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2
MANIFEST.in
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include *.txt
recursive-include test *.py

1
kivycharts/__init__.py
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from .version import __version__

135
kivycharts/chart2d.py
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import math
from kivy.factory import Factory
from kivy.utils import get_color_from_hex as rgb
from kivyblocks.threadcall import HttpClient
from .graph import *
class Chart2d(Graph):
"""
json format:
{
"widgettype":"Chart2d",
"options":{
"xlabel":"Xlabel",
"ylable":"Ylabel",
"x_ticks_minor":1,
"x_ticks_major":5,
"y_ticks_minor":1,
"y_ticks_major":5,
"x_grid_label":true,
"y_grid_label":true,
"padding":5,
"xlog":false,
"ylog":false,
"x_grid":true,
"y_grid":true,
"xmin":0,
"xmax":100,
"ymax":100,
"ymin":1,
"x_field":"xxx",
"dataurl":"xxx",
"charts":[
{
"y_field":"yy",
"color":"efefef",
"charttype":"LinePlot"
}
]
}
}
"""
plotmappings={
"line":LinePlot,
"hbar":BarPlot
}
default_options = {
"x_grid_label":True,
"y_grid_label":True,
"xlabel":"Xlabel",
"ylabel":"Ylabel",
"xmin":0,
"xmax":100,
"ymax":100,
"ymin":1,
"x_grid":True,
"y_grid":True,
"padding":5,
"xlog":False,
"ylog":False,
'x_ticks_minor':1,
'x_ticks_major':5,
"y_ticks_minor":1,
"y_ticks_major":5,
'label_options': {
'color': rgb('444444'), # color of tick labels and titles
'bold': True},
'background_color': rgb('f8f8f2'), # canvas background color
'tick_color': rgb('808080'), # ticks and grid
'border_color': rgb('808080') # border drawn around each graph
}
def __init__(self, dataurl='',
data=None,
x_field='',
params={},
headers={},
charts=[],
**kw):
self._dataurl = dataurl
self._params = params
self._headers = {}
self.x_field = x_field
self._data = data
if not self._data:
self._data = self.get_data()
print('_data=',self._data, 'url=', self._dataurl)
xmax = len(self._data)
ymax = 0
xvalue = [ self._data[i][self.x_field] for i in range(xmax) ]
self._charts = charts
print('charts=', charts)
plots = []
for c in charts:
plotKlass = self.plotmappings.get(c['charttype'])
if not plotKlass:
print('charttype not defined', c)
continue
yvalue = [self._data[i][c['y_field']] for i in range(xmax)]
print('yvalue=', yvalue)
color = rgb(c.get('color','d8d8d8'))
plot = plotKlass(color=color)
plot.points = [(i,yvalue[i]) for i in range(xmax)]
plots.append(plot)
maxv = max(yvalue)
if ymax < maxv:
ymax = maxv
gkw = self.default_options.copy()
gkw.update(kw)
gkw['ymax'] = math.ceil(ymax)
gkw['y_ticks_minor'] = gkw['ymax'] / 10
gkw['y_ticks_major'] = gkw['ymax'] / 2
gkw['x_ticks_minor'] = 1
if gkw['x_ticks_major'] > xmax:
gkw['x_ticks_major'] = xmax
gkw['xmax'] = xmax
print('gkw=', gkw)
Graph.__init__(self, **gkw)
print('plots=', plots)
for p in plots:
print('points=', p.points)
self.add_plot(p)
if hasattr(p,'bind_to_graph'):
p.bind_to_graph(self)
def get_data(self):
hc = HttpClient()
d = hc.get(self._dataurl,
params=self._params,
headers=self._headers)
return d
Factory.register('Chart2D', Chart2d)

