def plot_bargraph (self, data, cats=None, config={}):
""" Plot a horizontal bar graph. Expects a 2D dict of sample
data. Also can take info about categories. There are quite a
few variants of how to use this function, see CONTRIBUTING.md
for documentation and examples.
:param data: 2D dict, first keys as sample names, then x:y data pairs
Can supply a list of dicts and will have buttons to switch
:param cats: optional list, dict or OrderedDict with plot categories
:param config: optional dict with config key:value pairs
:return: HTML and JS, ready to be inserted into the page
"""
# Given one dataset - turn it into a list
if type(data) is not list:
data = [data]
# Check we have a list of cats
if type(cats) is not list or type(cats[0]) is str:
cats = [cats]
# Check that we have cats at all - find them from the data
for idx, cat in enumerate(cats):
if cats[idx] is None:
cats[idx] = list(set(k for s in data[idx].keys() for k in data[idx][s].keys() ))
# Given a list of cats - turn it into a dict
for idx, cat in enumerate(cats):
if type(cat) is list:
newcats = OrderedDict()
for c in cat:
newcats[c] = {'name': c}
cats[idx] = newcats
# Parse the data into a HighCharts friendly format
plotsamples = list()
plotdata = list()
for idx, d in enumerate(data):
hc_samples = sorted(list(d.keys()))
hc_data = list()
for c in cats[idx].keys():
thisdata = list()
for s in hc_samples:
try:
thisdata.append(d[s][c])
except KeyError:
pass
if max(thisdata) > 0:
thisdict = { 'name': cats[idx][c]['name'], 'data': thisdata }
if 'color' in cats[idx][c]:
thisdict['color'] = cats[idx][c]['color']
hc_data.append(thisdict)
plotsamples.append(hc_samples)
plotdata.append(hc_data)
# Build the HTML
if config.get('id') is None:
config['id'] = 'mqc_hcplot_'+''.join(random.sample(letters, 10))
html = '<div class="mqc_hcplot_plotgroup">'
# Counts / Percentages Switch
if config.get('cpswitch') is not False:
if config.get('cpswitch_c_active', True) is True:
c_active = 'active'
p_active = ''
else:
c_active = ''
p_active = 'active'
config['stacking'] = 'percent'
c_label = config.get('cpswitch_counts_label', 'Counts')
p_label = config.get('cpswitch_percent_label', 'Percentages')
html += '<div class="btn-group switch_group"> \n\
<button class="btn btn-default btn-sm {c_a}" data-action="set_numbers" data-target="{id}">{c_l}</button> \n\
<button class="btn btn-default btn-sm {p_a}" data-action="set_percent" data-target="{id}">{p_l}</button> \n\
</div> '.format(id=config['id'], c_a=c_active, p_a=p_active, c_l=c_label, p_l=p_label)
if len(plotdata) > 1:
html += ' '
# Buttons to cycle through different datasets
if len(plotdata) > 1:
html += '<div class="btn-group switch_group">\n'
for k, p in enumerate(plotdata):
active = 'active' if k == 0 else ''
try: name = config['data_labels'][k]
except: name = k+1
try: ylab = 'data-ylab="{}"'.format(config['data_labels'][k]['ylab'])
except: ylab = 'data-ylab="{}"'.format(name) if name != k+1 else ''
html += '<button class="btn btn-default btn-sm {a}" data-action="set_data" {y} data-newdata="{k}" data-target="{id}">{n}</button>\n'.format(a=active, id=config['id'], n=name, y=ylab, k=k)
html += '</div>\n\n'
# Plot and javascript function
html += '<div class="hc-plot-wrapper"><div id="{id}" class="hc-plot not_rendered hc-bar-plot"><small>loading..</small></div></div> \n\
</div> \n\
<script type="text/javascript"> \n\
mqc_plots["{id}"] = {{ \n\
"plot_type": "bar_graph", \n\
"samples": {s}, \n\
"datasets": {d}, \n\
"config": {c} \n\
}} \n\
</script>'.format(id=config['id'], s=json.dumps(plotsamples), d=json.dumps(plotdata), c=json.dumps(config));
return html
def plot_bargraph(self, data, cats=None, config={}):
""" Plot a horizontal bar graph. Expects a 2D dict of sample
data. Also can take info about categories. There are quite a
few variants of how to use this function, see CONTRIBUTING.md
for documentation and examples.
