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#2241 update fix of adding "set as unique values" in conditional hist…
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…ogram
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@lixun910
lixun910 committed Oct 20, 2020
1 parent 8e3851f commit dc0a13f
Showing 1 changed file with 119 additions and 51 deletions.
170 changes: 119 additions & 51 deletions Explore/ConditionalHistogramView.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -338,14 +338,43 @@ void ConditionalHistogramCanvas::ResizeSelectableShps(int virtual_scrn_w,

GdaShape* s;
if (show_axes) {
int t = var_info[HIST_VAR].time;
double x_min = 0;
double x_max = left_pad_const + right_pad_const + interval_width_const * cur_intervals + interval_gap_const * (cur_intervals-1);

// orig_x_pos is the center of each histogram bar
std::vector<double> orig_x_pos(cur_intervals);
for (int i=0; i<cur_intervals; i++) {
orig_x_pos[i] = left_pad_const + interval_width_const/2.0 + i * (interval_width_const + interval_gap_const);
}

for (int r=0; r<vert_num_cats; r++) {
for (int c=0; c<horiz_num_cats; c++) {
s = new GdaAxis(*x_axis);
s->applyScaleTrans(st[r][c]);
foreground_shps.push_front(s);

s = new GdaAxis(*y_axis);
s->applyScaleTrans(st[r][c]);
foreground_shps.push_front(s);

if (set_uniquevalue) {
for (int ival=0; ival<cur_intervals; ival++) {
double x0 = orig_x_pos[ival] - interval_width_const/2.0;
double x1 = orig_x_pos[ival] + interval_width_const/2.0;
double y0 = 0;
double y1 = cell_data[0][r][c].ival_obs_cnt[ival];
// add label for x-axis

GdaShapeText* brk = new GdaShapeText(s_ival_breaks[t][ival],
*GdaConst::small_font,
wxRealPoint(x0 /2.0 + x1 /2.0, y0), 0,
GdaShapeText::h_center,
GdaShapeText::v_center, 0, 25);
brk->applyScaleTrans(st[r][c]);
foreground_shps.push_back(brk);
}
}
}
}
}
Expand Down Expand Up @@ -531,22 +560,23 @@ void ConditionalHistogramCanvas::PopulateCanvas()
axis_scale_x.tics_str.resize(axis_scale_x.ticks);
axis_scale_x.tics_str_show.resize(axis_scale_x.tics_str.size());
for (int i=0; i<axis_scale_x.ticks; i++) {
axis_scale_x.tics[i] =
axis_scale_x.data_min +
range*((double) i)/((double) axis_scale_x.ticks-1);
axis_scale_x.tics[i] = axis_scale_x.data_min + range*((double) i)/((double) axis_scale_x.ticks-1);
wxString flt = GenUtils::DblToStr(axis_scale_x.tics[i],
axis_display_precision,
axis_display_fixed_point);
axis_scale_x.tics_str[i] = flt.ToStdString();
axis_scale_x.tics_str_show[i] = false;
}
int tick_freq = ceil(((double) cur_intervals)/5.0);
for (int i=0; i<axis_scale_x.ticks; i++) {
if (i % tick_freq == 0) {
axis_scale_x.tics_str_show[i] = true;
}
}
if (!set_uniquevalue) {
int tick_freq = ceil(((double) cur_intervals)/5.0);
for (int i=0; i<axis_scale_x.ticks; i++) {
if (i % tick_freq == 0) {
axis_scale_x.tics_str_show[i] = true;
}
}
}
axis_scale_x.tic_inc = axis_scale_x.tics[1]-axis_scale_x.tics[0];

x_axis = new GdaAxis(GetNameWithTime(2), axis_scale_x, wxRealPoint(0,0),
wxRealPoint(x_max, 0), 0, 9);
}
Expand All @@ -560,13 +590,10 @@ void ConditionalHistogramCanvas::PopulateCanvas()
double x1 = orig_x_pos[ival] + interval_width_const/2.0;
double y0 = 0;
double y1 = cell_data[0][r][c].ival_obs_cnt[ival];
selectable_shps[i] = new GdaRectangle(wxRealPoint(x0, 0),
wxRealPoint(x1, y1));
selectable_shps[i] = new GdaRectangle(wxRealPoint(x0, 0), wxRealPoint(x1, y1));
int sz = GdaConst::qualitative_colors.size();
selectable_shps[i]->
setPen(GdaConst::qualitative_colors[ival%sz]);
selectable_shps[i]->
setBrush(GdaConst::qualitative_colors[ival%sz]);
selectable_shps[i]->setPen(GdaConst::qualitative_colors[ival%sz]);
selectable_shps[i]->setBrush(GdaConst::qualitative_colors[ival%sz]);
i++;
}
}
Expand Down Expand Up @@ -765,20 +792,22 @@ void ConditionalHistogramCanvas::HistogramIntervals()
obs_id_to_sel_shp, ival_obs_cnt and ival_obs_sel_cnt */
void ConditionalHistogramCanvas::InitIntervals()
{
s_ival_breaks.resize(boost::extents[num_time_vals][cur_intervals]);

std::vector<bool>& hs = highlight_state->GetHighlight();
std::vector<bool>& hs = highlight_state->GetHighlight();

// determine correct ivals for each obs in current time period
min_ival_val.resize(num_time_vals);
max_ival_val.resize(num_time_vals);
max_num_obs_in_ival.resize(num_time_vals);

overall_max_num_obs_in_ival = 0;
for (int t=0; t<num_time_vals; t++)
for (int t=0; t<num_time_vals; t++) {
max_num_obs_in_ival[t] = 0;

