Meditation Practice Calendar

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches

np.random.seed(321)

# Generate meditation minutes (0, 5, 10, 15, 20, 30+)
days = 365
meditation = np.random.choice([0, 0, 5, 10, 15, 20, 30], size=days, p=[0.25, 0.1, 0.15, 0.2, 0.15, 0.1, 0.05])

# Normalize to levels
med_levels = np.digitize(meditation, bins=[0, 1, 5, 10, 15, 25]) - 1

weeks = 53
data = np.zeros((7, weeks))
for i, val in enumerate(med_levels):
    week = i // 7
    day = i % 7
    if week < weeks:
        data[day, week] = val

# Cyan/teal gradient for calm
colors = ['#0a0a0f', '#042f2e', '#0d9488', '#2dd4bf', '#5eead4']
cmap = LinearSegmentedColormap.from_list('meditation', colors, N=256)

fig, ax = plt.subplots(figsize=(16, 4), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

im = ax.imshow(data, cmap=cmap, aspect='auto', vmin=0, vmax=4)

ax.set_yticks(range(7))
ax.set_yticklabels(['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'], fontsize=9, color='#e2e8f0')
ax.set_xticks(range(0, 52, 4))
ax.set_xticklabels(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec', ''], 
                   fontsize=9, color='#e2e8f0')

ax.set_title('Meditation Practice - Daily Minutes', fontsize=16, color='white', fontweight='bold', pad=15)

for i in range(8):
    ax.axhline(y=i-0.5, color='#1e293b', linewidth=0.5)
for i in range(weeks+1):
    ax.axvline(x=i-0.5, color='#1e293b', linewidth=0.5)

ax.tick_params(colors='#e2e8f0', length=0)
for spine in ax.spines.values():
    spine.set_visible(False)

legend_elements = [mpatches.Patch(facecolor=c, label=l, edgecolor='#334155') 
                   for c, l in zip(colors, ['None', '5min', '10min', '15min', '20min+'])]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.15), ncol=5, 
          fontsize=8, facecolor='#1e293b', edgecolor='#334155', labelcolor='white')

practice_days = int(np.sum(meditation > 0))
total_mins = int(np.sum(meditation))
ax.annotate(f'{practice_days} days practiced | {total_mins//60}h {total_mins%60}m total', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=11, color='#2dd4bf', ha='right', fontweight='bold')

plt.tight_layout()
plt.subplots_adjust(bottom=0.25)
plt.show()