988
kivycharts/graph/base.py
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'''
Graph
======
The :class:`Graph` widget is a widget for displaying plots. It supports
drawing multiple plot with different colors on the Graph. It also supports
axes titles, ticks, labeled ticks, grids and a log or linear representation on
both the x and y axis, independently.
To display a plot. First create a graph which will function as a "canvas" for
the plots. Then create plot objects e.g. MeshLinePlot and add them to the
graph.
To create a graph with x-axis between 0-100, y-axis between -1 to 1, x and y
labels of and X and Y, respectively, x major and minor ticks every 25, 5 units,
respectively, y major ticks every 1 units, full x and y grids and with
a red line plot containing a sin wave on this range::
from kivy_garden.graph import Graph, MeshLinePlot
graph = Graph(xlabel='X', ylabel='Y', x_ticks_minor=5,
x_ticks_major=25, y_ticks_major=1,
y_grid_label=True, x_grid_label=True, padding=5,
x_grid=True, y_grid=True, xmin=-0, xmax=100, ymin=-1, ymax=1)
plot = MeshLinePlot(color=[1, 0, 0, 1])
plot.points = [(x, sin(x / 10.)) for x in range(0, 101)]
graph.add_plot(plot)
The MeshLinePlot plot is a particular plot which draws a set of points using
a mesh object. The points are given as a list of tuples, with each tuple
being a (x, y) coordinate in the graph's units.
You can create different types of plots other than MeshLinePlot by inheriting
from the Plot class and implementing the required functions. The Graph object
provides a "canvas" to which a Plot's instructions are added. The plot object
is responsible for updating these instructions to show within the bounding
box of the graph the proper plot. The Graph notifies the Plot when it needs
to be redrawn due to changes. See the MeshLinePlot class for how it is done.
The current availables plots are:
* `MeshStemPlot`
* `MeshLinePlot`
* `SmoothLinePlot` - require Kivy 1.8.1
.. note::
The graph uses a stencil view to clip the plots to the graph display area.
As with the stencil graphics instructions, you cannot stack more than 8
stencil-aware widgets.
'''
from kivy.uix.widget import Widget
from kivy.uix.label import Label
from kivy.uix.stencilview import StencilView
from kivy.properties import NumericProperty, BooleanProperty,\
BoundedNumericProperty, StringProperty, ListProperty, ObjectProperty,\
DictProperty, AliasProperty
from kivy.clock import Clock
from kivy.graphics import Mesh, Color, Rectangle, Point
from kivy.graphics import Fbo
from kivy.graphics.texture import Texture
from kivy.event import EventDispatcher
from kivy.lang import Builder
from kivy.logger import Logger
from kivy import metrics
from math import log10, floor, ceil
from decimal import Decimal
from itertools import chain
try:
import numpy as np
except ImportError as e:
np = None
from ._version import __version__
def identity(x):
return x
def exp10(x):
return 10 ** x
Builder.load_string("""
<GraphRotatedLabel>:
canvas.before:
PushMatrix
Rotate:
angle: root.angle
axis: 0, 0, 1
origin: root.center
canvas.after:
PopMatrix
""")
class GraphRotatedLabel(Label):
angle = NumericProperty(0)
class Axis(EventDispatcher):
pass
class XAxis(Axis):
pass
class YAxis(Axis):
pass
class Graph(Widget):
'''Graph class, see module documentation for more information.
'''
# triggers a full reload of graphics
_trigger = ObjectProperty(None)
# triggers only a repositioning of objects due to size/pos updates
_trigger_size = ObjectProperty(None)
# triggers only a update of colors, e.g. tick_color
_trigger_color = ObjectProperty(None)
# holds widget with the x-axis label
_xlabel = ObjectProperty(None)
# holds widget with the y-axis label
_ylabel = ObjectProperty(None)
# holds all the x-axis tick mark labels
_x_grid_label = ListProperty([])
# holds all the y-axis tick mark labels
_y_grid_label = ListProperty([])
# the mesh drawing all the ticks/grids
_mesh_ticks = ObjectProperty(None)
# the mesh which draws the surrounding rectangle
_mesh_rect = ObjectProperty(None)
# a list of locations of major and minor ticks. The values are not
# but is in the axis min - max range
_ticks_majorx = ListProperty([])
_ticks_minorx = ListProperty([])
_ticks_majory = ListProperty([])
_ticks_minory = ListProperty([])
tick_color = ListProperty([.25, .25, .25, 1])
'''Color of the grid/ticks, default to 1/4. grey.
'''
background_color = ListProperty([0, 0, 0, 0])
'''Color of the background, defaults to transparent
'''
border_color = ListProperty([1, 1, 1, 1])
'''Color of the border, defaults to white
'''
x_grid_texts = ListProperty(None)
label_options = DictProperty()
'''Label options that will be passed to `:class:`kivy.uix.Label`.
'''
_with_stencilbuffer = BooleanProperty(True)
'''Whether :class:`Graph`'s FBO should use FrameBuffer (True) or not
(False).
.. warning:: This property is internal and so should be used with care.
It can break some other graphic instructions used by the :class:`Graph`,
for example you can have problems when drawing :class:`SmoothLinePlot`
plots, so use it only when you know what exactly you are doing.
:data:`_with_stencilbuffer` is a :class:`~kivy.properties.BooleanProperty`,
defaults to True.
'''
def __init__(self, **kwargs):
super(Graph, self).__init__(**kwargs)
with self.canvas:
self._fbo = Fbo(
size=self.size, with_stencilbuffer=self._with_stencilbuffer)
with self._fbo:
self._background_color = Color(*self.background_color)
self._background_rect = Rectangle(size=self.size)
self._mesh_ticks_color = Color(*self.tick_color)
self._mesh_ticks = Mesh(mode='lines')
self._mesh_rect_color = Color(*self.border_color)
self._mesh_rect = Mesh(mode='line_strip')
with self.canvas:
Color(1, 1, 1)
self._fbo_rect = Rectangle(
size=self.size, texture=self._fbo.texture)
mesh = self._mesh_rect
mesh.vertices = [0] * (5 * 4)
mesh.indices = range(5)
self._plot_area = StencilView()
self.add_widget(self._plot_area)
t = self._trigger = Clock.create_trigger(self._redraw_all)
ts = self._trigger_size = Clock.create_trigger(self._redraw_size)
tc = self._trigger_color = Clock.create_trigger(self._update_colors)
self.bind(center=ts, padding=ts, precision=ts, plots=ts, x_grid=ts,
y_grid=ts, draw_border=ts)
self.bind(xmin=t, xmax=t, xlog=t, x_ticks_major=t, x_ticks_minor=t,
xlabel=t, x_grid_label=t, ymin=t, ymax=t, ylog=t,
y_ticks_major=t, y_ticks_minor=t, ylabel=t, y_grid_label=t,
font_size=t, label_options=t, x_ticks_angle=t)
self.bind(tick_color=tc, background_color=tc, border_color=tc)
self._trigger()
def add_widget(self, widget):
if widget is self._plot_area:
canvas = self.canvas
self.canvas = self._fbo
super(Graph, self).add_widget(widget)
if widget is self._plot_area:
self.canvas = canvas
def remove_widget(self, widget):
if widget is self._plot_area:
canvas = self.canvas
self.canvas = self._fbo
super(Graph, self).remove_widget(widget)
if widget is self._plot_area:
self.canvas = canvas
def _get_ticks(self, major, minor, log, s_min, s_max):
if major and s_max > s_min:
if log:
s_min = log10(s_min)
s_max = log10(s_max)
# count the decades in min - max. This is in actual decades,
# not logs.
n_decades = floor(s_max - s_min)
# for the fractional part of the last decade, we need to
# convert the log value, x, to 10**x but need to handle
# differently if the last incomplete decade has a decade
# boundary in it
if floor(s_min + n_decades) != floor(s_max):
n_decades += 1 - (10 ** (s_min + n_decades + 1) - 10 **
s_max) / 10 ** floor(s_max + 1)
else:
n_decades += ((10 ** s_max - 10 ** (s_min + n_decades)) /
10 ** floor(s_max + 1))
# this might be larger than what is needed, but we delete
# excess later
n_ticks_major = n_decades / float(major)
n_ticks = int(floor(n_ticks_major * (minor if minor >=
1. else 1.0))) + 2
# in decade multiples, e.g. 0.1 of the decade, the distance
# between ticks
decade_dist = major / float(minor if minor else 1.0)
points_minor = [0] * n_ticks
points_major = [0] * n_ticks
k = 0 # position in points major
k2 = 0 # position in points minor
# because each decade is missing 0.1 of the decade, if a tick
# falls in < min_pos skip it
min_pos = 0.1 - 0.00001 * decade_dist
s_min_low = floor(s_min)
# first real tick location. value is in fractions of decades
# from the start we have to use decimals here, otherwise
# floating point inaccuracies results in bad values
start_dec = ceil((10 ** Decimal(s_min - s_min_low - 1)) /
Decimal(decade_dist)) * decade_dist
count_min = (0 if not minor else
floor(start_dec / decade_dist) % minor)
start_dec += s_min_low
count = 0 # number of ticks we currently have passed start
while True:
# this is the current position in decade that we are.
# e.g. -0.9 means that we're at 0.1 of the 10**ceil(-0.9)
# decade
pos_dec = start_dec + decade_dist * count
pos_dec_low = floor(pos_dec)
diff = pos_dec - pos_dec_low
zero = abs(diff) < 0.001 * decade_dist
if zero:
# the same value as pos_dec but in log scale
pos_log = pos_dec_low
else:
pos_log = log10((pos_dec - pos_dec_low
) * 10 ** ceil(pos_dec))
if pos_log > s_max:
break
count += 1
if zero or diff >= min_pos:
if minor and not count_min % minor:
points_major[k] = pos_log
k += 1
else:
points_minor[k2] = pos_log
k2 += 1
count_min += 1
else:
# distance between each tick
tick_dist = major / float(minor if minor else 1.0)
n_ticks = int(floor((s_max - s_min) / tick_dist) + 1)
points_major = [0] * int(floor((s_max - s_min) / float(major))
+ 1)
points_minor = [0] * (n_ticks - len(points_major) + 1)
k = 0 # position in points major
k2 = 0 # position in points minor
for m in range(0, n_ticks):
if minor and m % minor:
if k2 >= len(points_minor):
continue
points_minor[k2] = m * tick_dist + s_min
k2 += 1
else:
points_major[k] = m * tick_dist + s_min
k += 1
del points_major[k:]
del points_minor[k2:]
