put plots with many differences first'),
('unsort', 'Keep original order')],
multiple=False),
self.widgets.trim.view(
'Trim plots',
self.widgets.apply,
[('yes', 'Convert values lower than threshold to 0'),
('no', 'Don\'t trim')],
multiple=False),
self.widgets.trim_thresh.view('Trim threshold',
self.widgets.apply),
self.widgets.apply.view())
main_views = []
shift = self.widgets.shift.value_as_float()
plots_for_legend = OrderedDict()
colorer = axes.Colorer()
# Check that the user has already chosen dimensions. Otherwise, ask him
# to do so.
if self.widgets.dims.values.choices:
timer = MultiTimer(len(self.widgets.dims.values.choices))
for i, dim in enumerate(self.widgets.dims.values.choices):
try:
# Go over every dimension and create the histogram:
# First create a new figure:
fig = self.create_and_adjust_figure(tables)
ax = fig.add_subplot(111)
# Draw the histogram for every input
plots = []
sorted_tables = tables
sort_method = self.widgets.sort_inside.values.choices[0]
if sort_method == 'unsort':
sorted_tables = tables
elif sort_method == 'similarity':
thresh = None
if self.widgets.trim.get_choices()[0] == 'yes':
thresh = self.widgets.trim_thresh.value_as_float()
# get distances table:
distances = datatable.ks_distances(tables, dim, thresh)
# sort by distance
sorted_tables = greedy_distance_sort(distances, tables)
else:
# we need to sort by tags:
tag_for_sort = self.widgets.sort_inside.values.choices[
0]
sorted_tables = sorted(
tables, key=lambda table: table.tags[tag_for_sort])
for i, table in enumerate(sorted_tables):
color_tags = self.widgets.color.values.choices
color_key = tuple([table.tags[c] for c in color_tags])
min_x = None
if self.widgets.trim.get_choices()[0] == 'yes':
min_x = self.widgets.trim_thresh.value_as_float()
plot = axes.kde1d(ax,
table,
dim,
color=colorer.get_color(color_key),
min_x=min_x,
shift=shift * i)
plots_for_legend[color_key] = plot
# Add ticks with table names:
if self.widgets.shift.value_as_float() > 0:
ax.set_yticks(np.arange(0, len(tables) * shift, shift))
ax.set_yticklabels([
t.get_tags(self.widgets.text.values.choices)
for t in sorted_tables
],
size='xx-small')
# set axes y range:
ax.set_ylim(bottom=-0.1,
top=0.8 + shift * (len(sorted_tables) - 1))
# Make sure we don't create the same widget twice. We create a new widget
# for every dimension asked.
widget_key = self._normalize_id(dim)
if not widget_key in self.widgets:
self._add_widget(widget_key, Figure)
figure_widget = self.widgets[widget_key]
if len(tables) > 1:
from scipy.stats import ks_2samp
ks, p_ks = ks_2samp(tables[0].get_cols(dim)[0],
tables[1].get_cols(dim)[0])
ks_view = View(self,
'ks: %.3f, p_ks: %.10f' % (ks, p_ks))
final_view = stack_lines(ks_view,
figure_widget.view(fig))
else:
ks, p_ks = 0, 0
final_view = figure_widget.view(fig)
# Add the new widget's view
main_views.append((ks, p_ks, final_view))
except Exception as e:
logging.exception('Exception when drawing histogram')
main_views.append((0, 0, View(self, str(e))))
timer.complete_task(dim)
# sort by the ks test:
main_views = sorted(main_views, key=itemgetter(0), reverse=True)
main_views = [v[2] for v in main_views]
# create legend:
legened_titles = plots_for_legend.keys()
print len(legened_titles)
max_title_len = max([len(str(t)) for t in legened_titles] + [0])
print max_title_len
WIDTH_PER_LETTER = 7
EXTRA_WIDTH = 60
HEIGHT_PER_LINE = 30
EXTRA_HEIGHT = 50
MIN_X = 300
MIN_Y = 100
legend_x = max(MIN_X,
EXTRA_WIDTH + WIDTH_PER_LETTER * max_title_len)
legend_y = max(
MIN_Y, EXTRA_HEIGHT + HEIGHT_PER_LINE * len(legened_titles))
fig = axes.new_figure(legend_x, legend_y)
ax = fig.add_subplot(111)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.legend(plots_for_legend.values(),
plots_for_legend.keys(),
loc='center',
mode='expand',
frameon=False,
prop={'size': 'xx-small'})
main_views = [self.widgets.legend_figure.view(fig)] + main_views
main_view = view.stack_left(*main_views)
else:
main_view = View(None, 'Please select dimensions')
# combine the control panel and the main view togeteher:
return self.widgets.layout.view(main_view, control_panel_view)