:param data: 2D dict, first keys as sample names, then x:y data pairs
Can supply a list of dicts and will have buttons to switch
:param cats: optional list, dict or OrderedDict with plot categories
:param config: optional dict with config key:value pairs
:return: HTML and JS, ready to be inserted into the page
"""
# Given one dataset - turn it into a list
if type(data) is not list:
data = [data]
# Check we have a list of cats
if type(cats) is not list or type(cats[0]) is str:
cats = [cats]
# Check that we have cats at all - find them from the data
for idx, cat in enumerate(cats):
if cats[idx] is None:
cats[idx] = list(
set(k for s in data[idx].keys()
for k in data[idx][s].keys()))
# Given a list of cats - turn it into a dict
for idx, cat in enumerate(cats):
if type(cat) is list:
newcats = OrderedDict()
for c in cat:
newcats[c] = {'name': c}
cats[idx] = newcats
# Parse the data into a HighCharts friendly format
plotsamples = list()
plotdata = list()
for idx, d in enumerate(data):
hc_samples = sorted(list(d.keys()))
hc_data = list()
for c in cats[idx].keys():
thisdata = list()
for s in hc_samples:
try:
thisdata.append(d[s][c])
except KeyError:
pass
if max(thisdata) > 0:
thisdict = {'name': cats[idx][c]['name'], 'data': thisdata}
if 'color' in cats[idx][c]:
thisdict['color'] = cats[idx][c]['color']
hc_data.append(thisdict)
plotsamples.append(hc_samples)
plotdata.append(hc_data)
# Build the HTML
if config.get('id') is None:
config['id'] = 'mqc_hcplot_' + ''.join(random.sample(letters, 10))
html = '<div class="mqc_hcplot_plotgroup">'
# Counts / Percentages Switch
if config.get('cpswitch') is not False:
if config.get('cpswitch_c_active', True) is True:
c_active = 'active'
p_active = ''
else:
c_active = ''
p_active = 'active'
config['stacking'] = 'percent'
c_label = config.get('cpswitch_counts_label', 'Counts')
p_label = config.get('cpswitch_percent_label', 'Percentages')
html += '<div class="btn-group switch_group"> \n\
<button class="btn btn-default btn-sm {c_a}" data-action="set_numbers" data-target="{id}">{c_l}</button> \n\
<button class="btn btn-default btn-sm {p_a}" data-action="set_percent" data-target="{id}">{p_l}</button> \n\
</div> '.format(id=config['id'],
c_a=c_active,
p_a=p_active,
c_l=c_label,
p_l=p_label)
if len(plotdata) > 1:
html += ' '
# Buttons to cycle through different datasets
if len(plotdata) > 1:
html += '<div class="btn-group switch_group">\n'
for k, p in enumerate(plotdata):
active = 'active' if k == 0 else ''
try:
name = config['data_labels'][k]
except:
name = k + 1
try:
ylab = 'data-ylab="{}"'.format(
config['data_labels'][k]['ylab'])
except:
ylab = 'data-ylab="{}"'.format(
name) if name != k + 1 else ''
html += '<button class="btn btn-default btn-sm {a}" data-action="set_data" {y} data-newdata="{k}" data-target="{id}">{n}</button>\n'.format(
a=active, id=config['id'], n=name, y=ylab, k=k)
html += '</div>\n\n'
# Plot and javascript function
html += '<div class="hc-plot-wrapper"><div id="{id}" class="hc-plot not_rendered hc-bar-plot"><small>loading..</small></div></div> \n\
</div> \n\
<script type="text/javascript"> \n\
mqc_plots["{id}"] = {{ \n\
"plot_type": "bar_graph", \n\
"samples": {s}, \n\
"datasets": {d}, \n\
"config": {c} \n\
}} \n\
</script>'.format(id=config['id'],
s=json.dumps(plotsamples),
d=json.dumps(plotdata),
c=json.dumps(config))
return html
def plot_xy_data(self, data, config={}):
""" Plot a line graph with X,Y data. See CONTRIBUTING.md for
further instructions on use.
