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models_datasets.py
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models_datasets.py
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import json
from django.db import models
from django.utils.translation import ugettext_lazy as _
from djangocms_charts.consts import *
from djangocms_charts.models_options import OptionsParentBase
from djangocms_charts.utils import transpose
import djangocms_charts.cache as charts_cache
class DatasetBase(OptionsParentBase):
"""
Dataset Mixin
"""
label = models.CharField(_("Name"), max_length=256, blank=True, null=True)
type = models.CharField(_("Chart Type"), max_length=50, choices=CHART_TYPES.get_choices)
# Table data
table_data = models.TextField(_("Chart Table data"), blank=True)
# Set Data Input Options
labels_top = models.BooleanField(_("Labels top row"), default=True)
labels_left = models.BooleanField(_("Labels left column"), default=True)
data_series_format = models.CharField(_("Multiple Datasets in Rows or Columns"), max_length=10,
default='rows', choices=DATASET_FORMATS)
# Set Options and Axes
color_by_dataset = models.BooleanField(_('Color by Dataset'), blank=True, null=True, default=False,
help_text=_('True to color each Dataset, False to color each element in a Series'))
colors = models.ForeignKey('ColorGroupModel', on_delete=models.CASCADE, related_name="%(class)s_colors", blank=True, null=True)
dataset_options_group = models.ForeignKey('DatasetOptionsGroupModel', on_delete=models.CASCADE, related_name="%(class)s_options", blank=True, null=True)
xAxis = models.ForeignKey('AxisOptionsGroupModel', on_delete=models.CASCADE, related_name="%(class)s_xAxis", blank=True, null=True)
yAxis = models.ForeignKey('AxisOptionsGroupModel', on_delete=models.CASCADE, related_name="%(class)s_yAxis", blank=True, null=True)
def save(self, *args, **kwargs):
super().save(*args, **kwargs)
charts_cache.clear_all()
def delete(self, *args, **kwargs):
super().delete(*args, **kwargs)
charts_cache.clear_all()
class Meta:
"""Abstract model."""
abstract = True
@property
def chart_type(self):
return CHART_TYPES.LINE if self.type == CHART_TYPES.LINE_XY else self.type
DEFAULT_SCALAR_AXES = {
# https://stackoverflow.com/a/57130191/12400711
"id": "default_scalar",
"type": "linear", # MANDATORY TO SHOW YOUR POINTS! (THIS IS THE IMPORTANT BIT)
"display": True, # mandatory
"position": 'bottom',
"scaleLabel": {
"display": True, # mandatory
},
}
def get_as_dict(self):
# Get Datasets
datasets = self.get_datasets()
# Get X Labels
x_labels = self.get_x_labels()
# Get Axes
x_axis = [self.xAxis.get_axis_as_dict('x')] if self.xAxis else []
if not x_axis and self.type == CHART_TYPES.LINE_XY:
x_axis = [self.DEFAULT_SCALAR_AXES]
y_axis = [self.yAxis.get_axis_as_dict('y')] if self.yAxis else []