else:
points_major = []
points_minor = []
return points_major, points_minor
def _update_labels(self):
xlabel = self._xlabel
ylabel = self._ylabel
x = self.x
y = self.y
width = self.width
height = self.height
padding = self.padding
x_next = padding + x
y_next = padding + y
xextent = width + x
yextent = height + y
ymin = self.ymin
ymax = self.ymax
xmin = self.xmin
precision = self.precision
x_overlap = False
y_overlap = False
# set up x and y axis labels
if xlabel:
xlabel.text = self.xlabel
xlabel.texture_update()
xlabel.size = xlabel.texture_size
xlabel.pos = int(
x + width / 2. - xlabel.width / 2.), int(padding + y)
y_next += padding + xlabel.height
if ylabel:
ylabel.text = self.ylabel
ylabel.texture_update()
ylabel.size = ylabel.texture_size
ylabel.x = padding + x - (ylabel.width / 2. - ylabel.height / 2.)
x_next += padding + ylabel.height
xpoints = self._ticks_majorx
xlabels = self._x_grid_label
xlabel_grid = self.x_grid_label
ylabel_grid = self.y_grid_label
ypoints = self._ticks_majory
ylabels = self._y_grid_label
# now x and y tick mark labels
if len(ylabels) and ylabel_grid:
# horizontal size of the largest tick label, to have enough room
funcexp = exp10 if self.ylog else identity
funclog = log10 if self.ylog else identity
ylabels[0].text = precision % funcexp(ypoints[0])
ylabels[0].texture_update()
y1 = ylabels[0].texture_size
y_start = y_next + (padding + y1[1] if len(xlabels) and xlabel_grid
else 0) + \
(padding + y1[1] if not y_next else 0)
yextent = y + height - padding - y1[1] / 2.
ymin = funclog(ymin)
ratio = (yextent - y_start) / float(funclog(ymax) - ymin)
y_start -= y1[1] / 2.
y1 = y1[0]
for k in range(len(ylabels)):
ylabels[k].text = precision % funcexp(ypoints[k])
ylabels[k].texture_update()
ylabels[k].size = ylabels[k].texture_size
y1 = max(y1, ylabels[k].texture_size[0])
ylabels[k].pos = (
int(x_next),
int(y_start + (ypoints[k] - ymin) * ratio))
if len(ylabels) > 1 and ylabels[0].top > ylabels[1].y:
y_overlap = True
else:
x_next += y1 + padding
if len(xlabels) and xlabel_grid:
funcexp = exp10 if self.xlog else identity
funclog = log10 if self.xlog else identity
# find the distance from the end that'll fit the last tick label
if self.x_grid_texts:
xlabels[0].text = self.x_grid_texts[int(xpoints[-1])]
else:
xlabels[0].text = precision % funcexp(xpoints[-1])
xlabels[0].texture_update()
xextent = x + width - xlabels[0].texture_size[0] / 2. - padding
# find the distance from the start that'll fit the first tick label
if not x_next:
if self.x_grid_texts:
xlabels[0].text = self.x_grid_texts[int(xpoints[0])]
else:
xlabels[0].text = precision % funcexp(xpoints[0])
xlabels[0].texture_update()
x_next = padding + xlabels[0].texture_size[0] / 2.
xmin = funclog(xmin)
ratio = (xextent - x_next) / float(funclog(self.xmax) - xmin)
right = -1
for k in range(len(xlabels)):
if self.x_grid_texts:
xlabels[k].text = self.x_grid_texts[int(xpoints[k])]
else:
xlabels[k].text = precision % funcexp(xpoints[k])
# update the size so we can center the labels on ticks
xlabels[k].texture_update()
xlabels[k].size = xlabels[k].texture_size
half_ts = xlabels[k].texture_size[0] / 2.
xlabels[k].pos = (
int(x_next + (xpoints[k] - xmin) * ratio - half_ts),
int(y_next))
if xlabels[k].x < right:
x_overlap = True
break
right = xlabels[k].right
if not x_overlap:
y_next += padding + xlabels[0].texture_size[1]
# now re-center the x and y axis labels
if xlabel:
xlabel.x = int(
x_next + (xextent - x_next) / 2. - xlabel.width / 2.)
if ylabel:
ylabel.y = int(
y_next + (yextent - y_next) / 2. - ylabel.height / 2.)
ylabel.angle = 90
if x_overlap:
for k in range(len(xlabels)):
xlabels[k].text = ''
if y_overlap:
for k in range(len(ylabels)):
ylabels[k].text = ''
return x_next - x, y_next - y, xextent - x, yextent - y
def _update_ticks(self, size):
# re-compute the positions of the bounding rectangle
mesh = self._mesh_rect
vert = mesh.vertices
if self.draw_border:
s0, s1, s2, s3 = size
vert[0] = s0
vert[1] = s1
vert[4] = s2
vert[5] = s1
vert[8] = s2
vert[9] = s3
vert[12] = s0
vert[13] = s3
vert[16] = s0
vert[17] = s1
else:
vert[0:18] = [0 for k in range(18)]
mesh.vertices = vert
# re-compute the positions of the x/y axis ticks
mesh = self._mesh_ticks
vert = mesh.vertices
start = 0
xpoints = self._ticks_majorx
ypoints = self._ticks_majory
xpoints2 = self._ticks_minorx
ypoints2 = self._ticks_minory
ylog = self.ylog
xlog = self.xlog
xmin = self.xmin
xmax = self.xmax
if xlog:
xmin = log10(xmin)
xmax = log10(xmax)
ymin = self.ymin
ymax = self.ymax
if ylog:
ymin = log10(ymin)
ymax = log10(ymax)
if len(xpoints):
top = size[3] if self.x_grid else metrics.dp(12) + size[1]
ratio = (size[2] - size[0]) / float(xmax - xmin)
for k in range(start, len(xpoints) + start):
vert[k * 8] = size[0] + (xpoints[k - start] - xmin) * ratio
vert[k * 8 + 1] = size[1]
vert[k * 8 + 4] = vert[k * 8]
vert[k * 8 + 5] = top
start += len(xpoints)
if len(xpoints2):
top = metrics.dp(8) + size[1]
ratio = (size[2] - size[0]) / float(xmax - xmin)
for k in range(start, len(xpoints2) + start):
vert[k * 8] = size[0] + (xpoints2[k - start] - xmin) * ratio
vert[k * 8 + 1] = size[1]
vert[k * 8 + 4] = vert[k * 8]
vert[k * 8 + 5] = top
start += len(xpoints2)
if len(ypoints):
top = size[2] if self.y_grid else metrics.dp(12) + size[0]
ratio = (size[3] - size[1]) / float(ymax - ymin)
for k in range(start, len(ypoints) + start):
vert[k * 8 + 1] = size[1] + (ypoints[k - start] - ymin) * ratio
vert[k * 8 + 5] = vert[k * 8 + 1]
vert[k * 8] = size[0]
vert[k * 8 + 4] = top
start += len(ypoints)
if len(ypoints2):
top = metrics.dp(8) + size[0]
ratio = (size[3] - size[1]) / float(ymax - ymin)
for k in range(start, len(ypoints2) + start):
vert[k * 8 + 1] = size[1] + (
ypoints2[k - start] - ymin) * ratio
vert[k * 8 + 5] = vert[k * 8 + 1]
vert[k * 8] = size[0]
vert[k * 8 + 4] = top
mesh.vertices = vert
x_axis = ListProperty([None])
y_axis = ListProperty([None])
def get_x_axis(self, axis=0):
if axis == 0:
return self.xlog, self.xmin, self.xmax
info = self.x_axis[axis]
return info["log"], info["min"], info["max"]
def get_y_axis(self, axis=0):
if axis == 0:
return self.ylog, self.ymin, self.ymax
info = self.y_axis[axis]
return info["log"], info["min"], info["max"]
def add_x_axis(self, xmin, xmax, xlog=False):
data = {
"log": xlog,
"min": xmin,
"max": xmax
}
self.x_axis.append(data)
return data
def add_y_axis(self, ymin, ymax, ylog=False):
data = {
"log": ylog,
"min": ymin,
"max": ymax
}
self.y_axis.append(data)
return data
def _update_plots(self, size):
for plot in self.plots:
xlog, xmin, xmax = self.get_x_axis(plot.x_axis)
ylog, ymin, ymax = self.get_y_axis(plot.y_axis)
plot._update(xlog, xmin, xmax, ylog, ymin, ymax, size)
def _update_colors(self, *args):
self._mesh_ticks_color.rgba = tuple(self.tick_color)
self._background_color.rgba = tuple(self.background_color)
self._mesh_rect_color.rgba = tuple(self.border_color)
def _redraw_all(self, *args):
# add/remove all the required labels
xpoints_major, xpoints_minor = self._redraw_x(*args)
ypoints_major, ypoints_minor = self._redraw_y(*args)
mesh = self._mesh_ticks
n_points = (len(xpoints_major) + len(xpoints_minor) +
len(ypoints_major) + len(ypoints_minor))
mesh.vertices = [0] * (n_points * 8)
mesh.indices = [k for k in range(n_points * 2)]
self._redraw_size()
def _redraw_x(self, *args):
font_size = self.font_size
if self.xlabel:
xlabel = self._xlabel
if not xlabel:
xlabel = Label()
self.add_widget(xlabel)
self._xlabel = xlabel
xlabel.font_size = font_size
for k, v in self.label_options.items():
setattr(xlabel, k, v)
else:
xlabel = self._xlabel
if xlabel:
self.remove_widget(xlabel)
self._xlabel = None
grids = self._x_grid_label
xpoints_major, xpoints_minor = self._get_ticks(self.x_ticks_major,
self.x_ticks_minor,
self.xlog, self.xmin,
self.xmax)
self._ticks_majorx = xpoints_major
self._ticks_minorx = xpoints_minor
if not self.x_grid_label:
n_labels = 0
else:
n_labels = len(xpoints_major)
for k in range(n_labels, len(grids)):
self.remove_widget(grids[k])
del grids[n_labels:]
grid_len = len(grids)
grids.extend([None] * (n_labels - len(grids)))
for k in range(grid_len, n_labels):
grids[k] = GraphRotatedLabel(
font_size=font_size, angle=self.x_ticks_angle,
**self.label_options)
self.add_widget(grids[k])
return xpoints_major, xpoints_minor
def _redraw_y(self, *args):
font_size = self.font_size
if self.ylabel:
ylabel = self._ylabel
if not ylabel:
ylabel = GraphRotatedLabel()
self.add_widget(ylabel)
self._ylabel = ylabel
ylabel.font_size = font_size
for k, v in self.label_options.items():
setattr(ylabel, k, v)
else:
ylabel = self._ylabel
if ylabel:
self.remove_widget(ylabel)
self._ylabel = None
grids = self._y_grid_label
ypoints_major, ypoints_minor = self._get_ticks(self.y_ticks_major,
self.y_ticks_minor,
self.ylog, self.ymin,
self.ymax)
self._ticks_majory = ypoints_major
self._ticks_minory = ypoints_minor
if not self.y_grid_label:
n_labels = 0
else:
n_labels = len(ypoints_major)
for k in range(n_labels, len(grids)):
self.remove_widget(grids[k])
del grids[n_labels:]
grid_len = len(grids)
grids.extend([None] * (n_labels - len(grids)))
for k in range(grid_len, n_labels):
grids[k] = Label(font_size=font_size, **self.label_options)
self.add_widget(grids[k])
return ypoints_major, ypoints_minor
def _redraw_size(self, *args):
# size a 4-tuple describing the bounding box in which we can draw
# graphs, it's (x0, y0, x1, y1), which correspond with the bottom left
# and top right corner locations, respectively
self._clear_buffer()
size = self._update_labels()
self.view_pos = self._plot_area.pos = (size[0], size[1])
self.view_size = self._plot_area.size = (
size[2] - size[0], size[3] - size[1])
if self.size[0] and self.size[1]:
self._fbo.size = self.size
else:
self._fbo.size = 1, 1 # gl errors otherwise
