def __init__(self, x_seq, y_seq, *args, **kwargs):
x_bins = kwargs.get('x_bins', 10)
y_bins = kwargs.get('y_bins', 10)
# First pass through data, find the range of values:
bbox = kwargs.get('hist_bbox', find_bounding_box(x_seq, y_seq))
# bounding box needs stretching!
self.img_bbox = bbox
# Second pass trough the data to create the histogram.
self.array = bin_data_2d(x_seq, y_seq, x_bins, y_bins, bbox)
# Color code the data (on gray scale for now).
# save the relevant information:
self.gradient = kwargs.get('gradient', None)
def __init__(self, x_seq, y_seq, *args, **kwargs):
x_bins = kwargs.get('x_bins', 10)
y_bins = kwargs.get('y_bins', 10)
# First pass through data, find the range of values:
bbox = kwargs.get('hist_bbox', find_bounding_box(x_seq, y_seq))
# bounding box needs stretching!
self.img_bbox = bbox
# Second pass trough the data to create the histogram.
self.array = bin_data_2d(x_seq, y_seq, x_bins, y_bins, bbox)
# Color code the data (on gray scale for now).
# save the relevant information:
self.gradient = kwargs.get('gradient', None)
def __init__(self, x_seq, y_seq, *args, **kwargs):
x_bins = kwargs.get('x_bins', 10)
y_bins = kwargs.get('y_bins', 10)
# First pass through data, find the range of values:
hist_bbox = kwargs.get('hist_bbox', find_bounding_box(x_seq, y_seq))
# Second pass trough the data to create the histogram.
ar = bin_data_2d(x_seq, y_seq, x_bins, y_bins, hist_bbox)
# Color code the data (on gray scale for now).
max_val = numpy.amax(ar)
min_val = 0
gradient = kwargs.get(
'gradient', RGBGradient((min_val, max_val), (0, 0, 1), (1, 0, 0)))
colors = colorcode_ar_2d(ar, gradient)
# save the relevant information:
self.gradient = gradient
self.encoded_png = colorcoded_ar_2d2png_string(colors)
self.img_bbox = hist_bbox
def __init__(self, x_seq, y_seq, *args, **kwargs):
x_bins = kwargs.get('x_bins', 10)
y_bins = kwargs.get('y_bins', 10)
# First pass through data, find the range of values:
hist_bbox = kwargs.get('hist_bbox', find_bounding_box(x_seq, y_seq))
# Second pass trough the data to create the histogram.
ar = bin_data_2d(x_seq, y_seq, x_bins, y_bins, hist_bbox)
# Color code the data (on gray scale for now).
max_val = numpy.amax(ar)
min_val = 0
gradient = kwargs.get('gradient',
RGBGradient((min_val, max_val), (0, 0, 1),
(1, 0, 0)))
colors = colorcode_ar_2d(ar, gradient)
# save the relevant information:
self.gradient = gradient
self.encoded_png = colorcoded_ar_2d2png_string(colors)
self.img_bbox = hist_bbox
def prepare_bbox(self, data_bbox):
'''Update bounding box with the data for this scatter plot.'''
return find_bounding_box(self.datapoints[0], self.datapoints[1],
data_bbox)
def prepare_bbox(self, data_bbox):
'''Update bounding box with the data for this scatter plot.'''
return find_bounding_box(self.datapoints[0], self.datapoints[1],
data_bbox)
