From a26a831e3e23c0c3af4d01996eaf54095b3c8184 Mon Sep 17 00:00:00 2001 From: leburnett Date: Thu, 2 Oct 2025 19:16:51 -0400 Subject: [PATCH 01/60] test code for new service --- src/quickpage/services/index_service.py | 62 +++++++++++++++++++++++++ 1 file changed, 62 insertions(+) diff --git a/src/quickpage/services/index_service.py b/src/quickpage/services/index_service.py index a47465a..663ce4f 100644 --- a/src/quickpage/services/index_service.py +++ b/src/quickpage/services/index_service.py @@ -73,6 +73,10 @@ async def create_index(self, command) -> Result[str, str]: # Generate index data from corrected neuron types index_data = self._generate_index_data(corrected_neuron_types) + # Generate scatterplot data for corrected neuron types + plot_data = self._generate_plot_data(corrected_neuron_types) + print(plot_data) + # Log performance summary self._log_performance_summary( corrected_neuron_types, cache_performance, scan_time @@ -477,6 +481,64 @@ def _generate_index_data(self, neuron_types): f"Index data generation completed: {len(index_data)} entries, all with cached data" ) return index_data + + def _generate_plot_data(self, neuron_types): + """Generate plot data from neuron types.""" + cached_data_lazy = ( + self.cache_manager.get_cached_data_lazy() if self.cache_manager else None + ) + plot_data = [] + cached_count = 0 + missing_cache_count = 0 + + for neuron_type, sides in neuron_types.items(): + # Check if we have cached data for this neuron type + cache_data = cached_data_lazy.get(neuron_type) if cached_data_lazy else None + + entry = { + "name": neuron_type, + "total_count": 0, + "left_count": 0, + "right_count": 0, + "middle_count": 0, + "undefined_count": 0, + "has_undefined": False, + "spatial_metrics": {}, + } + + # Use cached data if available (NO DATABASE QUERIES!) + if cache_data: + entry["spatial_metrics"] = cache_data.spatial_metrics + entry["total_count"] = cache_data.total_count + entry["left_count"] = cache_data.soma_side_counts.get("left", 0) + entry["right_count"] = cache_data.soma_side_counts.get("right", 0) + entry["middle_count"] = cache_data.soma_side_counts.get("middle", 0) + entry["undefined_count"] = cache_data.soma_side_counts.get("unknown", 0) + entry["has_undefined"] = entry["undefined_count"] > 0 + + logger.debug(f"Used cached data for {neuron_type}") + cached_count += 1 + else: + # No cached data available - use minimal defaults + logger.debug( + f"No cached data available for {neuron_type}, using minimal defaults" + ) + missing_cache_count += 1 + + plot_data.append(entry) + + # Sort results + plot_data.sort(key=lambda x: x["name"]) + + if missing_cache_count > 0: + logger.warning( + f"Plot data generation completed: {len(plot_data)} entries, {cached_count} with cache, {missing_cache_count} missing cache. Run 'quickpage generate' to populate cache." + ) + else: + logger.info( + f"Plot data generation completed: {len(plot_data)} entries, all with cached data" + ) + return plot_data async def _generate_all_pages(self, output_dir, index_data, command, connector): """Generate all the index pages and associated files.""" From 11500a5ebfe094677ad732a66ac28d964d035fa8 Mon Sep 17 00:00:00 2001 From: leburnett Date: Fri, 3 Oct 2025 14:51:18 -0400 Subject: [PATCH 02/60] Create scatterplot_service.py --- src/neuview/services/scatterplot_service.py | 464 ++++++++++++++++++++ 1 file changed, 464 insertions(+) create mode 100644 src/neuview/services/scatterplot_service.py diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py new file mode 100644 index 0000000..28951b4 --- /dev/null +++ b/src/neuview/services/scatterplot_service.py @@ -0,0 +1,464 @@ +""" +Interactive Scatterplot Service + +Simplified service that coordinates other specialized services to create +interactive scatterplot page with plots related to the spatial metrics per type. +""" + +import logging +import time +from pathlib import Path +from collections import defaultdict +from typing import List, Tuple, Dict, Any, Set +import plotly.graph_objects as go +import plotly.io as pio +from cmap import Colormap +import pandas as pd + +from ..cache import NeuronTypeCacheData +from ..result import Result, Ok, Err +from ..utils import get_git_version +from .roi_hierarchy_service import ROIHierarchyService +from .neuron_name_service import NeuronNameService +from .roi_analysis_service import ROIAnalysisService +from .index_generator_service import IndexGeneratorService +from ..index_service import IndexService +from .file_service import FileService + +logger = logging.getLogger(__name__) + +class ScatterplotService: + """Service for creating scatterplots with markers for all available neuron types.""" + + def __init__(self, config, page_generator): + self.config = config + self.page_generator = page_generator + self._batch_neuron_cache = {} + + # Initialize cache manager for neuron type data + self.cache_manager = None + if config and hasattr(config, "output") and hasattr(config.output, "directory"): + from ..cache import create_cache_manager + self.cache_manager = create_cache_manager(config.output.directory) + + async def create_scatterplots(self, command) -> Result[str, str]: + """Create a scatterplot containing markers for all neuron types found in the output directory.""" + try: + logger.info("Starting plot creation using cached data") + + # Determine output directory + output_dir = Path(command.output_directory or self.config.output.directory) + if not output_dir.exists(): + return Err(f"Output directory does not exist: {output_dir}") + + # Discover neuron types from cache or file scanning + neuron_types, _ = IndexService._discover_neuron_types(output_dir) + if not neuron_types: + return Err("No neuron type HTML files found in output directory") + + # Initialize connector if needed for database lookups + connector = await IndexService._initialize_connector_if_needed( + neuron_types, output_dir + ) + + # Correct neuron names (convert filenames back to original names) + corrected_neuron_types, _ = IndexService._correct_neuron_names( + neuron_types, connector + ) + + # Generate scatterplot data for corrected neuron types + plot_data = self._generate_plot_data(corrected_neuron_types) + + # Generate the plots + + # Collect all generated file paths + generated_files = [str(output_dir / command.index_filename)] + if hasattr(self, "generated_files"): + generated_files.extend(self.generated_files) + + return Ok(generated_files) + + except Exception as e: + logger.error(f"Failed to create optimized index: {e}") + return Err(f"Failed to create index: {str(e)}") + + + + def _generate_plot_data(self, neuron_types): + """Generate plot data from neuron types.""" + cached_data_lazy = ( + self.cache_manager.get_cached_data_lazy() if self.cache_manager else None + ) + plot_data = [] + cached_count = 0 + missing_cache_count = 0 + + for neuron_type, sides in neuron_types.items(): + # Check if we have cached data for this neuron type + cache_data = cached_data_lazy.get(neuron_type) if cached_data_lazy else None + + entry = { + "name": neuron_type, + "total_count": 0, + "left_count": 0, + "right_count": 0, + "middle_count": 0, + "undefined_count": 0, + "has_undefined": False, + "spatial_metrics": {}, + } + + # Use cached data if available (NO DATABASE QUERIES!) + if cache_data: + entry["spatial_metrics"] = cache_data.spatial_metrics + entry["total_count"] = cache_data.total_count + entry["left_count"] = cache_data.soma_side_counts.get("left", 0) + entry["right_count"] = cache_data.soma_side_counts.get("right", 0) + entry["middle_count"] = cache_data.soma_side_counts.get("middle", 0) + entry["undefined_count"] = cache_data.soma_side_counts.get("unknown", 0) + entry["has_undefined"] = entry["undefined_count"] > 0 + + logger.debug(f"Used cached data for {neuron_type}") + cached_count += 1 + else: + # No cached data available - use minimal defaults + logger.debug( + f"No cached data available for {neuron_type}, using minimal defaults" + ) + missing_cache_count += 1 + + plot_data.append(entry) + + # Sort results + plot_data.sort(key=lambda x: x["name"]) + + if missing_cache_count > 0: + logger.warning( + f"Plot data generation completed: {len(plot_data)} entries, {cached_count} with cache, {missing_cache_count} missing cache. Run 'quickpage generate' to populate cache." + ) + else: + logger.info( + f"Plot data generation completed: {len(plot_data)} entries, all with cached data" + ) + return plot_data + + + # Make an svg - in JS when hover over - that marker is large. + def _make_scatterplot( + xval:str + , yval:str + , roi_str:str + , style:dict + , sizing:dict + , plot_specs:dict + , star_neurons:list + , save_plot:bool=True) -> go.Figure: + """ + Plot scatterplot with 'star_neuron' types highlighted. + + Parameters + ---------- + xval : str + Column of 'df' to be shown on the x-axis. + yval : str + Column of 'df' to be shown on the y-axis. + roi_str : str + Optic lobe region of interest to plot the data from. + style : dict + Dict containing the values of the fixed styling formatting variables. + sizing : dict + Dict containing the values of the size formatting variables. + plot_specs : dict + Dict containing the values of the formatting variables relevant to the specific plot. + star_neurons : list + List of 'star neurons' to highlight in the plot. + save_plot : bool, default = True + Whether to save the plot or only return it. + + Returns + ------- + fig : go.Figure + Formatted plotly scatterplot. + """ + pio.kaleido.scope.mathjax = None + + assert plot_specs["colorscale"] in ["red", "group"]\ + , f"Colorscale must be 'red' or 'group', not '{plot_specs['colorscale']}'" + + # load the data + df = load_and_process_df(roi_str=roi_str) + if xval == "instance": + df = df.sort_values(yval) + + df["markersize"] = float(sizing["markersize"]) + df["markerlinewidth"] = sizing["markerlinewidth"] + df["text"] = "" + + if star_neurons: + df.loc[df["instance"].isin(star_neurons), "markersize"] = ( + sizing["markersize"] * 1.75 + ) + df.loc[df["instance"].isin(star_neurons), "markerlinewidth"] = ( + sizing["markerlinewidth"] * 7 + ) + df.loc[df["instance"].isin(star_neurons), "group"] = 6 + + # get sizing values + if style["export_type"] == "svg": + pixelsperinch = 72 + else: + pixelsperinch = 96 + pixelspermm = pixelsperinch / 25.4 + plot_width = (sizing["fig_width"] - sizing["fig_margin"]) * pixelspermm + plot_height = (sizing["fig_height"] - sizing["fig_margin"]) * pixelspermm + fsize_ticks_px = sizing["fsize_ticks_pt"] * (1 / 72) * pixelsperinch + fsize_title_px = sizing["fsize_title_pt"] * (1 / 72) * pixelsperinch + + cmap = Colormap("reds_5").to_plotly() # colorscale == 'red'; default + if plot_specs["colorscale"] == "group": + cmap = [ + [0, "rgb(200, 200, 200)"] + , [0.1666, "rgb(200, 200, 200)"] + , [0.1666, "rgb(2, 158, 115)"] + , [0.333, "rgb(2, 158, 115)"] + , [0.333, "rgb(213, 94, 0)"] + , [0.5, "rgb(213, 94, 0)"] + , [0.5, "rgb(1,115,178)"] + , [0.666, "rgb(1,115,178)"] + , [0.6666, "rgb(222,143,5)"] + , [0.833, "rgb(222,143,5)"] + , [0.833, "rgb(204, 120, 188)"] + , [1.0, "rgb(204, 120, 188)"] + ] + + # set the maximum + _, n_cols_region = find_neuropil_hex_coords(roi_str) + + fig = go.Figure() + + match yval: + case "coverage_factor_trim": + fig.add_shape( + type="line" + , y0=1 + , x0=1 + , x1=n_cols_region + , y1=1 + , layer="below" + , line={"color": "grey", "width": 0.8, "dash": "solid"} + ) + + case "cell_size_cols": + for multipl in [0.2, 0.5, 1, 2, 5]: + if multipl < 0.5 or multipl > 2: + line_width = 0.25 + elif multipl != 1: + line_width = 0.4 + else: + line_width = 0.8 + + fig.add_shape( + type="line" + , x0=1 + , y0=n_cols_region * multipl + , x1=n_cols_region * multipl + , y1=1 + , layer="below" + , line={"color": "grey", "width": line_width, "dash": "solid"} + ) + + # add groups in order to ensure star neurons are plotted last + gp_values = df["group"].sort_values(ascending=True).unique() + for grp in gp_values: + + df_gp = df[df["group"] == grp] + + fig.add_trace( + go.Scatter( + x=df_gp[xval] + , y=df_gp[yval] + , text=[df_gp["text"]] + , textposition="top center" + , customdata=np.stack( + (df_gp["instance"], df_gp[plot_specs["color_factor"]]), axis=-1 + ) + , hovertemplate=plot_specs["hover_template"] + , opacity=0.95 + , mode="markers" + , marker={ + "cmax": plot_specs["cmax"] + , "cmin": plot_specs["cmin"] + , "size": df_gp["markersize"] + , "color": df_gp[plot_specs["color_factor"]] + , "line": { + "width": df_gp["markerlinewidth"] + , "color": style["markerlinecolor"] + }, + "colorscale": cmap, + "colorbar": { + "orientation": "v" + , "outlinecolor": style["linecolor"] + , "outlinewidth": sizing["axislinewidth"] + , "thickness": sizing["cbar_thickness"] + , "len": sizing["cbar_length"] + , "ticklen": sizing["cbar_tick_length"] + , "tickcolor": "black" + , "tickwidth": sizing["cbar_tick_width"] + , "tickmode": "array" + , "tickvals": plot_specs["tickvals"] + , "ticktext": plot_specs["ticktext"] + , "tickfont": {"size": fsize_ticks_px, "color": "black"} + , "title": { + "font": { + "family": style["font_type"] + , "size": fsize_title_px + , "color": "black" + }, + "side": "right" + , "text": plot_specs["cbar_title"] + } + } + } + ) + ) + + xlabel = get_axis_labels(xval, label_type="axis") + ylabel = get_axis_labels(yval, label_type="axis") + + if plot_specs["log_x"]: + typex = "log" + tickformx = ".1r" + else: + typex = "-" + tickformx = "" + + if plot_specs["log_y"]: + typey = "log" + tickformy = ".1r" + else: + typey = "-" + tickformy = "" + + fig.update_layout( + autosize=False, + width=plot_width, + height=plot_height, + margin={ + "l": plot_width // 8, + "r": 0, + "b": plot_height // 4, + "t": 0, + "pad": plot_width // 30, + }, + showlegend=False, + paper_bgcolor="rgba(255,255,255,1)", + plot_bgcolor="rgba(255,255,255,1)", + ) + + fig.update_xaxes( + title={ + "font": { + "size": fsize_title_px, + "family": style["font_type"], + "color": style["linecolor"], + }, + "text": xlabel, + }, + title_standoff=(plot_height // 4) / 4, + ticks="outside", + ticklen=sizing["ticklen"], + tickwidth=sizing["tickwidth"], + tickfont={ + "family": style["font_type"], + "size": fsize_ticks_px, + "color": style["linecolor"], + }, + tickformat=tickformx, + tickcolor="black", + type=typex, + showgrid=False, + showline=True, + linewidth=sizing["axislinewidth"], + linecolor=style["linecolor"], + range=plot_specs["range_x"], + ) + + match xval: + case "instance": + fig.update_xaxes(title="", tickvals=[], visible=False) + case "coverage_factor_trim": + fig.update_xaxes(tickvals=[1, 2, 4, 8, 12]) + case "cell_size_cols": + fig.update_xaxes(tickvals=[1, 10, 100, 1000]) + case "area_covered_pop": + fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) + case "cols_covered_pop": + fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) + case "population_size": + fig.update_xaxes(tickvals=[1, 10, 100, 1000]) + + fig.update_yaxes( + title={ + "font": { + "size": fsize_title_px + , "family": style["font_type"] + , "color": style["linecolor"] + } + , "text": f"{ylabel}" + } + , title_standoff=(plot_width // 5) / 5 + , ticks="outside" + , tickcolor="black" + , ticklen=sizing["ticklen"] + , tickwidth=sizing["tickwidth"] + , tickfont={ + "size": fsize_ticks_px + , "family": style["font_type"] + , "color": "black" + } + , tickformat=tickformy + , type=typey + , showgrid=False + , showline=True + , linewidth=sizing["axislinewidth"] + , linecolor=style["linecolor"] + , scaleanchor="x" + , scaleratio=1 + , anchor="free" + , side="left" + , overlaying="y" + , range=plot_specs["range_y"] + ) + + match yval: + case "coverage_factor_trim": + fig.update_yaxes(tickvals=[1, 2, 4, 8, 12], scaleanchor=False) + case "cell_size_cols": + fig.update_yaxes(tickvals=[1, 10, 100, 1000]) + case "area_covered_pop": + fig.update_yaxes(tickvals=[0, 200, 400, 600, 800, 1000]) + case "population_size": + fig.update_yaxes(tickvals=[1, 10, 100, 1000]) + + if save_plot: + save_path = plot_specs["save_path"] + assert isinstance(save_path, Path)\ + , f"save_path needs to be 'Path', not '{type(save_path)}'" + save_path.mkdir(parents=True, exist_ok=True) + + basename = ( + save_path + / f"{roi_str[:-3]}_{xval}_versus_{yval}_{sizing['fsize_title_pt']}pt_" + f"w{sizing['fig_width']}_h{sizing['fig_height']}_cscale-{plot_specs['color_factor']}" + ) + + if style["export_type"] == "html": + fig.write_html(f"{basename}.html") + else: + pio.write_image( + fig, + f"{basename}.{style['export_type']}", + width=plot_width, + height=plot_height, + ) + return fig \ No newline at end of file From 1a92eab5ae4777f59642ca4ac9334a8e4dc157fe Mon Sep 17 00:00:00 2001 From: leburnett Date: Fri, 3 Oct 2025 22:07:51 -0400 Subject: [PATCH 03/60] test --- config/config.cns.yaml | 47 +- src/neuview/services/index_service.py | 12 +- src/neuview/services/scatterplot_service.py | 682 ++++++++++---------- templates/scatterplot.svg.jinja | 383 +++++++++++ test/test_scatter.py | 255 ++++++++ test/test_scatterplot_service.py | 42 ++ 6 files changed, 1050 insertions(+), 371 deletions(-) create mode 100644 templates/scatterplot.svg.jinja create mode 100644 test/test_scatter.py create mode 100644 test/test_scatterplot_service.py diff --git a/config/config.cns.yaml b/config/config.cns.yaml index adfb473..8a78e65 100644 --- a/config/config.cns.yaml +++ b/config/config.cns.yaml @@ -30,25 +30,36 @@ html: youtube_channel: "https://www.youtube.com/@ReiserLab" test_neuron_types: + # normal-set: + # - "SAD103" + # - "SAD052" + # - "Tm3" + # - "SIP071" + # - "AOTU019" + # - "AVLP346" + # - "IN08A006" + # - "SNta35" + # - "'Tergotr. MN'" + # - "'Tergopleural/Pleural promotor MN'" + # - "'IN20A.22A070,IN20A.22A080'" + # - "'PEN_b(PEN2)'" + # - "AN07B013" + # - "'AN08B059'" + # - "'AVLP727m'" + # - "'AOTU103m'" + # - '"KCa''b''-ap1"' + # - "'Acc. ti flexor MN'" normal-set: - - "SAD103" - - "SAD052" - - "Tm3" - - "SIP071" - - "AOTU019" - - "AVLP346" - - "IN08A006" - - "SNta35" - - "'Tergotr. MN'" - - "'Tergopleural/Pleural promotor MN'" - - "'IN20A.22A070,IN20A.22A080'" - - "'PEN_b(PEN2)'" - - "AN07B013" - - "'AN08B059'" - - "'AVLP727m'" - - "'AOTU103m'" - - '"KCa''b''-ap1"' - - "'Acc. ti flexor MN'" + - "L1" + - "Dm4" + - "MeVP14" + - "Dm12" + - "C3" + - "TmY13" + - "Dm9" + - "MeVPMe2" + - "Pm5" + - "Tm35" small-set: - "SAD103" - "Tm3" diff --git a/src/neuview/services/index_service.py b/src/neuview/services/index_service.py index c075329..3a01238 100644 --- a/src/neuview/services/index_service.py +++ b/src/neuview/services/index_service.py @@ -56,17 +56,17 @@ async def create_index(self, command) -> Result[str, str]: return Err(f"Output directory does not exist: {output_dir}") # Discover neuron types from cache or file scanning - neuron_types, scan_time = self._discover_neuron_types(output_dir) + neuron_types, scan_time = self.discover_neuron_types(output_dir) if not neuron_types: return Err("No neuron type HTML files found in output directory") # Initialize connector if needed for database lookups - connector = await self._initialize_connector_if_needed( + connector = await self.initialize_connector_if_needed( neuron_types, output_dir ) # Correct neuron names (convert filenames back to original names) - corrected_neuron_types, cache_performance = self._correct_neuron_names( + corrected_neuron_types, cache_performance = self.correct_neuron_names( neuron_types, connector ) @@ -99,7 +99,7 @@ async def create_index(self, command) -> Result[str, str]: logger.error(f"Failed to create optimized index: {e}") return Err(f"Failed to create index: {str(e)}") - def _discover_neuron_types(self, output_dir: Path) -> tuple: + def discover_neuron_types(self, output_dir: Path) -> tuple: """Discover neuron types from queue file to ensure all are included.""" neuron_types = defaultdict(set) @@ -213,7 +213,7 @@ def _discover_neuron_types(self, output_dir: Path) -> tuple: ) return neuron_types, 0.0 - async def _initialize_connector_if_needed(self, neuron_types, output_dir): + async def initialize_connector_if_needed(self, neuron_types, output_dir): """Initialize database connector only if needed for lookups.""" # Pre-load ROI hierarchy from cache (no database queries if cached) roi_hierarchy_loaded = False @@ -267,7 +267,7 @@ async def _initialize_connector_if_needed(self, neuron_types, output_dir): return connector - def _correct_neuron_names(self, neuron_types, connector): + def correct_neuron_names(self, neuron_types, connector): """Correct neuron names by converting filenames back to original names.""" cached_data_lazy = ( self.cache_manager.get_cached_data_lazy() if self.cache_manager else None diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py index 28951b4..80a13d2 100644 --- a/src/neuview/services/scatterplot_service.py +++ b/src/neuview/services/scatterplot_service.py @@ -6,23 +6,12 @@ """ import logging -import time from pathlib import Path -from collections import defaultdict -from typing import List, Tuple, Dict, Any, Set -import plotly.graph_objects as go -import plotly.io as pio -from cmap import Colormap import pandas as pd -from ..cache import NeuronTypeCacheData from ..result import Result, Ok, Err -from ..utils import get_git_version -from .roi_hierarchy_service import ROIHierarchyService -from .neuron_name_service import NeuronNameService -from .roi_analysis_service import ROIAnalysisService -from .index_generator_service import IndexGeneratorService -from ..index_service import IndexService + +from .index_service import IndexService from .file_service import FileService logger = logging.getLogger(__name__) @@ -52,38 +41,37 @@ async def create_scatterplots(self, command) -> Result[str, str]: return Err(f"Output directory does not exist: {output_dir}") # Discover neuron types from cache or file scanning - neuron_types, _ = IndexService._discover_neuron_types(output_dir) + neuron_types, _ = IndexService.discover_neuron_types(self, output_dir) if not neuron_types: return Err("No neuron type HTML files found in output directory") # Initialize connector if needed for database lookups - connector = await IndexService._initialize_connector_if_needed( - neuron_types, output_dir + connector = await IndexService.initialize_connector_if_needed( + self, neuron_types, output_dir ) # Correct neuron names (convert filenames back to original names) - corrected_neuron_types, _ = IndexService._correct_neuron_names( - neuron_types, connector + corrected_neuron_types, _ = IndexService.correct_neuron_names( + self, neuron_types, connector ) # Generate scatterplot data for corrected neuron types plot_data = self._generate_plot_data(corrected_neuron_types) + print(plot_data) # Generate the plots - # Collect all generated file paths - generated_files = [str(output_dir / command.index_filename)] - if hasattr(self, "generated_files"): - generated_files.extend(self.generated_files) + # # Collect all generated file paths + # generated_files = [str(output_dir / command.index_filename)] + # if hasattr(self, "generated_files"): + # generated_files.extend(self.generated_files) - return Ok(generated_files) - - except Exception as e: - logger.error(f"Failed to create optimized index: {e}") - return Err(f"Failed to create index: {str(e)}") + return plot_data #Ok(generated_files) + except Exception as e: + logger.error(f"Failed to create optimized index: {e}") + return Err(f"Failed to create index: {str(e)}") - def _generate_plot_data(self, neuron_types): """Generate plot data from neuron types.""" cached_data_lazy = ( @@ -143,322 +131,322 @@ def _generate_plot_data(self, neuron_types): return plot_data - # Make an svg - in JS when hover over - that marker is large. - def _make_scatterplot( - xval:str - , yval:str - , roi_str:str - , style:dict - , sizing:dict - , plot_specs:dict - , star_neurons:list - , save_plot:bool=True) -> go.Figure: - """ - Plot scatterplot with 'star_neuron' types highlighted. - - Parameters - ---------- - xval : str - Column of 'df' to be shown on the x-axis. - yval : str - Column of 'df' to be shown on the y-axis. - roi_str : str - Optic lobe region of interest to plot the data from. - style : dict - Dict containing the values of the fixed styling formatting variables. - sizing : dict - Dict containing the values of the size formatting variables. - plot_specs : dict - Dict containing the values of the formatting variables relevant to the specific plot. - star_neurons : list - List of 'star neurons' to highlight in the plot. - save_plot : bool, default = True - Whether to save the plot or only return it. - - Returns - ------- - fig : go.Figure - Formatted plotly scatterplot. - """ - pio.kaleido.scope.mathjax = None - - assert plot_specs["colorscale"] in ["red", "group"]\ - , f"Colorscale must be 'red' or 'group', not '{plot_specs['colorscale']}'" - - # load the data - df = load_and_process_df(roi_str=roi_str) - if xval == "instance": - df = df.sort_values(yval) - - df["markersize"] = float(sizing["markersize"]) - df["markerlinewidth"] = sizing["markerlinewidth"] - df["text"] = "" - - if star_neurons: - df.loc[df["instance"].isin(star_neurons), "markersize"] = ( - sizing["markersize"] * 1.75 - ) - df.loc[df["instance"].isin(star_neurons), "markerlinewidth"] = ( - sizing["markerlinewidth"] * 7 - ) - df.loc[df["instance"].isin(star_neurons), "group"] = 6 - - # get sizing values - if style["export_type"] == "svg": - pixelsperinch = 72 - else: - pixelsperinch = 96 - pixelspermm = pixelsperinch / 25.4 - plot_width = (sizing["fig_width"] - sizing["fig_margin"]) * pixelspermm - plot_height = (sizing["fig_height"] - sizing["fig_margin"]) * pixelspermm - fsize_ticks_px = sizing["fsize_ticks_pt"] * (1 / 72) * pixelsperinch - fsize_title_px = sizing["fsize_title_pt"] * (1 / 72) * pixelsperinch - - cmap = Colormap("reds_5").to_plotly() # colorscale == 'red'; default - if plot_specs["colorscale"] == "group": - cmap = [ - [0, "rgb(200, 200, 200)"] - , [0.1666, "rgb(200, 200, 200)"] - , [0.1666, "rgb(2, 158, 115)"] - , [0.333, "rgb(2, 158, 115)"] - , [0.333, "rgb(213, 94, 0)"] - , [0.5, "rgb(213, 94, 0)"] - , [0.5, "rgb(1,115,178)"] - , [0.666, "rgb(1,115,178)"] - , [0.6666, "rgb(222,143,5)"] - , [0.833, "rgb(222,143,5)"] - , [0.833, "rgb(204, 120, 188)"] - , [1.0, "rgb(204, 120, 188)"] - ] - - # set the maximum - _, n_cols_region = find_neuropil_hex_coords(roi_str) - - fig = go.Figure() - - match yval: - case "coverage_factor_trim": - fig.add_shape( - type="line" - , y0=1 - , x0=1 - , x1=n_cols_region - , y1=1 - , layer="below" - , line={"color": "grey", "width": 0.8, "dash": "solid"} - ) - - case "cell_size_cols": - for multipl in [0.2, 0.5, 1, 2, 5]: - if multipl < 0.5 or multipl > 2: - line_width = 0.25 - elif multipl != 1: - line_width = 0.4 - else: - line_width = 0.8 - - fig.add_shape( - type="line" - , x0=1 - , y0=n_cols_region * multipl - , x1=n_cols_region * multipl - , y1=1 - , layer="below" - , line={"color": "grey", "width": line_width, "dash": "solid"} - ) - - # add groups in order to ensure star neurons are plotted last - gp_values = df["group"].sort_values(ascending=True).unique() - for grp in gp_values: - - df_gp = df[df["group"] == grp] - - fig.add_trace( - go.Scatter( - x=df_gp[xval] - , y=df_gp[yval] - , text=[df_gp["text"]] - , textposition="top center" - , customdata=np.stack( - (df_gp["instance"], df_gp[plot_specs["color_factor"]]), axis=-1 - ) - , hovertemplate=plot_specs["hover_template"] - , opacity=0.95 - , mode="markers" - , marker={ - "cmax": plot_specs["cmax"] - , "cmin": plot_specs["cmin"] - , "size": df_gp["markersize"] - , "color": df_gp[plot_specs["color_factor"]] - , "line": { - "width": df_gp["markerlinewidth"] - , "color": style["markerlinecolor"] - }, - "colorscale": cmap, - "colorbar": { - "orientation": "v" - , "outlinecolor": style["linecolor"] - , "outlinewidth": sizing["axislinewidth"] - , "thickness": sizing["cbar_thickness"] - , "len": sizing["cbar_length"] - , "ticklen": sizing["cbar_tick_length"] - , "tickcolor": "black" - , "tickwidth": sizing["cbar_tick_width"] - , "tickmode": "array" - , "tickvals": plot_specs["tickvals"] - , "ticktext": plot_specs["ticktext"] - , "tickfont": {"size": fsize_ticks_px, "color": "black"} - , "title": { - "font": { - "family": style["font_type"] - , "size": fsize_title_px - , "color": "black" - }, - "side": "right" - , "text": plot_specs["cbar_title"] - } - } - } - ) - ) - - xlabel = get_axis_labels(xval, label_type="axis") - ylabel = get_axis_labels(yval, label_type="axis") - - if plot_specs["log_x"]: - typex = "log" - tickformx = ".1r" - else: - typex = "-" - tickformx = "" - - if plot_specs["log_y"]: - typey = "log" - tickformy = ".1r" - else: - typey = "-" - tickformy = "" - - fig.update_layout( - autosize=False, - width=plot_width, - height=plot_height, - margin={ - "l": plot_width // 8, - "r": 0, - "b": plot_height // 4, - "t": 0, - "pad": plot_width // 30, - }, - showlegend=False, - paper_bgcolor="rgba(255,255,255,1)", - plot_bgcolor="rgba(255,255,255,1)", - ) - - fig.update_xaxes( - title={ - "font": { - "size": fsize_title_px, - "family": style["font_type"], - "color": style["linecolor"], - }, - "text": xlabel, - }, - title_standoff=(plot_height // 4) / 4, - ticks="outside", - ticklen=sizing["ticklen"], - tickwidth=sizing["tickwidth"], - tickfont={ - "family": style["font_type"], - "size": fsize_ticks_px, - "color": style["linecolor"], - }, - tickformat=tickformx, - tickcolor="black", - type=typex, - showgrid=False, - showline=True, - linewidth=sizing["axislinewidth"], - linecolor=style["linecolor"], - range=plot_specs["range_x"], - ) - - match xval: - case "instance": - fig.update_xaxes(title="", tickvals=[], visible=False) - case "coverage_factor_trim": - fig.update_xaxes(tickvals=[1, 2, 4, 8, 12]) - case "cell_size_cols": - fig.update_xaxes(tickvals=[1, 10, 100, 1000]) - case "area_covered_pop": - fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) - case "cols_covered_pop": - fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) - case "population_size": - fig.update_xaxes(tickvals=[1, 10, 100, 1000]) - - fig.update_yaxes( - title={ - "font": { - "size": fsize_title_px - , "family": style["font_type"] - , "color": style["linecolor"] - } - , "text": f"{ylabel}" - } - , title_standoff=(plot_width // 5) / 5 - , ticks="outside" - , tickcolor="black" - , ticklen=sizing["ticklen"] - , tickwidth=sizing["tickwidth"] - , tickfont={ - "size": fsize_ticks_px - , "family": style["font_type"] - , "color": "black" - } - , tickformat=tickformy - , type=typey - , showgrid=False - , showline=True - , linewidth=sizing["axislinewidth"] - , linecolor=style["linecolor"] - , scaleanchor="x" - , scaleratio=1 - , anchor="free" - , side="left" - , overlaying="y" - , range=plot_specs["range_y"] - ) - - match yval: - case "coverage_factor_trim": - fig.update_yaxes(tickvals=[1, 2, 4, 8, 12], scaleanchor=False) - case "cell_size_cols": - fig.update_yaxes(tickvals=[1, 10, 100, 1000]) - case "area_covered_pop": - fig.update_yaxes(tickvals=[0, 200, 400, 600, 800, 1000]) - case "population_size": - fig.update_yaxes(tickvals=[1, 10, 100, 1000]) - - if save_plot: - save_path = plot_specs["save_path"] - assert isinstance(save_path, Path)\ - , f"save_path needs to be 'Path', not '{type(save_path)}'" - save_path.mkdir(parents=True, exist_ok=True) - - basename = ( - save_path - / f"{roi_str[:-3]}_{xval}_versus_{yval}_{sizing['fsize_title_pt']}pt_" - f"w{sizing['fig_width']}_h{sizing['fig_height']}_cscale-{plot_specs['color_factor']}" - ) - - if style["export_type"] == "html": - fig.write_html(f"{basename}.html") - else: - pio.write_image( - fig, - f"{basename}.{style['export_type']}", - width=plot_width, - height=plot_height, - ) - return fig \ No newline at end of file + # # Make an svg - in JS when hover over - that marker is large. + # def _make_scatterplot(self, + # xval:str + # , yval:str + # , roi_str:str + # , style:dict + # , sizing:dict + # , plot_specs:dict + # , star_neurons:list + # , save_plot:bool=True) -> go.Figure: + # """ + # Plot scatterplot with 'star_neuron' types highlighted. + + # Parameters + # ---------- + # xval : str + # Column of 'df' to be shown on the x-axis. + # yval : str + # Column of 'df' to be shown on the y-axis. + # roi_str : str + # Optic lobe region of interest to plot the data from. + # style : dict + # Dict containing the values of the fixed styling formatting variables. + # sizing : dict + # Dict containing the values of the size formatting variables. + # plot_specs : dict + # Dict containing the values of the formatting variables relevant to the specific plot. + # star_neurons : list + # List of 'star neurons' to highlight in the plot. + # save_plot : bool, default = True + # Whether to save the plot or only return it. + + # Returns + # ------- + # fig : go.Figure + # Formatted plotly scatterplot. + # """ + # pio.kaleido.scope.mathjax = None + + # assert plot_specs["colorscale"] in ["red", "group"]\ + # , f"Colorscale must be 'red' or 'group', not '{plot_specs['colorscale']}'" + + # # load the data + # df = load_and_process_df(roi_str=roi_str) + # if xval == "instance": + # df = df.sort_values(yval) + + # df["markersize"] = float(sizing["markersize"]) + # df["markerlinewidth"] = sizing["markerlinewidth"] + # df["text"] = "" + + # if star_neurons: + # df.loc[df["instance"].isin(star_neurons), "markersize"] = ( + # sizing["markersize"] * 1.75 + # ) + # df.loc[df["instance"].isin(star_neurons), "markerlinewidth"] = ( + # sizing["markerlinewidth"] * 7 + # ) + # df.loc[df["instance"].isin(star_neurons), "group"] = 6 + + # # get sizing values + # if style["export_type"] == "svg": + # pixelsperinch = 72 + # else: + # pixelsperinch = 96 + # pixelspermm = pixelsperinch / 25.4 + # plot_width = (sizing["fig_width"] - sizing["fig_margin"]) * pixelspermm + # plot_height = (sizing["fig_height"] - sizing["fig_margin"]) * pixelspermm + # fsize_ticks_px = sizing["fsize_ticks_pt"] * (1 / 72) * pixelsperinch + # fsize_title_px = sizing["fsize_title_pt"] * (1 / 72) * pixelsperinch + + # cmap = Colormap("reds_5").to_plotly() # colorscale == 'red'; default + # if plot_specs["colorscale"] == "group": + # cmap = [ + # [0, "rgb(200, 200, 200)"] + # , [0.1666, "rgb(200, 200, 200)"] + # , [0.1666, "rgb(2, 158, 115)"] + # , [0.333, "rgb(2, 158, 115)"] + # , [0.333, "rgb(213, 94, 0)"] + # , [0.5, "rgb(213, 94, 0)"] + # , [0.5, "rgb(1,115,178)"] + # , [0.666, "rgb(1,115,178)"] + # , [0.6666, "rgb(222,143,5)"] + # , [0.833, "rgb(222,143,5)"] + # , [0.833, "rgb(204, 120, 188)"] + # , [1.0, "rgb(204, 120, 188)"] + # ] + + # # set the maximum + # _, n_cols_region = find_neuropil_hex_coords(roi_str) + + # fig = go.Figure() + + # match yval: + # case "coverage_factor_trim": + # fig.add_shape( + # type="line" + # , y0=1 + # , x0=1 + # , x1=n_cols_region + # , y1=1 + # , layer="below" + # , line={"color": "grey", "width": 0.8, "dash": "solid"} + # ) + + # case "cell_size_cols": + # for multipl in [0.2, 0.5, 1, 2, 5]: + # if multipl < 0.5 or multipl > 2: + # line_width = 0.25 + # elif multipl != 1: + # line_width = 0.4 + # else: + # line_width = 0.8 + + # fig.add_shape( + # type="line" + # , x0=1 + # , y0=n_cols_region * multipl + # , x1=n_cols_region * multipl + # , y1=1 + # , layer="below" + # , line={"color": "grey", "width": line_width, "dash": "solid"} + # ) + + # # add groups in order to ensure star neurons are plotted last + # gp_values = df["group"].sort_values(ascending=True).unique() + # for grp in gp_values: + + # df_gp = df[df["group"] == grp] + + # fig.add_trace( + # go.Scatter( + # x=df_gp[xval] + # , y=df_gp[yval] + # , text=[df_gp["text"]] + # , textposition="top center" + # , customdata=np.stack( + # (df_gp["instance"], df_gp[plot_specs["color_factor"]]), axis=-1 + # ) + # , hovertemplate=plot_specs["hover_template"] + # , opacity=0.95 + # , mode="markers" + # , marker={ + # "cmax": plot_specs["cmax"] + # , "cmin": plot_specs["cmin"] + # , "size": df_gp["markersize"] + # , "color": df_gp[plot_specs["color_factor"]] + # , "line": { + # "width": df_gp["markerlinewidth"] + # , "color": style["markerlinecolor"] + # }, + # "colorscale": cmap, + # "colorbar": { + # "orientation": "v" + # , "outlinecolor": style["linecolor"] + # , "outlinewidth": sizing["axislinewidth"] + # , "thickness": sizing["cbar_thickness"] + # , "len": sizing["cbar_length"] + # , "ticklen": sizing["cbar_tick_length"] + # , "tickcolor": "black" + # , "tickwidth": sizing["cbar_tick_width"] + # , "tickmode": "array" + # , "tickvals": plot_specs["tickvals"] + # , "ticktext": plot_specs["ticktext"] + # , "tickfont": {"size": fsize_ticks_px, "color": "black"} + # , "title": { + # "font": { + # "family": style["font_type"] + # , "size": fsize_title_px + # , "color": "black" + # }, + # "side": "right" + # , "text": plot_specs["cbar_title"] + # } + # } + # } + # ) + # ) + + # xlabel = get_axis_labels(xval, label_type="axis") + # ylabel = get_axis_labels(yval, label_type="axis") + + # if plot_specs["log_x"]: + # typex = "log" + # tickformx = ".1r" + # else: + # typex = "-" + # tickformx = "" + + # if plot_specs["log_y"]: + # typey = "log" + # tickformy = ".1r" + # else: + # typey = "-" + # tickformy = "" + + # fig.update_layout( + # autosize=False, + # width=plot_width, + # height=plot_height, + # margin={ + # "l": plot_width // 8, + # "r": 0, + # "b": plot_height // 4, + # "t": 0, + # "pad": plot_width // 30, + # }, + # showlegend=False, + # paper_bgcolor="rgba(255,255,255,1)", + # plot_bgcolor="rgba(255,255,255,1)", + # ) + + # fig.update_xaxes( + # title={ + # "font": { + # "size": fsize_title_px, + # "family": style["font_type"], + # "color": style["linecolor"], + # }, + # "text": xlabel, + # }, + # title_standoff=(plot_height // 4) / 4, + # ticks="outside", + # ticklen=sizing["ticklen"], + # tickwidth=sizing["tickwidth"], + # tickfont={ + # "family": style["font_type"], + # "size": fsize_ticks_px, + # "color": style["linecolor"], + # }, + # tickformat=tickformx, + # tickcolor="black", + # type=typex, + # showgrid=False, + # showline=True, + # linewidth=sizing["axislinewidth"], + # linecolor=style["linecolor"], + # range=plot_specs["range_x"], + # ) + + # match xval: + # case "instance": + # fig.update_xaxes(title="", tickvals=[], visible=False) + # case "coverage_factor_trim": + # fig.update_xaxes(tickvals=[1, 2, 4, 8, 12]) + # case "cell_size_cols": + # fig.update_xaxes(tickvals=[1, 10, 100, 1000]) + # case "area_covered_pop": + # fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) + # case "cols_covered_pop": + # fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) + # case "population_size": + # fig.update_xaxes(tickvals=[1, 10, 100, 1000]) + + # fig.update_yaxes( + # title={ + # "font": { + # "size": fsize_title_px + # , "family": style["font_type"] + # , "color": style["linecolor"] + # } + # , "text": f"{ylabel}" + # } + # , title_standoff=(plot_width // 5) / 5 + # , ticks="outside" + # , tickcolor="black" + # , ticklen=sizing["ticklen"] + # , tickwidth=sizing["tickwidth"] + # , tickfont={ + # "size": fsize_ticks_px + # , "family": style["font_type"] + # , "color": "black" + # } + # , tickformat=tickformy + # , type=typey + # , showgrid=False + # , showline=True + # , linewidth=sizing["axislinewidth"] + # , linecolor=style["linecolor"] + # , scaleanchor="x" + # , scaleratio=1 + # , anchor="free" + # , side="left" + # , overlaying="y" + # , range=plot_specs["range_y"] + # ) + + # match yval: + # case "coverage_factor_trim": + # fig.update_yaxes(tickvals=[1, 2, 4, 8, 12], scaleanchor=False) + # case "cell_size_cols": + # fig.update_yaxes(tickvals=[1, 10, 100, 1000]) + # case "area_covered_pop": + # fig.update_yaxes(tickvals=[0, 200, 400, 600, 800, 1000]) + # case "population_size": + # fig.update_yaxes(tickvals=[1, 10, 100, 1000]) + + # if save_plot: + # save_path = plot_specs["save_path"] + # assert isinstance(save_path, Path)\ + # , f"save_path needs to be 'Path', not '{type(save_path)}'" + # save_path.mkdir(parents=True, exist_ok=True) + + # basename = ( + # save_path + # / f"{roi_str[:-3]}_{xval}_versus_{yval}_{sizing['fsize_title_pt']}pt_" + # f"w{sizing['fig_width']}_h{sizing['fig_height']}_cscale-{plot_specs['color_factor']}" + # ) + + # if style["export_type"] == "html": + # fig.write_html(f"{basename}.html") + # else: + # pio.write_image( + # fig, + # f"{basename}.{style['export_type']}", + # width=plot_width, + # height=plot_height, + # ) + # return fig \ No newline at end of file diff --git a/templates/scatterplot.svg.jinja b/templates/scatterplot.svg.jinja new file mode 100644 index 0000000..24b6298 --- /dev/null +++ b/templates/scatterplot.svg.jinja @@ -0,0 +1,383 @@ + + + + + + + +{#-- Background --#} + + +{#-- Title, Subtitle, and Layer Scrollbar --#} +{{ title }} +{{ subtitle }} + +{#-- Hexagon Path Definition --#} +{% set hex_path = "M" + hex_points|join(" L") + " Z" %} + +{#-- Hexagons --#} + +{%- for hex_data in hexagons -%} +{%- set x = (hex_data.x + margin) | round(number_precision) -%} +{%- set y = (hex_data.y + margin) | round(number_precision) -%} + +{# +#}{# + #}{{ hex_data.tooltip }}{# +#}{# +#} +{%- endfor -%} + + +{#-- Legend (only if there's actual data) -- #} +{% if data_hexagons %} + {#-- We store both threshold sets on the legend group as JSON -- #} + + {{ legend_title }} + + {#-- Color Legend Rectangles (5 bins) -- #} + {% for i, color in enumerate(colors) %} + {% set rect_y = legend_y + legend_height - (i + 1) * bin_height %} + + {#-- Initial title from default thresholds --#} + {{ thresholds[i]|round(0)|int }}…{{ thresholds[i+1]|round(0)|int }} + + {% endfor %} + + {#-- Threshold Labels (6 ticks) --#} + {% for i, threshold in enumerate(thresholds) %} + {% set label_y = legend_y + legend_height - i * bin_height %} + {{ threshold|round(0)|int }} + {% endfor %} + +{% endif %} + +{#-- Tooltip (rendered last to appear on top) --#} + + + + + + diff --git a/test/test_scatter.py b/test/test_scatter.py new file mode 100644 index 0000000..c194be1 --- /dev/null +++ b/test/test_scatter.py @@ -0,0 +1,255 @@ + +# scatter_svg_from_plot_data.py +from math import ceil, floor +from jinja2 import Template + +plot_data = [{'name': 'ANXXX006', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'AVLP370_a', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'AVLP447', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'C3', 'total_count': 1779, 'left_count': 887, 'right_count': 892, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 880, 'coverage': 6.196590909090909, 'cell_size': 6.0}, 'LO': {'cols_innervated': 2, 'coverage': 1.5, 'cell_size': 1.5}, 'LOP': {'cols_innervated': 2, 'coverage': 1.0, 'cell_size': 1.0}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 6.36322869955157, 'cell_size': 6.0}, 'LO': {'cols_innervated': 3, 'coverage': 1.0, 'cell_size': 1.5}, 'LOP': {'cols_innervated': 3, 'coverage': 1.0, 'cell_size': 1.0}}, 'both': {'ME': {'cols_innervated': 886.0, 'coverage': 6.279909804321239, 'cell_size': 6.0}, 'LO': {'cols_innervated': 2.5, 'coverage': 1.25, 'cell_size': 1.5}, 'LOP': {'cols_innervated': 2.5, 'coverage': 1.0, 'cell_size': 1.0}}}}, {'name': 'CB3417', 'total_count': 10, 'left_count': 5, 'right_count': 5, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'Dm12', 'total_count': 276, 'left_count': 139, 'right_count': 137, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 880, 'coverage': 4.795454545454546, 'cell_size': 30.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 4.996636771300448, 'cell_size': 31.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 10, 'coverage': 1.0, 'cell_size': 10.0}}, 'both': {'ME': {'cols_innervated': 886.0, 'coverage': 4.896045658377497, 'cell_size': 30.5}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 5.0, 'coverage': 1.0, 'cell_size': 10.0}}}}, {'name': 'Dm4', 'total_count': 99, 'left_count': 51, 'right_count': 48, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 876, 'coverage': 1.6232876712328768, 'cell_size': 27.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 890, 'coverage': 1.5853932584269663, 'cell_size': 29.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 883.0, 'coverage': 1.6043404648299215, 'cell_size': 28.0}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'Dm9', 'total_count': 273, 'left_count': 138, 'right_count': 135, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 853, 'coverage': 2.7960140679953107, 'cell_size': 18.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 885, 'coverage': 3.218079096045198, 'cell_size': 21.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 869.0, 'coverage': 3.007046582020254, 'cell_size': 19.5}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN01B041', 'total_count': 4, 'left_count': 2, 'right_count': 2, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN01B099', 'total_count': 4, 'left_count': 2, 'right_count': 2, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN19B107', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN23B083', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'L1', 'total_count': 1776, 'left_count': 884, 'right_count': 892, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 880, 'coverage': 3.853409090909091, 'cell_size': 4.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 3.874439461883408, 'cell_size': 4.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 886.0, 'coverage': 3.86392427639625, 'cell_size': 4.0}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'MeVP14', 'total_count': 33, 'left_count': 16, 'right_count': 17, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 363, 'coverage': 3.0137741046831956, 'cell_size': 70.0}, 'LO': {'cols_innervated': 91, 'coverage': 3.32967032967033, 'cell_size': 18.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 404, 'coverage': 3.2747524752475248, 'cell_size': 80.0}, 'LO': {'cols_innervated': 106, 'coverage': 3.5377358490566038, 'cell_size': 18.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 383.5, 'coverage': 3.14426328996536, 'cell_size': 75.0}, 'LO': {'cols_innervated': 98.5, 'coverage': 3.433703089363467, 'cell_size': 18.0}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'MeVPMe2', 'total_count': 10, 'left_count': 5, 'right_count': 5, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 851, 'coverage': 5.048178613396004, 'cell_size': 419.5}, 'LO': {'cols_innervated': 47, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 44, 'coverage': 1.0227272727272727, 'cell_size': 7.0}}, 'R': {'ME': {'cols_innervated': 873, 'coverage': 5.128293241695304, 'cell_size': 438.5}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 32, 'coverage': 1.21875, 'cell_size': 19.5}}, 'both': {'ME': {'cols_innervated': 862.0, 'coverage': 5.088235927545654, 'cell_size': 429.0}, 'LO': {'cols_innervated': 23.5, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 38.0, 'coverage': 1.1207386363636362, 'cell_size': 13.25}}}}, {'name': 'Pm5', 'total_count': 182, 'left_count': 88, 'right_count': 94, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 877, 'coverage': 4.866590649942988, 'cell_size': 48.0}, 'LO': {'cols_innervated': 6, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 5.0459641255605385, 'cell_size': 47.5}, 'LO': {'cols_innervated': 3, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 884.5, 'coverage': 4.956277387751763, 'cell_size': 47.75}, 'LO': {'cols_innervated': 4.5, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'SLP018', 'total_count': 10, 'left_count': 5, 'right_count': 5, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'SNpp10', 'total_count': 7, 'left_count': 0, 'right_count': 0, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'Tm35', 'total_count': 86, 'left_count': 43, 'right_count': 43, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 507, 'coverage': 2.035502958579882, 'cell_size': 24.0}, 'LO': {'cols_innervated': 560, 'coverage': 2.244642857142857, 'cell_size': 29.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 560, 'coverage': 2.0892857142857144, 'cell_size': 27.0}, 'LO': {'cols_innervated': 561, 'coverage': 2.1853832442067738, 'cell_size': 28.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 533.5, 'coverage': 2.0623943364327983, 'cell_size': 25.5}, 'LO': {'cols_innervated': 560.5, 'coverage': 2.2150130506748154, 'cell_size': 28.5}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'TmY13', 'total_count': 432, 'left_count': 221, 'right_count': 211, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 875, 'coverage': 4.619428571428571, 'cell_size': 18.0}, 'LO': {'cols_innervated': 855, 'coverage': 2.2432748538011698, 'cell_size': 9.0}, 'LOP': {'cols_innervated': 654, 'coverage': 1.607033639143731, 'cell_size': 5.0}}, 'R': {'ME': {'cols_innervated': 891, 'coverage': 4.721661054994389, 'cell_size': 20.0}, 'LO': {'cols_innervated': 850, 'coverage': 2.2411764705882353, 'cell_size': 9.0}, 'LOP': {'cols_innervated': 713, 'coverage': 1.817671809256662, 'cell_size': 7.0}}, 'both': {'ME': {'cols_innervated': 883.0, 'coverage': 4.67054481321148, 'cell_size': 19.0}, 'LO': {'cols_innervated': 852.5, 'coverage': 2.2422256621947025, 'cell_size': 9.0}, 'LOP': {'cols_innervated': 683.5, 'coverage': 1.7123527242001964, 'cell_size': 6.0}}}}] + +def extract_points(records, side, region): + pts = [] + for rec in records: + name = rec.get("name", "unknown") + x = rec.get("total_count") + y = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("cell_size") + ) + if x is None or y is None: + continue + try: y = float(y) + except: continue + pts.append({"name": name, "x": int(x), "y": y}) + return pts + +def nice_ticks(vmin, vmax, n=5): + """Very small 'nice' tick helper for axes.""" + if vmin == vmax: + return [vmin] + span = vmax - vmin + raw = span / max(1, (n - 1)) + # round raw to 1/2/5 * 10^k + pow10 = 10 ** floor(len(str(int(raw))) - 1 if raw >= 1 else 0) + base = raw / pow10 + if base <= 1: step = 1 + elif base <= 2: step = 2 + elif base <= 5: step = 5 + else: step = 10 + step *= pow10 + start = floor(vmin / step) * step + end = ceil(vmax / step) * step + ticks = [] + v = start + # cap to avoid runaway in pathological cases + for _ in range(1000): + ticks.append(v) + v += step + if v > end + 1e-9: + break + return ticks + +def scale(v, vmin, vmax, a, b): + if vmax == vmin: + return (a + b) / 2.0 + return a + (v - vmin) * (b - a) / (vmax - vmin) + +def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): + """Compute pixel positions for an SVG scatter plot.""" + top, right, bottom, left = margins + plot_w = width - left - right + plot_h = height - top - bottom + + xmin = min(p["x"] for p in points) + xmax = max(p["x"] for p in points) + ymin = min(p["y"] for p in points) + ymax = max(p["y"] for p in points) + + # expand bounds a little so dots don't sit on the frame + pad_x = 0.05 * (xmax - xmin or 1) + pad_y = 0.08 * (ymax - ymin or 1) + xmin -= pad_x; xmax += pad_x + ymin -= pad_y; ymax += pad_y + + # ticks + xticks = nice_ticks(xmin, xmax, n=6) + yticks = nice_ticks(ymin, ymax, n=6) + + # scale points to pixels (y inverted for SVG) + for p in points: + p["sx"] = scale(p["x"], xmin, xmax, 0, plot_w) + p["sy"] = scale(p["y"], ymin, ymax, plot_h, 0) + p["r"] = 4 + p["tooltip"] = f"{p['name']}\ncount: {p['x']}\nL→ME cell_size: {p['y']:.3f}" + + ctx = { + "width": width, + "height": height, + "margin_top": top, + "margin_right": right, + "margin_bottom": bottom, + "margin_left": left, + "plot_w": plot_w, + "plot_h": plot_h, + "xticks": xticks, + "yticks": yticks, + "xmin": xmin, "xmax": xmax, + "ymin": ymin, "ymax": ymax, + "points": points, + "title": "L → ME: total_count vs cell_size", + "subtitle": "one marker per name", + } + return ctx + +SVG_TEMPLATE = Template(r""" + + + + + + + + +{{ title }} +{{ subtitle }} + + + + + + + {% for t in xticks %} + {% set px = (t - xmin) / (xmax - xmin) * plot_w if xmax != xmin else plot_w/2 %} + + {{ '{:.0f}'.format(t) }} + {% endfor %} + + + + {% for t in yticks %} + {% set py = plot_h - (t - ymin) / (ymax - ymin) * plot_h if ymax != ymin else plot_h/2 %} + + {{ '{:.2f}'.format(t) }} + {% endfor %} + + + + {% for p in points %} + + + {{ p.tooltip }} + + + {% endfor %} + + + + + + + + +""") + +if __name__ == "__main__": + side = "R" + region = "ME" + points = extract_points(plot_data, side=side, region=region) + print(points) + if not points: + raise SystemExit("No points found: ensure R→ME cell_size values exist.") + ctx = prepare(points) + svg = SVG_TEMPLATE.render(**ctx) + with open(f"scatter_{side}_{region}.svg", "w", encoding="utf-8") as f: + f.write(svg) + print(f"Wrote scatter_{side}_{region}.svg") diff --git a/test/test_scatterplot_service.py b/test/test_scatterplot_service.py new file mode 100644 index 0000000..8163f78 --- /dev/null +++ b/test/test_scatterplot_service.py @@ -0,0 +1,42 @@ +""" +Test scatterplot service +""" + +import pytest +import sys +import os + +# Add src directory to path for imports +sys.path.append(os.path.join(os.path.dirname(__file__), "..", "src")) + +from neuview.config import Config +from neuview.neuprint_connector import NeuPrintConnector +from neuview.services.scatterplot_service import ScatterplotService + +class TestScatterPlotService: + """Test scatterplot data""" + + @pytest.fixture + def config(self): + """Create test configuration.""" + # Try to load from actual config file if available, otherwise use minimal config + config_path = os.path.join(os.path.dirname(__file__), "..", "config.yaml") + + if os.path.exists(config_path): + try: + return Config.load(config_path) + except Exception: + # Fall back to minimal config if loading fails + return Config.create_minimal_for_testing() + else: + return Config.create_minimal_for_testing() + + @pytest.fixture + def neuprint_connector(self, config): + """Create NeuPrint connector instance.""" + return NeuPrintConnector(config) + + @pytest.fixture + def service(self): + # Build with a dummy config; we'll override the output dir per-test + return ScatterplotService(config=self.config, page_generator=None) From d20bc37158127df0c9866789e3f568f31cc98421 Mon Sep 17 00:00:00 2001 From: leburnett Date: Sun, 5 Oct 2025 20:23:38 -0400 Subject: [PATCH 04/60] add testing code --- my_file.pkl | Bin 0 -> 4319120 bytes 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file) # Log performance summary self._log_performance_summary( diff --git a/test/test_scatter.py b/test/test_scatter.py index c194be1..aceba90 100644 --- a/test/test_scatter.py +++ b/test/test_scatter.py @@ -1,11 +1,20 @@ - # scatter_svg_from_plot_data.py -from math import ceil, floor +from math import ceil, floor, log10, isfinite from jinja2 import Template +import pickle + +file_path = 'my_file.pkl' +with open(file_path, 'rb') as f: + plot_data = pickle.load(f) -plot_data = [{'name': 'ANXXX006', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'AVLP370_a', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'AVLP447', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'C3', 'total_count': 1779, 'left_count': 887, 'right_count': 892, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 880, 'coverage': 6.196590909090909, 'cell_size': 6.0}, 'LO': {'cols_innervated': 2, 'coverage': 1.5, 'cell_size': 1.5}, 'LOP': {'cols_innervated': 2, 'coverage': 1.0, 'cell_size': 1.0}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 6.36322869955157, 'cell_size': 6.0}, 'LO': {'cols_innervated': 3, 'coverage': 1.0, 'cell_size': 1.5}, 'LOP': {'cols_innervated': 3, 'coverage': 1.0, 'cell_size': 1.0}}, 'both': {'ME': {'cols_innervated': 886.0, 'coverage': 6.279909804321239, 'cell_size': 6.0}, 'LO': {'cols_innervated': 2.5, 'coverage': 1.25, 'cell_size': 1.5}, 'LOP': {'cols_innervated': 2.5, 'coverage': 1.0, 'cell_size': 1.0}}}}, {'name': 'CB3417', 'total_count': 10, 'left_count': 5, 'right_count': 5, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'Dm12', 'total_count': 276, 'left_count': 139, 'right_count': 137, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 880, 'coverage': 4.795454545454546, 'cell_size': 30.