self._fbo_rect.texture = self._fbo.texture
self._fbo_rect.size = self.size
self._fbo_rect.pos = self.pos
self._background_rect.size = self.size
self._update_ticks(size)
self._update_plots(size)
def _clear_buffer(self, *largs):
fbo = self._fbo
fbo.bind()
fbo.clear_buffer()
fbo.release()
def add_plot(self, plot):
'''Add a new plot to this graph.
:Parameters:
`plot`:
Plot to add to this graph.
>>> graph = Graph()
>>> plot = MeshLinePlot(mode='line_strip', color=[1, 0, 0, 1])
>>> plot.points = [(x / 10., sin(x / 50.)) for x in range(-0, 101)]
>>> graph.add_plot(plot)
'''
if plot in self.plots:
return
add = self._plot_area.canvas.add
for instr in plot.get_drawings():
add(instr)
plot.bind(on_clear_plot=self._clear_buffer)
self.plots.append(plot)
def remove_plot(self, plot):
'''Remove a plot from this graph.
:Parameters:
`plot`:
Plot to remove from this graph.
>>> graph = Graph()
>>> plot = MeshLinePlot(mode='line_strip', color=[1, 0, 0, 1])
>>> plot.points = [(x / 10., sin(x / 50.)) for x in range(-0, 101)]
>>> graph.add_plot(plot)
>>> graph.remove_plot(plot)
'''
if plot not in self.plots:
return
remove = self._plot_area.canvas.remove
for instr in plot.get_drawings():
remove(instr)
plot.unbind(on_clear_plot=self._clear_buffer)
self.plots.remove(plot)
self._clear_buffer()
def collide_plot(self, x, y):
'''Determine if the given coordinates fall inside the plot area. Use
`x, y = self.to_widget(x, y, relative=True)` to first convert into
widget coordinates if it's in window coordinates because it's assumed
to be given in local widget coordinates, relative to the graph's pos.
:Parameters:
`x, y`:
The coordinates to test.
'''
adj_x, adj_y = x - self._plot_area.pos[0], y - self._plot_area.pos[1]
return 0 <= adj_x <= self._plot_area.size[0] \
and 0 <= adj_y <= self._plot_area.size[1]
def to_data(self, x, y):
'''Convert widget coords to data coords. Use
`x, y = self.to_widget(x, y, relative=True)` to first convert into
widget coordinates if it's in window coordinates because it's assumed
to be given in local widget coordinates, relative to the graph's pos.
:Parameters:
`x, y`:
The coordinates to convert.
If the graph has multiple axes, use :class:`Plot.unproject` instead.
'''
adj_x = float(x - self._plot_area.pos[0])
adj_y = float(y - self._plot_area.pos[1])
norm_x = adj_x / self._plot_area.size[0]
norm_y = adj_y / self._plot_area.size[1]
if self.xlog:
xmin, xmax = log10(self.xmin), log10(self.xmax)
conv_x = 10.**(norm_x * (xmax - xmin) + xmin)
else:
conv_x = norm_x * (self.xmax - self.xmin) + self.xmin
if self.ylog:
ymin, ymax = log10(self.ymin), log10(self.ymax)
conv_y = 10.**(norm_y * (ymax - ymin) + ymin)
else:
conv_y = norm_y * (self.ymax - self.ymin) + self.ymin
return [conv_x, conv_y]
xmin = NumericProperty(0.)
'''The x-axis minimum value.
If :data:`xlog` is True, xmin must be larger than zero.
:data:`xmin` is a :class:`~kivy.properties.NumericProperty`, defaults to 0.
'''
xmax = NumericProperty(100.)
'''The x-axis maximum value, larger than xmin.
:data:`xmax` is a :class:`~kivy.properties.NumericProperty`, defaults to 0.
'''
xlog = BooleanProperty(False)
'''Determines whether the x-axis should be displayed logarithmically (True)
or linearly (False).
:data:`xlog` is a :class:`~kivy.properties.BooleanProperty`, defaults
to False.
'''
x_ticks_major = BoundedNumericProperty(0, min=0)
'''Distance between major tick marks on the x-axis.
Determines the distance between the major tick marks. Major tick marks
start from min and re-occur at every ticks_major until :data:`xmax`.
If :data:`xmax` doesn't overlap with a integer multiple of ticks_major,
no tick will occur at :data:`xmax`. Zero indicates no tick marks.
If :data:`xlog` is true, then this indicates the distance between ticks
in multiples of current decade. E.g. if :data:`xmin` is 0.1 and
ticks_major is 0.1, it means there will be a tick at every 10th of the
decade, i.e. 0.1 ... 0.9, 1, 2... If it is 0.3, the ticks will occur at
0.1, 0.3, 0.6, 0.9, 2, 5, 8, 10. You'll notice that it went from 8 to 10
instead of to 20, that's so that we can say 0.5 and have ticks at every
half decade, e.g. 0.1, 0.5, 1, 5, 10, 50... Similarly, if ticks_major is
1.5, there will be ticks at 0.1, 5, 100, 5,000... Also notice, that there's
always a major tick at the start. Finally, if e.g. :data:`xmin` is 0.6
and this 0.5 there will be ticks at 0.6, 1, 5...
:data:`x_ticks_major` is a
:class:`~kivy.properties.BoundedNumericProperty`, defaults to 0.
'''
x_ticks_minor = BoundedNumericProperty(0, min=0)
'''The number of sub-intervals that divide x_ticks_major.
Determines the number of sub-intervals into which ticks_major is divided,
if non-zero. The actual number of minor ticks between the major ticks is
ticks_minor - 1. Only used if ticks_major is non-zero. If there's no major
tick at xmax then the number of minor ticks after the last major
tick will be however many ticks fit until xmax.
If self.xlog is true, then this indicates the number of intervals the
distance between major ticks is divided. The result is the number of
multiples of decades between ticks. I.e. if ticks_minor is 10, then if
ticks_major is 1, there will be ticks at 0.1, 0.2...0.9, 1, 2, 3... If
ticks_major is 0.3, ticks will occur at 0.1, 0.12, 0.15, 0.18... Finally,
as is common, if ticks major is 1, and ticks minor is 5, there will be
ticks at 0.1, 0.2, 0.4... 0.8, 1, 2...
:data:`x_ticks_minor` is a
:class:`~kivy.properties.BoundedNumericProperty`, defaults to 0.
'''
x_grid = BooleanProperty(False)
'''Determines whether the x-axis has tick marks or a full grid.
If :data:`x_ticks_major` is non-zero, then if x_grid is False tick marks
will be displayed at every major tick. If x_grid is True, instead of ticks,
a vertical line will be displayed at every major tick.
:data:`x_grid` is a :class:`~kivy.properties.BooleanProperty`, defaults
to False.
'''
x_grid_label = BooleanProperty(False)
'''Whether labels should be displayed beneath each major tick. If true,
each major tick will have a label containing the axis value.
:data:`x_grid_label` is a :class:`~kivy.properties.BooleanProperty`,
defaults to False.
'''
xlabel = StringProperty('')
'''The label for the x-axis. If not empty it is displayed in the center of
the axis.
:data:`xlabel` is a :class:`~kivy.properties.StringProperty`,
defaults to ''.
'''
ymin = NumericProperty(0.)
'''The y-axis minimum value.
If :data:`ylog` is True, ymin must be larger than zero.
:data:`ymin` is a :class:`~kivy.properties.NumericProperty`, defaults to 0.
'''
ymax = NumericProperty(100.)
'''The y-axis maximum value, larger than ymin.
:data:`ymax` is a :class:`~kivy.properties.NumericProperty`, defaults to 0.
'''
ylog = BooleanProperty(False)
'''Determines whether the y-axis should be displayed logarithmically (True)
or linearly (False).
:data:`ylog` is a :class:`~kivy.properties.BooleanProperty`, defaults
to False.
'''
y_ticks_major = BoundedNumericProperty(0, min=0)
'''Distance between major tick marks. See :data:`x_ticks_major`.
:data:`y_ticks_major` is a
:class:`~kivy.properties.BoundedNumericProperty`, defaults to 0.
'''
y_ticks_minor = BoundedNumericProperty(0, min=0)
'''The number of sub-intervals that divide ticks_major.
See :data:`x_ticks_minor`.
:data:`y_ticks_minor` is a
:class:`~kivy.properties.BoundedNumericProperty`, defaults to 0.
'''
y_grid = BooleanProperty(False)
'''Determines whether the y-axis has tick marks or a full grid. See
:data:`x_grid`.
:data:`y_grid` is a :class:`~kivy.properties.BooleanProperty`, defaults
to False.
'''
y_grid_label = BooleanProperty(False)
'''Whether labels should be displayed beneath each major tick. If true,
each major tick will have a label containing the axis value.
:data:`y_grid_label` is a :class:`~kivy.properties.BooleanProperty`,
defaults to False.
'''
ylabel = StringProperty('')
'''The label for the y-axis. If not empty it is displayed in the center of
the axis.
:data:`ylabel` is a :class:`~kivy.properties.StringProperty`,
defaults to ''.
'''
padding = NumericProperty('5dp')
'''Padding distances between the labels, axes titles and graph, as
well between the widget and the objects near the boundaries.
:data:`padding` is a :class:`~kivy.properties.NumericProperty`, defaults
to 5dp.
'''
font_size = NumericProperty('15sp')
'''Font size of the labels.
:data:`font_size` is a :class:`~kivy.properties.NumericProperty`, defaults
to 15sp.
'''
x_ticks_angle = NumericProperty(0)
'''Rotate angle of the x-axis tick marks.
:data:`x_ticks_angle` is a :class:`~kivy.properties.NumericProperty`,
defaults to 0.
'''
precision = StringProperty('%g')
'''Determines the numerical precision of the tick mark labels. This value
governs how the numbers are converted into string representation. Accepted
values are those listed in Python's manual in the
"String Formatting Operations" section.
:data:`precision` is a :class:`~kivy.properties.StringProperty`, defaults
to '%g'.
'''
draw_border = BooleanProperty(True)
'''Whether a border is drawn around the canvas of the graph where the
plots are displayed.
:data:`draw_border` is a :class:`~kivy.properties.BooleanProperty`,
defaults to True.
'''
plots = ListProperty([])
'''Holds a list of all the plots in the graph. To add and remove plots
from the graph use :data:`add_plot` and :data:`add_plot`. Do not add
directly edit this list.
:data:`plots` is a :class:`~kivy.properties.ListProperty`,
defaults to [].
'''
view_size = ObjectProperty((0, 0))
'''The size of the graph viewing area - the area where the plots are
displayed, excluding labels etc.
'''
view_pos = ObjectProperty((0, 0))
'''The pos of the graph viewing area - the area where the plots are
displayed, excluding labels etc. It is relative to the graph's pos.
'''