return datasets, x_labels, x_axis, y_axis
# DATA FORMATS:
# ------------
#
# LABELS + VALUE TYPES:
#
# Line:
# -----
# type: 'line',
# data: {
# labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
# datasets: [{
# data: [20, 50, 100, 75, 25, 0],
# label: 'Left dataset',
#
# // This binds the dataset to the left y axis
# yAxisID: 'left-y-axis'
# }, {
# data: [0.1, 0.5, 1.0, 2.0, 1.5, 0],
# label: 'Right dataset',
#
# // This binds the dataset to the right y axis
# yAxisID: 'right-y-axis'
# }],
# },
#
# Bar:
# ----
# data: {
# datasets: [{
# data: [10, 20, 30, 40, 50, 60, 70],
# label: 'Bar dataset'
# }],
# labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
# };
#
# Radar:
# ------
# data: {
# datasets: [{
# data: [20, 10, 4, 2]
# }],
# labels: ['Running', 'Swimming', 'Eating', 'Cycling']
# }
#
# Doughnut/Pie:
# -------------
# data = {
# datasets: [{
# data: [10, 20, 30]
# }],
#
# // These labels appear in the legend and in the tooltips when hovering different arcs
# labels: ['Red', 'Yellow', 'Blue']
# };
#
# PolarArea:
# ----------
# data = {
# datasets: [{
# data: [10, 20, 30]
# }],
#
# // These labels appear in the legend and in the tooltips when hovering different arcs
# labels: ['Red', 'Yellow', 'Blue']
# };
#
#
# COORDINATE + VALUE TYPES:
#
# Bubble:
# ----------
# type: 'bubble',
# data: {
# datasets: [{
# label: 'Bubble Dataset',
# data: [{
# // X Value
# x: number,
#
# // Y Value
# y: number,
#
# // Bubble radius in pixels (not scaled).
# r: number
# }, ...]
# }],
# labels: ['Red', 'Yellow', 'Blue']
# };
#
# Scatter / Line_XY
# --------
# type: 'scatter', OR 'line'
# data: {
# datasets: [{
# label: 'Scatter Dataset',
# data: [{
# x: -10,
# y: 0
# }, {
# x: 0,
# y: 10
# }, {
# x: 10,
# y: 5
# }]
# }]
# },
# options: {
# scales: {
# xAxes: [{
# type: 'linear',
# position: 'bottom'
# }]
# }
# }
# INPUT DATA:
# -----------
#
# Line, Bar, Radar, Doughnut, Pie, PolarArea
# ------------------------------------------
# Datasets in 'cols' > TRANSPOSED
# Label_1, Label_2, ...
# Jan-20 10 30
# Feb-20 20 40
# ...
#
# OR
#
# Datasets in 'rows' > USE THIS FORMAT INTERNALLY
# Jan-20 Feb-20, ...
# Label_1 10 20
# Label_2 30 40
# ...
#
# Bubble [r], Scatter, Line_XY
# ----------------------------
# [r - radius - is ignored for line and scatter]
#
# Datasets in 'cols' > TRANSPOSED
# x 10 20 ...
# y 30 40 ...
# [r] 5 10 ...
#
# OR
#
# Datasets in 'rows' > USE THIS FORMAT INTERNALLY
# x, y, [r]
# 10 30 5
# 20 40 10
# ...
#
def _init_data(self):
if hasattr(self, '_table_data'):
return
#If Table data is a string (as saved by django) then load it as array.
table_data = json.loads(self.table_data) if \
isinstance(self.table_data, str) else self.table_data
# Switch top/left if data is transposed
self._data_series_in_rows = (self.data_series_format == 'rows')
if self._data_series_in_rows:
self._has_x_labels = int(self.labels_top)
self._has_data_labels = int(self.labels_left)
self._table_data = table_data
else:
self._has_data_labels = int(self.labels_top)
self._has_x_labels = int(self.labels_left)
self._table_data = transpose(table_data)
# Get X Labels as list, or None
def get_x_labels(self):
self._init_data()
if not self._table_data:
return []
if CHART_TYPES.is_coordinate_type(self.type):
return []
# Get the X Axes Labels or Categories
if self._has_x_labels:
return self._table_data[0][self._has_data_labels:]
return []
def apply_colors(self, datasets, color_dict=None):
# Get or provide a color dictionary
if color_dict is None:
if self.colors:
color_dict = self.colors.get_as_dict()
else:
return
# For each dataset, either append the array of colors, or index by dataset.
for i, dataset in enumerate(datasets):
chart_type_color_dict = color_dict.get(dataset['type'], None)
if not chart_type_color_dict:
continue # No colors for that chart type
for namespace_key, color_list in chart_type_color_dict.items():
if namespace_key in dataset:
continue # Color(s) already set for that dataset/type
if self.color_by_dataset:
if i < len(color_list):
# Set the color for each Dataset e.g. { 'backgroundColor': '#ff000' ...}
# Do not overwrite if previously set (i.e. 1. Dataset, 2. Chart, 3. Global)
dataset.setdefault(namespace_key, color_list[i])
else:
# Provide the whole color list for each dataset by Series
# e.g. { 'backgroundColor': ['#ff000', '#ff000',...]}
dataset.setdefault(namespace_key, color_list)
# Get Data as List
def get_datasets(self):
# Init and format data
self._init_data()
if not self._table_data:
return []
# Get datasets as list of dicts
if CHART_TYPES.is_coordinate_type(self.type):
datasets = self._get_datasets_as_coordinate_values()
else:
datasets = self._get_datasets_as_labels_values()
# Append common information
for i, dataset in enumerate(datasets):
# Add dataset type, redundant for main chart
dataset['type'] = self.chart_type
# Add dataset options if included
if self.dataset_options_group:
dataset.update(self.dataset_options_group.get_as_dict())
# Add Dataset specific options only for a dataset i.e. not chart
if self.__class__.__name__ == "DatasetModel":
dataset.update(self.get_options_as_dict())
if self.xAxis:
dataset['xAxisID'] = self.xAxis.get_axis_id('x')
if self.yAxis:
dataset['yAxisID'] = self.yAxis.get_axis_id('y')
# Apply colors indexed by dataset
if self.colors:
self.apply_colors(datasets)
return datasets
def _get_datasets_as_labels_values(self):
datasets = []
for r in range(self._has_x_labels, len(self._table_data)):
dataset = {}
if self._has_data_labels:
dataset['label'] = self._table_data[r][0]
elif self.label:
dataset['label'] = self.label
dataset['data'] = self._table_data[r][self._has_data_labels:]
datasets.append(dataset)
return datasets
def _get_datasets_as_coordinate_values(self):
# Get the X Axes Labels or Categories
if self._has_x_labels:
labels = self._table_data[0][self._has_data_labels:]
else:
# trim to x, y or x, y, r
labels = ['x', 'y', 'r'][:len(self._table_data[0][self._has_data_labels:])]
# Build unique datasets on the dataset label or each row label if provided
all_datasets = {}
for r in range(self._has_x_labels, len(self._table_data)):
# Get label from first col (if set) or from dataset label
label = self._table_data[r][0] if self._has_data_labels else self.label
# Get or set the default data as a list
data_list = all_datasets.setdefault(label, [])
# Create the coordinate dictionary based on the labels {'x': 1, 'y':2}
data_list.append({labels[i]: self._table_data[r][i + self._has_data_labels]
for i in range(len(labels))})
# Format as data dictionary
datasets = []
for label, data_list in all_datasets.items():
dataset = {}
dataset['label'] = label
dataset['data'] = data_list
datasets.append(dataset)
return datasets