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 4.996636771300448, 'cell_size': 31.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 10, 'coverage': 1.0, 'cell_size': 10.0}}, 'both': {'ME': {'cols_innervated': 886.0, 'coverage': 4.896045658377497, 'cell_size': 30.5}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 5.0, 'coverage': 1.0, 'cell_size': 10.0}}}}, {'name': 'Dm4', 'total_count': 99, 'left_count': 51, 'right_count': 48, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 876, 'coverage': 1.6232876712328768, 'cell_size': 27.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 890, 'coverage': 1.5853932584269663, 'cell_size': 29.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 883.0, 'coverage': 1.6043404648299215, 'cell_size': 28.0}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'Dm9', 'total_count': 273, 'left_count': 138, 'right_count': 135, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 853, 'coverage': 2.7960140679953107, 'cell_size': 18.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 885, 'coverage': 3.218079096045198, 'cell_size': 21.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 869.0, 'coverage': 3.007046582020254, 'cell_size': 19.5}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN01B041', 'total_count': 4, 'left_count': 2, 'right_count': 2, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN01B099', 'total_count': 4, 'left_count': 2, 'right_count': 2, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN19B107', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'IN23B083', 'total_count': 2, 'left_count': 1, 'right_count': 1, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'L1', 'total_count': 1776, 'left_count': 884, 'right_count': 892, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 880, 'coverage': 3.853409090909091, 'cell_size': 4.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 3.874439461883408, 'cell_size': 4.0}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 886.0, 'coverage': 3.86392427639625, 'cell_size': 4.0}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'MeVP14', 'total_count': 33, 'left_count': 16, 'right_count': 17, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 363, 'coverage': 3.0137741046831956, 'cell_size': 70.0}, 'LO': {'cols_innervated': 91, 'coverage': 3.32967032967033, 'cell_size': 18.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 404, 'coverage': 3.2747524752475248, 'cell_size': 80.0}, 'LO': {'cols_innervated': 106, 'coverage': 3.5377358490566038, 'cell_size': 18.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 383.5, 'coverage': 3.14426328996536, 'cell_size': 75.0}, 'LO': {'cols_innervated': 98.5, 'coverage': 3.433703089363467, 'cell_size': 18.0}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'MeVPMe2', 'total_count': 10, 'left_count': 5, 'right_count': 5, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 851, 'coverage': 5.048178613396004, 'cell_size': 419.5}, 'LO': {'cols_innervated': 47, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 44, 'coverage': 1.0227272727272727, 'cell_size': 7.0}}, 'R': {'ME': {'cols_innervated': 873, 'coverage': 5.128293241695304, 'cell_size': 438.5}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 32, 'coverage': 1.21875, 'cell_size': 19.5}}, 'both': {'ME': {'cols_innervated': 862.0, 'coverage': 5.088235927545654, 'cell_size': 429.0}, 'LO': {'cols_innervated': 23.5, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 38.0, 'coverage': 1.1207386363636362, 'cell_size': 13.25}}}}, {'name': 'Pm5', 'total_count': 182, 'left_count': 88, 'right_count': 94, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 877, 'coverage': 4.866590649942988, 'cell_size': 48.0}, 'LO': {'cols_innervated': 6, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 892, 'coverage': 5.0459641255605385, 'cell_size': 47.5}, 'LO': {'cols_innervated': 3, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 884.5, 'coverage': 4.956277387751763, 'cell_size': 47.75}, 'LO': {'cols_innervated': 4.5, 'coverage': 1.0, 'cell_size': 1.0}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'SLP018', 'total_count': 10, 'left_count': 5, 'right_count': 5, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'SNpp10', 'total_count': 7, 'left_count': 0, 'right_count': 0, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LO': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'Tm35', 'total_count': 86, 'left_count': 43, 'right_count': 43, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 507, 'coverage': 2.035502958579882, 'cell_size': 24.0}, 'LO': {'cols_innervated': 560, 'coverage': 2.244642857142857, 'cell_size': 29.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'R': {'ME': {'cols_innervated': 560, 'coverage': 2.0892857142857144, 'cell_size': 27.0}, 'LO': {'cols_innervated': 561, 'coverage': 2.1853832442067738, 'cell_size': 28.0}, 'LOP': {'cols_innervated': 0, 'coverage': None, 'cell_size': None}}, 'both': {'ME': {'cols_innervated': 533.5, 'coverage': 2.0623943364327983, 'cell_size': 25.5}, 'LO': {'cols_innervated': 560.5, 'coverage': 2.2150130506748154, 'cell_size': 28.5}, 'LOP': {'cols_innervated': 0.0, 'coverage': None, 'cell_size': None}}}}, {'name': 'TmY13', 'total_count': 432, 'left_count': 221, 'right_count': 211, 'middle_count': 0, 'undefined_count': 0, 'has_undefined': False, 'spatial_metrics': {'L': {'ME': {'cols_innervated': 875, 'coverage': 4.619428571428571, 'cell_size': 18.0}, 'LO': {'cols_innervated': 855, 'coverage': 2.2432748538011698, 'cell_size': 9.0}, 'LOP': {'cols_innervated': 654, 'coverage': 1.607033639143731, 'cell_size': 5.0}}, 'R': {'ME': {'cols_innervated': 891, 'coverage': 4.721661054994389, 'cell_size': 20.0}, 'LO': {'cols_innervated': 850, 'coverage': 2.2411764705882353, 'cell_size': 9.0}, 'LOP': {'cols_innervated': 713, 'coverage': 1.817671809256662, 'cell_size': 7.0}}, 'both': {'ME': {'cols_innervated': 883.0, 'coverage': 4.67054481321148, 'cell_size': 19.0}, 'LO': {'cols_innervated': 852.5, 'coverage': 2.2422256621947025, 'cell_size': 9.0}, 'LOP': {'cols_innervated': 683.5, 'coverage': 1.7123527242001964, 'cell_size': 6.0}}}}] def extract_points(records, side, region): + """ + Collect points, requiring: + - total_count (x) > 0 + - cell_size (y) > 0 from spatial_metrics[side][region].cell_size + - coverage (c) present and >= 0 (used only for color scale) + """ pts = [] for rec in records: name = rec.get("name", "unknown") @@ -16,46 +25,60 @@ def extract_points(records, side, region): .get(region, {}) .get("cell_size") ) - if x is None or y is None: + c = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("coverage") + ) + # require x,y positive for log scales + if x is None or y is None or c is None: + continue + try: + x = float(x) + y = float(y) + c = float(c) + except Exception: continue - try: y = float(y) - except: continue - pts.append({"name": name, "x": int(x), "y": y}) + if x <= 0 or y <= 0: + continue + pts.append({"name": name, "x": x, "y": y, "coverage": c}) return pts -def nice_ticks(vmin, vmax, n=5): - """Very small 'nice' tick helper for axes.""" - if vmin == vmax: - return [vmin] - span = vmax - vmin - raw = span / max(1, (n - 1)) - # round raw to 1/2/5 * 10^k - pow10 = 10 ** floor(len(str(int(raw))) - 1 if raw >= 1 else 0) - base = raw / pow10 - if base <= 1: step = 1 - elif base <= 2: step = 2 - elif base <= 5: step = 5 - else: step = 10 - step *= pow10 - start = floor(vmin / step) * step - end = ceil(vmax / step) * step - ticks = [] - v = start - # cap to avoid runaway in pathological cases - for _ in range(1000): - ticks.append(v) - v += step - if v > end + 1e-9: - break - return ticks - -def scale(v, vmin, vmax, a, b): - if vmax == vmin: +def log_ticks(vmin, vmax): + """Decade ticks for a log10 axis between (vmin, vmax), inclusive.""" + if vmin <= 0 or vmax <= 0 or vmin >= vmax: + return [] + lo = floor(log10(vmin)) + hi = ceil(log10(vmax)) + return [10 ** e for e in range(lo, hi + 1)] + +def scale_log10(v, vmin, vmax, a, b): + """Log10 scaling to pixels.""" + lv = log10(v) + lmin = log10(vmin) + lmax = log10(vmax) + if lmax == lmin: return (a + b) / 2.0 - return a + (v - vmin) * (b - a) / (vmax - vmin) + return a + (lv - lmin) * (b - a) / (lmax - lmin) + +def lerp(a, b, t): + return a + (b - a) * t + +def cov_to_rgb(t): + """ + Map t in [0,1] to a white→dark red gradient. + start = white (255,255,255), end = dark red (~180,0,0) + """ + r0, g0, b0 = 255, 255, 255 + r1, g1, b1 = 255, 0, 0 + r = int(round(lerp(r0, r1, t))) + g = int(round(lerp(g0, g1, t))) + b = int(round(lerp(b0, b1, t))) + return f"rgb({r},{g},{b})" -def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): - """Compute pixel positions for an SVG scatter plot.""" +def prepare(points, width=680, height=440, margins=(60, 24, 44, 64)): + """Compute pixel positions for an SVG scatter plot (log–log, color by coverage).""" top, right, bottom, left = margins plot_w = width - left - right plot_h = height - top - bottom @@ -65,22 +88,36 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): ymin = min(p["y"] for p in points) ymax = max(p["y"] for p in points) - # expand bounds a little so dots don't sit on the frame - pad_x = 0.05 * (xmax - xmin or 1) - pad_y = 0.08 * (ymax - ymin or 1) - xmin -= pad_x; xmax += pad_x - ymin -= pad_y; ymax += pad_y + # expand bounds slightly so dots don't sit on the frame (keep >0) + pad_x = xmin * 0.05 + pad_y = ymin * 0.08 + xmin = max(1e-12, xmin - pad_x) + ymin = max(1e-12, ymin - pad_y) + xmax *= 1.05 + ymax *= 1.08 - # ticks - xticks = nice_ticks(xmin, xmax, n=6) - yticks = nice_ticks(ymin, ymax, n=6) + # ticks (log decades) + xticks = log_ticks(xmin, xmax) + yticks = log_ticks(ymin, ymax) + + # coverage color scaling + cmin = min(p["coverage"] for p in points) + cmax = max(p["coverage"] for p in points) + crng = (cmax - cmin) if isfinite(cmax - cmin) and (cmax - cmin) > 0 else 1.0 - # scale points to pixels (y inverted for SVG) for p in points: - p["sx"] = scale(p["x"], xmin, xmax, 0, plot_w) - p["sy"] = scale(p["y"], ymin, ymax, plot_h, 0) + p["sx"] = scale_log10(p["x"], xmin, xmax, 0, plot_w) + p["sy"] = scale_log10(p["y"], ymin, ymax, plot_h, 0) # invert later via SVG coords + # color by coverage + t = (p["coverage"] - cmin) / crng + p["color"] = cov_to_rgb(max(0.0, min(1.0, t))) p["r"] = 4 - p["tooltip"] = f"{p['name']}\ncount: {p['x']}\nL→ME cell_size: {p['y']:.3f}" + p["tooltip"] = ( + f"{p['name']}\n" + f"count: {int(p['x'])}\n" + f"L→ME cell_size: {p['y']:.3f}\n" + f"coverage: {p['coverage']:.3f}" + ) ctx = { "width": width, @@ -95,12 +132,38 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): "yticks": yticks, "xmin": xmin, "xmax": xmax, "ymin": ymin, "ymax": ymax, + "cmin": cmin, "cmax": cmax, "points": points, - "title": "L → ME: total_count vs cell_size", - "subtitle": "one marker per name", + "title": "L → ME: total_count vs cell_size (log–log)", + "subtitle": "color = coverage (blue→red)", } + + # Precompute pixel tick positions for Jinja (avoid math inside template) + def log_pos_x(t): + return scale_log10(t, xmin, xmax, 0, plot_w) + def log_pos_y(t): + return scale_log10(t, ymin, ymax, plot_h, 0) + + xtick_data = [{"t": t, "px": log_pos_x(t)} for t in xticks] + ytick_data = [{"t": t, "py": log_pos_y(t)} for t in yticks] + + ctx.update({ + "xtick_data": xtick_data, + "ytick_data": ytick_data, + }) + return ctx +def fmt_decade(v): + """Format decade tick as 10^n, fallback to number if not exact.""" + try: + e = round(log10(v)) + if abs((10**e) - v) / v < 1e-9: + return f"10^{e}" + except Exception: + pass + return f"{v:g}" + SVG_TEMPLATE = Template(r""" @@ -129,14 +193,12 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): function showTip(evt) { const svg = evt.currentTarget.ownerSVGElement; const tip = svg.getElementById("tooltip"); - const g = evt.currentTarget; // + const g = evt.currentTarget; const c = g.querySelector("circle"); - // enlarge circle const base = parseFloat(c.getAttribute("data-base-r") || "4"); c.setAttribute("r", String(base * 1.8)); - // compute tooltip text from data-title const text = c.getAttribute("data-title") || ""; if (!text) return; @@ -158,12 +220,11 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): } const rect = svg.getElementById("tooltip-bg"); - const boxW = Math.max(maxW + pad * 2, 120); + const boxW = Math.max(maxW + pad * 2, 140); const boxH = lines.length * lh + pad * 2; rect.setAttribute("width", boxW); rect.setAttribute("height", boxH); - // position near mouse, clamp to viewport const bounds = svg.getBoundingClientRect(); let x = evt.clientX - bounds.left + 10; let y = evt.clientY - bounds.top - boxH - 10; @@ -174,7 +235,6 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): tip.setAttribute("transform", "translate(" + x + "," + y + ")"); tip.setAttribute("opacity", "1"); - // suppress native popups const tEl = g.querySelector("title"); if (tEl) tEl.textContent = ""; } @@ -184,13 +244,11 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): const tip = svg.getElementById("tooltip"); tip.setAttribute("opacity", "0"); - // restore radius const g = evt.currentTarget; const c = g.querySelector("circle"); const base = parseFloat(c.getAttribute("data-base-r") || "4"); c.setAttribute("r", String(base)); - // restore native title text for accessibility const text = c.getAttribute("data-title") || ""; const tEl = g.querySelector("title"); if (tEl) tEl.textContent = text; @@ -200,56 +258,75 @@ def prepare(points, width=680, height=420, margins=(50, 20, 30, 50)): {{ title }} -{{ subtitle }} +{{ subtitle }} - - {% for t in xticks %} - {% set px = (t - xmin) / (xmax - xmin) * plot_w if xmax != xmin else plot_w/2 %} - - {{ '{:.0f}'.format(t) }} - {% endfor %} + + - - {% for t in yticks %} - {% set py = plot_h - (t - ymin) / (ymax - ymin) * plot_h if ymax != ymin else plot_h/2 %} - - {{ '{:.2f}'.format(t) }} + + {% for tick in xtick_data %} + + + {{ fmt_decade(tick.t) }} + + {% endfor %} + + + {% for tick in ytick_data %} + + + {{ fmt_decade(tick.t) }} + {% endfor %} - {% for p in points %} - + {{ p.tooltip }} {% endfor %} + + + + + + + + + + coverage: {{ '%.3f' % cmin }} + {{ '%.3f' % cmax }} + + - + -""") +""", trim_blocks=True, lstrip_blocks=True) + +# Jinja helper registrations +SVG_TEMPLATE.globals.update(fmt_decade=fmt_decade) if __name__ == "__main__": side = "R" region = "ME" points = extract_points(plot_data, side=side, region=region) - print(points) if not points: - raise SystemExit("No points found: ensure R→ME cell_size values exist.") + raise SystemExit("No points found: ensure R→ME cell_size values exist and x,y > 0.") ctx = prepare(points) svg = SVG_TEMPLATE.render(**ctx) with open(f"scatter_{side}_{region}.svg", "w", encoding="utf-8") as f: f.write(svg) - print(f"Wrote scatter_{side}_{region}.svg") + print(f"Wrote scatter_{side}_{region}.svg") \ No newline at end of file From 6345726f7e6d4ca3abbe138befcefe9df35c55b3 Mon Sep 17 00:00:00 2001 From: leburnett Date: Mon, 6 Oct 2025 13:02:38 -0400 Subject: [PATCH 05/60] Update test_scatter.py --- test/test_scatter.py | 255 ++++++++++++++++++++++++++++++------------- 1 file changed, 181 insertions(+), 74 deletions(-) diff --git a/test/test_scatter.py b/test/test_scatter.py index aceba90..21f675e 100644 --- a/test/test_scatter.py +++ b/test/test_scatter.py @@ -1,4 +1,4 @@ -# scatter_svg_from_plot_data.py +# scatter_svg_from_plot_data.py (updated) from math import ceil, floor, log10, isfinite from jinja2 import Template import pickle @@ -14,6 +14,7 @@ def extract_points(records, side, region): - total_count (x) > 0 - cell_size (y) > 0 from spatial_metrics[side][region].cell_size - coverage (c) present and >= 0 (used only for color scale) + Also retain cols_innervated for reference lines. """ pts = [] for rec in records: @@ -31,6 +32,13 @@ def extract_points(records, side, region): .get(region, {}) .get("coverage") ) + col_count = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("cols_innervated") + ) + # require x,y positive for log scales if x is None or y is None or c is None: continue @@ -42,9 +50,25 @@ def extract_points(records, side, region): continue if x <= 0 or y <= 0: continue - pts.append({"name": name, "x": x, "y": y, "coverage": c}) + + # Optional data quality filter from prior script + if col_count is not None: + try: + if float(col_count) <= 9: + continue + except Exception: + pass + + pts.append({ + "name": name, + "x": x, + "y": y, + "coverage": c, + "col_count": float(col_count) if col_count is not None else None, + }) return pts + def log_ticks(vmin, vmax): """Decade ticks for a log10 axis between (vmin, vmax), inclusive.""" if vmin <= 0 or vmax <= 0 or vmin >= vmax: @@ -53,6 +77,7 @@ def log_ticks(vmin, vmax): hi = ceil(log10(vmax)) return [10 ** e for e in range(lo, hi + 1)] + def scale_log10(v, vmin, vmax, a, b): """Log10 scaling to pixels.""" lv = log10(v) @@ -62,27 +87,60 @@ def scale_log10(v, vmin, vmax, a, b): return (a + b) / 2.0 return a + (lv - lmin) * (b - a) / (lmax - lmin) + def lerp(a, b, t): return a + (b - a) * t + def cov_to_rgb(t): """ Map t in [0,1] to a white→dark red gradient. start = white (255,255,255), end = dark red (~180,0,0) """ r0, g0, b0 = 255, 255, 255 - r1, g1, b1 = 255, 0, 0 + r1, g1, b1 = 150, 0, 0 r = int(round(lerp(r0, r1, t))) g = int(round(lerp(g0, g1, t))) b = int(round(lerp(b0, b1, t))) return f"rgb({r},{g},{b})" -def prepare(points, width=680, height=440, margins=(60, 24, 44, 64)): - """Compute pixel positions for an SVG scatter plot (log–log, color by coverage).""" + +def percentile(values, p): + """Return the p-th percentile (0-100) with linear interpolation, pure Python.""" + vals = sorted(v for v in values if v is not None) + n = len(vals) + if n == 0: + return None + if n == 1: + return vals[0] + # rank in [0, n-1] + r = (p / 100.0) * (n - 1) + lo = int(r) + hi = min(lo + 1, n - 1) + t = r - lo + return vals[lo] * (1 - t) + vals[hi] * t + + +def prepare(points, width=680, height=460, margins=(60, 72, 64, 72), *, axis_gap_px=10, n_cols_region=None, side=None, region=None): + """Compute pixel positions for an SVG scatter plot (log–log, color by coverage). + + Changes vs. prior version: + - Adds an inner pixel gap (axis_gap_px) so points do not touch the axes. + - Removes the plot "box" (background rect) in the template. + - Adds five light-grey guide lines (below points) for k = n_cols_region × {0.2,0.5,1,2,5} + where the guides follow x*y = k (straight anti-diagonals in log–log). + If n_cols_region is None, it is estimated as the max of available `col_count`. + - Sets color max to the 98th percentile of coverage values (legend reflects this clip). + - Adds axis labels for X and Y. + """ top, right, bottom, left = margins plot_w = width - left - right plot_h = height - top - bottom + side_px = min(plot_w, plot_h) + plot_w = side_px + plot_h = side_px + xmin = min(p["x"] for p in points) xmax = max(p["x"] for p in points) ymin = min(p["y"] for p in points) @@ -96,29 +154,87 @@ def prepare(points, width=680, height=440, margins=(60, 24, 44, 64)): xmax *= 1.05 ymax *= 1.08 - # ticks (log decades) - xticks = log_ticks(xmin, xmax) - yticks = log_ticks(ymin, ymax) + # fixed ticks at 1, 10, 100, 1000 (only those within the current axis range) + xticks = [1, 10, 100, 1000] + yticks = xticks - # coverage color scaling - cmin = min(p["coverage"] for p in points) - cmax = max(p["coverage"] for p in points) + # coverage color scaling with 98th percentile clipping + coverages = [p["coverage"] for p in points] + cmin = min(coverages) + cmax = percentile(coverages, 98.0) or max(coverages) crng = (cmax - cmin) if isfinite(cmax - cmin) and (cmax - cmin) > 0 else 1.0 + # Inner drawing range to create a visible gap to axes + inner_x0, inner_x1 = axis_gap_px, max(axis_gap_px, plot_w - axis_gap_px) + inner_y0, inner_y1 = plot_h - axis_gap_px, axis_gap_px # inverted + + def sx(v): + return scale_log10(v, xmin, xmax, inner_x0, inner_x1) + + def sy(v): + return scale_log10(v, ymin, ymax, inner_y0, inner_y1) + for p in points: - p["sx"] = scale_log10(p["x"], xmin, xmax, 0, plot_w) - p["sy"] = scale_log10(p["y"], ymin, ymax, plot_h, 0) # invert later via SVG coords - # color by coverage - t = (p["coverage"] - cmin) / crng - p["color"] = cov_to_rgb(max(0.0, min(1.0, t))) + p["sx"] = sx(p["x"]) + p["sy"] = sy(p["y"]) # SVG y grows downward + # color by coverage (clipped at cmax) + t_raw = (min(p["coverage"], cmax) - cmin) / crng + t = max(0.0, min(1.0, t_raw)) + p["color"] = cov_to_rgb(t) p["r"] = 4 p["tooltip"] = ( - f"{p['name']}\n" - f"count: {int(p['x'])}\n" - f"L→ME cell_size: {p['y']:.3f}\n" - f"coverage: {p['coverage']:.3f}" + f"{p['name']} - {region}({side}):\n" + f" {int(p['x'])} cells:\n" + f" cell_size: {p['y']:.3f}\n" + f" coverage: {p['coverage']:.3f}" ) + # Reference (anti-diagonal) guide lines under points + if n_cols_region is None: + col_counts = [p["col_count"] for p in points if p.get("col_count")] + if col_counts: + n_cols_region = max(col_counts) + else: + n_cols_region = 10 ** ((log10(xmin * ymin) + log10(xmax * ymax)) / 4) + + multipliers = [0.2, 0.5, 1, 2, 5] + + def guide_width(m): + if m < 0.5 or m > 2: + return 0.25 + elif m != 1: + return 0.4 + else: + return 0.8 + + guide_lines = [] + for m in multipliers: + k = n_cols_region * m # x*y = k + # Clip hyperbola segment to the [xmin,xmax]×[ymin,ymax] window in data space + x0_clip = max(xmin, k / ymax) + x1_clip = min(xmax, k / ymin) + if x0_clip >= x1_clip: + continue # out of view + y0 = k / x0_clip + y1 = k / x1_clip + guide_lines.append({ + "x1": sx(x0_clip), + "y1": sy(y0), + "x2": sx(x1_clip), + "y2": sy(y1), + "w": guide_width(m), + }) + + # Precompute pixel tick positions for Jinja (avoid math inside template) + def log_pos_x(t): + return scale_log10(t, xmin, xmax, inner_x0, inner_x1) + + def log_pos_y(t): + return scale_log10(t, ymin, ymax, inner_y0, inner_y1) + + xtick_data = [{"t": t, "px": log_pos_x(t)} for t in xticks] + ytick_data = [{"t": t, "py": log_pos_y(t)} for t in yticks] + ctx = { "width": width, "height": height, @@ -134,36 +250,17 @@ def prepare(points, width=680, height=440, margins=(60, 24, 44, 64)): "ymin": ymin, "ymax": ymax, "cmin": cmin, "cmax": cmax, "points": points, - "title": "L → ME: total_count vs cell_size (log–log)", - "subtitle": "color = coverage (blue→red)", - } - - # Precompute pixel tick positions for Jinja (avoid math inside template) - def log_pos_x(t): - return scale_log10(t, xmin, xmax, 0, plot_w) - def log_pos_y(t): - return scale_log10(t, ymin, ymax, plot_h, 0) - - xtick_data = [{"t": t, "px": log_pos_x(t)} for t in xticks] - ytick_data = [{"t": t, "py": log_pos_y(t)} for t in yticks] - - ctx.update({ + "title": f"{region}({side}): total_count vs cell_size", + "subtitle": "colorscale = coverage (max at 98th percentile)", "xtick_data": xtick_data, "ytick_data": ytick_data, - }) + "guide_lines": guide_lines, + "xlabel": "Population size (no. cells per type)", + "ylabel": "Cell size (no. columns per cell)", + } return ctx -def fmt_decade(v): - """Format decade tick as 10^n, fallback to number if not exact.""" - try: - e = round(log10(v)) - if abs((10**e) - v) / v < 1e-9: - return f"10^{e}" - except Exception: - pass - return f"{v:g}" - SVG_TEMPLATE = Template(r""" @@ -256,24 +354,19 @@ def fmt_decade(v): //]]> - -{{ title }} -{{ subtitle }} - - - + - + {% for tick in xtick_data %} - {{ fmt_decade(tick.t) }} + {{ tick.t }} {% endfor %} @@ -281,10 +374,15 @@ def fmt_decade(v): {% for tick in ytick_data %} - {{ fmt_decade(tick.t) }} + {{ tick.t }} {% endfor %} + + {% for g in guide_lines %} + + {% endfor %} + {% for p in points %} @@ -295,20 +393,25 @@ def fmt_decade(v): {% endfor %} - - - - - - - - - - coverage: {{ '%.3f' % cmin }} - {{ '%.3f' % cmax }} - + +{{ xlabel }} +{{ ylabel }} + + + + + + + + + + + + >{{ '%.0f' % cmax }} + {{ '%.0f' % cmin }} + - + @@ -317,16 +420,20 @@ def