795
kivycharts/graph/plot.py
View File

@ -1,795 +0,0 @@
from kivy.uix.widget import Widget
from kivy.uix.label import Label
from kivy.uix.stencilview import StencilView
from kivy.properties import NumericProperty, BooleanProperty,\
BoundedNumericProperty, StringProperty, ListProperty, ObjectProperty,\
DictProperty, AliasProperty
from kivy.clock import Clock
from kivy.graphics import Mesh, Color, Rectangle, Point
from kivy.graphics import Fbo
from kivy.graphics.texture import Texture
from kivy.event import EventDispatcher
from kivy.lang import Builder
from kivy.logger import Logger
from kivy import metrics
from math import log10, floor, ceil
from decimal import Decimal
from itertools import chain
try:
import numpy as np
except ImportError as e:
np = None
class Plot(EventDispatcher):
'''Plot class, see module documentation for more information.
:Events:
`on_clear_plot`
Fired before a plot updates the display and lets the fbo know that
it should clear the old drawings.
..versionadded:: 0.4
'''
__events__ = ('on_clear_plot', )
# most recent values of the params used to draw the plot
params = DictProperty({'xlog': False, 'xmin': 0, 'xmax': 100,
'ylog': False, 'ymin': 0, 'ymax': 100,
'size': (0, 0, 0, 0)})
color = ListProperty([1, 1, 1, 1])
'''Color of the plot.
'''
points = ListProperty([])
'''List of (x, y) points to be displayed in the plot.
The elements of points are 2-tuples, (x, y). The points are displayed
based on the mode setting.
:data:`points` is a :class:`~kivy.properties.ListProperty`, defaults to
[].
'''
x_axis = NumericProperty(0)
'''Index of the X axis to use, defaults to 0
'''
y_axis = NumericProperty(0)
'''Index of the Y axis to use, defaults to 0
'''
def __init__(self, **kwargs):
super(Plot, self).__init__(**kwargs)
self.ask_draw = Clock.create_trigger(self.draw)
self.bind(params=self.ask_draw, points=self.ask_draw)
self._drawings = self.create_drawings()
def funcx(self):
"""Return a function that convert or not the X value according to plot
prameters"""
return log10 if self.params["xlog"] else lambda x: x
def funcy(self):
"""Return a function that convert or not the Y value according to plot
prameters"""
return log10 if self.params["ylog"] else lambda y: y
def x_px(self):
"""Return a function that convert the X value of the graph to the
pixel coordinate on the plot, according to the plot settings and axis
settings. It's relative to the graph pos.
"""
funcx = self.funcx()
params = self.params
size = params["size"]
xmin = funcx(params["xmin"])
xmax = funcx(params["xmax"])
ratiox = (size[2] - size[0]) / float(xmax - xmin)
return lambda x: (funcx(x) - xmin) * ratiox + size[0]
def y_px(self):
"""Return a function that convert the Y value of the graph to the
pixel coordinate on the plot, according to the plot settings and axis
settings. The returned value is relative to the graph pos.
"""
funcy = self.funcy()
params = self.params
size = params["size"]
ymin = funcy(params["ymin"])
ymax = funcy(params["ymax"])
ratioy = (size[3] - size[1]) / float(ymax - ymin)
return lambda y: (funcy(y) - ymin) * ratioy + size[1]
def unproject(self, x, y):
"""Return a function that unproject a pixel to a X/Y value on the plot
(works only for linear, not log yet). `x`, `y`, is relative to the
graph pos, so the graph's pos needs to be subtracted from x, y before
passing it in.
"""
params = self.params
size = params["size"]
xmin = params["xmin"]
xmax = params["xmax"]
ymin = params["ymin"]
ymax = params["ymax"]
ratiox = (size[2] - size[0]) / float(xmax - xmin)
ratioy = (size[3] - size[1]) / float(ymax - ymin)
x0 = (x - size[0]) / ratiox + xmin
y0 = (y - size[1]) / ratioy + ymin
return x0, y0
def get_px_bounds(self):
"""Returns a dict containing the pixels bounds from the plot parameters.
The returned values are relative to the graph pos.
"""
params = self.params
x_px = self.x_px()
y_px = self.y_px()
return {
"xmin": x_px(params["xmin"]),
"xmax": x_px(params["xmax"]),
"ymin": y_px(params["ymin"]),
"ymax": y_px(params["ymax"]),
}
def update(self, xlog, xmin, xmax, ylog, ymin, ymax, size):
'''Called by graph whenever any of the parameters
change. The plot should be recalculated then.
log, min, max indicate the axis settings.
size a 4-tuple describing the bounding box in which we can draw
graphs, it's (x0, y0, x1, y1), which correspond with the bottom left
and top right corner locations, respectively.
'''
self.params.update({
'xlog': xlog, 'xmin': xmin, 'xmax': xmax, 'ylog': ylog,
'ymin': ymin, 'ymax': ymax, 'size': size})
def get_group(self):
'''returns a string which is unique and is the group name given to all
the instructions returned by _get_drawings. Graph uses this to remove
these instructions when needed.
'''
return ''
def get_drawings(self):
'''returns a list of canvas instructions that will be added to the
graph's canvas.
'''
if isinstance(self._drawings, (tuple, list)):
return self._drawings
return []
def create_drawings(self):
'''called once to create all the canvas instructions needed for the
plot
'''
pass
def draw(self, *largs):
'''draw the plot according to the params. It dispatches on_clear_plot
so derived classes should call super before updating.
'''
self.dispatch('on_clear_plot')
def iterate_points(self):
'''Iterate on all the points adjusted to the graph settings
'''
x_px = self.x_px()
y_px = self.y_px()
for x, y in self.points:
yield x_px(x), y_px(y)
def on_clear_plot(self, *largs):
pass
# compatibility layer
_update = update
_get_drawings = get_drawings
_params = params
class MeshLinePlot(Plot):
'''MeshLinePlot class which displays a set of points similar to a mesh.
'''
def _set_mode(self, value):
if hasattr(self, '_mesh'):
self._mesh.mode = value
mode = AliasProperty(lambda self: self._mesh.mode, _set_mode)
'''VBO Mode used for drawing the points. Can be one of: 'points',
'line_strip', 'line_loop', 'lines', 'triangle_strip', 'triangle_fan'.
See :class:`~kivy.graphics.Mesh` for more details.
Defaults to 'line_strip'.
'''
def create_drawings(self):
self._color = Color(*self.color)
self._mesh = Mesh(mode='line_strip')
self.bind(
color=lambda instr, value: setattr(self._color, "rgba", value))
return [self._color, self._mesh]
def draw(self, *args):
super(MeshLinePlot, self).draw(*args)
self.plot_mesh()
def plot_mesh(self):
points = [p for p in self.iterate_points()]
mesh, vert, _ = self.set_mesh_size(len(points))
for k, (x, y) in enumerate(points):
vert[k * 4] = x
vert[k * 4 + 1] = y
mesh.vertices = vert
def set_mesh_size(self, size):
mesh = self._mesh
vert = mesh.vertices
ind = mesh.indices
diff = size - len(vert) // 4
if diff < 0:
del vert[4 * size:]
del ind[size:]
elif diff > 0:
ind.extend(range(len(ind), len(ind) + diff))
vert.extend([0] * (diff * 4))
mesh.vertices = vert
return mesh, vert, ind
class MeshStemPlot(MeshLinePlot):
'''MeshStemPlot uses the MeshLinePlot class to draw a stem plot. The data