}

std::map<wxString, int> unique_ival_dict;
ival_breaks.resize(boost::extents[num_time_vals][cur_intervals-1]);
s_ival_breaks.resize(boost::extents[num_time_vals][cur_intervals]);

for (int t=0; t<num_time_vals; t++) {
if (set_uniquevalue) {
std::map<wxString, int> unique_dict;
Expand All @@ -797,6 +826,7 @@ void ConditionalHistogramCanvas::InitIntervals()
for (it=unique_dict.begin(); it!=unique_dict.end();it++){
wxString lbl = it->first;
s_ival_breaks[t][cur_ival] = lbl;
unique_ival_dict[lbl] = cur_ival;
cur_ival += 1;
}

Expand Down Expand Up @@ -862,40 +892,78 @@ void ConditionalHistogramCanvas::InitIntervals()
int dt = var_info[HIST_VAR].time_min;
if (var_info[HIST_VAR].sync_with_global_time)
dt += t;

// record each obs in the correct cell and ival.

int cur_ival = 0;
for (int i=0; i<num_obs; i++) {
int id = data_sorted[dt][i].second;
if (undef_tms[t][id]) continue;
while (cur_ival <= cur_intervals-2 &&
data_sorted[dt][i].first >= ival_breaks[0][cur_ival])
{
cur_ival++;
}
int r = 0, c = 0;
if (!vert_cat_data.categories.empty()) {
r = vert_cat_data.categories[vt].id_to_cat[id];

// record each obs in the correct cell and ival.
if (set_uniquevalue) {
for (int i=0; i<num_obs; i++) {
int id = s_data_sorted[dt][i].second;
if (undef_tms[t][id]) {
continue;
}
wxString cat = s_data_sorted[dt][i].first;
cur_ival = unique_ival_dict[cat];

s_ival_breaks[dt];
int r = 0, c = 0;
if (!vert_cat_data.categories.empty()) {
r = vert_cat_data.categories[vt].id_to_cat[id];
}
if (!horiz_cat_data.categories.empty()) {
c = horiz_cat_data.categories[ht].id_to_cat[id];
}
obs_id_to_sel_shp[t][id] = cell_to_sel_shp_gen(r, c, cur_ival,
cols, cur_intervals);
cell_data[0][r][c].ival_to_obs_ids[cur_ival].push_front(id);
cell_data[0][r][c].ival_obs_cnt[cur_ival]++;
if (cell_data[0][r][c].ival_obs_cnt[cur_ival] > max_num_obs_in_ival[t])
{
max_num_obs_in_ival[t] = cell_data[0][r][c].ival_obs_cnt[cur_ival];
if (max_num_obs_in_ival[t] > overall_max_num_obs_in_ival) {
overall_max_num_obs_in_ival = max_num_obs_in_ival[t];
}
}
if (hs[s_data_sorted[dt][i].second]) {
cell_data[0][r][c].ival_obs_sel_cnt[cur_ival]++;
}
}
if (!horiz_cat_data.categories.empty()) {
c = horiz_cat_data.categories[ht].id_to_cat[id];

} else {

for (int i=0; i<num_obs; i++) {
int id = data_sorted[dt][i].second;
if (undef_tms[t][id]) {
continue;
}
while (cur_ival <= cur_intervals-2 &&
data_sorted[dt][i].first >= ival_breaks[0][cur_ival])
{
cur_ival++;
}
int r = 0, c = 0;
if (!vert_cat_data.categories.empty()) {
r = vert_cat_data.categories[vt].id_to_cat[id];
}
if (!horiz_cat_data.categories.empty()) {
c = horiz_cat_data.categories[ht].id_to_cat[id];
}
obs_id_to_sel_shp[t][id] = cell_to_sel_shp_gen(r, c, cur_ival,
cols, cur_intervals);
cell_data[0][r][c].ival_to_obs_ids[cur_ival].push_front(id);
cell_data[0][r][c].ival_obs_cnt[cur_ival]++;
if (cell_data[0][r][c].ival_obs_cnt[cur_ival] > max_num_obs_in_ival[t])
{
max_num_obs_in_ival[t] = cell_data[0][r][c].ival_obs_cnt[cur_ival];
if (max_num_obs_in_ival[t] > overall_max_num_obs_in_ival) {
overall_max_num_obs_in_ival = max_num_obs_in_ival[t];
}
}
if (hs[data_sorted[dt][i].second]) {
cell_data[0][r][c].ival_obs_sel_cnt[cur_ival]++;
}
}
obs_id_to_sel_shp[t][id] = cell_to_sel_shp_gen(r, c, cur_ival,
cols, cur_intervals);
cell_data[0][r][c].ival_to_obs_ids[cur_ival].push_front(id);
cell_data[0][r][c].ival_obs_cnt[cur_ival]++;
if (cell_data[0][r][c].ival_obs_cnt[cur_ival] > max_num_obs_in_ival[t])
{
max_num_obs_in_ival[t] =
cell_data[0][r][c].ival_obs_cnt[cur_ival];
if (max_num_obs_in_ival[t] > overall_max_num_obs_in_ival) {
overall_max_num_obs_in_ival = max_num_obs_in_ival[t];
}
}
if (hs[data_sorted[dt][i].second]) {
cell_data[0][r][c].ival_obs_sel_cnt[cur_ival]++;
}
}
}
}

}
Expand Down

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