fmt_decade(v): """, trim_blocks=True, lstrip_blocks=True) # Jinja helper registrations -SVG_TEMPLATE.globals.update(fmt_decade=fmt_decade) +# SVG_TEMPLATE.globals.update(fmt_decade=fmt_decade) if __name__ == "__main__": side = "R" region = "ME" + points = extract_points(plot_data, side=side, region=region) if not points: raise SystemExit("No points found: ensure R→ME cell_size values exist and x,y > 0.") - ctx = prepare(points) + + ctx = prepare(points, axis_gap_px=10, n_cols_region=None, side=side, region=region) + svg = SVG_TEMPLATE.render(**ctx) with open(f"scatter_{side}_{region}.svg", "w", encoding="utf-8") as f: f.write(svg) - print(f"Wrote scatter_{side}_{region}.svg") \ No newline at end of file + + print(f"Wrote scatter_{side}_{region}.svg") From 3d6d15aeee3cbd44a034c931ba588f89fe1febd3 Mon Sep 17 00:00:00 2001 From: leburnett Date: Mon, 6 Oct 2025 17:07:21 -0400 Subject: [PATCH 06/60] Update test_scatter.py --- test/test_scatter.py | 25 +++++++++++++++++++++++-- 1 file changed, 23 insertions(+), 2 deletions(-) diff --git a/test/test_scatter.py b/test/test_scatter.py index 21f675e..a98a05f 100644 --- a/test/test_scatter.py +++ b/test/test_scatter.py @@ -154,6 +154,22 @@ def prepare(points, width=680, height=460, margins=(60, 72, 64, 72), *, axis_gap xmax *= 1.05 ymax *= 1.08 + lxmin, lxmax = log10(xmin), log10(xmax) + lymin, lymax = log10(ymin), log10(ymax) + dx = lxmax - lxmin + dy = lymax - lymin + + if dx > dy: + # expand Y range to match X span (around geometric center) + cy = (lymin + lymax) / 2.0 + lymin, lymax = cy - dx / 2.0, cy + dx / 2.0 + ymin, ymax = 10 ** lymin, 10 ** lymax + elif dy > dx: + # expand X range to match Y span (around geometric center) + cx = (lxmin + lxmax) / 2.0 + lxmin, lxmax = cx - dy / 2.0, cx + dy / 2.0 + xmin, xmax = 10 ** lxmin, 10 ** lxmax + # fixed ticks at 1, 10, 100, 1000 (only those within the current axis range) xticks = [1, 10, 100, 1000] yticks = xticks @@ -275,13 +291,14 @@ def log_pos_y(t): .tick-label { fill:#444; font-size:14px; font-family:Helvetica, Arial, sans-serif; } .title { fill:#333; font-size:14px; font-family:Arial, sans-serif; } .subtitle { fill:#777; font-size:11px; font-family:Arial, sans-serif; } - .axis-label { fill:#333; font-size:14px; font-family:Helvetica, Arial, sans-serif; } + .axis-label { fill:#333; font-size:16px; font-family:Helvetica, Arial, sans-serif; } .dot { cursor:pointer; opacity:0.9; transition:opacity 0.15s; } .dot:hover { opacity:1; } .tooltip-box { pointer-events:none; transition:opacity 0.15s; } .tooltip-bg { fill:rgba(0,0,0,0.8); rx:3; ry:3; } .tooltip-text { fill:#fff; font-size:12px; font-family:Helvetica, Arial, sans-serif; } .legend-label { fill:#555; font-size:14px; font-family:Helvetica, Arial, sans-serif; } + .legend-title { fill:#555; font-size:14px; font-family:Helvetica, Arial, sans-serif; } .guide { stroke: #bfbfbf; fill: none; } @@ -405,6 +422,10 @@ def log_pos_y(t): + + Coverage factor (cells per column) + >{{ '%.0f' % cmax }} @@ -424,7 +445,7 @@ def log_pos_y(t): if __name__ == "__main__": side = "R" - region = "ME" + region = "LOP" points = extract_points(plot_data, side=side, region=region) if not points: From 8f7fbb817512d50886141c8bf0f086d308771564 Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 11:03:24 -0400 Subject: [PATCH 07/60] Update cache_service.py Update generation of cache file to include "incl_scatter" within the "roi_summary" part only for "ME", "LO" and "LOP". Uses the strict threshold service of 5% - either pre or post percentage of synapses must be >5% and there must be >50 synapses in the ROI to be included in the scatterplots. --- src/neuview/services/cache_service.py | 23 +++++++++++++++++------ 1 file changed, 17 insertions(+), 6 deletions(-) diff --git a/src/neuview/services/cache_service.py b/src/neuview/services/cache_service.py index 1002866..64ba1a5 100644 --- a/src/neuview/services/cache_service.py +++ b/src/neuview/services/cache_service.py @@ -10,7 +10,7 @@ import time import logging from pathlib import Path -from typing import Optional, Tuple, Dict +from typing import Optional, Tuple, Dict, List, Any import pandas as pd from ..models import ( @@ -171,6 +171,9 @@ async def save_neuron_data_to_cache( # Filter ROIs by threshold and clean names (same logic as IndexService) threshold = self.threshold_service.get_roi_filtering_threshold() + threshold_high = self.threshold_service.get_roi_filtering_threshold( + profile_name="roi_filtering_strict" + ) cleaned_roi_summary = [] seen_names = set() @@ -187,10 +190,10 @@ async def save_neuron_data_to_cache( if self.roi_hierarchy_service else roi["name"] ) + if clean_name not in seen_names: seen_names.add(clean_name) - cleaned_roi_summary.append( - { + entry = { "name": clean_name, "pre_percentage": roi["pre_percentage"], "post_percentage": roi["post_percentage"], @@ -198,7 +201,14 @@ async def save_neuron_data_to_cache( "pre_synapses": roi["pre"], "post_synapses": roi["post"], } - ) + if clean_name in ["ME", "LO", "LOP"]: + if (roi["pre_percentage"] >= threshold_high and (roi["pre"]+roi["post"])>50 + or roi["post_percentage"] >= threshold_high and (roi["pre"]+roi["post"])>50): + include_in_scatter = 1 + else: + include_in_scatter = 0 + entry["incl_scatter"] = include_in_scatter + cleaned_roi_summary.append(entry) roi_summary = cleaned_roi_summary @@ -228,8 +238,9 @@ async def save_neuron_data_to_cache( parent_rois = sorted(list(parent_rois_set)) - # Calculate spatial metrics for columns if column ROIs are present - # Currently these are calculated from both L and R instances + # Calculate spatial metrics for columns if column ROIs are present. + # These metrics are calculated using synapses within the ROI from + # both L and R instances. for side in ["L", "R"]: for region in ["ME", "LO", "LOP"]: str_pattern = f"{region}_{side}_col_" From 85701625379e71a558ecfca9cd7853916fdbc669 Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 15:29:47 -0400 Subject: [PATCH 08/60] Update scatterplot_service.py --- src/neuview/services/scatterplot_service.py | 691 ++++++++++---------- 1 file changed, 332 insertions(+), 359 deletions(-) diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py index 80a13d2..7ad0c98 100644 --- a/src/neuview/services/scatterplot_service.py +++ b/src/neuview/services/scatterplot_service.py @@ -8,7 +8,7 @@ import logging from pathlib import Path import pandas as pd - +from math import ceil, floor, log10, isfinite from ..result import Result, Ok, Err from .index_service import IndexService @@ -30,50 +30,69 @@ def __init__(self, config, page_generator): from ..cache import create_cache_manager self.cache_manager = create_cache_manager(config.output.directory) - async def create_scatterplots(self, command) -> Result[str, str]: - """Create a scatterplot containing markers for all neuron types found in the output directory.""" - try: - logger.info("Starting plot creation using cached data") + async def create_scatterplots(self, command): + """Create scatterplots of spatial metrics for optic lobe neuron types.""" + output_dir = command.output_directory + try: + logger.info("Extracting plot data from cached data") + + # Discover neuron types from cache or file scanning + neuron_types, _ = IndexService.discover_neuron_types(self, output_dir) + if not neuron_types: + return Err("No neuron type HTML files found in output directory") - # Determine output directory - output_dir = Path(command.output_directory or self.config.output.directory) - if not output_dir.exists(): - return Err(f"Output directory does not exist: {output_dir}") + # Initialize connector if needed for database lookups + connector = await IndexService.initialize_connector_if_needed( + self, neuron_types, output_dir + ) - # Discover neuron types from cache or file scanning - neuron_types, _ = IndexService.discover_neuron_types(self, output_dir) - if not neuron_types: - return Err("No neuron type HTML files found in output directory") + # Correct neuron names (convert filenames back to original names) + corrected_neuron_types, _ = IndexService.correct_neuron_names( + self, neuron_types, connector + ) - # Initialize connector if needed for database lookups - connector = await IndexService.initialize_connector_if_needed( - self, neuron_types, output_dir - ) + # Generate scatterplot data for corrected neuron types + plot_data = self._extract_plot_data(corrected_neuron_types) - # Correct neuron names (convert filenames back to original names) - corrected_neuron_types, _ = IndexService.correct_neuron_names( - self, neuron_types, connector + # Within loop for side + side = "both" + + for region in ["ME", "LO", "LOP"]: + points = self._extract_points(plot_data, side=side, region=region) + if not points: + raise SystemExit( + f"No points found: ensure values exist for types within {side}{region}." + ) + + ctx = self._prepare( + points, axis_gap_px=10, n_cols_region=None, side=side, region=region ) - # Generate scatterplot data for corrected neuron types - plot_data = self._generate_plot_data(corrected_neuron_types) - print(plot_data) + # Use the page generator's Jinja environment + template = self.page_generator.env.get_template("scatterplot.svg.jinja") + svg_content = template.render(ctx) - # Generate the plots + # Write the index file + scatter_path = ( + output_dir / f"{region}_{side}_{command.scatter_filename}" + ) - # # Collect all generated file paths - # generated_files = [str(output_dir / command.index_filename)] - # if hasattr(self, "generated_files"): - # generated_files.extend(self.generated_files) + with open(scatter_path, "w", encoding="utf-8") as f: + f.write(svg_content) - return plot_data #Ok(generated_files) + return - except Exception as e: - logger.error(f"Failed to create optimized index: {e}") - return Err(f"Failed to create index: {str(e)}") + except Exception as e: + logger.error(f"Failed to create plot_data: {e}") + return Err(f"Failed to create plot_data: {str(e)}") - def _generate_plot_data(self, neuron_types): - """Generate plot data from neuron types.""" + def _extract_plot_data(self, neuron_types): + """Generate plot data from list of neuron types. + Generates the list of dicts containing the spatial metrics + data used to generate the interactive scatterplots for optic + lobe cell types. It extracts the relevant data from the + output/.cache/type.json files generated when making each neuron + type's respective page.""" cached_data_lazy = ( self.cache_manager.get_cached_data_lazy() if self.cache_manager else None ) @@ -81,7 +100,7 @@ def _generate_plot_data(self, neuron_types): cached_count = 0 missing_cache_count = 0 - for neuron_type, sides in neuron_types.items(): + for neuron_type in neuron_types.items(): # Check if we have cached data for this neuron type cache_data = cached_data_lazy.get(neuron_type) if cached_data_lazy else None @@ -94,25 +113,25 @@ def _generate_plot_data(self, neuron_types): "undefined_count": 0, "has_undefined": False, "spatial_metrics": {}, + "roi_summary": {}, } - # Use cached data if available (NO DATABASE QUERIES!) + # Use cached data if available if cache_data: entry["spatial_metrics"] = cache_data.spatial_metrics + entry["roi_summary"] = cache_data.roi_summary entry["total_count"] = cache_data.total_count entry["left_count"] = cache_data.soma_side_counts.get("left", 0) entry["right_count"] = cache_data.soma_side_counts.get("right", 0) entry["middle_count"] = cache_data.soma_side_counts.get("middle", 0) entry["undefined_count"] = cache_data.soma_side_counts.get("unknown", 0) entry["has_undefined"] = entry["undefined_count"] > 0 - + logger.debug(f"Used cached data for {neuron_type}") cached_count += 1 else: # No cached data available - use minimal defaults - logger.debug( - f"No cached data available for {neuron_type}, using minimal defaults" - ) + logger.debug(f"No cached data available for {neuron_type}") missing_cache_count += 1 plot_data.append(entry) @@ -130,323 +149,277 @@ def _generate_plot_data(self, neuron_types): ) return plot_data + def _extract_points(self, plot_data, side, region): + """ + Collate the data points required to make the spatial + metric scatterplots. + """ + pts = [] + for rec in plot_data: + + # incl = rec.get("roi_summary", {}).get(region, {}).get("incl_scatter") + # print(incl) + + # # Only include types that have "incl_scatter" == 1. + # # Pass threshold for syn % and syn #. + # if incl is not None: + name = rec.get("name", "unknown") + x = rec.get("total_count") + y = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("cell_size") + ) + c = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("coverage") + ) + col_count = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("cols_innervated") + ) + + # require x,y positive for log scales + if x is None or y is None or c is None: + continue + try: + x = float(x) + y = float(y) + c = float(c) + except Exception: + continue + if x <= 0 or y <= 0: + continue + + # Optional data quality filter from prior script + if col_count is not None: + try: + if float(col_count) <= 9: + continue + except Exception: + pass + + pts.append( + { + "name": name, + "x": x, + "y": y, + "coverage": c, + "col_count": float(col_count) if col_count is not None else None, + } + ) + return pts + + def _prepare( + self, + points, + width=680, + height=460, + margins=(60, 72, 64, 72), + *, + axis_gap_px=10, + n_cols_region=None, + side=None, + region=None, + ): + """Compute pixel positions for an SVG scatter plot (color by coverage).""" + top, right, bottom, left = margins + plot_w = width - left - right + plot_h = height - top - bottom + + side_px = min(plot_w, plot_h) + plot_w = side_px + plot_h = side_px + + xmin = min(p["x"] for p in points) + xmax = max(p["x"] for p in points) + ymin = min(p["y"] for p in points) + ymax = max(p["y"] for p in points) + + # expand bounds slightly so dots don't sit on the frame (keep >0) + pad_x = xmin * 0.05 + pad_y = ymin * 0.08 + xmin = max(1e-12, xmin - pad_x) + ymin = max(1e-12, ymin - pad_y) + xmax *= 1.05 + ymax *= 1.08 + + lxmin, lxmax = log10(xmin), log10(xmax) + lymin, lymax = log10(ymin), log10(ymax) + dx = lxmax - lxmin + dy = lymax - lymin + + if dx > dy: + # expand Y range to match X span (around geometric center) + cy = (lymin + lymax) / 2.0 + lymin, lymax = cy - dx / 2.0, cy + dx / 2.0 + ymin, ymax = 10**lymin, 10**lymax + elif dy > dx: + # expand X range to match Y span (around geometric center) + cx = (lxmin + lxmax) / 2.0 + lxmin, lxmax = cx - dy / 2.0, cx + dy / 2.0 + xmin, xmax = 10**lxmin, 10**lxmax + + # fixed ticks at 1, 10, 100, 1000 (only those within the current axis range) + xticks = [1, 10, 100, 1000] + yticks = xticks + + # coverage color scaling with 98th percentile clipping + coverages = [p["coverage"] for p in points] + cmin = min(coverages) + cmax = self._percentile(coverages, 98.0) or max(coverages) + crng = (cmax - cmin) if isfinite(cmax - cmin) and (cmax - cmin) > 0 else 1.0 + + # Inner drawing range to create a visible gap to axes + inner_x0, inner_x1 = axis_gap_px, max(axis_gap_px, plot_w - axis_gap_px) + inner_y0, inner_y1 = plot_h - axis_gap_px, axis_gap_px # inverted + + def sx(v): + return self._scale_log10(v, xmin, xmax, inner_x0, inner_x1) + + def sy(v): + return self._scale_log10(v, ymin, ymax, inner_y0, inner_y1) + + for p in points: + p["sx"] = sx(p["x"]) + p["sy"] = sy(p["y"]) # SVG y grows downward + # color by coverage (clipped at cmax) + t_raw = (min(p["coverage"], cmax) - cmin) / crng + t = max(0.0, min(1.0, t_raw)) + p["color"] = self._cov_to_rgb(t) + p["r"] = 4 + p["tooltip"] = ( + f"{p['name']} - {region}({side}):\n" + f" {int(p['x'])} cells:\n" + f" cell_size: {p['y']:.2f}\n" + f" coverage: {p['coverage']:.2f}" + ) + + # Reference (anti-diagonal) guide lines under points + if n_cols_region is None: + col_counts = [p["col_count"] for p in points if p.get("col_count")] + if col_counts: + n_cols_region = max(col_counts) + else: + n_cols_region = 10 ** ((log10(xmin * ymin) + log10(xmax * ymax)) / 4) + + multipliers = [0.2, 0.5, 1, 2, 5] + + def guide_width(m): + if m < 0.5 or m > 2: + return 0.25 + elif m != 1: + return 0.4 + else: + return 0.8 + + guide_lines = [] + for m in multipliers: + k = n_cols_region * m # x*y = k + x0_clip = max(xmin, k / ymax) + x1_clip = min(xmax, k / ymin) + if x0_clip >= x1_clip: + continue # out of view + y0 = k / x0_clip + y1 = k / x1_clip + guide_lines.append( + { + "x1": sx(x0_clip), + "y1": sy(y0), + "x2": sx(x1_clip), + "y2": sy(y1), + "w": guide_width(m), + } + ) - # # Make an svg - in JS when hover over - that marker is large. - # def _make_scatterplot(self, - # xval:str - # , yval:str - # , roi_str:str - # , style:dict - # , sizing:dict - # , plot_specs:dict - # , star_neurons:list - # , save_plot:bool=True) -> go.Figure: - # """ - # Plot scatterplot with 'star_neuron' types highlighted. - - # Parameters - # ---------- - # xval : str - # Column of 'df' to be shown on the x-axis. - # yval : str - # Column of 'df' to be shown on the y-axis. - # roi_str : str - # Optic lobe region of interest to plot the data from. - # style : dict - # Dict containing the values of the fixed styling formatting variables. - # sizing : dict - # Dict containing the values of the size formatting variables. - # plot_specs : dict - # Dict containing the values of the formatting variables relevant to the specific plot. - # star_neurons : list - # List of 'star neurons' to highlight in the plot. - # save_plot : bool, default = True - # Whether to save the plot or only return it. - - # Returns - # ------- - # fig : go.Figure - # Formatted plotly scatterplot. - # """ - # pio.kaleido.scope.mathjax = None - - # assert plot_specs["colorscale"] in ["red", "group"]\ - # , f"Colorscale must be 'red' or 'group', not '{plot_specs['colorscale']}'" - - # # load the data - # df = load_and_process_df(roi_str=roi_str) - # if xval == "instance": - # df = df.sort_values(yval) - - # df["markersize"] = float(sizing["markersize"]) - # df["markerlinewidth"] = sizing["markerlinewidth"] - # df["text"] = "" - - # if star_neurons: - # df.loc[df["instance"].isin(star_neurons), "markersize"] = ( - # sizing["markersize"] * 1.75 - # ) - # df.loc[df["instance"].isin(star_neurons), "markerlinewidth"] = ( - # sizing["markerlinewidth"] * 7 - # ) - # df.loc[df["instance"].isin(star_neurons), "group"] = 6 - - # # get sizing values - # if style["export_type"] == "svg": - # pixelsperinch = 72 - # else: - # pixelsperinch = 96 - # pixelspermm = pixelsperinch / 25.4 - # plot_width = (sizing["fig_width"] - sizing["fig_margin"]) * pixelspermm - # plot_height = (sizing["fig_height"] - sizing["fig_margin"]) * pixelspermm - # fsize_ticks_px = sizing["fsize_ticks_pt"] * (1 / 72) * pixelsperinch - # fsize_title_px = sizing["fsize_title_pt"] * (1 / 72) * pixelsperinch - - # cmap = Colormap("reds_5").to_plotly() # colorscale == 'red'; default - # if plot_specs["colorscale"] == "group": - # cmap = [ - # [0, "rgb(200, 200, 200)"] - # , [0.1666, "rgb(200, 200, 200)"] - # , [0.1666, "rgb(2, 158, 115)"] - # , [0.333, "rgb(2, 158, 115)"] - # , [0.333, "rgb(213, 94, 0)"] - # , [0.5, "rgb(213, 94, 0)"] - # , [0.5, "rgb(1,115,178)"] - # , [0.666, "rgb(1,115,178)"] - # , [0.6666, "rgb(222,143,5)"] - # , [0.833, "rgb(222,143,5)"] - # , [0.833, "rgb(204, 120, 188)"] - # , [1.0, "rgb(204, 120, 188)"] - # ] - - # # set the maximum - # _, n_cols_region = find_neuropil_hex_coords(roi_str) - - # fig = go.Figure() - - # match yval: - # case "coverage_factor_trim": - # fig.add_shape( - # type="line" - # , y0=1 - # , x0=1 - # , x1=n_cols_region - # , y1=1 - # , layer="below" - # , line={"color": "grey", "width": 0.8, "dash": "solid"} - # ) - - # case "cell_size_cols": - # for multipl in [0.2, 0.5, 1, 2, 5]: - # if multipl < 0.5 or multipl > 2: - # line_width = 0.25 - # elif multipl != 1: - # line_width = 0.4 - # else: - # line_width = 0.8 - - # fig.add_shape( - # type="line" - # , x0=1 - # , y0=n_cols_region * multipl - # , x1=n_cols_region * multipl - # , y1=1 - # , layer="below" - # , line={"color": "grey", "width": line_width, "dash": "solid"} - # ) - - # # add groups in order to ensure star neurons are plotted last - # gp_values = df["group"].sort_values(ascending=True).unique() - # for grp in gp_values: - - # df_gp = df[df["group"] == grp] - - # fig.add_trace( - # go.Scatter( - # x=df_gp[xval] - # , y=df_gp[yval] - # , text=[df_gp["text"]] - # , textposition="top center" - # , customdata=np.stack( - # (df_gp["instance"], df_gp[plot_specs["color_factor"]]), axis=-1 - # ) - # , hovertemplate=plot_specs["hover_template"] - # , opacity=0.95 - # , mode="markers" - # , marker={ - # "cmax": plot_specs["cmax"] - # , "cmin": plot_specs["cmin"] - # , "size": df_gp["markersize"] - # , "color": df_gp[plot_specs["color_factor"]] - # , "line": { - # "width": df_gp["markerlinewidth"] - # , "color": style["markerlinecolor"] - # }, - # "colorscale": cmap, - # "colorbar": { - # "orientation": "v" - # , "outlinecolor": style["linecolor"] - # , "outlinewidth": sizing["axislinewidth"] - # , "thickness": sizing["cbar_thickness"] - # , "len": sizing["cbar_length"] - # , "ticklen": sizing["cbar_tick_length"] - # , "tickcolor": "black" - # , "tickwidth": sizing["cbar_tick_width"] - # , "tickmode": "array" - # , "tickvals": plot_specs["tickvals"] - # , "ticktext": plot_specs["ticktext"] - # , "tickfont": {"size": fsize_ticks_px, "color": "black"} - # , "title": { - # "font": { - # "family": style["font_type"] - # , "size": fsize_title_px - # , "color": "black" - # }, - # "side": "right" - # , "text": plot_specs["cbar_title"] - # } - # } - # } - # ) - # ) - - # xlabel = get_axis_labels(xval, label_type="axis") - # ylabel = get_axis_labels(yval, label_type="axis") - - # if plot_specs["log_x"]: - # typex = "log" - # tickformx = ".1r" - # else: - # typex = "-" - # tickformx = "" - - # if plot_specs["log_y"]: - # typey = "log" - # tickformy = ".1r" - # else: - # typey = "-" - # tickformy = "" - - # fig.update_layout( - # autosize=False, - # width=plot_width, - # height=plot_height, - # margin={ - # "l": plot_width // 8, - # "r": 0, - # "b": plot_height // 4, - # "t": 0, - # "pad": plot_width // 30, - # }, - # showlegend=False, - # paper_bgcolor="rgba(255,255,255,1)", - # plot_bgcolor="rgba(255,255,255,1)", - # ) - - # fig.update_xaxes( - # title={ - # "font": { - # "size": fsize_title_px, - # "family": style["font_type"], - # "color": style["linecolor"], - # }, - # "text": xlabel, - # }, - # title_standoff=(plot_height // 4) / 4, - # ticks="outside", - # ticklen=sizing["ticklen"], - # tickwidth=sizing["tickwidth"], - # tickfont={ - # "family": style["font_type"], - # "size": fsize_ticks_px, - # "color": style["linecolor"], - # }, - # tickformat=tickformx, - # tickcolor="black", - # type=typex, - # showgrid=False, - # showline=True, - # linewidth=sizing["axislinewidth"], - # linecolor=style["linecolor"], - # range=plot_specs["range_x"], - # ) - - # match xval: - # case "instance": - # fig.update_xaxes(title="", tickvals=[], visible=False) - # case "coverage_factor_trim": - # fig.update_xaxes(tickvals=[1, 2, 4, 8, 12]) - # case "cell_size_cols": - # fig.update_xaxes(tickvals=[1, 10, 100, 1000]) - # case "area_covered_pop": - # fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) - # case "cols_covered_pop": - # fig.update_xaxes(tickvals=[0, 200, 400, 600, 800, 1000]) - # case "population_size": - # fig.update_xaxes(tickvals=[1, 10, 100, 1000]) - - # fig.update_yaxes( - # title={ - # "font": { - # "size": fsize_title_px - # , "family": style["font_type"] - # , "color": style["linecolor"] - # } - # , "text": f"{ylabel}" - # } - # , title_standoff=(plot_width // 5) / 5 - # , ticks="outside" - # , tickcolor="black" - # , ticklen=sizing["ticklen"] - # , tickwidth=sizing["tickwidth"] - # , tickfont={ - # "size": fsize_ticks_px - # , "family": style["font_type"] - # , "color": "black" - # } - # , tickformat=tickformy - # , type=typey - # , showgrid=False - # , showline=True - # , linewidth=sizing["axislinewidth"] - # , linecolor=style["linecolor"] - # , scaleanchor="x" - # , scaleratio=1 - # , anchor="free" - # , side="left" - # , overlaying="y" - # , range=plot_specs["range_y"] - # ) - - # match yval: - # case "coverage_factor_trim": - # fig.update_yaxes(tickvals=[1, 2, 4, 8, 12], scaleanchor=False) - # case "cell_size_cols": - # fig.update_yaxes(tickvals=[1, 10, 100, 1000]) - # case "area_covered_pop": - # fig.update_yaxes(tickvals=[0, 200, 400, 600, 800, 1000]) - # case "population_size": - # fig.update_yaxes(tickvals=[1, 10, 100, 1000]) - - # if save_plot: - # save_path = plot_specs["save_path"] - # assert isinstance(save_path, Path)\ - # , f"save_path needs to be 'Path', not '{type(save_path)}'" - # save_path.mkdir(parents=True, exist_ok=True) - - # basename = ( - # save_path - # / f"{roi_str[:-3]}_{xval}_versus_{yval}_{sizing['fsize_title_pt']}pt_" - # f"w{sizing['fig_width']}_h{sizing['fig_height']}_cscale-{plot_specs['color_factor']}" - # ) - - # if style["export_type"] == "html": - # fig.write_html(f"{basename}.html") - # else: - # pio.write_image( - # fig, - # f"{basename}.