provided is graphed from origin to the data point.
'''
def plot_mesh(self):
points = [p for p in self.iterate_points()]
mesh, vert, _ = self.set_mesh_size(len(points) * 2)
y0 = self.y_px()(0)
for k, (x, y) in enumerate(self.iterate_points()):
vert[k * 8] = x
vert[k * 8 + 1] = y0
vert[k * 8 + 4] = x
vert[k * 8 + 5] = y
mesh.vertices = vert
class LinePlot(Plot):
"""LinePlot draws using a standard Line object.
"""
line_width = NumericProperty(1)
def create_drawings(self):
from kivy.graphics import Line, RenderContext
self._grc = RenderContext(
use_parent_modelview=True,
use_parent_projection=True)
with self._grc:
self._gcolor = Color(*self.color)
self._gline = Line(
points=[], cap='none',
width=self.line_width, joint='round')
return [self._grc]
def draw(self, *args):
super(LinePlot, self).draw(*args)
# flatten the list
points = []
for x, y in self.iterate_points():
points += [x, y]
self._gline.points = points
def on_line_width(self, *largs):
if hasattr(self, "_gline"):
self._gline.width = self.line_width
class SmoothLinePlot(Plot):
'''Smooth Plot class, see module documentation for more information.
This plot use a specific Fragment shader for a custom anti aliasing.
'''
SMOOTH_FS = '''
$HEADER$
void main(void) {
float edgewidth = 0.015625 * 64.;
float t = texture2D(texture0, tex_coord0).r;
float e = smoothstep(0., edgewidth, t);
gl_FragColor = frag_color * vec4(1, 1, 1, e);
}
'''
# XXX This gradient data is a 64x1 RGB image, and
# values goes from 0 -> 255 -> 0.
GRADIENT_DATA = (
b"\x00\x00\x00\x07\x07\x07\x0f\x0f\x0f\x17\x17\x17\x1f\x1f\x1f"
b"'''///777???GGGOOOWWW___gggooowww\x7f\x7f\x7f\x87\x87\x87"
b"\x8f\x8f\x8f\x97\x97\x97\x9f\x9f\x9f\xa7\xa7\xa7\xaf\xaf\xaf"
b"\xb7\xb7\xb7\xbf\xbf\xbf\xc7\xc7\xc7\xcf\xcf\xcf\xd7\xd7\xd7"
b"\xdf\xdf\xdf\xe7\xe7\xe7\xef\xef\xef\xf7\xf7\xf7\xff\xff\xff"
b"\xf6\xf6\xf6\xee\xee\xee\xe6\xe6\xe6\xde\xde\xde\xd5\xd5\xd5"
b"\xcd\xcd\xcd\xc5\xc5\xc5\xbd\xbd\xbd\xb4\xb4\xb4\xac\xac\xac"
b"\xa4\xa4\xa4\x9c\x9c\x9c\x94\x94\x94\x8b\x8b\x8b\x83\x83\x83"
b"{{{sssjjjbbbZZZRRRJJJAAA999111))) \x18\x18\x18\x10\x10\x10"
b"\x08\x08\x08\x00\x00\x00")
def create_drawings(self):
from kivy.graphics import Line, RenderContext
# very first time, create a texture for the shader
if not hasattr(SmoothLinePlot, '_texture'):
tex = Texture.create(size=(1, 64), colorfmt='rgb')
tex.add_reload_observer(SmoothLinePlot._smooth_reload_observer)
SmoothLinePlot._texture = tex
SmoothLinePlot._smooth_reload_observer(tex)
self._grc = RenderContext(
fs=SmoothLinePlot.SMOOTH_FS,
use_parent_modelview=True,
use_parent_projection=True)
with self._grc:
self._gcolor = Color(*self.color)
self._gline = Line(
points=[], cap='none', width=2.,
texture=SmoothLinePlot._texture)
return [self._grc]
@staticmethod
def _smooth_reload_observer(texture):
texture.blit_buffer(SmoothLinePlot.GRADIENT_DATA, colorfmt="rgb")
def draw(self, *args):
super(SmoothLinePlot, self).draw(*args)
# flatten the list
points = []
for x, y in self.iterate_points():
points += [x, y]
self._gline.points = points
class ContourPlot(Plot):
"""
ContourPlot visualizes 3 dimensional data as an intensity map image.
The user must first specify 'xrange' and 'yrange' (tuples of min,max) and
then 'data', the intensity values.
`data`, is a MxN matrix, where the first dimension of size M specifies the
`y` values, and the second dimension of size N specifies the `x` values.
Axis Y and X values are assumed to be linearly spaced values from
xrange/yrange and the dimensions of 'data', `MxN`, respectively.
The color values are automatically scaled to the min and max z range of the
data set.
"""
_image = ObjectProperty(None)
data = ObjectProperty(None, force_dispatch=True)
xrange = ListProperty([0, 100])
yrange = ListProperty([0, 100])
def __init__(self, **kwargs):
super(ContourPlot, self).__init__(**kwargs)
self.bind(data=self.ask_draw, xrange=self.ask_draw,
yrange=self.ask_draw)
def create_drawings(self):
self._image = Rectangle()
self._color = Color([1, 1, 1, 1])
self.bind(
color=lambda instr, value: setattr(self._color, 'rgba', value))
return [self._color, self._image]
def draw(self, *args):
super(ContourPlot, self).draw(*args)
data = self.data
xdim, ydim = data.shape
# Find the minimum and maximum z values
zmax = data.max()
zmin = data.min()
rgb_scale_factor = 1.0 / (zmax - zmin) * 255
# Scale the z values into RGB data
buf = np.array(data, dtype=float, copy=True)
np.subtract(buf, zmin, out=buf)
np.multiply(buf, rgb_scale_factor, out=buf)
# Duplicate into 3 dimensions (RGB) and convert to byte array
buf = np.asarray(buf, dtype=np.uint8)
buf = np.expand_dims(buf, axis=2)
buf = np.concatenate((buf, buf, buf), axis=2)
buf = np.reshape(buf, (xdim, ydim, 3))
charbuf = bytearray(np.reshape(buf, (buf.size)))
self._texture = Texture.create(size=(xdim, ydim), colorfmt='rgb')
self._texture.blit_buffer(charbuf, colorfmt='rgb', bufferfmt='ubyte')
image = self._image
image.texture = self._texture
x_px = self.x_px()
y_px = self.y_px()
bl = x_px(self.xrange[0]), y_px(self.yrange[0])
tr = x_px(self.xrange[1]), y_px(self.yrange[1])
image.pos = bl
w = tr[0] - bl[0]
h = tr[1] - bl[1]
image.size = (w, h)
class BarPlot(Plot):
'''BarPlot class which displays a bar graph.
'''
bar_width = NumericProperty(1)
bar_spacing = NumericProperty(1.)
graph = ObjectProperty(allownone=True)
def __init__(self, *ar, **kw):
super(BarPlot, self).__init__(*ar, **kw)
self.bind(bar_width=self.ask_draw)
self.bind(points=self.update_bar_width)
self.bind(graph=self.update_bar_width)
def update_bar_width(self, *ar):
if not self.graph:
return
if len(self.points) < 2:
return
if self.graph.xmax == self.graph.xmin:
return
point_width = (
len(self.points) *
float(abs(self.graph.xmax) + abs(self.graph.xmin)) /
float(abs(max(self.points)[0]) + abs(min(self.points)[0])))
if not self.points:
self.bar_width = 1
else:
self.bar_width = (
(self.graph.width - self.graph.padding) /
point_width * self.bar_spacing)
def create_drawings(self):
self._color = Color(*self.color)
self._mesh = Mesh()
self.bind(
color=lambda instr, value: setattr(self._color, 'rgba', value))
return [self._color, self._mesh]
def draw(self, *args):
super(BarPlot, self).draw(*args)
points = self.points
# The mesh only supports (2^16) - 1 indices, so...
if len(points) * 6 > 65535:
Logger.error(
"BarPlot: cannot support more than 10922 points. "
"Ignoring extra points.")
points = points[:10922]
point_len = len(points)
mesh = self._mesh
mesh.mode = 'triangles'
vert = mesh.vertices
ind = mesh.indices
diff = len(points) * 6 - len(vert) // 4
if diff < 0:
del vert[24 * point_len:]
del ind[point_len:]
elif diff > 0:
ind.extend(range(len(ind), len(ind) + diff))
vert.extend([0] * (diff * 4))
bounds = self.get_px_bounds()
x_px = self.x_px()
y_px = self.y_px()
ymin = y_px(0)
bar_width = self.bar_width
if bar_width < 0:
bar_width = x_px(bar_width) - bounds["xmin"]
for k in range(point_len):
p = points[k]
x1 = x_px(p[0])
