Upload climate_data.py

data/climate_data.py

@@ -21,11 +21,6 @@ from datetime import datetime, timedelta
 import re
 import logging
 from os.path import join as os_join
-import psychrolib
-from psychrochart import PsychroChart
-import matplotlib.pyplot as plt
-from io import BytesIO
-import base64
 
 # Set up logging
 logging.basicConfig(level=logging.INFO)
@@ -1077,155 +1072,91 @@ class ClimateData:
             return "8"
 
     def plot_psychrometric_chart(self, location: ClimateLocation, epw_data: pd.DataFrame):
-        """Plot psychrometric chart with ASHRAE 55 comfort zone and psychrometric lines using psychrochart."""
+        """Plot psychrometric chart with ASHRAE 55 comfort zone and psychrometric lines."""
         st.subheader("Psychrometric Chart")
-    
-        try:
-            # Initialize psychrolib for SI units
-            psychrolib.SetUnitSystem(psychrolib.SI)
-    
-            # Extract data from EPW
-            dry_bulb = pd.to_numeric(epw_data[6], errors='coerce').values
-            humidity = pd.to_numeric(epw_data[8], errors='coerce').values
-            valid_mask = ~np.isnan(dry_bulb) & ~np.isnan(humidity)
-            dry_bulb = dry_bulb[valid_mask]
-            humidity = humidity[valid_mask]
-            pressure = location.pressure  # Pa
-    
-            if len(dry_bulb) == 0:
-                st.error("No valid data points for psychrometric chart after filtering NaN values.")
-                logger.error("Empty dry_bulb or humidity arrays after filtering.")
-                return
-    
-            # Calculate humidity ratio (g/kg dry air) with error handling
-            humidity_ratio = np.zeros_like(dry_bulb)
-            for i, (t, rh) in enumerate(zip(dry_bulb, humidity)):
-                try:
-                    hr = psychrolib.GetHumRatioFromRelHum(t, rh / 100, pressure) * 1000
-                    humidity_ratio[i] = hr if not np.isnan(hr) else 0.0
-                except Exception as e:
-                    logger.warning(f"Error calculating humidity ratio for index {i}: {str(e)}")
-                    humidity_ratio[i] = 0.0
-    
-            valid_hr_mask = (humidity_ratio > 0) & ~np.isnan(humidity_ratio)
-            dry_bulb = dry_bulb[valid_hr_mask]
-            humidity_ratio = humidity_ratio[valid_hr_mask]
-    
-            if len(dry_bulb) == 0:
-                st.error("No valid humidity ratio data points after calculation.")
-                logger.error("Empty humidity_ratio array after calculation.")
-                return
-    
-            # Define axis limits based on data
-            temp_min = float(np.min(dry_bulb)) - 5 if len(dry_bulb) > 0 else -10
-            temp_max = float(np.max(dry_bulb)) + 5 if len(dry_bulb) > 0 else 40
-            hr_max = float(np.max(humidity_ratio)) + 5 if len(humidity_ratio) > 0 else 30
-    
-            # Define custom style for psychrochart
-            custom_style = {
-                "figure": {
-                    "x_label": "Dry-Bulb Temperature (°C)",
-                    "y_label": "Humidity Ratio (g/kg dry air)",
-                    "x_axis": {"color": [0.0, 0.0, 0.0], "linewidth": 1.5, "linestyle": "-"},
-                    "x_axis_labels": {"color": [0.0, 0.0, 0.0], "fontsize": 8},
-                    "x_axis_ticks": {"direction": "out", "color": [0.0, 0.0, 0.0]},
-                    "y_axis": {"color": [0.0, 0.0, 0.0], "linewidth": 1.5, "linestyle": "-"},
-                    "y_axis_labels": {"color": [0.0, 0.0, 0.0], "fontsize": 8},
-                    "y_axis_ticks": {"direction": "out", "color": [0.0, 0.0, 0.0]},
-                    "partial_axis": False,
-                    "position": [0.025, 0.075, 0.925, 0.875]
-                },
-                "limits": {
-                    "range_temp_c": [max(-10, temp_min), min(40, temp_max)],
-                    "range_humidity_g_kg": [0, max(30, hr_max)],