{style['export_type']}", - # width=plot_width, - # height=plot_height, - # ) - # return fig \ No newline at end of file + # Precompute pixel tick positions for Jinja (avoid math inside template) + def log_pos_x(t): + return self._scale_log10(t, xmin, xmax, inner_x0, inner_x1) + + def log_pos_y(t): + return self._scale_log10(t, ymin, ymax, inner_y0, inner_y1) + + xtick_data = [{"t": t, "px": log_pos_x(t)} for t in xticks] + ytick_data = [{"t": t, "py": log_pos_y(t)} for t in yticks] + + ctx = { + "width": width, + "height": height, + "margin_top": top, + "margin_right": right, + "margin_bottom": bottom, + "margin_left": left, + "plot_w": plot_w, + "plot_h": plot_h, + "xticks": xticks, + "yticks": yticks, + "xmin": xmin, + "xmax": xmax, + "ymin": ymin, + "ymax": ymax, + "cmin": cmin, + "cmax": cmax, + "points": points, + "title": f"{region}({side}): total_count vs cell_size", + "subtitle": "colorscale = coverage (max at 98th percentile)", + "xtick_data": xtick_data, + "ytick_data": ytick_data, + "guide_lines": guide_lines, + "xlabel": "Population size (no. cells per type)", + "ylabel": "Cell size (no. columns per cell)", + } + + return ctx + + def _log_ticks(self, vmin, vmax): + """Ticks for a log10 axis between (vmin, vmax), inclusive.""" + if vmin <= 0 or vmax <= 0 or vmin >= vmax: + return [] + lo = floor(log10(vmin)) + hi = ceil(log10(vmax)) + return [10**e for e in range(lo, hi + 1)] + + def _scale_log10(self, v, vmin, vmax, a, b): + """Log10 scaling to pixels.""" + lv = log10(v) + lmin = log10(vmin) + lmax = log10(vmax) + if lmax == lmin: + return (a + b) / 2.0 + return a + (lv - lmin) * (b - a) / (lmax - lmin) + + def _lerp(self, a, b, t): + return a + (b - a) * t + + def _cov_to_rgb(self, t): + """ + Map t in [0,1] to a white→dark red gradient. + start = white (255,255,255), end = dark red (~180,0,0) + """ + r0, g0, b0 = 255, 255, 255 + r1, g1, b1 = 180, 0, 0 + r = int(round(self._lerp(r0, r1, t))) + g = int(round(self._lerp(g0, g1, t))) + b = int(round(self._lerp(b0, b1, t))) + return f"rgb({r},{g},{b})" + + def _percentile(self, values, p): + """ + p in [0, 100]. Returns None on no finite data. + Uses pandas.Series.quantile with the right keyword for the installed version. + """ + s = pd.Series(values, dtype="float64").dropna() + if s.empty: + return None + + q = p / 100 + # Prefer the 2.x API if available; fall back to 1.5.x + try: + return float(s.quantile(q, method="linear")) # pandas 2.x + except TypeError: + return float(s.quantile(q, interpolation="linear")) # pandas 1.5.x From f20a4b4f2777d784da0be2acd53cb26cdb6fb815 Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 15:30:18 -0400 Subject: [PATCH 09/60] Update generate-all workflow to incl scatters --- pyproject.toml | 1 + src/neuview/cli.py | 29 +++++++++++++++++++++++ src/neuview/commands.py | 11 +++++++++ src/neuview/services/service_container.py | 12 ++++++++++ 4 files changed, 53 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index c00c848..e0b99ce 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -109,6 +109,7 @@ depends-on = [ { task = "clean-output" }, { task = "fill-all" }, { task = "pop-all" }, + { task = "create-scatter" }, { task = "create-list" }, { task = "increment-version" }, ] diff --git a/src/neuview/cli.py b/src/neuview/cli.py index f5c1682..b73a002 100644 --- a/src/neuview/cli.py +++ b/src/neuview/cli.py @@ -17,6 +17,7 @@ FillQueueCommand, PopCommand, CreateListCommand, + CreateScatterCommand, ) from .services import ServiceContainer from .services.neuron_discovery_service import InspectNeuronTypeCommand @@ -375,5 +376,33 @@ async def run_create_list(): asyncio.run(run_create_list()) +@main.command("create-scatter") +@click.option("--output-dir", help="Output directory to scan for neuron pages") +@click.pass_context +def create_scatter(ctx, output_dir: Optional[str]): + """Generate three SVG scatterplots of spatial metrics for optic lobe types. + """ + services = setup_services(ctx.obj["config_path"], ctx.obj["verbose"]) + + async def run_create_scatter(): + command = CreateScatterCommand(output_directory=output_dir) + + result = await services.scatter_service.create_scatterplots(command) + + # if result.is_ok(): + # generated_files = result.unwrap() + # if isinstance(generated_files, list): + # # Display main file first + # for file_path in generated_files: + # click.echo(f"✅ Created: {file_path}") + # else: + # # Handle backward compatibility if single string returned + # click.echo(f"✅ Created index page: {generated_files}") + # else: + # click.echo(f"❌ Error: {result.unwrap_err()}", err=True) + # sys.exit(1) + + asyncio.run(run_create_scatter()) + if __name__ == "__main__": main() diff --git a/src/neuview/commands.py b/src/neuview/commands.py index f058615..02a3cc0 100644 --- a/src/neuview/commands.py +++ b/src/neuview/commands.py @@ -93,6 +93,17 @@ def __post_init__(self): if self.requested_at is None: self.requested_at = datetime.now() +@dataclass +class CreateScatterCommand: + """Command to create svg scatterplots of spatial metrics.""" + + output_directory: Optional[str] = None + scatter_filename: str = "_scatter.svg" + requested_at: Optional[datetime] = None + + def __post_init__(self): + if self.requested_at is None: + self.requested_at = datetime.now() @dataclass class DatasetInfo: diff --git a/src/neuview/services/service_container.py b/src/neuview/services/service_container.py index df49aa2..63c2962 100644 --- a/src/neuview/services/service_container.py +++ b/src/neuview/services/service_container.py @@ -40,6 +40,7 @@ def __init__(self, config, copy_mode: str = "check_exists"): self._cache_service = None self._soma_detection_service = None self._neuron_statistics_service = None + self._scatter_service = None # Phase 3 managers self._template_manager = None @@ -299,6 +300,17 @@ def create(): return IndexService(self.config, self.page_generator) return self._get_or_create_service("index_service", create) + + @property + def scatter_service(self): + """Get or create scatterplot service.""" + + def create(): + from .scatterplot_service import ScatterplotService + + return ScatterplotService(self.config, self.page_generator) + + return self._get_or_create_service("scatter_service", create) def cleanup(self): """Clean up services and resources.""" From dd68d22ce9164fac94222826f62de07e463b976a Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 15:30:29 -0400 Subject: [PATCH 10/60] Update scatterplot.svg.jinja --- templates/scatterplot.svg.jinja | 481 +++++++++----------------------- 1 file changed, 129 insertions(+), 352 deletions(-) diff --git a/templates/scatterplot.svg.jinja b/templates/scatterplot.svg.jinja index 24b6298..3f0f754 100644 --- a/templates/scatterplot.svg.jinja +++ b/templates/scatterplot.svg.jinja @@ -1,383 +1,160 @@ - + - + \ No newline at end of file From daedd4abe453b272bca81640d1ee4397466f039e Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 15:30:55 -0400 Subject: [PATCH 11/60] update neuron page templates for scatterplots --- templates/neuron_page.html.jinja | 2 ++ templates/sections/scatterplots.html.jinja | 0 2 files changed, 2 insertions(+) create mode 100644 templates/sections/scatterplots.html.jinja diff --git a/templates/neuron_page.html.jinja b/templates/neuron_page.html.jinja index 2d7418d..8d38cda 100644 --- a/templates/neuron_page.html.jinja +++ b/templates/neuron_page.html.jinja @@ -20,6 +20,8 @@ {% include "sections/eyemaps.html.jinja" %} + {% include "sections/scatterplots.html.jinja" %} + {% include "sections/neuroglancer.html.jinja" %} {% include "sections/roi_innervation.html.jinja" %} diff --git a/templates/sections/scatterplots.html.jinja b/templates/sections/scatterplots.html.jinja new file mode 100644 index 0000000..e69de29 From 42d88a147242293eadcf140742a3cf98ea0afd07 Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 17:03:38 -0400 Subject: [PATCH 12/60] Update scatterplots.html.jinja --- templates/sections/scatterplots.html.jinja | 44 ++++++++++++++++++++++ 1 file changed, 44 insertions(+) diff --git a/templates/sections/scatterplots.html.jinja b/templates/sections/scatterplots.html.jinja index e69de29..36c490f 100644 --- a/templates/sections/scatterplots.html.jinja +++ b/templates/sections/scatterplots.html.jinja @@ -0,0 +1,44 @@ +{#-- Region-Specific Scatterplots of spatial metrics -- #} +{%- if spatial_metrics -%} +

+

+ Spatial coverage scatterplots +

+ +{# this is the html for single eyemaps - adapt for scatterplot images#} + +
+ {%- for region in ['ME', 'LO', 'LOP'] -%} + {%- if spatial_metrics.comprehensive_region_grids.get(region_side_key) -%} +
+ {%- if spatial_metrics.comprehensive_region_grids[region_side_key].synapse_density -%} + +
+ + + + Complete Synapse Density Grid for {{ region }} ({{ side }}) + + + + {%- if not (column_analysis.comprehensive_region_grids[region_side_key].synapse_density | is_png_data) -%} + {# Show download button for file-based images only #} + + + + + + + + + {%- endif -%} + +
+ {%- endif -%} +
+ {%- endif -%} + {%- endfor -%} +
+ + +
\ No newline at end of file From 89767f2860ca156c74de169719a0ba63ebb67a8b Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 17:04:00 -0400 Subject: [PATCH 13/60] Update scatterplot.svg.jinja Move selected marker on top of data --- templates/scatterplot.svg.jinja | 25 +++++++++++++++++++------ 1 file changed, 19 insertions(+), 6 deletions(-) diff --git a/templates/scatterplot.svg.jinja b/templates/scatterplot.svg.jinja index 3f0f754..6b855d6 100644 --- a/templates/scatterplot.svg.jinja +++ b/templates/scatterplot.svg.jinja @@ -29,10 +29,17 @@ function showTip(evt) { const svg = evt.currentTarget.ownerSVGElement; const tip = svg.getElementById("tooltip"); const g = evt.currentTarget; + g.parentNode.appendChild(g) const c = g.querySelector("circle"); - const base = parseFloat(c.getAttribute("data-base-r") || "4"); - c.setAttribute("r", String(base * 2.8)); + const baseR = parseFloat(c.getAttribute("data-base-r") || "4"); + c.setAttribute("r", String(baseR * 2.8)); + + const baseSW = parseFloat( + c.getAttribute("data-base-sw") || + (getComputedStyle(c).strokeWidth || "0.5") + ); + c.setAttribute("stroke-width", String(baseSW * 2.5)); const text = c.getAttribute("data-title") || ""; if (!text) return; @@ -81,8 +88,14 @@ function hideTip(evt) { const g = evt.currentTarget; const c = g.querySelector("circle"); - const base = parseFloat(c.getAttribute("data-base-r") || "4"); - c.setAttribute("r", String(base)); + const baseR = parseFloat(c.getAttribute("data-base-r") || "4"); + const baseSW = parseFloat( + c.getAttribute("data-base-sw") || + (getComputedStyle(c).strokeWidth || "0.5") + ); + + c.setAttribute("r", String(baseR)); + c.setAttribute("stroke-width", String(baseSW)); const text = c.getAttribute("data-title") || ""; const tEl = g.querySelector("title"); @@ -123,7 +136,7 @@ function hideTip(evt) { {% for p in points %} - + {{ p.tooltip }} @@ -144,7 +157,7 @@ function hideTip(evt) { - Coverage factor (cells per column) + {{legend_title}} From 664ed29ef1c8b09e9300763026fe51aabddfcd33 Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 17:04:13 -0400 Subject: [PATCH 14/60] Create scatter_config.py --- .../visualization/rendering/scatter_config.py | 133 ++++++++++++++++++ 1 file changed, 133 insertions(+) create mode 100644 src/neuview/visualization/rendering/scatter_config.py diff --git a/src/neuview/visualization/rendering/scatter_config.py b/src/neuview/visualization/rendering/scatter_config.py new file mode 100644 index 0000000..ee7156d --- /dev/null +++ b/src/neuview/visualization/rendering/scatter_config.py @@ -0,0 +1,133 @@ +""" +Scatter rendering config +""" +from typing import List, Dict, Any, Optional +from pathlib import Path +from dataclasses import dataclass +from ...utils import get_templates_dir + +@dataclass +class ScatterConfig: + """ + Configuration for rendering operations. + + This class encapsulates all the parameters needed to control + the rendering process, including output format, layout settings, + and file management options. + """ + + # Output configuration + output_format: str = "svg" + embed_mode: bool = False + save_to_files: bool = True + + # File management + output_dir: Optional[Path] = None + scatter_dir: Optional[Path] = None + + # Layout configuration + marker_size: int = 20 + margins: list = (60, 72, 64, 72) + axis_gap_px: int = 10 + + # SVG-specific configuration + template_name: str = "scatterplot.svg.jinja" + + # Content configuration + title: str = "" + xlabel: str = "Population size (no. cells per type)" + ylabel: str = "Cell size (no. columns per cell)" + optic_lobe_side: str = None + region_name: Optional[str] = None + + # Data configuration + min_max_data: Optional[Dict[str, Any]] = None + thresholds: Optional[Dict[str, Any]] = None + + def __post_init__(self): + """Post-initialization validation and setup.""" + + if self.scatter_dir is None and self.output_dir: + self.scatter_dir = self.output_dir / "scatter" + + # def get_template_path(self) -> Optional[Path]: + # """Get the full path to the template file.""" + # # Templates are now loaded from the built-in templates directory + # return get_templates_dir() / self.template_name + +@dataclass +class ScatterLayoutConfig: + """ + Configuration for layout calculations. + + This class contains parameters specific to layout computation + and coordinate transformations. + """ + + width: int = 0 + height: int = 0 + min_x: float = 0.0 + min_y: float = 0.0 + margin: int = 10 + legend_x: float = 0.0 + title_x: float = 0.0 + hex_points: str = "" + + # Legend configuration + legend_width: int = 12 + legend_height: int = 60 + legend_y: float = 0.0 + legend_title_x: float = 0.0 + legend_title_y: float = 0.0 + + # Layer control configuration + layer_control_x: float = 0.0 + layer_control_y: float = 0.0 + + def to_dict(self) -> Dict[str, Any]: + """Convert layout config to dictionary for template rendering.""" + return { + "width": self.width, + "height": self.height, + "min_x": self.min_x, + "min_y": self.min_y, + "margin": self.margin, + "legend_x": self.legend_x, + "title_x": self.title_x, + "hex_points": self.hex_points, + "legend_width": self.legend_width, + "legend_height": self.legend_height, + "legend_y": self.legend_y, + "legend_title_x": self.legend_title_x, + "legend_title_y": self.legend_title_y, + "layer_control_x": self.layer_control_x, + "layer_control_y": self.layer_control_y, + } + + +@dataclass +class ScatterLegendConfig: + """ + Configuration for legend rendering. + + This class contains parameters for rendering the color legend + and associated UI elements. + """ + + legend_title: str = "" + legend_type_name: str = "" + title_y: float = 0.0 + bin_height: int = 12 + thresholds: Optional[Dict[str, Any]] = None + layer_thresholds: Optional[Dict[str, Any]] = None + + def to_dict(self) -> Dict[str, Any]: + """Convert legend config to dictionary for template rendering.""" + return { + "legend_title": self.legend_title, + "legend_type_name": self.legend_type_name, + "title_y": self.title_y, + "bin_height": self.bin_height, + "thresholds": self.thresholds, + "layer_thresholds": self.layer_thresholds, + } From 1dad4525ccde6ae52654b1a6f4d1549ac79af740 Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 17:04:19 -0400 Subject: [PATCH 15/60] Update scatterplot_service.py --- src/neuview/services/scatterplot_service.py | 94 ++++++++++----------- 1 file changed, 43 insertions(+), 51 deletions(-) diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py index 7ad0c98..d743f7e 100644 --- a/src/neuview/services/scatterplot_service.py +++ b/src/neuview/services/scatterplot_service.py @@ -12,14 +12,14 @@ from ..result import Result, Ok, Err from .index_service import IndexService -from .file_service import FileService +from ..visualization.rendering.scatter_config import ScatterConfig logger = logging.getLogger(__name__) class ScatterplotService: """Service for creating scatterplots with markers for all available neuron types.""" - def __init__(self, config, page_generator): + def __init__(self, config: ScatterConfig, page_generator): self.config = config self.page_generator = page_generator self._batch_neuron_cache = {} @@ -64,9 +64,7 @@ async def create_scatterplots(self, command): f"No points found: ensure values exist for types within {side}{region}." ) - ctx = self._prepare( - points, axis_gap_px=10, n_cols_region=None, side=side, region=region - ) + ctx = self._prepare(self.config, points, side=side, region=region) # Use the page generator's Jinja environment template = self.page_generator.env.get_template("scatterplot.svg.jinja") @@ -217,25 +215,12 @@ def _extract_points(self, plot_data, side, region): def _prepare( self, + config, points, - width=680, - height=460, - margins=(60, 72, 64, 72), - *, - axis_gap_px=10, - n_cols_region=None, side=None, region=None, ): """Compute pixel positions for an SVG scatter plot (color by coverage).""" - top, right, bottom, left = margins - plot_w = width - left - right - plot_h = height - top - bottom - - side_px = min(plot_w, plot_h) - plot_w = side_px - plot_h = side_px - xmin = min(p["x"] for p in points) xmax = max(p["x"] for p in points) ymin = min(p["y"] for p in points) @@ -265,10 +250,6 @@ def _prepare( lxmin, lxmax = cx - dy / 2.0, cx + dy / 2.0 xmin, xmax = 10**lxmin, 10**lxmax - # fixed ticks at 1, 10, 100, 1000 (only those within the current axis range) - xticks = [1, 10, 100, 1000] - yticks = xticks - # coverage color scaling with 98th percentile clipping coverages = [p["coverage"] for p in points] cmin = min(coverages) @@ -276,8 +257,8 @@ def _prepare( crng = (cmax - cmin) if isfinite(cmax - cmin) and (cmax - cmin) > 0 else 1.0 # Inner drawing range to create a visible gap to axes - inner_x0, inner_x1 = axis_gap_px, max(axis_gap_px, plot_w - axis_gap_px) - inner_y0, inner_y1 = plot_h - axis_gap_px, axis_gap_px # inverted + inner_x0, inner_x1 = config.axis_gap_px, max(config.axis_gap_px, config.plot_w - config.axis_gap_px) + inner_y0, inner_y1 = config.plot_h - config.axis_gap_px, config.axis_gap_px # inverted def sx(v): return self._scale_log10(v, xmin, xmax, inner_x0, inner_x1) @@ -344,37 +325,48 @@ def log_pos_x(t): def log_pos_y(t): return self._scale_log10(t, ymin, ymax, inner_y0, inner_y1) - xtick_data = [{"t": t, "px": log_pos_x(t)} for t in xticks] - ytick_data = [{"t": t, "py": log_pos_y(t)} for t in yticks] - - ctx = { - "width": width, - "height": height, - "margin_top": top, - "margin_right": right, - "margin_bottom": bottom, - "margin_left": left, - "plot_w": plot_w, - "plot_h": plot_h, - "xticks": xticks, - "yticks": yticks, - "xmin": xmin, - "xmax": xmax, - "ymin": ymin, - "ymax": ymax, - "cmin": cmin, - "cmax": cmax, + xtick_data = [{"t": t, "px": log_pos_x(t)} for t in config.xticks] + ytick_data = [{"t": t, "py": log_pos_y(t)} for t in config.yticks] + ctx = self. _prepare_template_variables(self, points, config, region) + + return ctx + + def _prepare_template_variables(self, points, config, region): + """Prepare variables for template rendering. + Args: + points: Processed hexagon data + config: Scatter configuration + Returns: + Dictionary of template variables + """ + template_vars = { + "width": config.width, + "height": config.height, + "margin_top": config.margin[1], + "margin_right": config.margin[2], + "margin_bottom": config.margin[3], + "margin_left": config.margin[4], + "plot_w": config.plot_w, + "plot_h": config.plot_h, + "xticks": config.xticks, + "yticks": config.yticks, + "xmin": config.xmin, + "xmax": config.xmax, + "ymin": config.ymin, + "ymax": config.ymax, + "cmin": config.cmin, + "cmax": config.cmax, "points": points, - "title": f"{region}({side}): total_count vs cell_size", - "subtitle": "colorscale = coverage (max at 98th percentile)", - "xtick_data": xtick_data, - "ytick_data": ytick_data, - "guide_lines": guide_lines, + "title": f"{region}", + "xtick_data": config.xtick_data, + "ytick_data": config.ytick_data, + "guide_lines": config.guide_lines, "xlabel": "Population size (no. cells per type)", "ylabel": "Cell size (no. columns per cell)", + "legend_title": "Coverage factor (cells per column)", } - return ctx + return template_vars def _log_ticks(self, vmin, vmax): """Ticks for a log10 axis between (vmin, vmax), inclusive.""" From a297a9953b283baacc175dd8ee9249dc538ee14b Mon Sep 17 00:00:00 2001 From: leburnett Date: Tue, 7 Oct 2025 20:13:23 -0400 Subject: [PATCH 16/60] Bump version to v2.7.8 --- pyproject.toml | 179 +++++++++++++++++++++++++------------------------ 1 file changed, 93 insertions(+), 86 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e0b99ce..fd97483 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,34 +1,22 @@ [project] -authors = [{ name = "Frank Loesche", email = "loeschef@janelia.hhmi.org" }] -dependencies = [ - "click>=8.0.0", - "jinja2>=3.0.0", - "pyyaml>=6.0", - "requests>=2.28.0", - "pandas>=1.5.0", - "neuprint-python>=0.4.0", - "toml>=0.10.0", - "python-dotenv>=1.0.0", - "pycairo>=1.20.0", - "cairosvg>=2.5.0", - "minify-html>=0.16.4,<0.17", - "cst-lsp>=0.1.3,<0.2", - "gitpython>=3.1.0", -] +dependencies = [ "click>=8.0.0", "jinja2>=3.0.0", "pyyaml>=6.0", "requests>=2.28.0", "pandas>=1.5.0", "neuprint-python>=0.4.0", "toml>=0.10.0", "python-dotenv>=1.0.0", "pycairo>=1.20.0", "cairosvg>=2.5.0", "minify-html>=0.16.4,<0.17", "cst-lsp>=0.1.3,<0.2", "gitpython>=3.1.0",] name = "neuview" requires-python = ">= 3.11" -version = "0.1.0" - -[project.scripts] -neuview = "neuview.cli:main" +version = "2.7.8" +[[project.authors]] +name = "Frank Loesche" +email = "loeschef@janelia.hhmi.org" [build-system] build-backend = "hatchling.build" -requires = ["hatchling"] +requires = [ "hatchling",] + +[project.scripts] +neuview = "neuview.cli:main" [tool.pixi.project] -channels = ["conda-forge"] -platforms = ["linux-64", "win-64", "osx-64", "osx-arm64"] +channels = [ "conda-forge",] +platforms = [ "linux-64", "win-64", "osx-64", "osx-arm64",] [tool.pixi.dependencies] python = ">=3.11" @@ -41,7 +29,6 @@ toml = "*" pip = "*" python-dotenv = "*" gitpython = ">=3.1.45,<4" - pycairo = "*" cairosvg = "*" parallel = ">=20200322,<20250623" @@ -51,16 +38,8 @@ pyprojroot = ">=0.3.0,<0.4" psutil = ">=7.1.0,<8" semver = ">=3.0.4,<4" -[tool.pixi.feature.dev.dependencies] -pytest = "*" -pytest-cov = "*" -pytest-asyncio = ">=1.2.0,<2" - [tool.pixi.environments] -dev = ["dev"] - -[tool.pixi.pypi-dependencies] -neuview = { path = ".", editable = true } +dev = [ "dev",] [tool.pixi.tasks] clean-output = "rm -rf output/" @@ -71,76 +50,104 @@ setup-env = "cp .env.example .env && echo 'Created .env file. Please edit it and fill-all = "neuview fill-queue --all" create-list = "neuview create-list" -[tool.pixi.feature.dev.tasks] -test = "pytest test/" -test-verbose = "pytest -v test/" -test-coverage = "pytest --cov=src/neuview test/" -unit-test = "pytest -m unit test/" -unit-test-verbose = "pytest -m unit -v test/" -integration-test = "pytest -m integration test/" -integration-test-verbose = "pytest -m integration -v test/" -format = "ruff format src/ test/" -check = "ruff check src/ test/" - [tool.pytest.ini_options] -testpaths = ["test"] -python_files = ["test_*.py", "*_test.py"] -python_classes = ["Test*"] -python_functions = ["test_*"] -addopts = [ - "-v", - "--tb=short", - "--strict-markers", - "--disable-warnings", -] -markers = [ - "slow: marks tests as slow (deselect with '-m \"not slow\"')", - "integration: marks tests as integration tests", - "unit: marks tests as unit tests", - "asyncio: marks tests as async tests", -] +testpaths = [ "test",] +python_files = [ "test_*.py", "*_test.py",] +python_classes = [ "Test*",] +python_functions = [ "test_*",] +addopts = [ "-v", "--tb=short", "--strict-markers", "--disable-warnings",] +markers = [ "slow: marks tests as slow (deselect with '-m \"not slow\"')", "integration: marks tests as integration tests", "unit: marks tests as unit tests", "asyncio: marks tests as async tests",] + +[tool.pixi.pypi-dependencies.neuview] +path = "." +editable = true [tool.pixi.tasks.fill-type] -args = [{ arg = "neuron_type", default = "" }] cmd = "neuview fill-queue{{ ' -n ' ~ neuron_type if neuron_type != '' else '' }}" +[[tool.pixi.tasks.fill-type.args]] +arg = "neuron_type" +default = "" [tool.pixi.tasks.create-all-pages] -depends-on = [ - { task = "clean-output" }, - { task = "fill-all" }, - { task = "pop-all" }, - { task = "create-scatter" }, - { task = "create-list" }, - { task = "increment-version" }, -] +[[tool.pixi.tasks.create-all-pages.depends-on]] +task = "clean-output" + +[[tool.pixi.tasks.create-all-pages.depends-on]] +task = "fill-all" + +[[tool.pixi.tasks.create-all-pages.depends-on]] +task = "pop-all" + +[[tool.pixi.tasks.create-all-pages.depends-on]] +task = "create-list" + +[[tool.pixi.tasks.create-all-pages.depends-on]] +task = "increment-version" [tool.pixi.tasks.extract-and-fill] -args = [ - { arg = "config_file", default = "config.yaml" }, - { arg = "subset_category", default = "subset-medium" } -] cmd = "python scripts/extract_and_fill.py {{ config_file }} {{ subset_category }}" +[[tool.pixi.tasks.extract-and-fill.args]] +arg = "config_file" +default = "config.yaml" + +[[tool.pixi.tasks.extract-and-fill.args]] +arg = "subset_category" +default = "subset-medium" [tool.pixi.tasks.subset-medium-no-index] -depends-on = [ - { task = "clean-output" }, - { task = "extract-and-fill" }, - { task = "fill-type", args = ["",] }, - { task = "pop-all" }, -] +[[tool.pixi.tasks.subset-medium-no-index.depends-on]] +task = "clean-output" + +[[tool.pixi.tasks.subset-medium-no-index.depends-on]] +task = "extract-and-fill" + +[[tool.pixi.tasks.subset-medium-no-index.depends-on]] +task = "fill-type" +args = [ "",] + +[[tool.pixi.tasks.subset-medium-no-index.depends-on]] +task = "pop-all" [tool.pixi.tasks.subset-medium] -depends-on = [{ task = "subset-medium-no-index" }, { task = "create-list" }] +[[tool.pixi.tasks.subset-medium.depends-on]] +task = "subset-medium-no-index" + +[[tool.pixi.tasks.subset-medium.depends-on]] +task = "create-list" [tool.pixi.tasks.subset-small-no-index] -depends-on = [ - { task = "clean-output" }, - { task = "extract-and-fill", args = ["config.yaml", "subset-small"] }, - { task = "pop-all" }, -] +[[tool.pixi.tasks.subset-small-no-index.depends-on]] +task = "clean-output" + +[[tool.pixi.tasks.subset-small-no-index.depends-on]] +task = "extract-and-fill" +args = [ "config.yaml", "subset-small",] + +[[tool.pixi.tasks.subset-small-no-index.depends-on]] +task = "pop-all" [tool.pixi.tasks.subset-small] -depends-on = [{ task = "subset-small-no-index" }, { task = "create-list" }] +[[tool.pixi.tasks.subset-small.depends-on]] +task = "subset-small-no-index" + +[[tool.pixi.tasks.subset-small.depends-on]] +task = "create-list" [tool.pixi.tasks.increment-version] cmd = "python scripts/increment_version.py" + +[tool.pixi.feature.dev.dependencies] +pytest = "*" +pytest-cov = "*" +pytest-asyncio = ">=1.2.0,<2" + +[tool.pixi.feature.dev.tasks] +test = "pytest test/" +test-verbose = "pytest -v test/" +test-coverage = "pytest --cov=src/neuview test/" +unit-test = "pytest -m unit test/" +unit-test-verbose = "pytest -m unit -v test/" +integration-test = "pytest -m integration test/" +integration-test-verbose = "pytest -m integration -v test/" +format = "ruff format src/ test/" +check = "ruff check src/ test/" From 8eae233c7a625c918305e98cf554c84c453d8057 Mon Sep 17 00:00:00 2001 From: leburnett Date: Wed, 8 Oct 2025 14:29:19 -0400 Subject: [PATCH 17/60] Update cli.py --- src/neuview/cli.py | 30 +++++++++++++++--------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/src/neuview/cli.py b/src/neuview/cli.py index b73a002..5449498 100644 --- a/src/neuview/cli.py +++ b/src/neuview/cli.py @@ -10,6 +10,7 @@ import sys from typing import Optional import logging +from pathlib import Path from .commands import ( GeneratePageCommand, @@ -377,7 +378,7 @@ async def run_create_list(): @main.command("create-scatter") -@click.option("--output-dir", help="Output directory to scan for neuron pages") +@click.option("--output-dir", help="Output directory for scatterplots") @click.pass_context def