x2 = x1 + bar_width
y1 = ymin
y2 = y_px(p[1])
idx = k * 24
# first triangle
vert[idx] = x1
vert[idx + 1] = y2
vert[idx + 4] = x1
vert[idx + 5] = y1
vert[idx + 8] = x2
vert[idx + 9] = y1
# second triangle
vert[idx + 12] = x1
vert[idx + 13] = y2
vert[idx + 16] = x2
vert[idx + 17] = y2
vert[idx + 20] = x2
vert[idx + 21] = y1
mesh.vertices = vert
def _unbind_graph(self, graph):
graph.unbind(width=self.update_bar_width,
xmin=self.update_bar_width,
ymin=self.update_bar_width)
def bind_to_graph(self, graph):
old_graph = self.graph
if old_graph:
# unbind from the old one
self._unbind_graph(old_graph)
# bind to the new one
self.graph = graph
graph.bind(width=self.update_bar_width,
xmin=self.update_bar_width,
ymin=self.update_bar_width)
def unbind_from_graph(self):
if self.graph:
self._unbind_graph(self.graph)
class HBar(MeshLinePlot):
'''HBar draw horizontal bar on all the Y points provided
'''
def plot_mesh(self, *args):
points = self.points
mesh, vert, ind = self.set_mesh_size(len(points) * 2)
mesh.mode = "lines"
bounds = self.get_px_bounds()
px_xmin = bounds["xmin"]
px_xmax = bounds["xmax"]
y_px = self.y_px()
for k, y in enumerate(points):
y = y_px(y)
vert[k * 8] = px_xmin
vert[k * 8 + 1] = y
vert[k * 8 + 4] = px_xmax
vert[k * 8 + 5] = y
mesh.vertices = vert
class VBar(MeshLinePlot):
'''VBar draw vertical bar on all the X points provided
'''
def plot_mesh(self, *args):
points = self.points
mesh, vert, ind = self.set_mesh_size(len(points) * 2)
mesh.mode = "lines"
bounds = self.get_px_bounds()
px_ymin = bounds["ymin"]
px_ymax = bounds["ymax"]
x_px = self.x_px()
for k, x in enumerate(points):
x = x_px(x)
vert[k * 8] = x
vert[k * 8 + 1] = px_ymin
vert[k * 8 + 4] = x
vert[k * 8 + 5] = px_ymax
mesh.vertices = vert
class ScatterPlot(Plot):
"""
ScatterPlot draws using a standard Point object.
The pointsize can be controlled with :attr:`point_size`.
>>> plot = ScatterPlot(color=[1, 0, 0, 1], point_size=5)
"""
point_size = NumericProperty(1)
"""The point size of the scatter points. Defaults to 1.
"""
def create_drawings(self):
from kivy.graphics import Point, RenderContext
self._points_context = RenderContext(
use_parent_modelview=True,
use_parent_projection=True)
with self._points_context:
self._gcolor = Color(*self.color)
self._gpts = Point(points=[], pointsize=self.point_size)
return [self._points_context]
def draw(self, *args):
super(ScatterPlot, self).draw(*args)
# flatten the list
self._gpts.points = list(chain(*self.iterate_points()))
def on_point_size(self, *largs):
if hasattr(self, "_gpts"):
self._gpts.pointsize = self.point_size
class PointPlot(Plot):
'''Displays a set of points.
'''
point_size = NumericProperty(1)
'''
Defaults to 1.
'''
_color = None
_point = None
def __init__(self, **kwargs):
super(PointPlot, self).__init__(**kwargs)
def update_size(*largs):
if self._point:
self._point.pointsize = self.point_size
self.fbind('point_size', update_size)
def update_color(*largs):
if self._color:
self._color.rgba = self.color
self.fbind('color', update_color)
def create_drawings(self):
self._color = Color(*self.color)
self._point = Point(pointsize=self.point_size)
return [self._color, self._point]
def draw(self, *args):
super(PointPlot, self).draw(*args)
self._point.points = [v for p in self.iterate_points() for v in p]
if __name__ == '__main__':
import itertools
from math import sin, cos, pi
from random import randrange
from kivy.utils import get_color_from_hex as rgb
from kivy.uix.boxlayout import BoxLayout
from kivy.app import App
class TestApp(App):
def build(self):
b = BoxLayout(orientation='vertical')
# example of a custom theme
colors = itertools.cycle([
rgb('7dac9f'), rgb('dc7062'), rgb('66a8d4'), rgb('e5b060')])
graph_theme = {
'label_options': {
'color': rgb('444444'), # color of tick labels and titles
'bold': True},
'background_color': rgb('f8f8f2'), # canvas background color
'tick_color': rgb('808080'), # ticks and grid
'border_color': rgb('808080')} # border drawn around each graph
graph = Graph(
xlabel='Cheese',
ylabel='Apples',
x_ticks_minor=5,
x_ticks_major=25,
y_ticks_major=1,
y_grid_label=True,
x_grid_label=True,
padding=5,
xlog=False,
ylog=False,
x_grid=True,
y_grid=True,
xmin=-50,
xmax=50,
ymin=-1,
ymax=1,
**graph_theme)
plot = SmoothLinePlot(color=next(colors))
plot.points = [(x / 10., sin(x / 50.)) for x in range(-500, 501)]
# for efficiency, the x range matches xmin, xmax
graph.add_plot(plot)
plot = MeshLinePlot(color=next(colors))
plot.points = [(x / 10., cos(x / 50.)) for x in range(-500, 501)]
graph.add_plot(plot)
self.plot = plot # this is the moving graph, so keep a reference
plot = MeshStemPlot(color=next(colors))
graph.add_plot(plot)
plot.points = [(x, x / 50.) for x in range(-50, 51)]
plot = BarPlot(color=next(colors), bar_spacing=.72)
graph.add_plot(plot)
plot.bind_to_graph(graph)
plot.points = [(x, .1 + randrange(10) / 10.) for x in range(-50, 1)]
Clock.schedule_interval(self.update_points, 1 / 60.)
graph2 = Graph(
xlabel='Position (m)',
ylabel='Time (s)',
x_ticks_minor=0,
x_ticks_major=1,
y_ticks_major=10,
y_grid_label=True,
x_grid_label=True,
padding=5,
xlog=False,
ylog=False,
xmin=0,
ymin=0,
**graph_theme)
b.add_widget(graph)
if np is not None:
(xbounds, ybounds, data) = self.make_contour_data()
# This is required to fit the graph to the data extents
graph2.xmin, graph2.xmax = xbounds
graph2.ymin, graph2.ymax = ybounds
plot = ContourPlot()
plot.data = data
plot.xrange = xbounds
plot.yrange = ybounds
plot.color = [1, 0.7, 0.2, 1]
graph2.add_plot(plot)
b.add_widget(graph2)
self.contourplot = plot
Clock.schedule_interval(self.update_contour, 1 / 60.)
# Test the scatter plot
plot = ScatterPlot(color=next(colors), point_size=5)
graph.add_plot(plot)
plot.points = [(x, .1 + randrange(10) / 10.) for x in range(-50, 1)]
return b
def make_contour_data(self, ts=0):
omega = 2 * pi / 30
k = (2 * pi) / 2.0
ts = sin(ts * 2) + 1.5 # emperically determined 'pretty' values
npoints = 100
data = np.ones((npoints, npoints))
position = [ii * 0.1 for ii in range(npoints)]
time = [(ii % 100) * 0.6 for ii in range(npoints)]
for ii, t in enumerate(time):
for jj, x in enumerate(position):
data[ii, jj] = sin(
k * x + omega * t) + sin(-k * x + omega * t) / ts
return (0, max(position)), (0, max(time)), data
def update_points(self, *args):
self.plot.points = [
(x / 10., cos(Clock.get_time() + x / 50.))
for x in range(-500, 501)]
def update_contour(self, *args):
_, _, self.contourplot.data[:] = self.make_contour_data(
Clock.get_time())
# this does not trigger an update, because we replace the
# values of the arry and do not change the object.
# However, we cannot do "...data = make_contour_data()" as
# kivy will try to check for the identity of the new and
# old values. In numpy, 'nd1 == nd2' leads to an error
# (you have to use np.all). Ideally, property should be patched
# for this.
self.contourplot.ask_draw()
TestApp().run()