-                    "altitude_m": location.elevation,
-                    "step_temp": 1.0
-                },
-                "saturation": {"color": [0.0, 0.0, 0.0], "linewidth": 2, "linestyle": "-"},
-                "constant_rh": {"color": [0.8, 0.0, 0.0], "linewidth": 1, "linestyle": "-"},
-                "constant_v": {"color": [0.0, 0.4, 0.4], "linewidth": 0.5, "linestyle": "-"},
-                "constant_h": {"color": [1.0, 0.4, 0.0], "linewidth": 0.75, "linestyle": "-"},
-                "constant_wet_temp": {"color": [0.2, 0.8, 0.2], "linewidth": 1, "linestyle": "--"},
-                "constant_dry_temp": {"color": [0.0, 0.0, 0.0], "linewidth": 0.25, "linestyle": "-"},
-                "constant_humidity": {"color": [0.0, 0.0, 0.0], "linewidth": 0.25, "linestyle": "-"},
-                "chart_params": {
-                    "with_constant_rh": True,
-                    "constant_rh_curves": [20, 30, 40, 50, 60, 70, 80, 90],
-                    "constant_rh_labels": [20, 40, 60, 80],
-                    "with_constant_v": False,
-                    "constant_v_step": 0.01,
-                    "range_vol_m3_kg": [0.78, 0.96],
-                    "with_constant_h": True,
-                    "constant_h_step": 10,
-                    "constant_h_labels": [0],
-                    "range_h": [10, 130],
-                    "with_constant_wet_temp": True,
-                    "constant_wet_temp_step": 1,
-                    "range_wet_temp": [-10, 35],
-                    "constant_wet_temp_labels": [0, 5, 10, 15, 20, 25, 30],
-                    "with_constant_dry_temp": True,
-                    "constant_temp_step": 5,
-                    "with_constant_humidity": True,
-                    "constant_humid_step": 2,
-                    "with_zones": True
-                }
-            }
-    
-            # Create matplotlib figure
-            fig, ax = plt.subplots(figsize=(7, 3))
-            chart = PsychroChart(custom_style)  # Pass custom_style as positional argument
-            chart.plot(ax)
-    
-            # Add ASHRAE 55 comfort zones
-            zones_conf = {
-                "zones": [
-                    {
-                        "zone_type": "dbt-rh",
-                        "style": {
-                            "edgecolor": [0.0, 0.8, 0.0, 0.8],
-                            "facecolor": [0.0, 1.0, 0.0, 0.2],
-                            "linewidth": 2,
-                            "linestyle": "--"
-                        },
-                        "points_x": [20, 26],
-                        "points_y": [30, 60],
-                        "label": "ASHRAE 55 Comfort Zone"
-                    }
-                ]
-            }
-            chart.append_zones(zones_conf)
-    
-            # Subsample points to improve performance (every 10th point)
-            subsample_idx = np.arange(0, len(dry_bulb), 10)
-            dry_bulb_sub = dry_bulb[subsample_idx]
-            humidity_ratio_sub = humidity_ratio[subsample_idx]
-    
-            # Plot hourly data points
-            points = {
-                f"hour_{i}": {
-                    "label": "",
-                    "style": {"color": [0.0, 0.0, 1.0, 0.5], "marker": ".", "markersize": 3},
-                    "xy": (db, hr)
-                }
-                for i, (db, hr) in enumerate(zip(dry_bulb_sub, humidity_ratio_sub))
-            }
-            chart.plot_points_dbt_rh(points, connectors=[])
-    
-            # Add legend
-            chart.plot_legend(markerscale=0.7, frameon=False, fontsize=8, labelspacing=1.2)
-    
-            # Save plot to PNG for faster rendering
-            buffer = BytesIO()
-            plt.savefig(buffer, format="png", dpi=100, bbox_inches="tight")
-            buffer.seek(0)
-            plt.close(fig)
-    
-            # Display in Streamlit using st.image