create_scatter(ctx, output_dir: Optional[str]): """Generate three SVG scatterplots of spatial metrics for optic lobe types. @@ -387,20 +388,19 @@ def create_scatter(ctx, output_dir: Optional[str]): async def run_create_scatter(): command = CreateScatterCommand(output_directory=output_dir) - result = await services.scatter_service.create_scatterplots(command) - - # if result.is_ok(): - # generated_files = result.unwrap() - # if isinstance(generated_files, list): - # # Display main file first - # for file_path in generated_files: - # click.echo(f"✅ Created: {file_path}") - # else: - # # Handle backward compatibility if single string returned - # click.echo(f"✅ Created index page: {generated_files}") - # else: - # click.echo(f"❌ Error: {result.unwrap_err()}", err=True) - # sys.exit(1) + await services.scatter_service.create_scatterplots(command) + + # Print the three scatterplot files that should have been created + scfg = services.scatter_service.scatter_config + scatter_dir = Path(output_dir) if output_dir else Path(scfg.scatter_dir) + fname = scfg.scatter_fname + + for region in ("ME", "LO", "LOP"): + file_path = scatter_dir / f"{region}_{fname}" + if file_path.exists(): + click.echo(f"✅ Created: {file_path}") + else: + click.echo(f"⚠️ Expected but not found: {file_path}", err=True) asyncio.run(run_create_scatter()) From 1de1439b59382fe2b446dd649a1d37a9387c0686 Mon Sep 17 00:00:00 2001 From: leburnett Date: Wed, 8 Oct 2025 14:29:43 -0400 Subject: [PATCH 18/60] some updates --- src/neuview/commands.py | 1 - src/neuview/services/index_service.py | 7 ------- src/neuview/services/service_container.py | 4 ++-- 3 files changed, 2 insertions(+), 10 deletions(-) diff --git a/src/neuview/commands.py b/src/neuview/commands.py index 02a3cc0..14d7a4b 100644 --- a/src/neuview/commands.py +++ b/src/neuview/commands.py @@ -98,7 +98,6 @@ class CreateScatterCommand: """Command to create svg scatterplots of spatial metrics.""" output_directory: Optional[str] = None - scatter_filename: str = "_scatter.svg" requested_at: Optional[datetime] = None def __post_init__(self): diff --git a/src/neuview/services/index_service.py b/src/neuview/services/index_service.py index af696e6..dc21c1a 100644 --- a/src/neuview/services/index_service.py +++ b/src/neuview/services/index_service.py @@ -73,13 +73,6 @@ async def create_index(self, command) -> Result[str, str]: # Generate index data from corrected neuron types index_data = self._generate_index_data(corrected_neuron_types) - # Generate scatterplot data for corrected neuron types - plot_data = self._generate_plot_data(corrected_neuron_types) - - import pickle - with open('my_file.pkl', 'wb') as file: - pickle.dump(plot_data, file) - # Log performance summary self._log_performance_summary( corrected_neuron_types, cache_performance, scan_time diff --git a/src/neuview/services/service_container.py b/src/neuview/services/service_container.py index 63c2962..3ce2566 100644 --- a/src/neuview/services/service_container.py +++ b/src/neuview/services/service_container.py @@ -300,7 +300,7 @@ def create(): return IndexService(self.config, self.page_generator) return self._get_or_create_service("index_service", create) - + @property def scatter_service(self): """Get or create scatterplot service.""" @@ -308,7 +308,7 @@ def scatter_service(self): def create(): from .scatterplot_service import ScatterplotService - return ScatterplotService(self.config, self.page_generator) + return ScatterplotService() return self._get_or_create_service("scatter_service", create) From b56150cac08ae3cb5807944142c5343402db7eb6 Mon Sep 17 00:00:00 2001 From: leburnett Date: Wed, 8 Oct 2025 14:29:49 -0400 Subject: [PATCH 19/60] Update pyproject.toml --- pyproject.toml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index fd97483..49a0d5a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -81,6 +81,9 @@ task = "pop-all" [[tool.pixi.tasks.create-all-pages.depends-on]] task = "create-list" +[[tool.pixi.tasks.create-all-pages.depends-on]] +task = "create-scatter" + [[tool.pixi.tasks.create-all-pages.depends-on]] task = "increment-version" From ddc42af8d28fcbe6f19cd7f6f48e454ea6abe195 Mon Sep 17 00:00:00 2001 From: leburnett Date: Wed, 8 Oct 2025 14:29:52 -0400 Subject: [PATCH 20/60] Update scatterplot_service.py --- src/neuview/services/scatterplot_service.py | 335 ++++++++++++-------- 1 file changed, 202 insertions(+), 133 deletions(-) diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py index d743f7e..de30bfb 100644 --- a/src/neuview/services/scatterplot_service.py +++ b/src/neuview/services/scatterplot_service.py @@ -9,7 +9,10 @@ from pathlib import Path import pandas as pd from math import ceil, floor, log10, isfinite -from ..result import Result, Ok, Err +from ..result import Err +from jinja2 import Environment, FileSystemLoader, Template +from ..config import Config +from ..utils import get_templates_dir from .index_service import IndexService from ..visualization.rendering.scatter_config import ScatterConfig @@ -19,37 +22,41 @@ class ScatterplotService: """Service for creating scatterplots with markers for all available neuron types.""" - def __init__(self, config: ScatterConfig, page_generator): - self.config = config - self.page_generator = page_generator - self._batch_neuron_cache = {} + def __init__(self): + + self.config = Config.load("config.yaml") + self.scatter_config = ScatterConfig() + + if not getattr(self.scatter_config, "scatter_dir", None): + self.scatter_config.scatter_dir = Path(self.scatter_config.scatter_dir) + + self.output_dir = Path(self.scatter_config.scatter_dir) + self.output_dir.mkdir(parents=True, exist_ok=True) # Initialize cache manager for neuron type data self.cache_manager = None - if config and hasattr(config, "output") and hasattr(config.output, "directory"): + if self.config and hasattr(self.config, "output") and hasattr(self.config.output, "directory"): from ..cache import create_cache_manager - self.cache_manager = create_cache_manager(config.output.directory) + self.cache_manager = create_cache_manager(self.config.output.directory) async def create_scatterplots(self, command): """Create scatterplots of spatial metrics for optic lobe neuron types.""" - output_dir = command.output_directory + output_dir = Path(command.output_directory or self.config.output.directory) + try: - logger.info("Extracting plot data from cached data") + page_generator = None # or a tiny stub object if your constructors assume methods exist + index = IndexService(self.config, page_generator) - # Discover neuron types from cache or file scanning - neuron_types, _ = IndexService.discover_neuron_types(self, output_dir) + # 3) Use the instance properly + neuron_types, _ = index.discover_neuron_types(output_dir) if not neuron_types: - return Err("No neuron type HTML files found in output directory") - + return Err("No neuron type HTML files found in output directory") + # Initialize connector if needed for database lookups - connector = await IndexService.initialize_connector_if_needed( - self, neuron_types, output_dir - ) + connector = await index.initialize_connector_if_needed(neuron_types, output_dir) # Correct neuron names (convert filenames back to original names) - corrected_neuron_types, _ = IndexService.correct_neuron_names( - self, neuron_types, connector - ) + corrected_neuron_types, _ = index.correct_neuron_names(neuron_types, connector) # Generate scatterplot data for corrected neuron types plot_data = self._extract_plot_data(corrected_neuron_types) @@ -61,18 +68,21 @@ async def create_scatterplots(self, command): points = self._extract_points(plot_data, side=side, region=region) if not points: raise SystemExit( - f"No points found: ensure values exist for types within {side}{region}." + f"No points found: ensure values exist for types within {side} {region}." ) - ctx = self._prepare(self.config, points, side=side, region=region) + ctx = self._prepare(self.scatter_config, points, side=side, region=region) + + template_dir = get_templates_dir() + template_env = Environment(loader=FileSystemLoader(template_dir)) + template = template_env.get_template(self.scatter_config.template_name) - # Use the page generator's Jinja environment - template = self.page_generator.env.get_template("scatterplot.svg.jinja") - svg_content = template.render(ctx) + # template = Template(self.scatter_config.template_name, trim_blocks=True, lstrip_blocks=True) + svg_content = template.render(**ctx) # Write the index file scatter_path = ( - output_dir / f"{region}_{side}_{command.scatter_filename}" + f"{self.output_dir}/{region}_{self.scatter_config.scatter_fname}" ) with open(scatter_path, "w", encoding="utf-8") as f: @@ -85,25 +95,21 @@ async def create_scatterplots(self, command): return Err(f"Failed to create plot_data: {str(e)}") def _extract_plot_data(self, neuron_types): - """Generate plot data from list of neuron types. - Generates the list of dicts containing the spatial metrics - data used to generate the interactive scatterplots for optic - lobe cell types. It extracts the relevant data from the - output/.cache/type.json files generated when making each neuron - type's respective page.""" - cached_data_lazy = ( - self.cache_manager.get_cached_data_lazy() if self.cache_manager else None - ) + """Generate plot data from list of neuron types.""" + cached_data_lazy = self.cache_manager.get_cached_data_lazy() if self.cache_manager else None plot_data = [] cached_count = 0 missing_cache_count = 0 - for neuron_type in neuron_types.items(): - # Check if we have cached data for this neuron type - cache_data = cached_data_lazy.get(neuron_type) if cached_data_lazy else None + names = neuron_types.keys() if isinstance(neuron_types, dict) else neuron_types + + for neuron_name in names: + cache_data = None + if cached_data_lazy is not None: + cache_data = cached_data_lazy.get(neuron_name) entry = { - "name": neuron_type, + "name": neuron_name, "total_count": 0, "left_count": 0, "right_count": 0, @@ -111,40 +117,98 @@ def _extract_plot_data(self, neuron_types): "undefined_count": 0, "has_undefined": False, "spatial_metrics": {}, - "roi_summary": {}, } - # Use cached data if available - if cache_data: - entry["spatial_metrics"] = cache_data.spatial_metrics - entry["roi_summary"] = cache_data.roi_summary - entry["total_count"] = cache_data.total_count - entry["left_count"] = cache_data.soma_side_counts.get("left", 0) - entry["right_count"] = cache_data.soma_side_counts.get("right", 0) - entry["middle_count"] = cache_data.soma_side_counts.get("middle", 0) - entry["undefined_count"] = cache_data.soma_side_counts.get("unknown", 0) - entry["has_undefined"] = entry["undefined_count"] > 0 - - logger.debug(f"Used cached data for {neuron_type}") + if cache_data is not None: + # ---- counts ---- + if hasattr(cache_data, "total_count") and cache_data.total_count is not None: + entry["total_count"] = cache_data.total_count + + ssc = {} + if hasattr(cache_data, "soma_side_counts") and cache_data.soma_side_counts: + ssc = cache_data.soma_side_counts + + if isinstance(ssc, dict): + if "left" in ssc and ssc["left"] is not None: + entry["left_count"] = ssc["left"] + if "right" in ssc and ssc["right"] is not None: + entry["right_count"] = ssc["right"] + if "middle" in ssc and ssc["middle"] is not None: + entry["middle_count"] = ssc["middle"] + + undefined_sum = 0 + if "unknown" in ssc and ssc["unknown"] is not None: + undefined_sum += ssc["unknown"] + if "undefined" in ssc and ssc["undefined"] is not None: + undefined_sum += ssc["undefined"] + entry["undefined_count"] = undefined_sum + entry["has_undefined"] = undefined_sum > 0 + + # ---- spatial metrics (raw) ---- + sm = {} + if hasattr(cache_data, "spatial_metrics") and cache_data.spatial_metrics: + sm = cache_data.spatial_metrics + + # ---- roi_summary source (for incl_scatter) ---- + roi_source = {} + if hasattr(cache_data, "roi_summary") and cache_data.roi_summary: + rs = cache_data.roi_summary + if isinstance(rs, dict): + roi_source = rs + elif isinstance(rs, list): + # turn [{'name': 'ME', ...}, ...] into {'ME': {...}, ...} if applicable + tmp = {} + for item in rs: + if isinstance(item, dict) and "name" in item: + nm = item["name"] + tmp[nm] = item + roi_source = tmp + + # ---- write incl_scatter into each side/region dict ---- + # If you only want it under "both", change sides_to_update = ("both",) + sides_to_update = ("both", "L", "R") + for region in ("ME", "LO", "LOP"): + incl_val = None + if isinstance(roi_source, dict) and region in roi_source: + region_src = roi_source[region] + if isinstance(region_src, dict) and "incl_scatter" in region_src: + incl_val = region_src["incl_scatter"] + + for side_key in sides_to_update: + if isinstance(sm, dict): + if side_key not in sm or sm[side_key] is None: + sm[side_key] = {} + side_dict = sm[side_key] + if region not in side_dict or side_dict[region] is None: + side_dict[region] = {} + region_dict = side_dict[region] + if isinstance(region_dict, dict): + region_dict["incl_scatter"] = incl_val + + # finally attach sm + entry["spatial_metrics"] = sm + + logger.debug(f"Used cached data for {neuron_name}") cached_count += 1 else: - # No cached data available - use minimal defaults - logger.debug(f"No cached data available for {neuron_type}") + logger.debug(f"No cached data available for {neuron_name}") missing_cache_count += 1 plot_data.append(entry) - # Sort results plot_data.sort(key=lambda x: x["name"]) if missing_cache_count > 0: logger.warning( - f"Plot data generation completed: {len(plot_data)} entries, {cached_count} with cache, {missing_cache_count} missing cache. Run 'quickpage generate' to populate cache." + f"Plot data generation completed: {len(plot_data)} entries, " + f"{cached_count} with cache, {missing_cache_count} missing cache. " + f"Run 'quickpage generate' to populate cache." ) else: logger.info( f"Plot data generation completed: {len(plot_data)} entries, all with cached data" ) + return plot_data def _extract_points(self, plot_data, side, region): @@ -155,62 +219,66 @@ def _extract_points(self, plot_data, side, region): pts = [] for rec in plot_data: - # incl = rec.get("roi_summary", {}).get(region, {}).get("incl_scatter") - # print(incl) - - # # Only include types that have "incl_scatter" == 1. - # # Pass threshold for syn % and syn #. - # if incl is not None: - name = rec.get("name", "unknown") - x = rec.get("total_count") - y = ( - rec.get("spatial_metrics", {}) - .get(side, {}) - .get(region, {}) - .get("cell_size") - ) - c = ( - rec.get("spatial_metrics", {}) - .get(side, {}) - .get(region, {}) - .get("coverage") - ) - col_count = ( + incl = ( rec.get("spatial_metrics", {}) .get(side, {}) .get(region, {}) - .get("cols_innervated") + .get("incl_scatter") ) - # require x,y positive for log scales - if x is None or y is None or c is None: - continue - try: - x = float(x) - y = float(y) - c = float(c) - except Exception: - continue - if x <= 0 or y <= 0: - continue - - # Optional data quality filter from prior script - if col_count is not None: + # Only include types that have "incl_scatter" == 1. + # Pass threshold for syn % and syn #. + if incl == 1: + name = rec.get("name", "unknown") + x = rec.get("total_count") + y = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("cell_size") + ) + c = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("coverage") + ) + col_count = ( + rec.get("spatial_metrics", {}) + .get(side, {}) + .get(region, {}) + .get("cols_innervated") + ) + + # require x,y positive for log scales + if x is None or y is None or c is None: + continue try: - if float(col_count) <= 9: - continue + x = float(x) + y = float(y) + c = float(c) except Exception: - pass - - pts.append( - { - "name": name, - "x": x, - "y": y, - "coverage": c, - "col_count": float(col_count) if col_count is not None else None, - } - ) + continue + if x <= 0 or y <= 0: + continue + + # Optional data quality filter from prior script + if col_count is not None: + try: + if float(col_count) <= 9: + continue + except Exception: + pass + + pts.append( + { + "name": name, + "x": x, + "y": y, + "coverage": c, + "col_count": float(col_count) if col_count is not None else None, + } + ) return pts def _prepare( @@ -221,6 +289,8 @@ def _prepare( region=None, ): """Compute pixel positions for an SVG scatter plot (color by coverage).""" + + # Range depends on values of "points" xmin = min(p["x"] for p in points) xmax = max(p["x"] for p in points) ymin = min(p["y"] for p in points) @@ -273,7 +343,8 @@ def sy(v): t_raw = (min(p["coverage"], cmax) - cmin) / crng t = max(0.0, min(1.0, t_raw)) p["color"] = self._cov_to_rgb(t) - p["r"] = 4 + p["r"] = config.marker_size + p["line_width"] = config.marker_line_width p["tooltip"] = ( f"{p['name']} - {region}({side}):\n" f" {int(p['x'])} cells:\n" @@ -282,13 +353,13 @@ def sy(v): ) # Reference (anti-diagonal) guide lines under points - if n_cols_region is None: - col_counts = [p["col_count"] for p in points if p.get("col_count")] - if col_counts: - n_cols_region = max(col_counts) - else: - n_cols_region = 10 ** ((log10(xmin * ymin) + log10(xmax * ymax)) / 4) + col_counts = [p["col_count"] for p in points if p.get("col_count")] + if col_counts: + n_cols_region = max(col_counts) + else: + n_cols_region = 10 ** ((log10(xmin * ymin) + log10(xmax * ymax)) / 4) + # Add guide lines to scatter plot multipliers = [0.2, 0.5, 1, 2, 5] def guide_width(m): @@ -327,43 +398,41 @@ def log_pos_y(t): xtick_data = [{"t": t, "px": log_pos_x(t)} for t in config.xticks] ytick_data = [{"t": t, "py": log_pos_y(t)} for t in config.yticks] - ctx = self. _prepare_template_variables(self, points, config, region) + + ctx = self._prepare_template_variables(points, guide_lines, config, region, xtick_data, ytick_data, cmin, cmax) return ctx - def _prepare_template_variables(self, points, config, region): + def _prepare_template_variables(self, points, guide_lines, config, region, xtick_data, ytick_data, cmin, cmax): """Prepare variables for template rendering. Args: - points: Processed hexagon data + points: Processed scatter points + guide_lines: Points to draw plot guidelines config: Scatter configuration + region: Optic lobe region for which to generate plot. ME, LO or LOP. Returns: Dictionary of template variables """ template_vars = { "width": config.width, "height": config.height, - "margin_top": config.margin[1], - "margin_right": config.margin[2], - "margin_bottom": config.margin[3], - "margin_left": config.margin[4], + "margin_top": config.margin_top, + "margin_right": config.margin_right, + "margin_bottom": config.margin_bottom, + "margin_left": config.margin_left, "plot_w": config.plot_w, "plot_h": config.plot_h, - "xticks": config.xticks, - "yticks": config.yticks, - "xmin": config.xmin, - "xmax": config.xmax, - "ymin": config.ymin, - "ymax": config.ymax, - "cmin": config.cmin, - "cmax": config.cmax, + "cmin": cmin, + "cmax": cmax, "points": points, - "title": f"{region}", - "xtick_data": config.xtick_data, - "ytick_data": config.ytick_data, - "guide_lines": config.guide_lines, - "xlabel": "Population size (no. cells per type)", - "ylabel": "Cell size (no. columns per cell)", - "legend_title": "Coverage factor (cells per column)", + "xtick_data": xtick_data, + "ytick_data": ytick_data, + "guide_lines": guide_lines, + "title": region, + "xlabel": config.xlabel, + "ylabel": config.ylabel, + "legend_label": config.legend_label, + "legend_w": config.legend_w, } return template_vars From 213e9bf4dcbc551ea5ce30d34ce2d010313c3f58 Mon Sep 17 00:00:00 2001 From: leburnett Date: Wed, 8 Oct 2025 14:29:54 -0400 Subject: [PATCH 21/60] Update scatter_config.py --- .../visualization/rendering/scatter_config.py | 134 ++++++------------ 1 file changed, 44 insertions(+), 90 deletions(-) diff --git a/src/neuview/visualization/rendering/scatter_config.py b/src/neuview/visualization/rendering/scatter_config.py index ee7156d..f318d58 100644 --- a/src/neuview/visualization/rendering/scatter_config.py +++ b/src/neuview/visualization/rendering/scatter_config.py @@ -1,7 +1,7 @@ """ Scatter rendering config """ -from typing import List, Dict, Any, Optional +from typing import Dict, Any, Optional from pathlib import Path from dataclasses import dataclass from ...utils import get_templates_dir @@ -9,27 +9,25 @@ @dataclass class ScatterConfig: """ - Configuration for rendering operations. - - This class encapsulates all the parameters needed to control - the rendering process, including output format, layout settings, - and file management options. + Scatter config """ # Output configuration output_format: str = "svg" - embed_mode: bool = False save_to_files: bool = True # File management - output_dir: Optional[Path] = None - scatter_dir: Optional[Path] = None + scatter_dir: Optional[Path] = "output/scatter" + scatter_fname = f"scatter.{output_format}" # Layout configuration - marker_size: int = 20 margins: list = (60, 72, 64, 72) axis_gap_px: int = 10 + # Marker features + marker_size: int = 4 + marker_line_width: float = 0.5 + # SVG-specific configuration template_name: str = "scatterplot.svg.jinja" @@ -37,97 +35,53 @@ class ScatterConfig: title: str = "" xlabel: str = "Population size (no. cells per type)" ylabel: str = "Cell size (no. columns per cell)" - optic_lobe_side: str = None - region_name: Optional[str] = None + legend_label: str = "Coverage factor (cells per column)" # Data configuration min_max_data: Optional[Dict[str, Any]] = None thresholds: Optional[Dict[str, Any]] = None - def __post_init__(self): - """Post-initialization validation and setup.""" - - if self.scatter_dir is None and self.output_dir: - self.scatter_dir = self.output_dir / "scatter" + top, right, bottom, left = margins + margin_top = top + margin_right = right + margin_bottom = bottom + margin_left = left + width = 680 + height = 460 + plot_w = width - left - right + plot_h = height - top - bottom + + side_px = min(plot_w, plot_h) + plot_w = side_px + plot_h = side_px - # def get_template_path(self) -> Optional[Path]: - # """Get the full path to the template file.""" - # # Templates are now loaded from the built-in templates directory - # return get_templates_dir() / self.template_name - -@dataclass -class ScatterLayoutConfig: - """ - Configuration for layout calculations. + xticks = [1, 10, 100, 1000] + yticks = [1, 10, 100, 1000] - This class contains parameters specific to layout computation - and coordinate transformations. - """ - - width: int = 0 - height: int = 0 - min_x: float = 0.0 - min_y: float = 0.0 - margin: int = 10 - legend_x: float = 0.0 - title_x: float = 0.0 - hex_points: str = "" - - # Legend configuration - legend_width: int = 12 - legend_height: int = 60 - legend_y: float = 0.0 - legend_title_x: float = 0.0 - legend_title_y: float = 0.0 - - # Layer control configuration - layer_control_x: float = 0.0 - layer_control_y: float = 0.0 + legend_w = 12 + + def get_template_path(self) -> Optional[Path]: + """Get the full path to the template file.""" + # Templates are now loaded from the built-in templates directory + return get_templates_dir() / self.template_name def to_dict(self) -> Dict[str, Any]: """Convert layout config to dictionary for template rendering.""" return { "width": self.width, "height": self.height, - "min_x": self.min_x, - "min_y": self.min_y, - "margin": self.margin, - "legend_x": self.legend_x, - "title_x": self.title_x, - "hex_points": self.hex_points, - "legend_width": self.legend_width, - "legend_height": self.legend_height, - "legend_y": self.legend_y, - "legend_title_x": self.legend_title_x, - "legend_title_y": self.legend_title_y, - "layer_control_x": self.layer_control_x, - "layer_control_y": self.layer_control_y, - } - - -@dataclass -class ScatterLegendConfig: - """ - Configuration for legend rendering. - - This class contains parameters for rendering the color legend - and associated UI elements. - """ - - legend_title: str = "" - legend_type_name: str = "" - title_y: float = 0.0 - bin_height: int = 12 - thresholds: Optional[Dict[str, Any]] = None - layer_thresholds: Optional[Dict[str, Any]] = None - - def to_dict(self) -> Dict[str, Any]: - """Convert legend config to dictionary for template rendering.""" - return { - "legend_title": self.legend_title, - "legend_type_name": self.legend_type_name, - "title_y": self.title_y, - "bin_height": self.bin_height, - "thresholds": self.thresholds, - "layer_thresholds": self.layer_thresholds, + "xticks": self.xticks, + "yticks": self.yticks, + "marker_size": self.marker_size, + "margin_top": self.top, + "margin_right": self.right, + "margin_bottom": self.bottom, + "margin_left": self.left, + "legend_w": self.legend_w, + "xlabel": self.xlabel, + "ylabel": self.ylabel, + "legend_label": self.legend_label, + "axis_gap_px": self.axis_gap_px, + "plot_h": self.plot_h, + "plot_w": self.plot_w, } From efcc6cfd2519aa86daef61cc81b47d8005acf25d Mon Sep 17 00:00:00 2001 From: leburnett Date: Wed, 8 Oct 2025 14:30:19 -0400 Subject: [PATCH 22/60] update scatter templates svg and html --- templates/scatterplot.svg.jinja | 14 ++-- templates/sections/scatterplots.html.jinja | 75 ++++++++++------------ 2 files changed, 45 insertions(+), 44 deletions(-) diff --git a/templates/scatterplot.svg.jinja b/templates/scatterplot.svg.jinja index 6b855d6..ee2c48d 100644 --- a/templates/scatterplot.svg.jinja +++ b/templates/scatterplot.svg.jinja @@ -9,7 +9,7 @@ .axis-line { stroke:#444; stroke-width:1; shape-rendering:crispEdges; } .tick-mark { stroke:#444; stroke-width:1; shape-rendering:crispEdges; } .tick-label { fill:#444; font-size:14px; font-family:Helvetica, Arial, sans-serif; } - .title { fill:#333; font-size:14px; font-family:Arial, sans-serif; } + .title { fill:#333; font-size:30px; font-family:Arial, sans-serif; } .subtitle { fill:#777; font-size:11px; font-family:Arial, sans-serif; } .axis-label { fill:#333; font-size:16px; font-family:Helvetica, Arial, sans-serif; } .dot { cursor:pointer; opacity:0.9; transition:opacity 0.15s; } @@ -25,6 +25,7 @@ @@ -149,7 +196,7 @@ function hideTip(evt) { {{ ylabel }} + x="{{ plot_w + 70 }}" y="{{ 60 }}"> {{ title }} diff --git a/templates/sections/eyemaps.html.jinja b/templates/sections/eyemaps.html.jinja index 3da29bf..faec5f7 100644 --- a/templates/sections/eyemaps.html.jinja +++ b/templates/sections/eyemaps.html.jinja @@ -7,6 +7,7 @@ {%- if soma_side == 'combined' -%} {% include "sections/eyemaps_both.html.jinja" %} + {% include "sections/scatterplots.html.jinja" %} {%- else -%} {% include "sections/eyemaps_single.html.jinja" %} {%- endif -%} diff --git a/templates/sections/neuron_page_scripts.html.jinja b/templates/sections/neuron_page_scripts.html.jinja index df1681b..0572744 100644 --- a/templates/sections/neuron_page_scripts.html.jinja +++ b/templates/sections/neuron_page_scripts.html.jinja @@ -16,6 +16,14 @@ $(document).ready(function() { currentNeuronType: {{ neuron_data.type | tojson }} }; + (function () { + const needle = String({{ neuron_data.type | tojson }} || '').trim(); + $('object[type="image/svg+xml"]').each(function () { + const base = this.data.split('#')[0]; // strip any existing fragment + this.data = base + '#highlight=' + encodeURIComponent(needle); + }); + })(); + {# Initialize neuroglancer links BEFORE DataTables to ensure checkboxes are set up first #} initializeNeuroglancerLinks(neuroglancerData); diff --git a/templates/sections/scatterplots.html.jinja b/templates/sections/scatterplots.html.jinja index 9e05a22..42201c4 100644 --- a/templates/sections/scatterplots.html.jinja +++ b/templates/sections/scatterplots.html.jinja @@ -1,18 +1,12 @@ -{#-- Region-Specific Scatterplots of spatial metrics -- #} -{#-- Use the same clause for eyemap plots -- #} -{%- if column_analysis and column_analysis.comprehensive_region_grids and column_analysis.comprehensive_region_grids|length > 0 -%} - -