130
kivycharts/line.py
View File

@ -1,130 +0,0 @@
from kivy.properties import DictProperty, ListProperty, \
StringProperty, NumericProperty
from kivy.factory import Factory
from kivy.utils import get_color_from_hex as rgb
from kivyblocks.scrollpanel import ScrollPanel
from kivyblocks.utils import SUPER, CSize
from kivyblocks.threadcall import HttpClient
from kivyblocks.baseWidget import VBox
from .graph import Graph
from .graph import Plot, LinePlot, SmoothLinePlot
build_plots = {
'fold-line':LinePlot,
'smooth-line':SmoothLinePlot
}
class LineChart(VBox):
"""
series = [
{
yfield:xxxx,
charttype:smooth-line, fold-line, ...
color:
}
]
"""
dataurl = StringProperty(None)
params = DictProperty({})
method = StringProperty('get')
xlabel = StringProperty(None)
ylabel = StringProperty(None)
xfield = StringProperty(None)
x_ticks_angle = NumericProperty(45)
series = ListProperty(None)
data = ListProperty(None)
def __init__(self, **kw):
self.graph = None
SUPER(LineChart, self, kw)
def on_dataurl(self, o, url=None):
if not self.dataurl:
return
hc = HttpClient()
x = hc(self.dataurl,
method=self.method,
params=self.params)
self.data = x['rows']
self.url_call = True
def on_params(self, o, params=None):
if not self.url_call:
return
self.on_dataurl(None, None)
def build_plot(self, serie):
type = serie.get('charttype', 'smooth-line')
plotKlass = build_plots.get(type)
p = plotKlass(color=serie['color'])
return p
def on_data(self, o, data=None):
graph_theme = {
'label_options': {
'color': rgb('444444'), # color of tick labels and titles
'bold': True},
'background_color': rgb('f8f8f2'), # canvas background color
'tick_color': rgb('808080'), # ticks and grid
'border_color': rgb('808080')} # border drawn around each graph
xcnt = len(self.data)
ymin, ymax = 9999999999999999, 0
xlabel_text = [ r.get(self.xfield) for r in self.data ]
xlabel_text.insert(0,'0')
for s in self.series:
points = [ (i, r.get(s['yfield'])) \
for i,r in enumerate(self.data) ]
min1 = min([p[1] for p in points])
max1 = max([p[1] for p in points])
if max1 >ymax:
ymax = max1
if min1 < ymin:
ymin = min1
s['points'] = points
yadd = int((ymax - ymin) / 8)
ymin = int(ymin - yadd)
ymax = int(ymax + yadd)
y_ticks_major = int((ymax-ymin)/4)
x_ticks_major = int(xcnt/10)
xlabel = self.xlabel or self.xfield
ylabel = self.ylabel
if not self.graph:
self.graph = Graph(
xlabel = self.xlabel or self.xfield,
ylabel = self.ylabel,
y_ticks_major = int((ymax-ymin)/4),
x_ticks_major = int(xcnt/10),
ymin = ymin,
ymax = ymax,
xmin = 0,
xmax = xcnt,
y_grid_label=True,
x_grid_label=True,
xlog = False,
ylog = False,
x_grid = True,
y_grid = True,
padding = 5,
**graph_theme)
self.add_widget(self.graph)
else:
self.graph.xlabel = xlabel
self.graph.ylabel = ylabel
self.graph.ymin = ymin
self.graph.ymax = ymax
self.graph.xmin = 0
self.graph.xmax = xmax
self.graph.y_ticks_major = y_ticks_major
self.graph.x_ticks_major = x_ticks_major
for s in self.series:
s['plot'] = self.build_plot(s)
s['plot'].points = s['points']
self.graph.add_plot(s['plot'])
self.graph.x_grid_texts = xlabel_text
self.graph.x_ticks_angle = self.x_ticks_angle
Factory.register('LineChart', LineChart)

1
kivycharts/version.py
View File

@ -1 +0,0 @@
__version__ = '0.0.9'

2
requirements.txt
View File

@ -1,10 +1,10 @@
jinja2 jinja2
kivy kivy
kivyblocks
ffpyplayer ffpyplayer
qrcode qrcode
pillow pillow
requests requests
plyer plyer
python-osc
bs4 bs4
lxml lxml

36
setup.py
View File

@ -1,37 +1,43 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from kivycharts.version import __version__
import codecs import codecs
try: from distutils.core import setup
from setuptools import setup from setuptools import setup, find_packages
except ImportError: from Cython.Build import cythonize
from distutils.core import setup from version import version
# usage: # usage:
# python setup.py bdist_wininst generate a window executable file # python setup.py bdist_wininst generate a window executable file
# python setup.py bdist_egg generate a egg file # python setup.py bdist_egg generate a egg file
# Release information about eway # Release information about eway
# version = "0.0.4"
description = "kivy charts is a tool to build kivy data plot" description = "kivy charts is a tool to build kivy data plot"
author = "yumoqing" author = "yumoqing"
email = "yumoqing@icloud.com" email = "yumoqing@icloud.com"
version = __version__
depandent_packages = [] depandent_packages = []
with codecs.open('./requirements.txt', 'r', 'utf-8') as f: with codecs.open('./requirements.txt', 'r', 'utf-8') as f:
b = f.read() b = f.read()
b = ''.join(b.split('\r')) depandent_packages = b.split(',')
depandent_packages = b.split('\n')
print('########depandent_packages=', depandent_packages)
packages=find_packages()
package_data = { package_data = {
"":[ "kivyblocks":[
"*.txt" 'imgs/*.png',
] 'imgs/*.atlas',
'imgs/*.gif',
'imgs/*.jpg',
'ttf/*.ttf',
'ui/*.uidesc',
],
} }
setup( setup(
name="kivycharts", name="kivycharts",
ext_modules= [ ext_modules=cythonize(
], [
]),
version=version, version=version,
# uncomment the following lines if you fill them out in release.py # uncomment the following lines if you fill them out in release.py
@ -40,7 +46,7 @@ setup(
author_email=email, author_email=email,
install_requires=depandent_packages, install_requires=depandent_packages,
packages=[ 'kivycharts' ], packages=packages,
package_data=package_data, package_data=package_data,
keywords = [ keywords = [
], ],

147
test/tgraph.py
View File

@ -1,147 +0,0 @@
from kivycharts.graph import *
from kivy.clock import Clock
import numpy as np
if __name__ == '__main__':
import itertools
from math import sin, cos, pi
from random import randrange
from kivy.utils import get_color_from_hex as rgb
from kivy.uix.boxlayout import BoxLayout
from kivy.app import App
class TestApp(App):
def build(self):
b = BoxLayout(orientation='vertical')
# example of a custom theme
colors = itertools.cycle([
rgb('0000FF'), rgb('dc7062'), rgb('66a8d4'), rgb('e5b060')])
graph_theme = {
'label_options': {
'color': rgb('444444'), # color of tick labels and titles
'bold': True},
'background_color': rgb('f8f8f2'), # canvas background color
'tick_color': rgb('808080'), # ticks and grid
'border_color': rgb('808080')} # border drawn around each graph
graph = Graph(
xlabel='Cheese',
ylabel='Apples',
# x_ticks_minor=5,
# x_ticks_major=25,
x_ticks_major=5,
y_ticks_major=1,
y_grid_label=True,
x_grid_label=True,
padding=5,
xlog=False,
ylog=False,
x_grid=True,
y_grid=True,
xmin=-50,
xmax=50,
ymin=-1,
ymax=1,
**graph_theme)
"""
c = next(colors)
print(c)
plot = SmoothLinePlot(color=c)
plot.points = [(x / 10., sin(x / 50.)) for x in range(-500, 501)]
# for efficiency, the x range matches xmin, xmax
graph.add_plot(plot)
"""
plot = MeshLinePlot(color=next(colors))
plot.points = [(x / 10., cos(x / 50.)) for x in range(-500, 501)]
graph.add_plot(plot)
self.plot = plot # this is the moving graph, so keep a reference
"""
plot = MeshStemPlot(color=next(colors))
graph.add_plot(plot)
plot.points = [(x, x / 50.) for x in range(-50, 51)]
"""
plot = BarPlot(color=next(colors), bar_spacing=.72)
graph.add_plot(plot)
plot.bind_to_graph(graph)
plot.points = [(x, .1 + randrange(10) / 10.) for x in range(-50, 1)]
# Test the scatter plot
plot = ScatterPlot(color=next(colors), point_size=5)
graph.add_plot(plot)
plot.points = [(x, .1 + randrange(10) / 10.) for x in range(-50, 1)]
Clock.schedule_interval(self.update_points, 1 / 60.)
graph2 = Graph(
xlabel='Position (m)',
ylabel='Time (s)',
x_ticks_minor=0,
x_ticks_major=1,
y_ticks_major=10,
y_grid_label=True,
x_grid_label=True,
padding=5,
xlog=False,
ylog=False,
xmin=0,
ymin=0,
**graph_theme)
b.add_widget(graph)
if np is not None:
(xbounds, ybounds, data) = self.make_contour_data()
# This is required to fit the graph to the data extents
graph2.xmin, graph2.xmax = xbounds
graph2.ymin, graph2.ymax = ybounds
plot = ContourPlot()
plot.data = data
plot.xrange = xbounds
plot.yrange = ybounds
plot.color = [1, 0.7, 0.2, 1]
graph2.add_plot(plot)
b.add_widget(graph2)
self.contourplot = plot
Clock.schedule_interval(self.update_contour, 1 / 60.)
return b
def make_contour_data(self, ts=0):
omega = 2 * pi / 30
k = (2 * pi) / 2.0
ts = sin(ts * 2) + 1.5 # emperically determined 'pretty' values
npoints = 100
data = np.ones((npoints, npoints))
position = [ii * 0.1 for ii in range(npoints)]
time = [(ii % 100) * 0.6 for ii in range(npoints)]
for ii, t in enumerate(time):
for jj, x in enumerate(position):
data[ii, jj] = sin(
k * x + omega * t) + sin(-k * x + omega * t) / ts
return (0, max(position)), (0, max(time)), data
def update_points(self, *args):
self.plot.points = [
(x / 10., cos(Clock.get_time() + x / 50.))
for x in range(-500, 501)]
def update_contour(self, *args):
_, _, self.contourplot.data[:] = self.make_contour_data(
Clock.get_time())
# this does not trigger an update, because we replace the
# values of the arry and do not change the object.
# However, we cannot do "...data = make_contour_data()" as
# kivy will try to check for the identity of the new and
# old values. In numpy, 'nd1 == nd2' leads to an error
# (you have to use np.all). Ideally, property should be patched
# for this.
self.contourplot.ask_draw()
TestApp().run()