:param data: 2D dict, first keys as sample names, then x:y data pairs
:param config: optional dict with config key:value pairs. See CONTRIBUTING.md
:return: HTML and JS, ready to be inserted into the page
"""
# Given one dataset - turn it into a list
if type(data) is not list:
data = [data]
# Generate the data dict structure expected by HighCharts series
plotdata = list()
for d in data:
thisplotdata = list()
for s in sorted(d.keys()):
pairs = list()
maxval = 0
if 'categories' in config:
config['categories'] = list()
for k in d[s].keys():
config['categories'].append(k)
pairs.append(d[s][k])
maxval = max(maxval, d[s][k])
else:
for k in sorted(d[s].keys()):
pairs.append([k, d[s][k]])
maxval = max(maxval, d[s][k])
if maxval > 0 or config.get('hide_empty') is not True:
this_series = { 'name': s, 'data': pairs }
try:
this_series['color'] = config['colors'][s]
except: pass
thisplotdata.append(this_series)
plotdata.append(thisplotdata)
# Add on annotation data series
try:
for s in config['extra_series']:
plotdata[0].append(s)
except KeyError:
pass
# Build the HTML for the page
if config.get('id') is None:
config['id'] = 'mqc_hcplot_'+''.join(random.sample(letters, 10))
html = '<div class="mqc_hcplot_plotgroup">'
# Buttons to cycle through different datasets
if len(plotdata) > 1:
html += '<div class="btn-group switch_group">\n'
for k, p in enumerate(plotdata):
active = 'active' if k == 0 else ''
try: name = config['data_labels'][k]['name']
except: name = k+1
try: ylab = 'data-ylab="{}"'.format(config['data_labels'][k]['ylab'])
except: ylab = 'data-ylab="{}"'.format(name) if name != k+1 else ''
html += '<button class="btn btn-default btn-sm {a}" data-action="set_data" {y} data-newdata="{k}" data-target="{id}">{n}</button>\n'.format(a=active, id=config['id'], n=name, y=ylab, k=k)
html += '</div>\n\n'
# The plot div
html += '<div class="hc-plot-wrapper"><div id="{id}" class="hc-plot not_rendered hc-line-plot"><small>loading..</small></div></div></div> \n'.format(id=config['id'])
# Javascript with data dump
html += '<script type="text/javascript"> \n\
mqc_plots["{id}"] = {{ \n\
"plot_type": "xy_line", \n\
"datasets": {d}, \n\
"config": {c} \n\
}} \n\
</script>'.format(id=config['id'], d=json.dumps(plotdata), c=json.dumps(config));
return html
def plot_xy_data(self, data, config={}):
""" Plot a line graph with X,Y data. See CONTRIBUTING.md for
further instructions on use.
:param data: 2D dict, first keys as sample names, then x:y data pairs
:param config: optional dict with config key:value pairs. See CONTRIBUTING.md
:return: HTML and JS, ready to be inserted into the page
"""
# Given one dataset - turn it into a list
if type(data) is not list:
data = [data]
# Generate the data dict structure expected by HighCharts series
plotdata = list()
for d in data:
thisplotdata = list()
for s in sorted(d.keys()):
pairs = list()
maxval = 0
if 'categories' in config:
config['categories'] = list()
for k in d[s].keys():
config['categories'].append(k)
pairs.append(d[s][k])
maxval = max(maxval, d[s][k])
else:
for k in sorted(d[s].keys()):
pairs.append([k, d[s][k]])
maxval = max(maxval, d[s][k])
if maxval > 0 or config.get('hide_empty') is not True:
this_series = {'name': s, 'data': pairs}
try:
this_series['color'] = config['colors'][s]
except:
pass
thisplotdata.append(this_series)
plotdata.append(thisplotdata)
# Add on annotation data series
try:
for s in config['extra_series']:
plotdata[0].append(s)
except KeyError:
pass
# Build the HTML for the page
if config.get('id') is None:
config['id'] = 'mqc_hcplot_' + ''.join(random.sample(letters, 10))
html = '<div class="mqc_hcplot_plotgroup">'
# Buttons to cycle through different datasets
if len(plotdata) > 1:
html += '<div class="btn-group switch_group">\n'
for k, p in enumerate(plotdata):
active = 'active' if k == 0 else ''
try:
name = config['data_labels'][k]['name']
except:
name = k + 1
try:
ylab = 'data-ylab="{}"'.format(
config['data_labels'][k]['ylab'])
except:
ylab = 'data-ylab="{}"'.format(
name) if name != k + 1 else ''
html += '<button class="btn btn-default btn-sm {a}" data-action="set_data" {y} data-newdata="{k}" data-target="{id}">{n}</button>\n'.format(
a=active, id=config['id'], n=name, y=ylab, k=k)
html += '</div>\n\n'
# The plot div
html += '<div class="hc-plot-wrapper"><div id="{id}" class="hc-plot not_rendered hc-line-plot"><small>loading..</small></div></div></div> \n'.format(
id=config['id'])
# Javascript with data dump
html += '<script type="text/javascript"> \n\
mqc_plots["{id}"] = {{ \n\
"plot_type": "xy_line", \n\
"datasets": {d}, \n\
"config": {c} \n\
}} \n\
</script>'.format(id=config['id'],
d=json.dumps(plotdata),
c=json.dumps(config))
return html