-

Spatial coverage scatterplots

- -
+ +
{% for region in ['ME','LO','LOP'] %}
- {% set svg_path = 'output/scatter/scatter_' ~ region ~ '.svg' %} + {% set svg_path = '../../output/scatter/' ~ region ~ '_scatter.svg' %} - + Scatterplot of spatial metrics for {{ region }} @@ -32,8 +26,4 @@ {% endfor %} - - -{% endif %} - - \ No newline at end of file + From 7f7ebeaa98a91256400e1a1538c812648df863a5 Mon Sep 17 00:00:00 2001 From: leburnett Date: Thu, 9 Oct 2025 16:56:22 -0400 Subject: [PATCH 27/60] Update neuron-page.js --- static/js/neuron-page.js | 172 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 172 insertions(+) diff --git a/static/js/neuron-page.js b/static/js/neuron-page.js index 0adb10f..f2a822e 100644 --- a/static/js/neuron-page.js +++ b/static/js/neuron-page.js @@ -565,5 +565,177 @@ function initializeAllTooltips() { }, 100); } +// Try to highlight inside a given Document that contains an SVG plot. +function highlightInSvgDocument(doc, neuronType) { + const needle = String(neuronType || "").trim().toLowerCase(); + if (!needle) return 0; + + // markers considered: + let candidates = Array.from(doc.querySelectorAll('g.marker')); + if (candidates.length === 0) { + candidates = Array.from(doc.querySelectorAll('circle.dot')) + .map(c => c.closest('g.marker') || c.parentNode) + .filter(Boolean); + } + + if (candidates.length === 0) return 0; + + // Highlight at most one per + const seenSvgs = new WeakSet(); + let hitCount = 0; + + for (const g of candidates) { + const svgEl = g.ownerSVGElement || doc.querySelector('svg'); + if (!svgEl || seenSvgs.has(svgEl)) continue; + + const circle = g.querySelector('circle') || g; + if (!circle) continue; + + const dataTitle = (circle.getAttribute('data-title') || '').toLowerCase(); + const titleText = (g.querySelector('title')?.textContent || '').toLowerCase(); + const haystack = dataTitle || titleText; + if (!haystack || !haystack.includes(needle)) continue; + + const win = doc.defaultView; + const rect = circle.getBoundingClientRect(); + const evtLike = { + currentTarget: g, + clientX: rect.left + rect.width / 2, + clientY: rect.top + rect.height / 2 + }; + + let usedShowTip = false; + try { + if (win && typeof win.showTip === 'function') { + win.showTip(evtLike); + usedShowTip = true; + } + } catch (_) { /* cross-origin or blocked */ } + + // Fallback: manually “pin” the state if we can’t call showTip. + if (!usedShowTip) { + try { + // Bring marker to front + g.parentNode && g.parentNode.appendChild(g); + + const baseR = parseFloat(circle.getAttribute('data-base-r') || '4'); + const baseSW = parseFloat(circle.getAttribute('data-base-sw') || + (doc.defaultView?.getComputedStyle(circle).strokeWidth || '0.5')); + circle.setAttribute('r', String(baseR * 3)); + circle.setAttribute('stroke-width', String(baseSW * 3)); + + const tip = doc.getElementById('tooltip'); + const tg = doc.getElementById('tooltip-text-group'); + const bg = doc.getElementById('tooltip-bg'); + if (tip && tg && bg) { + // Build tooltip text + while (tg.firstChild) tg.removeChild(tg.firstChild); + const lines = (circle.getAttribute('data-title') || titleText || '') + .split('\n').filter(s => s.trim().length); + const pad = 6, lh = 14; + lines.forEach((line, i) => { + const t = doc.createElementNS('http://www.w3.org/2000/svg', 'text'); + t.setAttribute('x', pad); + t.setAttribute('y', pad + lh + i * lh); + t.setAttribute('class', 'tooltip-text'); + t.textContent = line; + tg.appendChild(t); + }); + const boxW = 350; + const boxH = lines.length * lh + pad * 2; + bg.setAttribute('width', boxW); + bg.setAttribute('height', boxH); + + const svgRect = svgEl.getBoundingClientRect(); + let x = rect.left - svgRect.left + 10; + let y = rect.top - svgRect.top - boxH - 10; + const vbW = svgEl.viewBox?.baseVal?.width || svgRect.width; + if (x + boxW > vbW) x = vbW - boxW - 5; + if (y < 0) y = rect.top - svgRect.top + 10; + + tip.setAttribute('transform', `translate(${x},${y})`); + tip.setAttribute('opacity', '1'); + + const tEl = g.querySelector('title'); + if (tEl) tEl.textContent = ''; + } + } catch (_) { /* ignore */ } + } + + seenSvgs.add(svgEl); + hitCount++; + } + + return hitCount; +} + +// Discover SVGs in the page and highlight all of them. +function highlightNeuronAllPlots(neuronType) { + const needle = String(neuronType || '').trim(); + if (!needle) return; + + let total = 0; + + // 1) Inline SVGs (if any) + try { + total += highlightInSvgDocument(document, needle); + } catch (_) {} + + // 2) + const objects = Array.from(document.querySelectorAll('object[type="image/svg+xml"]')); + for (const obj of objects) { + const run = () => { + try { + const doc = obj.contentDocument; + if (doc) { + const added = highlightInSvgDocument(doc, needle); + total += added; + if (added === 0) { + // helpful debug + console.warn('No match in SVG:', obj.data); + } + } + } catch (e) { + console.warn('Cannot access (likely cross-origin):', obj.data); + } + }; + if (obj.contentDocument && obj.contentDocument.readyState !== 'loading') { + run(); + } else { + obj.addEventListener('load', run, { once: true }); + } + } + + // 3) Scatterplot of spatial metrics for {{ region }} - - - - - - - - -
{% endfor %} From eb1999671dfa56823e4d7585b78a1c5cb4df6afa Mon Sep 17 00:00:00 2001 From: leburnett Date: Fri, 10 Oct 2025 09:35:10 -0400 Subject: [PATCH 30/60] Delete test_scatter.py --- test/test_scatter.py | 460 ------------------------------------------- 1 file changed, 460 deletions(-) delete mode 100644 test/test_scatter.py diff --git a/test/test_scatter.py b/test/test_scatter.py deleted file mode 100644 index a98a05f..0000000 --- a/test/test_scatter.py +++ /dev/null @@ -1,460 +0,0 @@ -# scatter_svg_from_plot_data.py (updated) -from math import ceil, floor, log10, isfinite -from jinja2 import Template -import pickle - -file_path = 'my_file.pkl' -with open(file_path, 'rb') as f: - plot_data = pickle.load(f) - - -def extract_points(records, side, region): - """ - Collect points, requiring: - - total_count (x) > 0 - - cell_size (y) > 0 from spatial_metrics[side][region].cell_size - - coverage (c) present and >= 0 (used only for color scale) - Also retain cols_innervated for reference lines. - """ - pts = [] - for rec in records: - name = rec.get("name", "unknown") - x = rec.get("total_count") - y = ( - rec.get("spatial_metrics", {}) - .get(side, {}) - .get(region, {}) - .get("cell_size") - ) - c = ( - rec.get("spatial_metrics", {}) - .get(side, {}) - .get(region, {}) - .get("coverage") - ) - col_count = ( - rec.get("spatial_metrics", {}) - .get(side, {}) - .get(region, {}) - .get("cols_innervated") - ) - - # require x,y positive for log scales - if x is None or y is None or c is None: - continue - try: - x = float(x) - y = float(y) - c = float(c) - except Exception: - continue - if x <= 0 or y <= 0: - continue - - # Optional data quality filter from prior script - if col_count is not None: - try: - if float(col_count) <= 9: - continue - except Exception: - pass - - pts.append({ - "name": name, - "x": x, - "y": y, - "coverage": c, - "col_count": float(col_count) if col_count is not None else None, - }) - return pts - - -def log_ticks(vmin, vmax): - """Decade ticks for a log10 axis between (vmin, vmax), inclusive.""" - if vmin <= 0 or vmax <= 0 or vmin >= vmax: - return [] - lo = floor(log10(vmin)) - hi = ceil(log10(vmax)) - return [10 ** e for e in range(lo, hi + 1)] - - -def scale_log10(v, vmin, vmax, a, b): - """Log10 scaling to pixels.""" - lv = log10(v) - lmin = log10(vmin) - lmax = log10(vmax) - if lmax == lmin: - return (a + b) / 2.0 - return a + (lv - lmin) * (b - a) / (lmax - lmin) - - -def lerp(a, b, t): - return a + (b - a) * t - - -def cov_to_rgb(t): - """ - Map t in [0,1] to a white→dark red gradient. - start = white (255,255,255), end = dark red (~180,0,0) - """ - r0, g0, b0 = 255, 255, 255 - r1, g1, b1 = 150, 0, 0 - r = int(round(lerp(r0, r1, t))) - g = int(round(lerp(g0, g1, t))) - b = int(round(lerp(b0, b1, t))) - return f"rgb({r},{g},{b})" - - -def percentile(values, p): - """Return the p-th percentile (0-100) with linear interpolation, pure Python.""" - vals = sorted(v for v in values if v is not None) - n = len(vals) - if n == 0: - return None - if n == 1: - return vals[0] - # rank in [0, n-1] - r = (p / 100.0) * (n - 1) - lo = int(r) - hi = min(lo + 1, n - 1) - t = r - lo - return vals[lo] * (1 - t) + vals[hi] * t - - -def prepare(points, width=680, height=460, margins=(60, 72, 64, 72), *, axis_gap_px=10, n_cols_region=None, side=None, region=None): - """Compute pixel positions for an SVG scatter plot (log–log, color by coverage). - - Changes vs. prior version: - - Adds an inner pixel gap (axis_gap_px) so points do not touch the axes. - - Removes the plot "box" (background rect) in the template. - - Adds five light-grey guide lines (below points) for k = n_cols_region × {0.2,0.5,1,2,5} - where the guides follow x*y = k (straight anti-diagonals in log–log). - If n_cols_region is None, it is estimated as the max of available `col_count`. - - Sets color max to the 98th percentile of coverage values (legend reflects this clip). - - Adds axis labels for X and Y. - """ - top, right, bottom, left = margins - plot_w = width - left - right - plot_h = height - top - bottom - - side_px = min(plot_w, plot_h) - plot_w = side_px - plot_h = side_px - - xmin = min(p["x"] for p in points) - xmax = max(p["x"] for p in points) - ymin = min(p["y"] for p in points) - ymax = max(p["y"] for p in points) - - # expand bounds slightly so dots don't sit on the frame (keep >0) - pad_x = xmin * 0.05 - pad_y = ymin * 0.08 - xmin = max(1e-12, xmin - pad_x) - ymin = max(1e-12, ymin - pad_y) - xmax *= 1.05 - ymax *= 1.08 - - lxmin, lxmax = log10(xmin), log10(xmax) - lymin, lymax = log10(ymin), log10(ymax) - dx = lxmax - lxmin - dy = lymax - lymin - - if dx > dy: - # expand Y range to match X span (around geometric center) - cy = (lymin + lymax) / 2.0 - lymin, lymax = cy - dx / 2.0, cy + dx / 2.0 - ymin, ymax = 10 ** lymin, 10 ** lymax - elif dy > dx: - # expand X range to match Y span (around geometric center) - cx = (lxmin + lxmax) / 2.0 - lxmin, lxmax = cx - dy / 2.0, cx + dy / 2.0 - xmin, xmax = 10 ** lxmin, 10 ** lxmax - - # fixed ticks at 1, 10, 100, 1000 (only those within the current axis range) - xticks = [1, 10, 100, 1000] - yticks = xticks - - # coverage color scaling with 98th percentile clipping - coverages = [p["coverage"] for p in points] - cmin = min(coverages) - cmax = percentile(coverages, 98.0) or max(coverages) - crng = (cmax - cmin) if isfinite(cmax - cmin) and (cmax - cmin) > 0 else 1.0 - - # Inner drawing range to create a visible gap to axes - inner_x0, inner_x1 = axis_gap_px, max(axis_gap_px, plot_w - axis_gap_px) - inner_y0, inner_y1 = plot_h - axis_gap_px, axis_gap_px # inverted - - def sx(v): - return scale_log10(v, xmin, xmax, inner_x0, inner_x1) - - def sy(v): - return scale_log10(v, ymin, ymax, inner_y0, inner_y1) - - for p in points: - p["sx"] = sx(p["x"]) - p["sy"] = sy(p["y"]) # SVG y grows downward - # color by coverage (clipped at cmax) - t_raw = (min(p["coverage"], cmax) - cmin) / crng - t = max(0.0, min(1.0, t_raw)) - p["color"] = cov_to_rgb(t) - p["r"] = 4 - p["tooltip"] = ( - f"{p['name']} - {region}({side}):\n" - f" {int(p['x'])} cells:\n" - f" cell_size: {p['y']:.3f}\n" - f" coverage: {p['coverage']:.3f}" - ) - - # Reference (anti-diagonal) guide lines under points - if n_cols_region is None: - col_counts = [p["col_count"] for p in points if p.get("col_count")] - if col_counts: - n_cols_region = max(col_counts) - else: - n_cols_region = 10 ** ((log10(xmin * ymin) + log10(xmax * ymax)) / 4) - - multipliers = [0.2, 0.5, 1, 2, 5] - - def guide_width(m): - if m < 0.5 or m > 2: - return 0.25 - elif m != 1: - return 0.4 - else: - return 0.8 - - guide_lines = [] - for m in multipliers: - k = n_cols_region * m # x*y = k - # Clip hyperbola segment to the [xmin,xmax]×[ymin,ymax] window in data space - x0_clip = max(xmin, k / ymax) - x1_clip = min(xmax, k / ymin) - if x0_clip >= x1_clip: - continue # out of view - y0 = k / x0_clip - y1 = k / x1_clip - guide_lines.append({ - "x1": sx(x0_clip), - "y1": sy(y0), - "x2": sx(x1_clip), - "y2": sy(y1), - "w": guide_width(m), - }) - - # Precompute pixel tick positions for Jinja (avoid math inside template) - def log_pos_x(t): - return scale_log10(t, xmin, xmax, inner_x0, inner_x1) - - def log_pos_y(t): - return scale_log10(t, ymin, ymax, inner_y0, inner_y1) - - xtick_data = [{"t": t, "px": log_pos_x(t)} for t in xticks] - ytick_data = [{"t": t, "py": log_pos_y(t)} for t in yticks] - - ctx = { - "width": width, - "height": height, - "margin_top": top, - "margin_right": right, - "margin_bottom": bottom, - "margin_left": left, - "plot_w": plot_w, - "plot_h": plot_h, - "xticks": xticks, - "yticks": yticks, - "xmin": xmin, "xmax": xmax, - "ymin": ymin, "ymax": ymax, - "cmin": cmin, "cmax": cmax, - "points": points, - "title": f"{region}({side}): total_count vs cell_size", - "subtitle": "colorscale = coverage (max at 98th percentile)", - "xtick_data": xtick_data, - "ytick_data": ytick_data, - "guide_lines": guide_lines, - "xlabel": "Population size (no. cells per type)", - "ylabel": "Cell size (no. columns per cell)", - } - - return ctx - -SVG_TEMPLATE = Template(r""" - - - - - - - - - - - - - - - - {% for tick in xtick_data %} - - - {{ tick.t }} - - {% endfor %} - - - {% for tick in ytick_data %} - - - {{ tick.t }} - - {% endfor %} - - - {% for g in guide_lines %} - - {% endfor %} - - - {% for p in points %} - - - {{ p.tooltip }} - - - {% endfor %} - - - -{{ xlabel }} -{{ ylabel }} - - - - - - - - - - - Coverage factor (cells per column) - - - - >{{ '%.0f' % cmax }} - {{ '%.0f' % cmin }} - - - - - - - - -""", trim_blocks=True, lstrip_blocks=True) - -# Jinja helper registrations -# SVG_TEMPLATE.globals.update(fmt_decade=fmt_decade) - -if __name__ == "__main__": - side = "R" - region = "LOP" - - points = extract_points(plot_data, side=side, region=region) - if not points: - raise SystemExit("No points found: ensure R→ME cell_size values exist and x,y > 0.") - - ctx = prepare(points, axis_gap_px=10, n_cols_region=None, side=side, region=region) - - svg = SVG_TEMPLATE.render(**ctx) - with open(f"scatter_{side}_{region}.svg", "w", encoding="utf-8") as f: - f.write(svg) - - print(f"Wrote scatter_{side}_{region}.svg") From f55a261a4e2e2a343f2e31dddd27d5b9443d08de Mon Sep 17 00:00:00 2001 From: leburnett Date: Fri, 10 Oct 2025 09:36:36 -0400 Subject: [PATCH 31/60] Delete my_file.pkl --- my_file.pkl | Bin 4319120 -> 0 bytes 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 my_file.pkl diff --git a/my_file.pkl b/my_file.pkl deleted file mode 100644 index 06b0aa32accfb01d753f6defcb8846f87e5c2e23..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 4319120 zcmce<2fSTX)xDicLhrpd>5xhiX$kFukOk6v2oSiLbVyK0tDF8j%f6HM*khkbpBws2n|X|ahblGHm%?I4Vpgt?)&d^@Px_x?KkP5Lncm{w8!*K z`b-8v!G1-@6arVam$D96&OwW+SKm( zW6rX%q_1|b*zxC;^FK3~o^MTm)t)S!(E4)Epw2J1z-;p+fLUvk-MZKATIa2vA8GeG zU1PU9s`>xvHnbMttsT182~!o+8WBYLYWLWlKmVj-(jL3^OzK`Y_cOSjQ3*v)j!x_v 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a/templates/sections/neuron_page_scripts.html.jinja b/templates/sections/neuron_page_scripts.html.jinja index 0572744..b085868 100644 --- a/templates/sections/neuron_page_scripts.html.jinja +++ b/templates/sections/neuron_page_scripts.html.jinja @@ -2,7 +2,7 @@ {% include "sections/global_scripts.html.jinja" %} {# -- Load external static JavaScript functions -- #} - + - + - + - + {% for tick in xtick_data %} - - {{ tick.t }} - + {{ tick.t }} {% endfor %} - + {% for tick in ytick_data %} - - {{ tick.t }} - + {{ tick.t }} {% endfor %} - + {% for g in guide_lines %} {% endfor %} {% for p in points %} - - - + + {% endfor %} -{{ xlabel }} -{{ ylabel }} +{{ xlabel }} +{{ ylabel }} - - {{ title }} - +{{ title }} - - - - - - - - - {{legend_label}} - - - - >{{ '%.0f' % cmax }} - {{ '%.0f' % cmin }} - + + + + + + + + {{ legend_label }} + + >{{ '%.0f' % cmax }} + {{ '%.0f' % cmin }} + - + - + - \ No newline at end of file + + From 0bd58679fe11bcfb2c23e56d9399cd00e9258ebc Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 14:48:57 -0500 Subject: [PATCH 54/60] update license --- pixi.lock | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/pixi.lock b/pixi.lock index fb6e856..d1094d1 100644 --- a/pixi.lock +++ b/pixi.lock @@ -2850,6 +2850,7 @@ packages: - libgcc-ng ==15.2.0=*_16 - libgomp 15.2.0 he0feb66_16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 1042798 timestamp: 1765256792743 @@ -2875,6 +2876,7 @@ packages: - libgcc-ng ==15.2.0=*_16 - libgomp 15.2.0 16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 402197 timestamp: 1765258985740 @@ -2889,6 +2891,7 @@ packages: - libgcc-ng ==15.2.0=*_16 - msys2-conda-epoch <0.0a0 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 819696 timestamp: 1765260437409 @@ -2898,6 +2901,7 @@ packages: depends: - libgcc 15.2.0 he0feb66_16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 27256 timestamp: 1765256804124 @@ -2909,6 +2913,7 @@ packages: constrains: - libgfortran-ng ==15.2.0=*_16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 27215 timestamp: 1765256845586 @@ -2932,6 +2937,7 @@ packages: constrains: - libgfortran-ng ==15.2.0=*_16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 138630 timestamp: 1765259217400 @@ -2944,6 +2950,7 @@ packages: constrains: - libgfortran 15.2.0 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 2480559 timestamp: 1765256819588 @@ -2967,6 +2974,7 @@ packages: constrains: - libgfortran 15.2.0 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 598291 timestamp: 1765258993165 @@ -3042,6 +3050,7 @@ packages: depends: - __glibc >=2.17,<3.0.a0 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 603284 timestamp: 1765256703881 @@ -3053,6 +3062,7 @@ packages: constrains: - msys2-conda-epoch <0.0a0 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 663567 timestamp: 1765260367147 @@ -3476,6 +3486,7 @@ packages: constrains: - libstdcxx-ng ==15.2.0=*_16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 5856456 timestamp: 1765256838573 @@ -3485,6 +3496,7 @@ packages: depends: - libstdcxx 15.2.0 h934c35e_16 license: GPL-3.0-only WITH GCC-exception-3.1 + license_family: GPL purls: [] size: 27300 timestamp: 1765256885128 From 2c931420b3526b92342474b7223a6e4b67826510 Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 15:20:32 -0500 Subject: [PATCH 55/60] improve layout for scatterplots --- src/neuview/services/scatterplot_service.py | 28 +++++++++++-- .../rendering/rendering_config.py | 6 +-- templates/scatterplot.svg.jinja | 40 +++++++++---------- 3 files changed, 47 insertions(+), 27 deletions(-) diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py index 7ceb86c..bf272e1 100644 --- a/src/neuview/services/scatterplot_service.py +++ b/src/neuview/services/scatterplot_service.py @@ -78,7 +78,9 @@ async def create_scatterplots(self): points = self._extract_points(plot_data, side=side, region=region) logger.info(f"Extracted {len(points)} points for {region}_{side}") - ctx = self._prepare(self.scatter_config, points, region=region) + ctx = self._prepare( + self.scatter_config, points, region=region, side=side + ) template_dir = get_templates_dir() template_env = Environment(loader=FileSystemLoader(template_dir)) @@ -302,6 +304,7 @@ def _prepare( config, points, region=None, + side="both", ): """Compute pixel positions for an SVG scatter plot (color by coverage).""" @@ -397,13 +400,30 @@ def guide_width(m): ytick_data = [{"t": t, "py": sy(t)} for t in config.yticks] ctx = self._prepare_template_variables( - points, guide_lines, config, region, xtick_data, ytick_data, cmin, cmax + points, + guide_lines, + config, + region, + side, + xtick_data, + ytick_data, + cmin, + cmax, ) return ctx def _prepare_template_variables( - self, points, guide_lines, config, region, xtick_data, ytick_data, cmin, cmax + self, + points, + guide_lines, + config, + region, + side, + xtick_data, + ytick_data, + cmin, + cmax, ): """Prepare variables for template rendering. Args: @@ -429,7 +449,7 @@ def _prepare_template_variables( "xtick_data": xtick_data, "ytick_data": ytick_data, "guide_lines": guide_lines, - "title": region, + "title": region if side == "both" else f"{region} ({side})", "xlabel": config.xlabel, "xlabel_hover": config.xlabel_hover, "ylabel": config.ylabel, diff --git a/src/neuview/visualization/rendering/rendering_config.py b/src/neuview/visualization/rendering/rendering_config.py index cfee661..20da114 100644 --- a/src/neuview/visualization/rendering/rendering_config.py +++ b/src/neuview/visualization/rendering/rendering_config.py @@ -191,7 +191,7 @@ class ScatterConfig: scatter_fname = ".svg" # Layout configuration - margins: list = (60, 72, 64, 72) + margins: list = (60, 72, 64, 50) axis_gap_px: int = 10 # Marker features @@ -219,8 +219,8 @@ class ScatterConfig: margin_right = right margin_bottom = bottom margin_left = left - width = 460 - height = 460 + width = 480 + height = 480 plot_w = width - left - right plot_h = height - top - bottom diff --git a/templates/scatterplot.svg.jinja b/templates/scatterplot.svg.jinja index bca2218..7446013 100644 --- a/templates/scatterplot.svg.jinja +++ b/templates/scatterplot.svg.jinja @@ -162,45 +162,45 @@ if (document.readyState === 'loading') { //]]> - +{#- Plot area -#} - + {#- axis baselines -#} - - {% for tick in xtick_data %} + {#- ticks (X) -#} + {%- for tick in xtick_data -%} {{ tick.t }} - {% endfor %} + {%- endfor -%} - - {% for tick in ytick_data %} + {#- ticks (Y) -#} + {%- for tick in ytick_data -%} - {{ tick.t }} - {% endfor %} + {{ tick.t }} + {%- endfor -%} - - {% for g in guide_lines %} + {#- guide lines -#} + {%- for g in guide_lines -%} - {% endfor %} + {%- endfor -%} - - {% for p in points %} + {#- markers -#} + {%- for p in points -%} - {% endfor %} + {%- endfor -%} - +{#- Axis labels -#} {{ xlabel }} -{{ ylabel }} +{{ ylabel }} -{{ title }} +{{ title }} - +{#- Legend -#} @@ -214,7 +214,7 @@ if (document.readyState === 'loading') { {{ '%.0f' % cmin }} - +{#- Tooltip -#} From c18b9447b9389e08813b921387ce511fe491bf26 Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 15:43:21 -0500 Subject: [PATCH 56/60] add download button for scatterplots --- static/css/neuron-page.css | 45 ++++++ templates/eyemap.svg.jinja | 138 +++++++++--------- templates/sections/scatterplots.html.jinja | 8 + .../sections/scatterplots_single.html.jinja | 8 + 4 files changed, 130 insertions(+), 69 deletions(-) diff --git a/static/css/neuron-page.css b/static/css/neuron-page.css index 11c41db..37e494a 100644 --- a/static/css/neuron-page.css +++ b/static/css/neuron-page.css @@ -1277,6 +1277,51 @@ abbr[data-original-title]:hover { box-shadow: 0 6px 16px rgba(0, 0, 0, 0.3); } +/* Scatterplot download functionality */ +.scatterplot-container { + position: relative; + display: inline-block; + width: 100%; +} + +.scatterplot-download-btn { + position: absolute; + top: 25px; + left: 10px; + width: 25px; + height: 25px; + background-color: var(--pm-secondary-color) !important; + border-radius: 50%; + display: flex; + align-items: center; + justify-content: center; + opacity: 0; + visibility: hidden; + transform: translateY(-20px); + transition: all 0.3s ease; + box-shadow: 0 4px 12px rgba(0, 0, 0, 0.2); + text-decoration: none; + z-index: 10; +} + +.scatterplot-download-btn svg { + width: 20px; + height: 20px; + color: white; +} + +.scatterplot-container:hover .scatterplot-download-btn { + opacity: 0.5; + visibility: visible; + transform: translateY(0); +} + +.scatterplot-download-btn:hover { + transform: scale(1.1); + opacity: 1 !important; + box-shadow: 0 6px 16px rgba(0, 0, 0, 0.3); +} + .no-data-text { color: #999; } diff --git a/templates/eyemap.svg.jinja b/templates/eyemap.svg.jinja index 82dacbc..d1ab277 100644 --- a/templates/eyemap.svg.jinja +++ b/templates/eyemap.svg.jinja @@ -11,7 +11,7 @@ .tooltip-rect { fill: rgba(0, 0, 0, 0.8); rx: 3; ry: 3; } .tooltip-text { fill: white; font-family: Helvetica, Arial, 'Liberation Sans', 'Nimbus Sans', 'DejaVu Sans', sans-serif; font-size: 14px; } -{# Layer control squares #} +{#- Layer control squares -#} .ls { cursor: pointer; } .ls.active { fill:#CCCC00; stroke-width: 0; } .ls.inactive { stroke: #bbbbbb; stroke-width: 1; } @@ -41,7 +41,7 @@ function getRegionAndLayerFromPath(path) { } function computeTitleForPath(path, layer) { - {# Always use attributes as source of truth #} + {#- Always use attributes as source of truth -#} let baseTitle = ""; try { baseTitle = JSON.parse(path.getAttribute("base-title") || '""'); } catch (_) {} let tips = []; @@ -57,23 +57,23 @@ function computeTitleForPath(path, layer) { } return baseTitle || ""; } -{# sT = showTooltip #} +{#- sT = showTooltip -#} function sT(evt) { const tooltip = document.getElementById("tooltip"); const path = evt.target; - {# figure out which layer is currently active #} + {#- figure out which layer is currently active -#} const { layer: currentLayer } = getRegionAndLayerFromPath(path); - {# compute the text to show; do NOT cache from #} + {#- compute the text to show; do NOT cache from <title> -#} const text = computeTitleForPath(path, currentLayer); if (!text) return; - {# suppress native tooltip #} + {#- suppress native tooltip -#} const titleElement = path.querySelector("title"); if (titleElement) titleElement.textContent = ""; - {# render custom tooltip #} + {#- render custom tooltip -#} const lines = text.split("\n"); const textGroup = document.getElementById("tooltip-text-group"); while (textGroup.firstChild) textGroup.removeChild(textGroup.firstChild); @@ -113,14 +113,14 @@ function sT(evt) { tooltip.setAttribute("opacity", "1"); } -/* ht = hideTooltip */ +{#- ht = hideTooltip -#} function ht() { var tooltip = document.getElementById("tooltip"); if (tooltip) { tooltip.setAttribute("opacity", "0"); } } -/* rT = restore Title */ +{#- rT = restore Title -#} function rT(evt) { const path = evt.target; const { layer: currentLayer } = getRegionAndLayerFromPath(path); @@ -130,7 +130,7 @@ function rT(evt) { } -/* Highlight the active layer square */ +{#- Highlight the active layer square -#} function setActiveLayerControl(regionId, layer) { var group = document.getElementById("layerControls-" + regionId); if (!group) return; @@ -147,35 +147,35 @@ function setActiveLayerControl(regionId, layer) { } -/* ===== Legend threshold switching ===== */ +{#- Legend threshold switching -#} function updateLegendThresholds(layer, regionId) { - // Find the legend group for this region + {#- Find the legend group for this region -#} var legend = document.getElementById("legend-" + regionId); if (!legend) return; var baseThresholds = []; - var regionThresholds = {}; // dict: { ME: [...], LO: [...], LOP: [...] } + var regionThresholds = {}; {#- dict: { ME: [...], LO: [...], LOP: [...] } -#} try { baseThresholds = JSON.parse(legend.getAttribute("data-base-thresholds") || "[]"); - // Previously this was a list-of-lists; now it's a dict keyed by regionId + {#- Previously this was a list-of-lists; now it's a dict keyed by regionId -#} var raw = legend.getAttribute("data-layer-thresholds") || "{}"; regionThresholds = JSON.parse(raw); } catch (e) { - return; // malformed JSON; bail quietly + return; {#- malformed JSON; bail quietly -#} } - // Choose thresholds + {#- Choose thresholds -#} var thr; if (layer === 0) { - thr = baseThresholds; // default thresholds (length 6) + thr = baseThresholds; {#- default thresholds (length 6) -#} } else { - // Same thresholds for all layers of the same region + {#- Same thresholds for all layers of the same region -#} thr = (regionThresholds && regionThresholds[regionId]) || baseThresholds; } - // Update tick labels (expect 6 ticks) + {#- Update tick labels (expect 6 ticks) -#} for (var i = 0; i < 6; i++) { var t = document.getElementById("legend-label-" + i + "-" + regionId); if (t) t.textContent = Math.round((thr[i] ?? 