-            st.image(buffer, use_column_width="auto", caption="Psychrometric Chart")
-    
-        except Exception as e:
-            st.error(f"Error rendering psychrometric chart: {str(e)}")
-            logger.error(f"Psychrometric chart error: {str(e)}", exc_info=True)
+        
+        dry_bulb = pd.to_numeric(epw_data[6], errors='coerce').values
+        humidity = pd.to_numeric(epw_data[8], errors='coerce').values
+        valid_mask = ~np.isnan(dry_bulb) & ~np.isnan(humidity)
+        dry_bulb = dry_bulb[valid_mask]
+        humidity = humidity[valid_mask]
+        
+        # Calculate humidity ratio (kg/kg dry air)
+        pressure = location.pressure / 1000  # kPa
+        saturation_pressure = 6.1078 * 10 ** (7.5 * dry_bulb / (dry_bulb + 237.3))
+        vapor_pressure = humidity / 100 * saturation_pressure
+        humidity_ratio = 0.62198 * vapor_pressure / (pressure - vapor_pressure) * 1000  # Convert to g/kg
+        
+        fig = go.Figure()
+        
+        # Hourly data points
+        fig.add_trace(go.Scatter(
+            x=dry_bulb,
+            y=humidity_ratio,
+            mode='markers',
+            marker=dict(size=5, opacity=0.5, color='blue'),
+            name='Hourly Conditions'
+        ))
+        
+        # ASHRAE 55 comfort zone
+        comfort_db = [20, 26, 26, 20, 20]
+        comfort_rh = [30, 30, 60, 60, 30]
+        comfort_vp = np.array(comfort_rh) / 100 * 6.1078 * 10 ** (7.5 * np.array(comfort_db) / (np.array(comfort_db) + 237.3))
+        comfort_hr = 0.62198 * comfort_vp / (pressure - comfort_vp) * 1000
+        fig.add_trace(go.Scatter(
+            x=comfort_db,
+            y=comfort_hr,
+            mode='lines',
+            line=dict(color='green', width=2),
+            fill='toself',
+            fillcolor='rgba(0, 255, 0, 0.2)',
+            name='ASHRAE 55 Comfort Zone'
+        ))
+        
+        # Constant humidity ratio lines
+        for hr in [5, 10, 15]:
+            db_range = np.linspace(0, 40, 100)
+            vp = (hr / 1000 * pressure) / (0.62198 + hr / 1000)
+            rh = vp / (6.1078 * 10 ** (7.5 * db_range / (db_range + 237.3))) * 100
+            hr_line = np.full_like(db_range, hr)
+            fig.add_trace(go.Scatter(
+                x=db_range,
+                y=hr_line,
+                mode='lines',
+                line=dict(color='gray', width=1, dash='dash'),
+                name=f'{hr} g/kg',
+                showlegend=True
+            ))
+        
+        # Constant wet-bulb temperature lines
+        wet_bulb_temps = [10, 15, 20]
+        for wbt in wet_bulb_temps:
+            db_range = np.linspace(0, 40, 100)
+            rh_range = np.linspace(5, 95, 100)
+            wb_values = self.calculate_wet_bulb(db_range, rh_range)
+            vp = rh_range / 100 * (6.1078 * 10 ** (7.5 * db_range / (db_range + 237.3)))
+            hr_values = 0.62198 * vp / (pressure - vp) * 1000
+            mask = (wb_values >= wbt - 0.5) & (wb_values <= wbt + 0.5)
+            if np.any(mask):
+                fig.add_trace(go.Scatter(
+                    x=db_range[mask],
+                    y=hr_values[mask],
+                    mode='lines',
+                    line=dict(color='purple', width=1, dash='dot'),
+                    name=f'Wet-Bulb {wbt}°C',
+                    showlegend=True
+                ))
+        
+        fig.update_layout(
+            title="Psychrometric Chart",
+            xaxis_title="Dry-Bulb Temperature (°C)",
+            yaxis_title="Humidity Ratio (g/kg dry air)",
+            xaxis=dict(range=[-5, 40]),
+            yaxis=dict(range=[0, 25]),
+            showlegend=True,
+            template='plotly_white'
+        )
+        st.plotly_chart(fig, use_container_width=True)
 
     def plot_sun_shading_chart(self, location: ClimateLocation):
         """Plot sun path chart for summer and winter solstices, inspired by Climate Consultant."""