#!/usr/bin/env python # Copyright (C) 2017-2020 Alex Manuskin, Gil Tsuker # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA from __future__ import absolute_import from s_tui.sturwid.complex_bar_graph import LabeledBarGraphVector from s_tui.sturwid.complex_bar_graph import ScalableBarGraph import logging import math logger = logging.getLogger(__name__) class BarGraphVector(LabeledBarGraphVector): @staticmethod def append_latest_value(values, new_val): values.append(new_val) return values[1:] MAX_SAMPLES = 300 SCALE_DENSITY = 5 def __init__(self, source, regular_colors, graph_count, visible_graph_list, alert_colors=None, bar_width=1): self.source = source self.graph_count = graph_count self.graph_name = self.source.get_source_name() self.measurement_unit = self.source.get_measurement_unit() self.num_samples = self.MAX_SAMPLES self.graph_data = [] # We must create new instances for each list for _ in range(graph_count): self.graph_data.append([0] * self.num_samples) # Set max to 1 as default self.graph_max = 1 self.color_a = regular_colors[0] self.color_b = regular_colors[1] self.smooth_a = regular_colors[2] self.smooth_b = regular_colors[3] if alert_colors: self.alert_colors = alert_colors else: self.alert_colors = regular_colors self.regular_colors = regular_colors self.satt = None y_label = [] graph_title = self.graph_name + ' [' + self.measurement_unit + ']' sub_title_list = self.source.get_sensor_list() # create several different instances of salable bar graph w = [] for _ in range(graph_count): graph = ScalableBarGraph(['bg background', self.color_a, self.color_b]) w.append(graph) super(BarGraphVector, self).__init__( graph_title, sub_title_list, y_label, w, visible_graph_list) for graph in self.bar_graph_vector: graph.set_bar_width(bar_width) self.color_counter_vector = [0] * graph_count def _set_colors(self, colors): self.color_a = colors[0] self.color_b = colors[1] self.smooth_a = colors[2] self.smooth_b = colors[3] if self.satt: self.satt = {(1, 0): self.smooth_a, (2, 0): self.smooth_b} for graph in self.bar_graph_vector: graph.set_segment_attributes( ['bg background', self.color_a, self.color_b], satt=self.satt) def get_graph_name(self): return self.graph_name def get_measurement_unit(self): return self.measurement_unit def get_is_available(self): return self.source.get_is_available() def get_label_scale(self, min_val, max_val, size): """Dynamically change the scale of the graph (y lable)""" if size < self.SCALE_DENSITY: label_cnt = 1 else: label_cnt = int(size / self.SCALE_DENSITY) try: if max_val >= 100: label = [int((min_val + i * (max_val - min_val) / label_cnt)) for i in range(label_cnt + 1)] else: label = [round((min_val + i * (max_val - min_val) / label_cnt), 1) for i in range(label_cnt + 1)] return label except ZeroDivisionError: logging.debug("Side label creation divided by 0") return "" def set_smooth_colors(self, smooth): if smooth: self.satt = {(1, 0): self.smooth_a, (2, 0): self.smooth_b} else: self.satt = None for graph in self.bar_graph_vector: graph.set_segment_attributes( ['bg background', self.color_a, self.color_b], satt=self.satt) def update(self): if not self.get_is_available(): return # NOTE setting edge trigger causes overhead try: if self.source.get_edge_triggered(): self._set_colors(self.alert_colors) else: self._set_colors(self.regular_colors) except NotImplementedError: pass current_reading = self.source.get_reading_list() logging.info("Reading %s", current_reading) y_label_size_max = 0 local_top_value = [] # update visible graph data, and maximum for graph_idx, graph in enumerate(self.bar_graph_vector): try: _ = self.visible_graph_list[graph_idx] except IndexError: # If a new graph "Appers", append it to visibles self.visible_graph_list.append(True) bars = [] if self.visible_graph_list[graph_idx]: self.graph_data[graph_idx] = self.append_latest_value( self.graph_data[graph_idx], current_reading[graph_idx]) # Get the graph width (dimension 1) num_displayed_bars = graph.get_size()[1] visible_id = self.MAX_SAMPLES - num_displayed_bars - 1 visible_graph_data = self.graph_data[graph_idx][visible_id:] local_top_value.append(max(visible_graph_data)) update_max = False if self.graph_max == 1: self.graph_max = self.source.get_top() update_max = True local_max = math.ceil(max(local_top_value)) if (local_max > self.graph_max): update_max = True self.graph_max = local_max # update the graph bars for graph_idx, graph in enumerate(self.bar_graph_vector): bars = [] if self.visible_graph_list[graph_idx]: # Get the graph width (dimension 1) num_displayed_bars = graph.get_size()[1] # Iterate over all the information in the graph if self.color_counter_vector[graph_idx] % 2 == 0: for n in range(self.MAX_SAMPLES - num_displayed_bars, self.MAX_SAMPLES): value = round(self.graph_data[graph_idx][n], 1) # toggle between two bar types if n & 1: bars.append([0, value]) else: bars.append([value, 0]) else: for n in range(self.MAX_SAMPLES - num_displayed_bars, self.MAX_SAMPLES): value = round(self.graph_data[graph_idx][n], 1) if n & 1: bars.append([value, 0]) else: bars.append([0, value]) self.color_counter_vector[graph_idx] += 1 graph.set_data(bars, float(self.graph_max)) y_label_size_max = max(y_label_size_max, graph.get_size()[0]) self.set_y_label(self.get_label_scale(0, self.graph_max, float(y_label_size_max))) # Only create new graphs if the maximum has changed if update_max: self.set_visible_graphs() def reset(self): self.graph_data = [] # Like in init, we create new instances for each list for _ in range(self.graph_count): self.graph_data.append([0] * self.num_samples) self.graph_max = 1