0)); @@ -184,7 +184,7 @@ function updateLegendThresholds(layer, regionId) { } function updateLayer(layer, regionId) { - // --- helpers --- + {#- --- helpers --- -#} const toInt = (v) => { const n = Number.parseInt(v, 10); return Number.isFinite(n) ? n : 0; @@ -202,29 +202,29 @@ function updateLayer(layer, regionId) { const chooseFallback = (defaultColor) => defaultColor === "#999999" ? defaultColor : "#ffffff"; - // --- inputs & container --- + {#- --- inputs & container --- -#} const L = toInt(layer); const hexplot = document.getElementById("hexplot-" + regionId); if (!hexplot) return; - // NodeList is iterable in modern browsers + {#- NodeList is iterable in modern browsers -#} const paths = hexplot.querySelectorAll("path"); paths.forEach((path) => { - // Palette and values per path + {#- Palette and values per path -#} const colors = parseJSONAttr(path, "layer-colors", []); - // Default color precedence: explicit default-fill, then existing fill, then white + {#- Default color precedence: explicit default-fill, then existing fill, then white -#} const defaultColor = path.getAttribute("default-fill") || path.getAttribute("fill") || "#ffffff"; - // Layer 0 => use default color directly + {#- Layer 0 => use default color directly -#} if (L === 0) { path.setAttribute("fill", defaultColor); } else { - // 1..N -> 0..N-1 index + {#- 1..N -> 0..N-1 index -#} const idx = L - 1; let chosen = defaultColor; @@ -232,19 +232,19 @@ function updateLayer(layer, regionId) { const candidate = colors[idx]; const hex = normHex(candidate); - // Treat pure white as "no data" and fall back + {#- Treat pure white as "no data" and fall back -#} const pass = hex !== "#ffffff" && hex !== ""; chosen = pass ? candidate : chooseFallback(normHex(defaultColor)); } else { - // If no palette entry, still fall back predictably + {#- If no palette entry, still fall back predictably -#} chosen = chooseFallback(normHex(defaultColor)); } path.setAttribute("fill", chosen); } - // ----- Tooltip/title handling ----- + {#- ----- Tooltip/title handling ----- -#} const titleEl = path.querySelector("title"); if (!titleEl) return; @@ -262,10 +262,10 @@ function updateLayer(layer, regionId) { titleEl.textContent = computeTitleForPath(path, L); }); - // Store current layer for other UI logic + {#- Store current layer for other UI logic -#} hexplot.setAttribute("data-current-layer", String(L)); - // External UI updates (assumed to exist) + {#- External UI updates (assumed to exist) -#} updateLegendThresholds(L, regionId); setActiveLayerControl(regionId, L); } @@ -370,21 +370,21 @@ function updateLayer(layer, regionId) { <g transform="translate({{ x + 10 }},{{ y }})">{# #}<path d="{{ hex_path }}" {# - #}fill="{{ hex_data.color }}" {# - #}default-fill="{{ hex_data.color }}" {# - #}layer-colors='{% if hex_data.layer_colors is defined %}{% if hex_data.metric_type == "synapse_density" %}{{ hex_data.layer_colors | synapses_to_colors(hex_data.region) | tojson }}{% elif hex_data.metric_type == "cell_count" %}{{ hex_data.layer_colors | neurons_to_colors(hex_data.region) | tojson }}{% else %}{{ hex_data.layer_colors | tojson }}{% endif %}{% else %}{}{% endif %}' {# - #}tooltip-layers='{% if hex_data.tooltip_layers is defined %}{{ hex_data.tooltip_layers | tojson }}{% else %}{}{% endif %}' {# - #}base-title='{% if hex_data.tooltip is defined %}{{ hex_data.tooltip | tojson }}{% else %}""{% endif %}' {# - #}stroke="none" opacity="0.8" style="cursor: pointer;" onmouseover="sT(evt)" onmouseout="ht(); rT(evt);" >{# - #}<title>{{ hex_data.tooltip }}{# + -#}fill="{{ hex_data.color }}" {# + -#}default-fill="{{ hex_data.color }}" {# + -#}layer-colors='{% if hex_data.layer_colors is defined %}{% if hex_data.metric_type == "synapse_density" %}{{ hex_data.layer_colors | synapses_to_colors(hex_data.region) | tojson }}{% elif hex_data.metric_type == "cell_count" %}{{ hex_data.layer_colors | neurons_to_colors(hex_data.region) | tojson }}{% else %}{{ hex_data.layer_colors | tojson }}{% endif %}{% else %}{}{% endif %}' {# + -#}tooltip-layers='{% if hex_data.tooltip_layers is defined %}{{ hex_data.tooltip_layers | tojson }}{% else %}{}{% endif %}' {# + -#}base-title='{% if hex_data.tooltip is defined %}{{ hex_data.tooltip | tojson }}{% else %}""{% endif %}' {# + -#}stroke="none" opacity="0.8" style="cursor: pointer;" onmouseover="sT(evt)" onmouseout="ht(); rT(evt);" >{# + -#}{{ hex_data.tooltip }}{# #}{# #} {%- endfor -%} -{#-- Legend (only if there's actual data) -- #} +{#-- Legend (only if there's actual data) -- -#} {% if data_hexagons %} - {#-- We store both threshold sets on the legend group as JSON -- #} + {#-- We store both threshold sets on the legend group as JSON -- -#} {{ legend_title }} - {#-- Color Legend Rectangles (5 bins) -- #} - {% for i, color in enumerate(colors) %} - {% set rect_y = legend_y + legend_height - (i + 1) * bin_height %} - + {#-- Color Legend Rectangles (5 bins) -- -#} + {%- for i, color in enumerate(colors) -%} + {%- set rect_y = legend_y + legend_height - (i + 1) * bin_height -%} + {#-- Initial title from default thresholds --#} - {{ thresholds[i]|round(0)|int }}…{{ thresholds[i+1]|round(0)|int }} + {{ thresholds[i]|round(0)|int }}…{{ thresholds[i+1]|round(0)|int }} - {% endfor %} + {%- endfor -%} {#-- Threshold Labels (6 ticks) --#} - {% for i, threshold in enumerate(thresholds) %} - {% set label_y = legend_y + legend_height - i * bin_height %} - {{ threshold|round(0)|int }} - {% endfor %} + {%- for i, threshold in enumerate(thresholds) -%} + {%- set label_y = legend_y + legend_height - i * bin_height -%} + {{ threshold|round(0)|int }} + {%- endfor -%} {% endif %} diff --git a/templates/sections/scatterplots.html.jinja b/templates/sections/scatterplots.html.jinja index 1eaf60b..c71328f 100644 --- a/templates/sections/scatterplots.html.jinja +++ b/templates/sections/scatterplots.html.jinja @@ -7,6 +7,14 @@ Scatterplot of spatial metrics for {{ region }} + + + + + + + +

{%- endfor -%} diff --git a/templates/sections/scatterplots_single.html.jinja b/templates/sections/scatterplots_single.html.jinja index 4560d00..f0de89f 100644 --- a/templates/sections/scatterplots_single.html.jinja +++ b/templates/sections/scatterplots_single.html.jinja @@ -13,6 +13,14 @@ Scatterplot of spatial metrics for {{ region }} + + + + + + + + {%- endfor -%} From 8775447b4be0bf3c52028f239fcd8cea8e50349f Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 15:59:36 -0500 Subject: [PATCH 57/60] add subset-medium-optic as a test set --- config/config.cns.yaml | 19 +++++++++++++++++++ pixi.lock | 2 +- pyproject.toml | 21 +++++++++++++++++++++ 3 files changed, 41 insertions(+), 1 deletion(-) diff --git a/config/config.cns.yaml b/config/config.cns.yaml index f26262a..9513440 100644 --- a/config/config.cns.yaml +++ b/config/config.cns.yaml @@ -48,6 +48,25 @@ subsets: - "'AOTU103m'" - '"KCa''b''-ap1"' - "'Acc. ti flexor MN'" + subset-medium-optic: + - "Cm5" + - "Dm8a" + - "Li30" + - "C2" + - "MeLo14" + - "TmY5a" + - "Y3" + - "dCal1" + - "LC17" + - "LoVP3" + - "MeVP62" + - "LT79" + - "vCal3" + - "LoVC23" + - "aMe30" + - "OLVC7" + - "AN27X013" + - "DNp30" subset-small: - "SAD103" - "Tm3" diff --git a/pixi.lock b/pixi.lock index d1094d1..efd8127 100644 --- a/pixi.lock +++ b/pixi.lock @@ -3998,7 +3998,7 @@ packages: - pypi: ./ name: neuview version: 2.7.10 - sha256: e3baa1a33031901d6bef383e0c985b287bd53f4908b57b882ab3ec8e7140ddee + sha256: 4c4321cc04ee257241e273290d14525ab8f2a7ec5d59b0a5fe286cfb4ae2825e requires_dist: - click>=8.0.0 - jinja2>=3.0.0 diff --git a/pyproject.toml b/pyproject.toml index 5ec6d37..8c5cd94 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -139,6 +139,27 @@ task = "subset-small-no-index" [[tool.pixi.tasks.subset-small.depends-on]] task = "create-list" +[tool.pixi.tasks.subset-medium-optic-no-index] +[[tool.pixi.tasks.subset-medium-optic-no-index.depends-on]] +task = "clean-output" + +[[tool.pixi.tasks.subset-medium-optic-no-index.depends-on]] +task = "extract-and-fill" +args = [ "config.yaml", "subset-medium-optic",] + +[[tool.pixi.tasks.subset-medium-optic-no-index.depends-on]] +task = "pop-all" + +[[tool.pixi.tasks.subset-medium-optic-no-index.depends-on]] +task = "create-scatter" + +[tool.pixi.tasks.subset-medium-optic] +[[tool.pixi.tasks.subset-medium-optic.depends-on]] +task = "subset-medium-optic-no-index" + +[[tool.pixi.tasks.subset-medium-optic.depends-on]] +task = "create-list" + [tool.pixi.tasks.increment-version] cmd = "python scripts/increment_version.py" From ad6f0fc02534db52b5577bf0da881864e2821c91 Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 16:08:13 -0500 Subject: [PATCH 58/60] before, LOVC23 was higlighted when I really just wanted C2 --- templates/scatterplot.svg.jinja | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/templates/scatterplot.svg.jinja b/templates/scatterplot.svg.jinja index 7446013..1d6f070 100644 --- a/templates/scatterplot.svg.jinja +++ b/templates/scatterplot.svg.jinja @@ -126,9 +126,8 @@ function highlightByName(name) { var c = g.querySelector('circle'); if (!c) continue; - var dataTitle = (c.getAttribute('data-title') || ''); - var haystack = (dataTitle).trim().toLowerCase(); - if (!haystack || haystack.indexOf(needle) === -1) continue; + var dataType = (c.getAttribute('data-type') || '').trim().toLowerCase(); + if (!dataType || dataType !== needle) continue; var rect = c.getBoundingClientRect(); sT({ From 47c30b3574ee218cedfe7a48e206cb694e0282af Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 18:12:47 -0500 Subject: [PATCH 59/60] save space in eyemaps --- templates/eyemap.svg.jinja | 140 ++++++++++++++----------------------- 1 file changed, 52 insertions(+), 88 deletions(-) diff --git a/templates/eyemap.svg.jinja b/templates/eyemap.svg.jinja index d1ab277..23d11f8 100644 --- a/templates/eyemap.svg.jinja +++ b/templates/eyemap.svg.jinja @@ -269,97 +269,61 @@ function updateLayer(layer, regionId) { updateLegendThresholds(L, regionId); setActiveLayerControl(regionId, L); } - //]]> {#-- Background --#} - + {#-- Plot Name, Region Name, Neuron Name, and Layer Scrollbar --#} -{{ plot_desc }} -{{ region_desc }} - {{ neuron_desc }} +{{ plot_desc }} +{{ region_desc }} +{{ neuron_desc }} {#-- Hexagon Path Definition --#} -{% set hex_path = "M" + hex_points|join(" L") + " Z" %} +{%- set hex_path = "M" + hex_points|join(" L") + " Z" -%} {#-- Layer buttons --#} -{% set square = 8 %} -{% set gap = 0 %} +{%- set square = 8 -%} +{%- set gap = 0 -%} -{% if hexagons[0].region == 'ME' %} -{% set n_layers = 10 %} -{% elif hexagons[0].region == 'LO' %} -{% set n_layers = 7 %} -{% elif hexagons[0].region == 'LOP' %} -{% set n_layers = 4 %} -{% else %} -{% set n_layers = 10 %} -{% endif %} +{%- if hexagons[0].region == 'ME' -%} +{%- set n_layers = 10 -%} +{%- elif hexagons[0].region == 'LO' -%} +{%- set n_layers = 7 -%} +{%- elif hexagons[0].region == 'LOP' -%} +{%- set n_layers = 4 -%} +{%- else -%} +{%- set n_layers = 10 -%} +{%- endif -%} -{% set all_button_width = square * 3 %} -{% set layer_button_width = square * 5 %} -{% set all_button_height = square * n_layers %} -{% set layer_button_height = square %} +{%- set all_button_width = square * 3 -%} +{%- set layer_button_width = square * 5 -%} +{%- set all_button_height = square * n_layers -%} +{%- set layer_button_height = square -%} {#-- Row 0: "All" --#} - + - {{ hexagons[0].region }} + {{ hexagons[0].region }} {#-- Rows 1..10 --#} - {% for i in range(1, n_layers+1) %} - + {%- for i in range(1, n_layers+1) -%} + - {% if hexagons[0].region == "LO" and i == 5 -%} 5A {% elif hexagons[0].region == "LO" and i == 6 %}5B{% elif hexagons[0].region== "LO" and i == 7 %}6{% else %}{{ i }}{% endif %} + + {%- if hexagons[0].region == "LO" and i == 5 -%} 5A + {%- elif hexagons[0].region == "LO" and i == 6 -%}5B + {%- elif hexagons[0].region== "LO" and i == 7 -%}6 + {%- else -%}{{ i }}{%- endif -%} - {% endfor %} + {%- endfor -%} {#-- Hexagons --#} @@ -372,9 +336,9 @@ function updateLayer(layer, regionId) { #}{# -#}{{ hex_data.tooltip }}{# #}{# @@ -383,22 +347,22 @@ function updateLayer(layer, regionId) { {#-- Legend (only if there's actual data) -- -#} -{% if data_hexagons %} +{%- if data_hexagons -%} {#-- We store both threshold sets on the legend group as JSON -- -#} - - {{ legend_title }} + + {{ legend_title }} {#-- Color Legend Rectangles (5 bins) -- -#} {%- for i, color in enumerate(colors) -%} @@ -434,7 +398,7 @@ function updateLayer(layer, regionId) { -#}>{{ threshold|round(0)|int }} {%- endfor -%} -{% endif %} +{%- endif -%} {#-- Tooltip (rendered last to appear on top) --#} From 21434ede3ccde87cacad7505491d16176e1a454a Mon Sep 17 00:00:00 2001 From: Frank Loesche Date: Fri, 12 Dec 2025 18:42:43 -0500 Subject: [PATCH 60/60] remove threshold --- config/config.cns.yaml | 4 ++ config/config.example.yaml | 3 ++ config/config.fafb.yaml | 3 ++ config/config.optic-lobe.yaml | 3 ++ docs/user-guide.md | 48 ++++++++++++++++++- src/neuview/cli.py | 18 ++++++- src/neuview/config.py | 21 +++++++- src/neuview/services/scatterplot_service.py | 21 ++++++-- .../rendering/rendering_config.py | 6 +++ 9 files changed, 119 insertions(+), 8 deletions(-) diff --git a/config/config.cns.yaml b/config/config.cns.yaml index 9513440..def2ff0 100644 --- a/config/config.cns.yaml +++ b/config/config.cns.yaml @@ -22,6 +22,10 @@ discovery: # Randomize selection (true) or use alphabetical order (false) randomize: true +# Scatter plot settings. It was 9 +scatter: + min_col_count_threshold: null + html: title_prefix: "Male CNS" github_repo: "https://github.com/reiserlab/celltype-explorer-drosophila-male-cns" diff --git a/config/config.example.yaml b/config/config.example.yaml index ce53005..1004c73 100644 --- a/config/config.example.yaml +++ b/config/config.example.yaml @@ -10,5 +10,8 @@ output: neuroglancer: base_url: "https://clio-ng.janelia.org/" +scatter: + min_col_count_threshold: null + html: title_prefix: "Neuron Type Report" diff --git a/config/config.fafb.yaml b/config/config.fafb.yaml index 222c42a..4b71333 100644 --- a/config/config.fafb.yaml +++ b/config/config.fafb.yaml @@ -22,6 +22,9 @@ discovery: # Randomize selection (true) or use alphabetical order (false) randomize: true +scatter: + min_col_count_threshold: null + html: title_prefix: "Female Adult Fly Brain" fathom_id: "GDMDXQVG" diff --git a/config/config.optic-lobe.yaml b/config/config.optic-lobe.yaml index 5602939..3ab8eeb 100644 --- a/config/config.optic-lobe.yaml +++ b/config/config.optic-lobe.yaml @@ -23,6 +23,9 @@ discovery: # Randomize selection (true) or use alphabetical order (false) randomize: true +scatter: + min_col_count_threshold: null + html: title_prefix: "Neuron Type Report" diff --git a/docs/user-guide.md b/docs/user-guide.md index 768ba7c..49b33cd 100644 --- a/docs/user-guide.md +++ b/docs/user-guide.md @@ -104,8 +104,35 @@ html: performance: max_workers: 4 cache_enabled: true + +scatter: + # Minimum column count threshold for data quality filtering + # Data points with cols_innervated <= this value will be excluded from scatter plots + # Set to null to disable this filter + min_col_count_threshold: null +``` + +### Scatter Plot Configuration + +Configure scatter plot generation for optic lobe datasets: + +```yaml +scatter: + min_col_count_threshold: 9.0 # Default threshold ``` +**Configuration Options:** +- `min_col_count_threshold`: Minimum number of columns a neuron type must innervate to be included in scatter plots + - Default: `9.0` (excludes types with ≤ 9 columns) + - Set to `null` to disable filtering and include all data points + - This filter helps exclude low-quality or sparse data from visualizations + - Can be overridden per-command using `--min-col-count` CLI option + +**Use Cases:** +- **Strict quality control** (default 9.0): Only well-sampled types with sufficient column coverage +- **Relaxed filtering** (e.g., 5.0): Include more types with moderate column coverage +- **No filtering** (null): Include all types regardless of column count + ### Dataset-Specific Configurations Different datasets may require specific settings: @@ -166,6 +193,15 @@ pixi run neuview build --types "Tm3,Mi1,T4" # Use a subset from config pixi run neuview build --subset small-test +# Generate scatter plots (for optic lobe datasets) +pixi run neuview create-scatter + +# Generate scatter plots with custom quality threshold +pixi run neuview create-scatter --min-col-count 5 + +# Generate scatter plots without quality filtering +pixi run neuview create-scatter --min-col-count -1 + # Verbose output for debugging pixi run neuview build --verbose ``` @@ -184,6 +220,16 @@ pixi run neuview build --verbose - `neuview inspect ` - Show detailed information about a neuron type - Displays: neuron count, soma distribution, connectivity stats +**`create-scatter` command:** +- `neuview create-scatter` - Generate SVG scatter plots of spatial metrics for optic lobe types +- `--min-col-count ` - Set minimum column count threshold for data quality filtering + - Default: 9.0 (excludes points with cols_innervated ≤ 9) + - Set to -1 to disable filtering + - Can also be configured in `config.yaml` under `scatter.min_col_count_threshold` +- Generates plots for ME, LO, and LOP regions +- Creates both combined (both hemispheres) and hemisphere-specific (L/R) plots +- Output: `output/scatter/*.svg` files + ## Generated Website Features ### Interactive Index Page @@ -712,4 +758,4 @@ A: Yes! The `data/neurons.json` file is a standard JSON API endpoint. A: Same data, different formats. JSON for web servers/APIs, JS for local file access. **Q: Why do some neurons have L/R pages and others don't?** -A: Automatically determined by soma distribution. Bilateral neurons get separate pages. \ No newline at end of file +A: Automatically determined by soma distribution. Bilateral neurons get separate pages. diff --git a/src/neuview/cli.py b/src/neuview/cli.py index b5420e5..c54cd0b 100644 --- a/src/neuview/cli.py +++ b/src/neuview/cli.py @@ -377,11 +377,27 @@ async def run_create_list(): @main.command("create-scatter") +@click.option( + "--min-col-count", + type=float, + default=None, + help="Minimum column count threshold for data quality filtering. Points with cols_innervated <= this value will be excluded. Set to -1 to disable filtering.", +) @click.pass_context -def create_scatter(ctx): +def create_scatter(ctx, min_col_count): """Generate SVG scatterplots of spatial metrics for optic lobe types (combined and per hemisphere).""" services = setup_services(ctx.obj["config_path"], ctx.obj["verbose"]) + # Override threshold if specified via CLI + if min_col_count is not None: + if min_col_count < 0: + # Disable filtering + services.scatter_service.scatter_config.min_col_count_threshold = None + else: + services.scatter_service.scatter_config.min_col_count_threshold = ( + min_col_count + ) + async def run_create_scatter(): await services.scatter_service.create_scatterplots() diff --git a/src/neuview/config.py b/src/neuview/config.py index 5d82ebc..f05dafb 100644 --- a/src/neuview/config.py +++ b/src/neuview/config.py @@ -2,11 +2,12 @@ Configuration management for neuView. """ -import yaml import os +from dataclasses import dataclass, field from pathlib import Path from typing import Optional -from dataclasses import dataclass, field + +import yaml from dotenv import load_dotenv @@ -54,6 +55,13 @@ class HtmlConfig: fathom_id: Optional[str] = None +@dataclass +class ScatterPlotConfig: + """Scatter plot configuration.""" + + min_col_count_threshold: Optional[float] = 9.0 + + @dataclass class Config: """Main configuration class.""" @@ -63,6 +71,7 @@ class Config: discovery: DiscoveryConfig neuroglancer: NeuroglancerConfig html: HtmlConfig + scatter: ScatterPlotConfig = field(default_factory=ScatterPlotConfig) @classmethod def load(cls, config_path: str) -> "Config": @@ -93,6 +102,7 @@ def load(cls, config_path: str) -> "Config": discovery_config = DiscoveryConfig(**data.get("discovery", {})) neuroglancer_config = NeuroglancerConfig(**data.get("neuroglancer", {})) html_config = HtmlConfig(**data.get("html", {})) + scatter_config = ScatterPlotConfig(**data.get("scatter", {})) return cls( neuprint=neuprint_config, @@ -100,6 +110,7 @@ def load(cls, config_path: str) -> "Config": discovery=discovery_config, neuroglancer=neuroglancer_config, html=html_config, + scatter=scatter_config, ) def get_neuprint_token(self) -> str: @@ -137,6 +148,7 @@ def create_minimal_for_testing(cls) -> "Config": discovery_config = DiscoveryConfig() html_config = HtmlConfig() + scatter_config = ScatterPlotConfig() return cls( neuprint=neuprint_config, @@ -144,6 +156,7 @@ def create_minimal_for_testing(cls) -> "Config": discovery=discovery_config, neuroglancer=NeuroglancerConfig(), html=html_config, + scatter=scatter_config, ) @classmethod @@ -157,6 +170,7 @@ def create_default(cls) -> "Config": discovery_config = DiscoveryConfig() html_config = HtmlConfig() + scatter_config = ScatterPlotConfig() return cls( neuprint=neuprint_config, @@ -164,6 +178,7 @@ def create_default(cls) -> "Config": discovery=discovery_config, neuroglancer=NeuroglancerConfig(), html=html_config, + scatter=scatter_config, ) @classmethod @@ -187,10 +202,12 @@ def from_dict(cls, config_dict: dict) -> "Config": discovery_config = DiscoveryConfig(**config_dict.get("discovery", {})) neuroglancer_config = NeuroglancerConfig(**config_dict.get("neuroglancer", {})) html_config = HtmlConfig(**config_dict.get("html", {})) + scatter_config = ScatterPlotConfig(**config_dict.get("scatter", {})) return cls( neuprint=neuprint_config, output=output_config, discovery=discovery_config, neuroglancer=neuroglancer_config, html=html_config, + scatter=scatter_config, ) diff --git a/src/neuview/services/scatterplot_service.py b/src/neuview/services/scatterplot_service.py index bf272e1..42be77b 100644 --- a/src/neuview/services/scatterplot_service.py +++ b/src/neuview/services/scatterplot_service.py @@ -26,7 +26,9 @@ class ScatterplotService: def __init__(self): self.config = Config.load("config.yaml") - self.scatter_config = ScatterConfig() + self.scatter_config = ScatterConfig( + min_col_count_threshold=self.config.scatter.min_col_count_threshold + ) if isinstance(self.scatter_config.scatter_dir, str): self.plot_output_dir = self.scatter_config.scatter_dir @@ -221,6 +223,10 @@ def _extract_points(self, plot_data, side, region): """ Collate the data points required to make the spatial metric scatterplots. + + Applies data quality filtering based on the min_col_count_threshold + configuration parameter. Points with cols_innervated at or below this + threshold are excluded from the plot. """ pts = [] for rec in plot_data: @@ -278,10 +284,17 @@ def _extract_points(self, plot_data, side, region): if x <= 0 or y <= 0: continue - # Optional data quality filter from prior script - if col_count is not None: + # Data quality filter: exclude points with low column counts + # This threshold can be configured via scatter_config.min_col_count_threshold + if ( + col_count is not None + and self.scatter_config.min_col_count_threshold is not None + ): try: - if float(col_count) <= 9: + if ( + float(col_count) + <= self.scatter_config.min_col_count_threshold + ): continue except Exception: pass diff --git a/src/neuview/visualization/rendering/rendering_config.py b/src/neuview/visualization/rendering/rendering_config.py index 20da114..8eb00b2 100644 --- a/src/neuview/visualization/rendering/rendering_config.py +++ b/src/neuview/visualization/rendering/rendering_config.py @@ -214,6 +214,12 @@ class ScatterConfig: min_max_data: Optional[Dict[str, Any]] = None thresholds: Optional[Dict[str, Any]] = None + # Data quality filtering + # Minimum column count threshold for including data points in scatter plots. + # Points with cols_innervated <= this value will be excluded. + # Set to None to disable this filter. + min_col_count_threshold: Optional[float] = None + top, right, bottom, left = margins margin_top = top margin_right = right